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Role of chemolithoautotrophic microorganisms involved in nitrogen and sulfur cycling
in coastal marine sediments
Yvonne Antonia Lipsewers
THIS RESEARCH WAS FINANCIALLY SUPPORTED BY
DARWIN CENTER FOR BIOGEOSCIENCES
NIOZ – ROYAL NETHERLANDS INSTITUTE FOR SEA RESEARCH
ISBN: 978-90-6266-492-4
Cover photos: S. Rampen, L. Villanueva, M. van der Meer
Printed by Ipskamp Printing, The Netherlands
Role of chemolithoautotrophic microorganisms involved in nitrogen and sulfur cycling in coastal marine sediments
De rol van chemolithoautotrofe micro-organismen die deelnemen in de stikstof- en zwavelcyclus in mariene
kustsedimenten (met een samenvatting in het Nederlands)
Proefschrift
ter verkrijging van de graad van doctor aan de Universiteit Utrecht op gezag van de rector magnificus, prof.dr. G.J. van der Zwaan, ingevolge het besluit van het college
voor promoties in het openbaar te verdedigen op dinsdag 5 december 2017 des ochtends te 10.30 uur
door
Yvonne Antonia Lipsewers
geboren op 18 juli 1977 te Salzkotten, Duitsland
Promotor: Prof. dr. ir. J.S. Sinninghe Damsté
Copromotor: Dr. L. Villanueva
„Hinterher ist man immer schlauer…“
Für meine Familie
Table of contents
Chapter 1 – Introduction .....................................................................................................1
Chapter 2 – Seasonality and depth distribution of the abundance and activity of am-monia oxidizing microorganisms in marine coastal sediments (North Sea) ..........23
Chapter 3 – Lack of 13C-label incorporation suggests low turnover rates of thaumar-chaeal intact polar tetraether lipids in sediments from the Iceland Shelf .............53
Chapter 4 – Abundance and diversity of denitrifying and anammox bacteria in season-ally hypoxic and sulfidic sediments of the saline Lake Grevelingen .......................79
Chapter 5 – Impact of seasonal hypoxia on activity and community structure of chem-olithoautotrophic bacteria in a coastal sediment .......................................................107
Chapter 6 – Potential recycling of thaumarchaeotal lipids by DPANN archaea in sea-sonally hypoxic surface marine sediments ...................................................................147
Chapter 7 – Synthesis ...........................................................................................................167
Summary ..................................................................................................................................187
Samenvatting ...........................................................................................................................191
References ...............................................................................................................................195
Acknowledgements ...............................................................................................................223
1
1. Introduction
Marine sediments are dynamic habitats shaped by interactions of biotic and abiotic processes including the redox reactions performed by microorganisms to gain energy for growth (Schrenk et al., 2010). The biogeochemical cycling of carbon-, nitrogen- and sulfur compounds in marine sediments is tightly coupled in space and time. Due to electron donor and acceptor availability, an overlap of the activity of metabolically diverse microorganisms involved in carbon-, nitrogen- and sulfur cycling occurs.
Aerobic mineralization processes of organic matter reaching the sediment surface are mainly mediated by the metabolism of phototrophic and chemoorganoheterotrophic microorganisms. These processes result in the consumption of oxygen (O2) within the first few millimeters/cen-timeters of marine sediments. Underneath the O2 penetration depth, anaerobic mineralization processes occur due to the vertical distribution of electron acceptors in the sediment: O2 → ni-trate (NO3
−) → manganese (IV) oxide (MnO2) → ferric iron (Fe3+) → sulfate (SO42−) → carbon
dioxide/bicarbonate (CO2/HCO3−) reflecting the gradual decrease of the redox potential. Most
microorganisms involved in anaerobic mineralization processes grow chemoorganoheterotro-phically, such as most denitrifying bacteria, manganese- or iron reducing bacteria, most sulfate reducing bacteria, fermenting bacteria, methane oxidizing bacteria and archaea. As a result, re-duced inorganic compounds, such as ammonium (NH4
+), nitrite (NO2−), NO3
−, ferrous iron (Fe2+) and reduced sulfur species, such as sulfide (H2S), elemental sulfur (S0), iron sulfide (FeS), thiosulfate (S2O3
2−) and sulfite (SO32−), accumulate in the sediment (Jørgensen, 2006; Herbert,
1999), which can subsequently be reoxidized by chemolithoautotrophic microorganisms. Chemolithoautotrophic microorganisms (bacteria and archaea) gain energy for growth using
chemical compounds as energy source (chemo-) in contrast to phototrophic organisms using light. Chemolithoautotrophs are able to use reduced inorganic compounds (litho-) as electron donor and inorganic carbon, CO2 and/or HCO3
−, as their only carbon source (-autotroph). The electron donors used by chemolithoautotrophic microorganisms comprise reduced nitrogen and sulfur compounds, as well as Fe2+, H2 and carbon monoxide (CO). Other microorganisms are able to assimilate organic carbon, while using inorganic electron donors, which is termed chemolithoheterotrophy, whereas those able to use inorganic or organic compounds as carbon source while utilizing inorganic electron donors are called mixotrophs. Many microorganisms use organic electron donors and fix organic carbon in a process known as chemoorganoheter-otrophy. Most chemolithoautotrophs are facultative chemolithoautotrophs, i.e. are able to grow chemolithoautotrophically as well as using a different metabolism. As chemolithoautotrophs are not able to synthesize adenosine triphosphate (ATP) from nicotinamide adenine dinucleotide (NADH) oxidation, most obligate chemolitoautotrophs couple the oxidation of their electron donors to the reduction of quinone or cytochromes supplying reducing equivalents for carbon fixation and biosynthesis through reverse electron transport (Kim and Gadd, 2008). Many per-form aerobic respiration using O2, while anaerobic chemolithoautotrophs use NO3
−, SO42−, CO2
or metal oxides as electron acceptors (Jørgensen, 2006). Chemolithoautotrophic microorganisms are metabolically versatile and able to use a broad
variety of electron donors for inorganic oxidation in coastal marine sediments (Table 1). Aer-obic and anaerobic ammonia oxidizing bacteria, sulfide oxidizing and sulfate reducing bacteria are believed to be the main contributors to chemolithoautotrophic carbon fixation in coastal
Chapter 1
2
Tabl
e 1:
Ver
satil
ity o
f ch
emol
ithoa
utot
roph
ic re
oxid
atio
n re
actio
ns/p
roce
sses
per
form
ed b
y m
icro
orga
nism
s in
coas
tal m
arin
e se
dim
ents
(mod
ified
fr
om Jø
rgen
sen,
200
6).
Ele
ctro
n do
natin
g re
actio
nPr
oces
sC
hem
olith
oaut
otro
phic
mic
roor
gani
sms
(e.g
.)
NH
4+ +
3 /2 O
2 →
NO
2− +
2H
+ +
H2O
amm
onia
oxi
datio
nam
mon
ia o
xidi
zing
bac
teria
(AO
B) (N
itros
omon
as),
amm
onia
oxi
dizi
ng a
rcha
ea (A
OA
) (N
itros
opum
ilus)
NO
2− +
½ O
2 → N
O3−
nitri
te o
xida
tion
nitri
fyin
g ba
cter
ia (T
hiob
acill
us, N
itrob
acter
)
NH
4+ +
NO
2− →
N2 +
2H
2Oan
aero
bic
amm
onia
oxi
datio
nan
amm
ox b
acte
ria (S
calin
dua
spp.
)
H2S
+ 2
O2 →
SO
42− +
2H
+
(oth
er p
ossib
le d
onor
s: SO
32−, S
2O32−
, S0 )
sulfu
r oxi
datio
nco
lorle
ss su
lfur b
acte
ria (T
hiob
acill
us, B
eggia
toa)
H2S
+ N
O3−
+H
+ +
H2O
→ S
O42−
+ N
H4+
(oth
er p
ossib
le d
onor
s: S0 ,
S 2O32−
)
sulfi
de o
xida
tion
coup
led
to
nitra
te re
duct
ion
to a
mm
onia
(D
NRA
)
deni
trify
ing
sulfu
r bac
teria
(Thi
obac
illus
den
itrifi
cans
),
nitra
te re
duci
ng su
lfur b
acte
ria (T
hiom
arga
rita)
,
larg
e su
lfur o
xidi
zing
bac
teria
(Beg
giatoa
)
4Fe2+
+ O
2 → 4
Fe3+
+ 2
H2O
(or M
n2+)
iron
and
man
gane
se o
xida
tion
iron
bact
eria
(Ferr
obac
illus
, She
wane
lla)
2H2 +
O2 →
2H
2Ohy
drog
en o
xida
tion
hydr
ogen
oxi
dizi
ng b
acte
ria (H
ydro
genob
acter
th
ermop
hilu
s)
4H2 +
SO
42– +
2H
+ →
4H
2O +
H2S
hydr
ogen
oxi
datio
n co
uple
d to
su
lfate
redu
ctio
nso
me
sulfa
te re
duci
ng b
acte
ria (D
esulfo
vibrio
spp.)
H2 +
CO
2 → C
H4
met
hano
gene
sism
etha
noge
nic
arch
aea
4H2 +
2C
O2 →
CH
3CO
OH
+ 2
H2O
acet
ogen
esis
acet
ogen
ic b
acte
ria
3
Introduction
marine sediments. In addition, many archaea are chemolithoautotrophs and representatives of the phylum Thaumarchaeota (formerly known as ‘marine group I Crenarchaeota’) have been determined to oxidize ammonia to gain energy for inorganic carbon fixation (Wuchter et al., 2003 and 2006; Könneke 2005, Brochier-Armanet et al., 2008) suggesting the contribution of archaea to the reoxidation of reduced inorganic compounds and inorganic carbon fixation in coastal marine sediments.
Chemolithoautotrophy in coastal sediments is generally considered to be insignificant in terms of biogeochemistry, due to the low growth yields of these microorganisms and the competition with photo- and heterotrophic processes, which are the main source of labile organic matter in coastal sediments (Jørgensen and Nelson, 2004). However, although chemolithoautotrophic microorganisms might play a minor role in terms of growth, they are able to reoxidize important amounts of reduced inorganic substrates (Cypionka, 2006). The dependency of chemolitho-autotrophic microorganisms on the availability of reduced inorganic compounds produced by chemoorganoheterotrophic microorganisms suggests a tight coupling between different micro-bial metabolic pathways in marine sediments. Unfortunately, direct measurements of chemo-lithoautotrophic activity are rare. Two rate measurements of dark CO2 fixation in shallow sub-tidal sediments of the Baltic Sea suggest that up to 20% of the inorganic carbon produced by mineralization appears to be reoxidized by chemoautotrophic microorganisms (Enoksson and Samuelsson, 1987; Thomsen and Kristensen, 1997). Only recently, chemolithoautotrophic sulfur oxidizing Gammaproteobacteria have been shown to contribute substantially to CO2 fixation by combined fluorescence in situ hybridization and microautoradiography (MAR FISH) analysis in the oxygen-, nitrate- and sulfide transition zone (0−3 cm) of intertidal sandy sediments (Lenk et al., 2011). Inorganic carbon fixation in coastal and ocean margin sediments, characterized by high organic carbon loadings, has been estimated to account for about 48% of the total oceanic chemoautotrophic carbon fixation rate (Middelburg, 2011). Considering the combination of high respiration rates and dominantly anoxic conditions, coastal and ocean margin sediments are presumably a hot spot for chemolithoautotrophy. The activity of chemolithoautotrophic microorganisms in coastal sediments has global implications for the cycling of carbon and the availability of nitrogen and sulfur compounds in marine environments. However, the diversity of chemolithoautotrophic microorganisms involved in nitrogen and sulfur cycling of coastal marine sediments, as well as the temporal and spatial distribution of their abundance and ac-tivity, is still poorly understood, especially in subsurface sediment layers. In the upper marine sediments, dark CO2 fixation is believed to be predominantly driven by oxidation of reduced nitrogen and sulfur compounds.
1.1. Chemolithoautotrophic contribution to nitrogen cycling in marine coastal sedimentsInorganic nitrogen concentrations (NH4
+, NO3−) in marine sediments are determined by the
sedimentation and decomposition rate of organic matter, as well as by diffusive transport rates and bioturbation. The cycling of nitrogen in coastal marine sediments consists of a series re-dox reaction performed by phototrophic, heterotrophic and autotrophic microorganisms and underlies complex regulatory mechanisms, comprising physicochemical and biological factors (Herbert, 1999; Joye and Anderson, 2006). The complexity of the cycle is revealed in Fig. 1.
Nitrogen fixation, e.g. the conversion of molecular nitrogen (N2) to bioavailable organic ni-
Chapter 1
4
Figu
re 1
: Nitr
ogen
cyc
ling
in c
oast
al m
arin
e se
dim
ents
(sim
plifi
ed a
nd m
odifi
ed fr
om H
erbe
rt, 1
999;
Joye
and
And
erso
n, 2
006)
. Das
hed
lines
indi
cate
di
ffus
ive,
adve
ctiv
e, or
sur
face
exc
hang
e be
twee
n co
mpa
rtm
ents
; sol
id li
nes
repr
esen
t mic
robi
al m
edia
ted
proc
esse
s. Bo
ld p
roce
ss in
dica
tes
chem
olith
o-au
totro
phic
con
tribu
tion.
5
Introduction
trogen compounds (Norg, e.g. proteins), is the initial step of the nitrogen cycling in marine sedi-ments. During the mineralization of organic nitrogenous matter ammonification, the release of NH4
+ occurs. The NH4+ released by ammonification is available for primary production and for
ammonia oxidation in the O2 transition zone of the sediment (Herbert, 1999). The fate of NH4+
regenerated in sediments may either be the adsorption to particles, the flux from the sediment to the overlying water, the consumption by biological processes within the sediment or at the sediment–water interface, the oxidation to NO2
− and then NO3− by nitrifying microorganisms,
or the transformation to molecular nitrogen (N2) via the denitrification and anammox process (Joye and Anderson, 2006).
1.1.1. Nitrification Nitrification is a two-step process, first ammonium is oxidized to NO2
− by chemolithoautotro-phic ammonium oxidizing bacteria (AOB) and archaea (AOA), which is then further oxidized to NO3
− by nitrite oxidizing bacteria (NOB) (Kim and Gadd, 2008). Aerobic ammonium ox-idation is a two-step process, in which ammonium is oxidized to hydroxylamine catalyzed by the enzyme ammonia monooxygenase (AMO). In bacteria, hydroxylamine is further oxidized to NO2
− by the enzyme hydroxylamine oxidoreductase (HAO), whereas in archaea, the oxida-tion of hydroxylamine to NO2
− may be catalyzed via nitroxyl oxidoreductase (NxOR) (Schlep-er and Nichol, 2010). In coastal marine sediments, AOB belong to the Gammaproteobacteria (Nitrosococcus oceanus) and to Betaproteobacteria (Nitrosomonas spp. and Nitrosospira spp.), based on the phylogenetic analysis of 16S rRNA genes (Herbert, 1999). Ammonia oxidizing archaea (AOA) belong to the distinct phylum of Thaumarchaeota (Brochier-Amanet et al., 2008). Most AOBs are obligate chemolithoautotrophs, whereas Thaumarchaeota can grow chemolithoau-totrophically (e.g. “Candidatus Nitrosopumilus” maritimus; Könneke et al., 2005) and possibly mixotrophically (e.g. “Nitrososphaera viennensis”; Tourna et al., 2011), besides heterotrophic growth cannot be ruled out (Pester, 2011). The communities of AOB and AOA seem to be favored by different physicochemical parameters, such as salinity, ammonia and O2 concentrations (Mosier and Francis, 2008; Santoro et al., 2008), with AOA preferring lower salinities and lower ammonia concentrations. The oxidation of NH4
+ plays an important role in generating nitrogen oxides (NO2
− and NO3−) for microorganisms utilizing these to gain energy for carbon fixation, such as
anammox and denitrifying bacteria.
1.1.2. Anammox Bacteria of the phylum Planctomycetes have been discovered to perform anaerobic ammonia oxidation (anammox) reaction, which consist on conversion of NH4
+ and NO2− into N2 while
growing chemolithoautotrophically (Strous et al., 1999, Kuypers et al., 2003). In addition to NO2
−, anammox bacteria are also able to use Fe3+, manganese oxides and NO3− as electron
acceptors in their metabolism (Strous et al., 2006). All five described anammox genera belong to the order Brocadiales and are related to the order Planctomycetales (Jetten et al., 2009), but at present only “Candidatus Scalindua” has been detected in marine sediments and O2 minimum zones (OMZs) (Daalsgard et al., 2005; Woebken et al., 2008; Lam et al., 2009). The contribution of the anammox process to the total nitrogen removal in marine sediments has been estimated to be between 0–80% (Dalsgaard, 2005).
Chapter 1
6
1.1.3. Denitrification After the consumption of dissolved O2 in the sediment pore water, organic matter decompo-sition continues via denitrification, anammox or dissimilatory nitrate reduction to ammonium (DNRA) (Zumft, 1997; Seitzinger, 2006). Whereas DNRA results in bioavailable ammonia, de-nitrification leads to the release of gaseous end products such as nitric oxide (NO), nitrous oxide (N2O), and dinitrogen gas (N2) to the atmosphere. Dissimilatory denitrification, the microbial oxidation of organic matter with NO3
− or NO2− as terminal electron acceptor, is considered to
be the sequence of nitrate respiration, nitrite respiration combined with NO reduction, and N2O respiration: NO3 → NO2 → NO → N2O → N2. The denitrification process is performed by facultative chemoorganoheterotrophic bacteria, some archaea and foraminifera (Zumft, 1997; Risgaard-Petersen et al., 2006), and occurs as well in chemolithoautotrophic organisms perform-ing the oxidation of an inorganic compound such as H2S coupled to nitrogen oxide reduction. Recently, sulfide-dependent denitrification, performed by autotrophic members of Alpha-, Beta- Gamma-, and Epsilonproteobacteria (especially Thiobacillus denitrificans and Sulfurimonas denitrifi-cans), has been suggested to play a major role in the denitrification process in the oxygen- and sulfide- transition zone of coastal marine sediments (Shao, 2010).
The processes of nitrification and denitrification in sediments are the major source of NO3−
for denitrification in some estuaries and shelf regions. In systems with low NO3− concentrations
(<10 μM) in the oxygenated bottom water, coupled nitrification/denitrification accounts for 90% of the NO3
− that is required for denitrification (Risgaard-Petersen, 2003). However, cou-pled nitrification/denitrification is a mechanism that can be responsible for substantial nitrogen removal from the sediment, which is in turn not available for primary producers. Nitrogen re-moval by denitrification, including anammox, might control the rate of eutrophication in coastal marine systems that receive large amounts of anthropogenic nitrogen (Herbert, 1999).
1.2. Chemolithoautotrophic sulfur cycling in coastal marine sediments Below the oxygen penetration depth (OPD) and after the depletion of electron acceptors, such as oxygen, NO3
−/NO2−, and metal oxides, sulfate reduction to H2S becomes the prevalent mi-
crobial redox process in marine sediments (Jørgensen, 2006). Sulfate reduction, the reduction of elemental sulfur (S0) and sulfur disproportionation can result in H2S production and upward diffusion. Most H2S is reoxidized by chemical and microbial mediated sulfur oxidation or buried as iron sulfide and pyrite (FeS, FeS2).
1.2.1. Sulfate reducing microorganisms Sulfate reducing microorganisms have a key role in the sulfur cycle, they use SO4
2– as a terminal electron acceptor in the degradation of organic matter, which results in the production of H2S (Muyzer and Stams, 2008), which subsequently can be oxidized aerobically and anaerobically by sulfur oxidizing bacteria (e.g. Thiobacillus or Beggiatoa spp.). During dissimilatory sulfate reduc-tion, SO4
2− is activated by the enzyme ATP sulfurylase, catalyzing the formation of adenosine phosphosulfate (APS) from SO4
2− and phosphate (ATP). The SO42− in APS is directly reduced
to SO32− by the cytoplasmic enzyme adenosine-5’ phosphosulfate (APS) reductase, which is then
further reduced to H2S by the enzyme sulfite reductase. Sulfate reducing microorganisms are metabolically and genetically divers, some grow chemoorganoheterotrophically by using acetate, propionate, butyrate or lactate as electron acceptor, whereas many chemolithoautotrophic repre-
7
Introduction
sentatives use hydrogen as electron donor and SO42− as electron acceptor while utilizing CO2 as
carbon source (e.g. Desulfovibrio spp.). Sulfate reducing bacteria belong to the class of Deltapro-teobacteria, as well as to the phyla of the Firmicutes and Nitrospirae. Within the archaea, sulfate reducing representatives belong to the genus Archaeglobus within the phylum of Euryarchaetoa, and to the phylum of Crenarchaeota (Muyzer and Stams, 2008). The activity of sulfate reducing microorganisms is especially important in organic-rich sediments underlying highly productive waters of continental shelves and slopes (Jørgensen, 1982a, b; Jørgensen and Kasten, 2006). It has been estimated that sulfate reduction can account for more than 50% of the organic carbon mineralization in marine sediments (Jørgensen, 1982a, b).
1.2.2. Sulfur oxidizing microorganisms in marine sediments Sulfur oxidation, i.e. the oxidation of reduced sulfur compounds, such as H2S, SO3
2−, S2O32−,
S0, to SO42− can be performed by taxonomical divers chemolithoautotrophic bacteria and some
archaea, using mainly O2 and NO3− as electron acceptor, which ultimately links the carbon-,
nitrogen- and sulfur cycling in marine sediments. Sulfide oxidation starts with the conversion of H2S (sulfur, thiosulfate) to sulfite. Some sulfur oxidizing chemolithoautotrophs use the enzyme sulfite oxidase, which transfers electrons directly to cytochrome c generating ATP during elec-tron transport and proton motive force formation. Others use the enzyme adenosine-5’ phos-phosulfate (APS) reductase, which is an essential enzyme of sulfate reducing bacteria, which results in SO4
2− production in sulfur oxidizers (Meyer and Kuever, 2007b). Chemolithoautotrophic bacteria belonging to the class of Betaproteobacteria (Thiobacillus),
Gammaproteobacteria (Thiomicrosprira), and to the Epsilonproteobacteria (Acrobacter, Sulfuri-monas, Sulfurovum), have been shown to contribute to chemolithoautotrophic sulfide oxidation in coastal marine sediments (Jørgensen and Nelson, 2004; Campbell et al., 2006; Lenk et al., 2011). Chemolithoautotrophic sulfur oxidizing bacteria are taxonomically broad, while chemolithoau-totrophic sulfur oxidizing archaea seem to be restricted to Sulfolobales (Crenarchaeota) using metal oxides, Thermoplasmatales (Euryarchaeota) using elemental sulfur, and only two genera seem to be able to oxidize H2S, i.e. Acidianus sulfidivorans and Ferroglobus placidus, using NO3
− and Fe3+ as electron acceptors (Hafenbradl et al., 1996; Plumb et al., 2007).
Additionally, large sulfur bacteria, Gammaproteobacteria of the order Thiotrichales (Beggiatoa, Thioploca, Thiomargarita), contribute substantially to sulfide oxidation in coastal marine sediments. Under low O2 conditions, Beggiatoaceae are able to store NO3
− in an internal vacuole at the sediment surface, before gliding into anoxic and sulfidic layers, where they oxidize H2S to S0 with the stored NO3
−. Here, S0 is stored in globules and transported back to the surface to complete the oxidation to sulfate. Most members of the marine Beggiatoaceae family are chemolithoau-totrophs, some species are able to use an organic carbon source for mixotrophic or chemooar-ganoheterotrophic growth (Mußmann et al., 2003; Jørgensen and Nelson, 2004).
1.3. Autotrophic CO2 fixation pathways of microorganisms Up to date six different CO2 fixation pathways used by taxonomically diverse bacteria and ar-chaea have been discovered (Fig. 2). In the Calvin-Benson-Bassham (CBB) cycle, CO2 reacts with ribulose 1,5-bisphosphate to gain two 3-phosphoglycerate, from which the sugar is formed. Apart from eukaryotes such as plants and algae, the CBB cycle is utilized by cyanobacteria, many aerobic or facultative aerobic Proteobacteria belonging to the Alpha-, Beta-, and Gamma- classes
Chapter 1
8
(including AOB), Sulfobacillus spp., iron and sulfur oxidizing Firmicutes, some mycobacteria, and bacteria of the phylum Chloroflexi (Oscillochloris) (Berg et al., 2010). The CBB cycle prevails un-der oxic conditions, whereas the more energy efficient and less O2 sensitive reductive tricarbox-ylic acid (rTCA) cycle is restricted to microaerobic and anaerobic conditions (Berg et al., 2010). The rTCA cycle reverses the reactions of the oxidative citric acid (Krebs-) cycle and operates in sulfate reducing Delta- and sulfur oxidizing Epsilonproteobacteria, green sulfur bacteria and in microaerophilic bacteria of the phylum Aquificae (Hügler et al., 2005; Campbell et al., 2006).
The strictly anaerobic reductive acetyl-coenzyme A (acetyl-CoA) pathway is a noncyclic path-way, in which one CO2 molecule is reduced to CO and one to a methyl group, from which acetyl-CoA is synthesized subsequently. The acetyl-CoA pathway functions in acetogenic and methanogenic bacteria, as well as in anammox bacteria (Planctomycetes), sulfate reducing Del-taproteobacteria (Desulfobacterium sp.), and in Euryarchaeota (Archaeglobales). The 3-hydroxy-propionate bicycle is currently restricted to members of the Chloroflexacae family. The 3-hydroxy-propionate/4-hydroxybutyrate cycle occurs in aerobic Crenarchaeota (Sulfolobales) and marine Thaumarchaeota (AOA), whereas the dicarboxylate/4-hydroxybutyrate cycle functions in anaer-obic Crenarchaeota of the orders Thermoproteales and Desulfurococcales. The prevalence of CO2 fixation pathways utilized by chemolithoautotrophic microorganisms in seasonally hypoxic coastal marine sediments is poorly known at present (Berg et al., 2010, and 2011).
Thaumarchaeota
Figure 2: Phylogenetic classification of autotrophic bacteria and archaea; green: Calvin-Benson-Bassham cycle, red: reductive tricarboxylic acid cycle, blue: reductive acetyl-CoA cycle, orange: 3-hydroxypropionate bicycle, purple: 3-hydroxypropionate-/ 4-hydroxybutyrate cycle, brown: dicarboxylate/4-hydroxybutyrate cycle (Figure modified from Hügler and Sievert, 2011).
9
Introduction
1.4. Physicochemical parameters affecting microbial chemolithoautotrophy in coastal marine sedimentsVarious abiotic and biotic factors control the abundance and activity of chemolithoauto trophic microorganisms involved in carbon-, nitrogen-, and sulfur cycling in marine sediments. Gener-ally, O2 is one of the most important ecological factors influencing chemolithoautotrophy, espe-cially in the oxygen transition zones of coastal marine sediments, where O2 is depleted within the first millimeters. The O2 concentration shapes the distribution of different autotrophic carbon fixation pathways, as well as the availability of suitable electron donors and acceptors, metals and coenzymes (Berg, 2011). Whereas nitrification is predominantly an obligate aerobic process, denitrification is a facultative anaerobic process, most denitrifiers prefer to respire O2 instead of NO3
− when O2 concentrations exceed 20 mM (Tiedje, 1982). Anammox bacteria are obligate anaerobes and despite their O2 tolerance, the activity seems to be limited to anoxic conditions (Dalsgaard et al., 2005; Risgaard-Petersen et al., 2004, and 2005).
Coastal regions, especially estuaries and coastal areas with limited water exchange, often ob-tain large amounts of anthropogenic nitrogen leading to eutrophication, (Howarth and Marino, 2006). Hypoxia is one of the common features of eutrophication and the phenomenon of seasonal hypoxia has expanded over the last decades in coastal regions. Seasonal hypoxia causes a decrease in the availability of electron acceptors, i.e. O2 and NO3
− in the bottom water (Rosen-berg and Diaz, 2008), suggesting consequences for chemolithoautotrophic microorganisms in-volved in carbon-, nitrogen-, and sulfur cycling in marine coastal sediments and thus for the biogeochemistry in marine sediments (Middleburg and Levin, 2009).
Extensive sulfate reduction leads to the accumulation of free H2S in anoxic sediments, which is diffusing upwards (Jørgensen and Nelson, 2004). Sulfide has been shown to inhibit ammonia oxidation (Joye and Hollibaugh, 1995), as well as enzymes catalyzing the last steps of denitrifica-tion (Sørensen, 1980; Porubsky et al., 2009). The effect of H2S on anammox is relatively unclear, but there is certain evidence, that the activity of anammox bacteria is inhibited in sulfidic waters of oxygen minimum zones (Daalsgaard 2003; Jensen et al., 2008), suggesting that the abundance and activity of anammox bacteria might as well be inhibited by rising H2S concentrations in coastal marine sediments.
However, it is well known that high concentrations of free H2S are toxic for benthic animals, such as bioturbating organisms (Vaquer-Sunyer and Duarte, 2008). The key role of bioturbation in nutrient cycling is well established (Meysman et al., 2006) and has been suggested to extend the area of O2 availability in deeper sediment layers, supporting aerobic microbial processes, such as nitrification, which in turn might fuel anammox and denitrification (Meyer et al., 2005). Recently, bioturbation has been shown to induce changes in the sedimentary microbial commu-nity composition, resulting in distinct communities within the burrow (Laverock et al., 2010).
1.5. Methods to study microbial chemolithoautotrophyThe majority of microorganisms that occur in natural environments cannot be cultured or iso-lated using traditional cultivation techniques, which limits our knowledge of environmental mi-crobial diversity (Rappé et al., 2003). In the last decades, a wide range of cultivation independent approaches have been developed to understand the abundance, diversity and metabolic activity of microbial communities in the environment using a wide range of organic and inorganic
Chapter 1
10
biomarker molecules, such as DNA/RNA and lipids, as well as the incorporation of labeled substrates into biomarker molecules.
1.5.1. Abundance and diversity of chemolithoautotrophic microorganisms using DNA-based methods The analyses of DNA sequences of microorganisms has expanded our knowledge of the tax-onomic and functional diversity of marine microbes to a large extent. Molecular methods re-vealed a diverse community of microorganisms with diverse metabolic capabilities, new species and novel pathways of organic matter cycling (Delong, 1992; Fuhrman et al., 1992). Advances in molecular microbiology allow for DNA sequence analysis and comparison to sequences that are already available in sequence databases. The development of quantitative PCR (qPCR) for the real time quantification of selected DNA sequences (genes) can be used to estimate the abundance of specific groups of microorganisms. In general, two kinds of genes are normally targeted, the 16S rRNA gene and functional genes.
The 16S ribosomal RNA is part of the 30S small subunit of a prokaryotic ribosome, and the 16S rRNA gene sequence has been used to reconstruct the microbial phylogeny (Woese and Fox, 1977). The 16S rRNA gene sequence is especially useful because as it is present in all Domains of life, i.e. Bacteria, Archaea and Eukarya. Variable regions of the 16S rRNA gene are diagnostic for specific groups of organisms, whereas highly conserved regions can be used to assess the diversity of the microbial community. Sequencing of the highly conserved and species specific 16S rRNA gene has been extensively used to characterize the microbial community in marine surface and subsurface sediments (Madsen, 2008). Nevertheless, the rapid development of new generation sequencing methods allows for high throughput sequencing, and 16S rRNA gene am-plicon sequencing has been shown to be a powerful tool to study the diversity of the microbial community as well as the relative abundance of specific groups in a high resolution in the marine environment (Gilbert and Dupont, 2011; Klindworth et al., 2013; Cruaud et al., 2014).
As the 16S rRNA gene gives only limited and indirect information about the metabolism, i.e. the contribution to CO2 fixation and reoxidation pathways, functional gene analysis, i.e. genes encoding for key-enzymes involved in different CO2 fixation and reoxidation pathways, is a powerful tool to study the diversity and abundance of chemolithoautotrophic microorganisms. Gene sequences, i.e. the cbbL gene coding for ribulose 1,5-bisphosphate carboxylase/oxygenase (RuBisCO) and the aclB gene coding for the ATP-citrate lyase, functioning in the CBB and rTCA cycle respectively, have been used to assess the diversity of chemolithoautotrophic microorgan-isms in intertidal mudflat sediments as well as in hydrothermal vent sediments and in sediments with an oxygen-sulfide chemocline (Nigro and King, 2007; Campbell et al., 2003, and 2006). However, the temporal and spatial distribution of the diversity and the abundance of chemolith-oautotrophic microorganisms using the CBB or rTCA cycle have rarely been studied in coastal marine sediments. Some important key-enzymes and their corresponding functional genes for inorganic carbon assimilation and reoxidation pathways are summarized in Table 2.
The key-enzyme of aerobic ammonia oxidation is a membrane-bound putative ammonia monooxygenase (AMO), catalyzing the oxidation of ammonium to hydroxylamine in Bacteria (Rotthauwe et al., 1997) and Archaea (Venter et al., 2004; Könneke et al., 2005; Yakimov et al., 2009). The metabolic gene amoA, encoding AMO, has been used to analyze the diversity and abundance of AOA and AOB in estuarine sediments (Beman and Francis, 2006; Mosier and
11
IntroductionTa
ble
2: Im
port
ant f
unct
iona
l gen
es o
f C
O2 fi
xatio
n an
d re
oxid
atio
n pa
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Prim
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ces a
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port
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the
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.
Path
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Key
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Func
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reoxidation
Am
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arch
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)
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c
Chapter 1
12
Francis, 2008; Abell et al., 2010) and in sandy coastal sediments (Santoro et al., 2008). Howev-er, the spatial and temporal distribution of the diversity and abundance of microbial ammonia oxidizers, as well as of anammox bacteria, denitrifiers, sulfate reducers and sulfur oxidizers, in seasonally hypoxic sediments, is still unknown. The hzsA and nirS gene of anammox bacteria, encoding for the hydrazine synthase (HZO) and cytochrome cd1-containing nitrite reductase (NIR), have been proposed as suitable biomarker to detect anammox bacteria diversity and abundance in the marine environment (Kartal et al., 2011; Harhanghi et al., 2012; Lam et al., 2009) as well as in marine sediments (Li et al., 2011). The cytochrome cd1-containing nitrite re-ductase, coded by the nirS gene, operates as well in the dissimilatory denitrification process, cata-lyzing the reduction of NO2
− to NO, the first gaseous product in the sequence of denitrification (Zumft, 1997; Braker, 1998). The nirS gene has been used to study the diversity and to estimate the abundance of denitrifying microorganisms in estuarine sediments (Smith at al., 2007; Mosi-er and Francis, 2010). The diversity of sulfate reducing and sulfur oxidizing microorganisms have been studied using the aprA gene encoding the disssimilatory adenosine-5’ phosphosulfate (APS) reductase, which is a key enzyme in sulfate reduction and sulfur oxidation processes. The APS reductase catalyzes the conversion of APS to AMP and SO3
2− in sulfate reducing micro-organisms, and operates in the reverse direction in sulfur oxidizing microorganisms. The highly conserved aprA gene has been shown to be a suitable biomarker to profile the community struc-ture of sulfate reducing and sulfur oxidizing microorganisms in marine and estuarine sediments (Meyer and Kuever, 2007c, Muyzer and Stams, 2008).
1.5.2. Archaeal and bacterial membrane lipids as taxonomic markers Membrane lipids are considered as taxonomic markers that can be used to estimate the abun-dance, distribution, and physiological status of certain microbial groups (White, 2007). In ad-dition, these lipids can be preserved in sediments upon cell depth and thus being used as bio-markers of the presence of certain organisms both in present and past ecosystems. On the contrary, other biomolecules like DNA have a more rapid turnover and they cannot be used for this purpose. In recent years, intact polar lipids (IPLs) are increasingly applied for tracing ‘living’ bacteria and archaea in the environment (Lipp et al., 2008; Rossel et al., 2008; Lipp and Hinrichs, 2009). IPLs with polar head groups are present in living cells but upon cell lysis the polar head groups are lost, releasing the core lipids (CLs) that may be preserved in the fossil record. Since IPLs degrade relatively quickly after cell death (Harvey et al., 1986), it is possible to associate the presence of IPLs in the environment with the occurrence of their living producers (Zink et al., 2003; Biddle et al., 2006; Huguet et al., 2010; Schubotz et al., 2009). Specifically, IPLs with phos-pho- head groups have been shown to degrade rapidly after cell death, while IPLs with glycosidic polar head groups might be preserved in the sediment record (White et al., 1979; Harvey et al., 1986; Bauersachs et al., 2010; Lengger et al., 2012).
Membrane lipids from bacteria and eukaryotes are composed of fatty acid chains that are linked to the glycerol moiety through ester bonds and organized in a bilayer structure. On the other hand, archaeal membrane lipids are characterized by ether bonds, isoprene-based alkyl moieties, and an opposite stereochemistry of the glycerol phosphate backbone, i.e. sn-glycer-ol-1-phosphate (G1P). Archaeal membrane lipids are typically a variation of two main struc-tures, sn-2,3-diphytanylglycerol diether (archaeol) with phytanyl (C20) chains in a bilayer structure, and sn-2,3-dibiphytanyl diglycerol tetraether (glycerol dibiphytanyl glycerol tetraether, GDGT), in which the two glycerol moieties are connected by two C40 isoprenoid chains, allowing the
13
Introduction
formation of monolayer membranes (Koga and Morii, 2007). GDGTs have been found to be ubiquitous in the marine water column and sediments (Schouten et al., 2000). Isoprenoid GDG-containing 0–8 cyclopentane moieties (Fig. 3) are commonly found in different archaeal groups, such as Thaumarchaeota (Wuchter et al., 2006), extremophiles (Huber et al., 1998; Lattuati et al., 1998; Ellen et al., 2009), methanogens (Koga et al., 1998; Gattinger et al., 2002; Zhang et al., 2011), and anaerobic methane-oxidizing archaea, ANME (Pancost et al., 2001). However, the isoprenoid GDGT crenarchaeol (Sinninghe Damsté et al., 2002a), containing four cyclopen-tane moieties and a cyclohexane moiety, is considered to be characteristic of Thaumarchaeota (Schouten et al., 2000; Sinninghe Damsté et al., 2002a; Zhang et al., 2006; Pester et al., 2011; Pitcher et al., 2011a). The culture-based GDGT compositions of the main archaeal groups, which are potentially involved in chemolithoautotrophy and sulfur metabolism in marine sedi-ments, are summarized in Table 3.
The distribution of thaumarchaeotal GDGTs in the marine environment has been shown to be affected by temperature, i.e. with increasing temperature there is an increase in the relative abundance of cyclopentane-containing GDGTs (Schouten et al., 2002; Wuchter et al., 2004, and 2005). Based on this relationship, the TEX86 paleotemperature proxy was developed and calibrated using sea surface temperature and it has been widely applied for more than a decade
Table 3: Membrane lipid composition of the main groups of archaea involved in chemolithoautotro-phy and sulfur metabolism in marine sediments (modified from Villanueva et al., 2014). Species specific GDGT occurrence and distributions of pure cultures are described in detail in Schouten et al. (2013) and references therein.
Phylum Order Metabolism Membrane lipid
Thaumarchaeota
(AOA)
Cenarchaealesammonia oxidizer
autotroph
GDGT-0 to 4,
crenarchaeol
Nitrosopumilalesammonia oxidizer
autotroph/mixotroph
GDGT-0 to 4,
crenarchaeol
Nitrosospheralesammonia oxidizer
autotroph
GDGT-0 to 4,
crenarchaeol
Crenarchaeota
Desulfurococcales sulfur dependent GDGT-0 to 4,
Sulfolobales sulfur dependentGDGT-0 to 4,
GDGT-5 to 8
Thermoproteales sulfur dependentGDGT-0 to 4,
GDGT-5 to 8
Euryarchaeota
Thermoplasmatales sulfur dependentGDGT-0 to 4,
GDGT-5 to 8
Thermococcales sulfur dependentarchaeol,
GDGT-0Archaeglobales sulfur dependent GDGT-0
ANME-clustermethane oxidation
chemoorganoautotrophGDGT-0 to 4
Chapter 1
14
(Schouten et al., 2002). However, evidences increasingly demonstrate that temperature is not the only variable affecting the GDGT distribution (Schouten et al., 2013, Pearson et al., 2013). For example, TEX86 responds to temperature in a different way in enrichments (Schouten et al., 2007a) and cultures (Pitcher et al., 2011a) than in suspended particulate matter (SPM) or when fossilized in surface sediments (Kim et al., 2010). It is also known that TEX86 does not reflect surface temperatures but rather subsurface temperatures (Huguet et al., 2007; Lopes dos Santos et al., 2010; Kim et al., 2010), and that archaeal production in the deeper water column may also contribute to the signal of GDGTs in sediments (Pearson et al., 2001; Shah et al., 2008). In addi-tion, the TEX86 signal may also be affected by input from other archaea, which could potentially synthesize GDGTs used in TEX86. For example, it has been suggested that in situ produced lipids of benthic and methanogenic archaea might contribute to the GDGT pool in marine sediments, which might be relevant for the reliability of the TEX86 proxy (Weijers et al., 2006a; Blaga et al., 2009; Sinninghe Damsté et al., 2012a). In addition, some studies have suggested that benthic archaea might be able to recycle core lipid GDGTs in marine sediments (Takano et al., 2010; Liu et al., 2011).
Recent advances in high performance liquid chromatography (HPLC)- mass spectrometry (MS) methods have allowed the analysis of core GDGTs as well as IPL GDGTs. IPL GDGTs have been analyzed by separating them from the core lipids using silica gel chromatography and hexane/EtOAc mixtures as eluent (Oba et al., 2006; Pitcher et al., 2009) followed by acid hydrolysis and high pressure liquid chromatography coupled via an atmospheric pressure chem-ical ionization interface to a mass spectrometer (HPLC−APCI−MS) (Hopmans et al., 2000; Sturt et al., 2004; Schouten et al., 2007a). With this method, IPL derived core GDGTs can be quantified using internal standards, but it does not allow to specify the kind of head group that was attached to the GDGT. In contrast, the development of HPLC combined with electrospray chemical ionization mass spectrometry (HPLC−ESI−MS), allows to analyze GDGT IPLs, with
Figure 3: Structures of isoprenoid GDGTs (0–8) and crenarchaeol (mod. from Schouten et al., 2013).
15
Introduction
the polar head group still attached to the core (Rütters et al., 2002; Zink et al., 2003; Sturt et al., 2004). Core and intact polar GDGTs have been analyzed by HPLC-ESI-MS2 in selected reac-tion monitoring (SRM) (Schouten et al., 2008a), in AOA sediment enrichment cultures, includ-ing “Candidatus Nitrosoarchaeum limnia” (Pitcher et al., 2011a), as well as in marine sediments (Lengger et al., 2012). Polar headgroups of creanarchaeol have been seen to be mainly com-prised by monohexose (MH), dihexose (DH), phosphohexose (PH) and hexose-phosphohexose (HPH) (Fig. 4) (Pitcher et al., 2011a). Results suggest that HPH-crenarchaeol is the most suitable lipid biomarker to trace living Thaumarchaeota of marine group I.1a due to the labile nature of the phosphate bond (Harvey et al., 1986; Schouten, et al., 2010) in comparison with glycosidic crenarchaeol-IPL-GDGTs. Additionally, it has been shown that the HPH-crenarchaeol con-centration corresponds well to DNA-based thaumarchaeal abundance (Pitcher, 2011a and b; Schouten et al., 2012a; Lengger et al., 2012).
Bacterial membrane lipids are composed by fatty acids linked by ester bonds to the glycer-ol-3-phosphate backbone. The phospholipid-linked fatty acids (PLFAs) have been extensively used to characterize bacteria and eukaryotic microorganisms in different environmental settings including estuarine sediments (Guckert et al., 1985). PLFAs have complex structures with dif-ferent carbon lengths, unsaturations, methylations and isomers (Vestal and White, 1989) and in some cases, PLFA signatures are specific enough to pinpoint shifts in the bacterial and eukary-otic community composition (Boschker and Middleburg, 2002) (Table 4), but it does not offer a high taxonomic resolution compared to DNA/RNA-based methods. PLFA concentrations can be analyzed by gas chromatography (GC)-flame ionization detection (FID) and MS according to a method previously described (Boschker et al., 1998).
Other membrane lipids, present in microbial cells can be used as biomarkers of the presence of their producer. For the case of chemolithoautotrophic microorganisms of importance in ma-rine sediment, the specific lipids contained in anammox bacteria are a clear example. Anammox bacteria contain a membrane bound compartment in the cytoplasm, the anammoxosome, in
Figure 4: Main head groups of crenarchaeol detected in cultures of “Ca. Nitrosopumilus maritimus”, “Ca. Nitrososphaera gargensis” and “Ca. Nitrosoarchaeum limnia”, as well as in marine sediments.
Chapter 1
16
which the anammox reaction takes place (van Niftrik et al., 2008). The anammoxosome consists of ladderane lipids with three or five linearly arranged cyclobutane rings (Sinninghe Damsté et al., 2002b). Ladderane lipids can be either ester- or ether bound to glycerol and major polar headgroups are phosphatidylcholine (PC), phosphoetanolamine (PE) and phosphoglycerol (PG) (Boumann et al., 2006; Rattray et al., 2008). Whereas ladderane core lipids have been shown to be suitable biomarkers for anammox bacteria abundance in the fossil sediment record, the C20-[3]-monoether ladderane lipid attached to a PC head group has been shown to be a suitable
Table 4: PLFA signatures of the main groups of chemoautotrophic bacteria in marine sediments. The rel-ative contributions of the main fatty acids to the total PLFA composition and complete PLFA signatures are described in the listed references (mod. from Vasquez-Cardenas, 2016). For details on the nomencla-ture of PLFAs see supplementary information.
Metabolism PLFA signature Reference
Ammonium oxidizers16:1ω7c
16:0Blumer et al., 1969
Nitrite oxidizers16:1ω7c
16:018:1ω7c
Lipski et al., 2001Blumer et al.,1969
Sulfate reducers(Deltaproteobacteria)
14:015:0i15:0
16:1ω7c16:0
i17:1ω7c17:1ω6c18:1ω7c
Taylor and Parks, 1983Edlund et al., 1985Suzuki et al., 2007Pagani et al., 2011
Mat forming sulfur oxidizers(Gammaproteobacteria)
14:016:1ω7c16:1ω7t
16:018:1ω7c
Zhang et al., 2005Li et al., 2007
Sulfur oxidizers(Epsilonproteobacteria)
14:016:1ω7c
16:018:1ω7c
Inagaki et al., 2003Takai et al., 2006
Donachie et al., 2005
Iron and Sulfur oxidizers
16:1ω7c16:0
cy17:0cy19:0
Knief et al., 2003
17
Introduction
biomarker for living anammox bacteria in continental shelf sediments (Jaeschke et al., 2010). Ladderane core lipids can be analyzed as fatty acid methyl esters (FAMEs) by HPLC-APCI-MS2 in selective reaction monitoring (SRM) mode as previously described (Hopmans et al., 2006) and modified to include short chain fatty acids (Rush et al., 2012). The PC-monoether ladderane lipid can be analyzed by HPLC-MS2 (Jaeschke et al., 2009), and quantified using an external PC-mon-oether ladderane standard. Main structures of ladderane core lipids and the intact PC-mono-ether ladderane lipid are summarized in Fig. 5.
1.5.3. Determining the activity of chemolithoautotrophic microorganisms The determination of active (chemolithoautotrophic) microorganisms in marine sediments has been a challenge and has been addressed using different methods by targeting the metabolic process or the activity of specific groups or specific microorganisms.
In sediments, microsensor profiling, i.e. concentration measurement of respiratory gases O2 and H2S has been used to identify active microbial processes, such as photosynthesis, respira-tion and sulfur oxidation (Nielsen et al., 1990; Schramm et al., 1996). The activity of microbes participating in nitrogen cycling processes, such as nitrification, denitrification and anammox, have been estimated by isotope tracer experiments with 15N- and 14N-labeled NO3
−, NO2− and
NH4+ by the discrimination of isotope pairing in marine sediments (Nielsen, 1992; Rysgaard et
al., 1993). Microsensor profiling, as well as isotope tracer experiments, are adequate methods to measure overall process rates, but do not provide any taxonomic information about metaboli-cally active microorganisms.
In contrast, the expression of functional genes, i.e. the quantification of mRNA by reverse transcription (Holmes et al., 2004) and subsequent qPCR, has been proposed to be a good marker to determine the activity of specific microorganisms in the marine environment. The positive gene expression of functional genes may serve as evidence for active in situ processes and provide insight into the diversity of active microorganisms (Nogales et al., 2002; Wellington
Figure 5: Chemical structures of ladderane core lipids and the intact PC-monoether ladderane lipid.
Chapter 1
18
et al., 2003). For the case of chemolithoautotrophic microorganisms, the transcript abundance of the ar-
chaeal amoA gene has been quantified to estimate the activity of Thaumarchaeota in oceanic waters, showing that marine Thaumarchaeota are actively involved in ammonia oxidation in the water column of the Pacific Ocean, as well as in the Peruvian OMZ and in the Mediterranean Sea (Lam et al., 2009; Church et al., 2010; Yakimov et al., 2011). Additionally, gene expression of the bacterial and archaeal amoA gene has been analyzed in soil, as well as in estuarine sediments as a measure of the transcriptional activity, indicating the protein production potential (Nicol et al., 2008; Abell et al., 2011). In estuarine sediments, the expression of bacterial amoA genes was reduced at low dissolved O2 (DO) concentrations, whereas the archaeal amoA gene expression was not affected, suggesting that AOB and AOA show different responses to changes in sedi-ment DO, which may be a significant factor in niche partitioning of different ammonia oxidizer groups. The gene expression of other functional genes has also been determined as an indicator for the potential activity of specific groups. For example, the nirS transcript abundance of de-nitrifying bacteria has been quantified in estuarine sediments (Nogales et al., 2002; Smith et al., 2007; Bulow et al., 2008), showing the decrease of potentially active denitrifying bacteria from the head to the mouth of the estuary. The nirS transcript abundance of anammox bacteria has been used to estimate the potential activity of anammox bacteria, showing the contribution of anammox bacteria to nitrogen removal the Peruvian oxygen minimum zone (Lam et al., 2009).
Stable carbon isotopes have been also used to track the activity of microorganisms in marine sediments. In contrast to radioactive isotopes (14C), stable carbon isotopes (12C, 13C) do not decay in nature and are less harmful. In nature, stable carbon and nitrogen isotopes occur in different abundances. Whereas the isotope with the low mass (e.g. 12C) is highly abundant (98%), the isotope with the higher mass (e.g. 13C) represents less than 2% (Fry, 2006). The difference in the abundance gives the possibility to track the cycling of elements by the metabolic incorporation of 13C into specific molecules. The labeled substrate is added to an environmental sample (e.g. intact sediment core) and biomarkers are purified and analyzed following the consumption of the substrate. Stable isotope probing (SIP) has been applied to track the incorporation of 13C substrates into membrane lipids, such as archaeal GDGTs (Wuchter et al., 2003), IPL derived GDGTs (Pitcher et al., 2011b) and bacterial PLFAs (Boschker et al., 2002). The 13C incorpo-ration into the biphytanes of GDGTs and into PLFAs can be measured by chromatography combustion isotope ratio mass spectrometry (GC-c-IRMS) (Boschker et al., 1998; Wuchter et al., 2003; Pitcher et al., 2011b). GDGT SIP, i.e. the incorporation of 13C labeled bicarbonate into the biphytanyl chains of crenarchaeol revealed the capability of Thaumarchaeota to grow auto-trophically (Wuchter et al., 2003), which was later confirmed by the isolation and physiological characterization of Candidatus Nitrosopumilus maritimus (Könneke et al., 2005). SIP has been used to label membrane lipids, as well as to track the incorporation of 13C into nucleic acids, such as DNA (DNA-SIP) and RNA (RNA-SIP) (Radajewski et al., 2000, and 2003). PLFA-SIP is the most sensitive method, whereas the DNA-SIP is the less sensitive approach. In contrast to RNA and PLFA, the replication of DNA depends on cell division in presence of the labeled substrate, which makes it difficult to accomplish sufficient incorporation for separation of labeled DNA (Neufeld et al., 2006).
A method that does not imply extraction of labeled compounds, but rather visualizes active microbial cells that have been targeted with a sequence specific labeled probe under the micro-
19
Introduction
scope, is fluorescence in situ hybridization (FISH). The combination of FISH with catalyzed reporter deposition (CARD-FISH) has been used to estimate the abundance of active microor-ganisms in the marine environment, targeting DNA and RNA molecules as well as rare mole-cules, such as mRNA and genes, with signal amplification using horseradish peroxidase (HRP) (Llobet-Brossa et al., 2002; Pernthaler et. al., 2002; Ishii et al., 2004). For example, the abun-dance of Crenarchaeota has been estimated by CARD-FISH in water samples of the Atlantic Ocean (Wuchter et al., 2006). CARD-FISH has been also combined with other approaches to determine metabolic activity in chemolithoautotrophic microorganisms. For example, catalyzed reporter deposition (CARD)-FISH combined with microautoradiography (MAR) demonstrated that novel groups of Gammaproteobacteria attached to sediment particles have been shown to incorporate 14C-labeled CO2 by MAR-FISH concluding that these groups performed a chemo-lithoautotrophic metabolism based on sulfur oxidation, and also suggesting that they play a more important role for H2S removal and primary production in marine sediments than previously thought (Lenk et al., 2011).
Another novel technique, providing information about elemental, isotopic and molecu-lar characteristics of single cells is nano-scale secondary ion mass spectrometry (NanoSIMS). NanoSIMS can be combined with SIP as well as with CARD-FISH methods. A combination of CARD-FISH and NanoSIMS has been used to track the fate of carbon and nitrogen in micro-bial aggregates (Behrens et al., 2008). However, the NanoSIMS method is cost-intense and time consuming regarding the sample preparation and fine tuning of the instrument.
1.6. Scope of this thesis The research described in this thesis is focused on the spatial and temporal distribution of chemolithoautotrophic microorganisms in coastal marine sediments. These microbes have not been studied extensively and there is a growing need to determine their role in the sedimentary carbon-, nitrogen-, and sulfur cycle, as well as to identify microbial key-players that are involved, especially in the oxygen transition zone of seasonally hypoxic sediments.
To this end, the diversity, abundance and activity of chemolithoautotrophic microorganisms, such as AOA, AOB, anammox and denitrifying bacteria, as well as sulfate reducing and sul-fur oxidizing microorganisms have been determined. Additionally, the diversity and activity of chemolithoautotrophic microorganisms involved in the CBB and rTCA cycle as well as the metabolism of Thaumarchaeota and the abundance of Archaea have been addressed. In the following studies, we focused on coastal marine sediments, exposed to summer hypoxia, i.e. (1) the seasonal hypoxic basin of the Oystergrounds in the central North Sea, (2) different sediment types (sand, clay, and mud) of the Iceland Shelf, and (3) seasonally hypoxic and sulfidic sedi-ments of saline Lake Grevelingen (The Netherlands). The work presented here is divided in the following chapters:
Chapter 2 shows the seasonal and depth distribution of the abundance and potential activity of archaeal and bacterial ammonia oxidizers (AOA and AOB) and anammox bacteria in coastal marine sediments of the southern North Sea. Specific intact polar lipids as well as the gene abundance and expression of the 16S rRNA gene, the ammonia monooxygenase subunit A (amoA) gene of AOA and AOB, and the hydrazine synthase (hzsA) of anammox bacteria were quantified in contrasting seasons (i.e. February, March and August). AOA, AOB and anammox bacteria were detected and transcriptionally active down to 12 cm sediment depth in all seasons.
Chapter 1
20
AOA seem to play a more dominant role in aerobic ammonia oxidation compared to AOB, as their abundance was higher in all seasons. Anammox bacteria were abundant and active even in bioturbated and oxygenated sediment layers, especially in August, suggesting that their growth and activity are favored by higher temperatures and lower O2 concentrations during summer stratification. The metabolic activity of the studied microbial groups is spatially coupled lead-ing to the assumption that the rapid consumption of O2 allows the coexistence of aerobic and aerobic ammonia oxidizers in the sediments of the Oyster Grounds in the southern North Sea.
In Chapter 3, we aimed to determine the metabolism of sedimentary Thaumarchaeota and bacteria by studying the incorporation of 13C-label from bicarbonate, pyruvate, glucose and ami-no acids into the thaumarchaeal IPL-GDGTs and bacterial/eukaryotal PLFAs during 4−6 days of incubation in intact marine sediment cores from three different sites on the Iceland shelf. The abundance of thaumarchaeal IPL-GDGTs, in particular HPH-crenarchaeol, were detected at all stations and the concentrations remained constant or decreased slightly during incubation, suggesting that living Thaumarchaeota were present in sediments at all stations. In organic-rich sediments a large uptake of 13C label from organic substrates in bacterial/eukaryotic IPL-derived fatty acids was found, implying that heterotrophic bacteria and potentially non-photosynthetic eukaryotes incorporated label into their biomass, whereas the incorporation of labeled bicar-bonate into the PLFAs of chemolithoautotrophic bacteria and archaea seem to be of minor rel-evance or under the detection limit of the method. In sandy sediments, some enrichment of 13C (1−4%) in thaumarchaeotal IPL-GDGTs was detected after the incubation with bicarbonate and pyruvate, but overall no substantial incorporation of 13C into the biphytanyl chains of HPH-cre-narchaeol has been detected. We conclude that the low incorporation rates detected suggest a slow growth of sedimentary Thaumarchaeota in contrast to other sedimentary organisms and/or a slow turn-over of thaumarchaeotal IPL-GDGTs in contrast to bacterial/eukaryotic PLFAs.
In Chapter 4 the abundance and diversity and potential activity of denitrifying and anammox bacteria, as well as of H2S dependent denitrifying bacteria in seasonally hypoxic and sulfidic sed-iments of saline Lake Grevelingen (The Netherlands) were studied. The depth distribution of 16S rRNA and nirS genes of denitrifying and anammox bacteria, as well as the aprA gene of sul-fur oxidizing and sulfate reducing bacteria, were estimated down to 5 cm sediment depth at three different locations before (March) and during (August) summer hypoxia. The abundance of denitrifying bacteria was relatively stable, whereas anammox bacteria were more abundant and active during summer hypoxia in sediments with lower H2S concentrations, suggesting a possible inhibition of anammox bacteria by sulfide. Heterotrophic and autotrophic denitrifiers as well as anammox bacteria and SRB/SOB spatially coexist, but nirS-type denitrifiers outnumbered anammox bacteria leading to the conclusion that anammox does not contribute significantly to nitrogen removal in Lake Grevelingen sediments. The transcriptional activity of denitrifying and anammox bacteria as well as of sulfur oxidizing, including sulfide-dependent denitrifiers, and sulfate reducing bacteria was potentially inhibited by the accumulation of H2S during sum-mer hypoxia. Both denitrifiers and anammox bacteria could be inhibited by the competition for NO3
− and NO2− with cable and Beggiatoa-like bacteria before summer hypoxia. Results suggest
that H2S detoxification mediated by sulfur oxidizers including sulfide-dependent denitrifiers is not sufficient to sustain the activity of denitrifying and anammox bacteria in Lake Grevelingen sediments.
In Chapter 5 the impact of seasonal hypoxia on the activity and the community structure of
21
Introduction
chemolithoautotrophic bacteria was studied in seasonally hypoxic and sulfidic sediments of sa-line Lake Grevelingen (The Netherlands) before (March) and during summer hypoxia (August). Combined 16S rRNA gene amplicon sequencing and PLFA analysis revealed a major temporal shift in the community structure. Aerobic sulfur oxidizing Gamma- and Epsilonproteobacteria predominated the chemolithoautotrophic community in spring, whereas Deltaproteobacteria were prevalent during summer hypoxia. Chemolithoautotrophic rates, determined by PLFA-SIP, were three times higher in spring than during summer hypoxia, especially in surface sediments. The abundance of cbbL (RuBisCO) and aclB (ATP-citrate lyase) genes revealed a predominance of microorganisms using the CBB cycle compared to the rTCA cycle independent of the season and location. Gene abundances of both, the cbbL and aclB genes decreased significantly between the seasons, suggesting that the abundance of chemolithoautotrophic bacteria using the CBB or the rTCA cycle is inhibited by the limited availability of electron acceptors, such as O2 and NO3
–, regulated by summer hypoxia.
In Chapter 6 the archaeal abundance and community composition was studied in seasonally hypoxic and sulfidic surface sediments of Lake Grevelingen (The Netherlands). We combined archaeal 16S rRNA gene amplicon sequencing and the analysis of archaeal GDGT IPLs to determine the biological sources of these archaeal lipids under changing O2 and H2S condi-tions, before (March) and during summer hypoxia (August). In spring, the archaeal communi-ty was predominated by aerobic Thaumarchaeota, whereas during summer hypoxia, anaerobic members of the DPANN superphylum prevailed. The abundance of IPL-GDGTs decreased one order of magnitude between March and August, and polar head groups changed from phospho- to glycosidic head groups, suggesting that Thaumarchaeota might be in a stationary growth phase and/or a slow degradation of these GDGTs in the sediment. The switch from a Thaumarchaeota to a DPANN-dominated community during summer hypoxia together with a change in the lipid composition suggest that DPANN archaea may use fossil lipids found in the surface sediment to build up their membranes as they are unable to do so themselves, suggesting that DPANN archaea could be considered as important lipid recyclers in sediment systems and should be taken into account in organic geochemistry interpretations.
23
2. Seasonality and depth distribution of the abundance and activity of ammonia oxidizing microorganisms in marine coastal sediments (North Sea)
Yvonne A. Lipsewers, Nicole J. Bale, Ellen C. Hopmans, Stefan Schouten, Jaap S. Sinninghe Damsté, and Laura Villanueva
Microbial processes such as nitrification and anaerobic ammonium oxidation (anammox) are important for nitrogen cycling in marine sediments. Seasonal variations of archaeal and bacte-rial ammonia oxidizers (AOA and AOB) and anammox bacteria, as well as the environmental factors affecting these groups, are not well studied. We have examined the seasonal and depth distribution of the abundance and potential activity of these microbial groups in coastal ma-rine sediments of the southern North Sea. This was achieved by quantifying specific intact polar lipids (IPLs) as well as the abundance and gene expression of their 16S rRNA gene, the ammonia monooxygenase subunit A (amoA) gene of AOA and AOB, and the hydrazine syn-thase (hzsA) gene of anammox bacteria. AOA, AOB and anammox bacteria were detected and transcriptionally active down to 12 cm sediment depth. In all seasons, the abundance of AOA was higher compared to the AOB abundance suggesting that AOA play a more dominant role in aerobic ammonia oxidation in these sediments. Anammox bacteria were abundant and active even in oxygenated and bioturbated parts of the sediment. The abundance of AOA and AOB was relatively stable with depth and over the seasonal cycle, while anammox bacteria abundance and transcriptional activity were highest in August. North Sea sediments thus seem to provide a common, stable, ecological niche for AOA, AOB and anammox bacteria.
Frontiers in Microbiology 5, 472, 2014
Chapter 2
24
2.1. IntroductionNitrogen is an essential component for living organisms and thus plays a critical role in con-trolling primary production (Gruber & Galloway 2008). Microbial aerobic and anaerobic nitro-gen cycling processes such as nitrification, denitrification and anaerobic ammonium oxidation are tightly coupled in marine sediments where 50% of marine nitrogen removal occurs (Zhang et al., 2013, and references therein). The discovery of ammonia-oxidizing archaea (AOA) (Kön-neke et al., 2005; Wuchter et al., 2006) belonging to the phylum Thaumarchaeota (Brochier-Ar-manet et al., 2008), and bacteria of the Planctomycetes phylum performing the anaerobic am-monia oxidation (anammox) reaction (Strous et al., 1999; Kuypers et al., 2003), has changed our perspective on the marine nitrogen cycle and the involved microbial key-players over the last decade. Ammonia oxidation is the first and rate-limiting step of nitrification in which ammonia is oxidized to nitrite by AOA and ammonia oxidizing bacteria (AOB) (see Prosser and Nicol, 2008 for a review). The anammox process involves the combination of ammonium with nitrite to form dinitrogen gas which is then released from the system (Kuenen et al., 2008).
Several studies focusing on ammonia oxidation in marine sediments have suggested that AOA have a more prominent role in marine nitrification than AOB based on the higher abundance of AOA amoA gene copies (Beman & Francis, 2006; Mosier & Francis, 2008; Santoro et al., 2008; Abell et al., 2010). Proposed environmental controls shaping the distribution and activity of AOA in marine and estuarine surface sediments include the presence of sulfide, salinity, dis-solved oxygen (DO) concentration, the availability of phosphorous, temperature and primary production (Bernhard et al., 2010; Dang et al., 2010; Erguder et al., 2009; Mosier & Francis, 2008; Sahan & Muyzer, 2008; Sakami et al., 2012; Bale et al., 2013). Beman et al. (2012) studied the seasonal distribution of AOA and AOB amoA gene abundance in Catalina Harbor down to 10 cm sediment depth and showed higher abundances of AOA and AOB amoA genes during summer compared to winter months as well as coinciding higher 15NH4
+ oxidation rates.For anammox bacteria, studies have shown that temperature, organic carbon content, nitrite
concentration, water depth, sediment characteristics and bioturbation play a role in their distri-bution, abundance and activity in marine and estuarine sediments (Dale et al., 2009; Dalsgaard & Thamdrup, 2002b; Engström et al., 2005; Meyer et al., 2005; Dang et al., 2010; Jaeschke et al., 2009; Li et al., 2010; Zhang et al., 2013; Laverock et al., 2013; Neubacher et al., 2011, 2013). However, most of the studies have focused on the spatial distribution of anammox bacteria abundance and activity only in surface sediments (Dalsgaard & Thamdrup, 2002a; Engström et al., 2005; Thamdrup & Dalsgaard, 2002; Nicholls & Trimmer, 2009; Bale et al., 2014). Limited studies have been focused on the abundance of anammox bacteria with sediment depth or the impact of seasonality on this group (Jaechke et al., 2009; Zhang et al., 2013). Anammox bac-teria abundance and activity has been previously detected using anammox specific ladderane biomarker lipids in combination with 15N-labeling experiments in continental shelf and slope sediments of the Irish and Celtic Sea down to eight centimeters depth with spatial differences (Jaeschke et al., 2009). Recently, anammox bacteria abundance was shown to be higher during summer compared to the winter months in surface sediments of three hyper-nutrified estuarine tidal flats of Laizhou Bay (Bohai Sea, China) through the quantification of anammox bacteria 16S rRNA gene (Zhang et al., 2013). A study by Laverock et al. (2013) indicated that the tem-poral variation in the abundance of N-cycling functional genes is directly influenced by biotur-bation activity varying between different bacterial and archaeal N-cycling genes. The relative
25
Introduction/Material and Methods
abundance of AOB amoA genes is significantly affected by bioturbation whereas the relative abundance of AOA amoA seems to be controlled by other factors (Laverock et al., 2013). Inter-estingly, bioturbation and mixing can extend the area of nitrate reduction in sediments leading to the production of nitrite which would fuel the anammox process (Meyer et al., 2005).
The aim of our study was to determine differences in abundance and activity of ammonia oxidizers with sediment depth (down to 12 cm depth) in marine sediments from the southern North Sea, a continental shelf sea. To address this issue, we quantified the abundance of 16S rRNA gene of ammonia oxidizer groups (AOA, AOB, and anammox bacteria), metabolic genes (amoA of AOA and AOB, and hzsA gene of anammox bacteria), and the intact polar membrane lipids specific for anammox bacteria (i.e. ladderane lipids, Sinninghe Damsté et al., 2002b), and Thaumarchaeota (i.e. crenarchaeol; Sinninghe Damsté et al., 2002a). The potential transcrip-tional activity of the target genes was analyzed to elucidate the potential activity of the target organisms in the sediment. Our results suggest that both aerobic and anaerobic ammonia oxi-dizers coexist in the same niche and are actively involved in the nitrogen cycle in oxygenated and bioturbated sediments in the North Sea.
2.2. Material and Methods
2.2.1. Study site and sampling The Oyster Grounds, an almost circular depression with a maximum depth of 50 m located in the southern North Sea (Weston et al., 2008), is a temporary deposition center for sediment (Raaphorst et al., 1998), which plays an important role in the carbon and nitrogen cycle in the region (Weston et al., 2008). The sedimentation of organic matter in this region leads to organic rich and muddy sediment, which supports high levels of benthic fauna (Van Raaphorst, 1992; Duineveld, 1991).
Sediment cores were collected at a station (4˚33.01’ E, 54˚13.00’ N) in the Oyster Grounds during three cruises on board of the R/V Pelagia in February, May and August 2011. Sediment was collected with 10 cm diameter multicores. Bottom water of the overlaying water was col-lected using a syringe and filtered (through a 0.45 µm 25 mm Acrodisc HT Tuffryn Membrane syringe filter) for nutrient analysis. The cores were sliced into 1 cm slices using a hydraulic slicer or a manual slicer. Samples were collected for lipid and DNA/RNA analysis and kept at –80ºC (DNA/RNA) and –40ºC (lipids) until processing.
Bottom water temperature, water depth and salinity were measured using a SBE911+ conduc-tivity-temperature depth (CTD) system (Seabird Electronics, Inc., WA). The oxygen concentra-tion in the water column was measured using a dissolved oxygen (DO) sensor SBE 43 (Seabird Electronics, Inc., WA) integrated in the CTD system.
2.2.2. Physicochemical parameters Pore water was extracted from 2.5 mm sediment slices from 0 to 2 cm depth, and from 1 cm sediment slices from 2–12 cm depth by centrifugation (approx. 4000 g, 5 min, through a 0.45 µm 25 mm Acrodisc HT Tuffryn Membrane syringe filter), and the obtained concentrations of the first 2 cm were averaged for the first and second centimeter of the sediment to estimate pore water nutrient concentrations in a 1 cm resolution. Pore water samples were stored in pre-rinsed pony vials and NH4
+, NO3–, NO2
– and PO43– concentrations were analyzed as described by
Bale et al. (2013). The total organic carbon (TOC) and total organic nitrogen (TON) content
Chapter 2
26
per gram of freeze dried sediment were determined after acidification of freeze dried sediment (0.5−1 g) with 2N HCl. Residues were analyzed by using a Thermo Finnigan Delta plus iso-tope ratio monitoring mass spectrometer (irmMS) connected to a Flash 2000 elemental analyzer (Thermo Fisher Scientific, Milan).
2.2.3. Intact polar lipid extraction and analysis IPLs were extracted following Bale et al. (2013). Hexose-phosphohexose (HPH) crenarchaeol, a specific biomarker lipid for AOA (Schouten et al., 2008b), was analyzed using high performance liquid chromatography mass spectrometry (HPLC/MS) as described by Pitcher et al. (2011a). Due to the lack of a standard the results are reported here as response unit per gram of sedi-ment (r.u. g–1). The anammox bacteria specific intact ladderane phospholipid, C20-[3]-monoether ladderane, attached to a phosphatidylcholine (PC) headgroup (PC-monoether ladderane) was analyzed by HPLC/MS following Jaeschke et al. (2009) and quantified using an external standard consisting of isolated PC-monoether ladderane.
2.2.4. DNA/RNA extraction DNA and RNA from sediment cores were extracted by using the DNA and RNA PowerSoil® Total Isolation Kit, respectively (Mo Bio Laboratories, Inc., Carlsbad, CA). Nucleic acid con-centrations were quantified spectrophotometrically (Nanodrop, Thermo Scientific, Wilming-ton, DE) and checked by agarose gel electrophoresis for integrity. Extracts were kept frozen at –80°C. The RNA extracts were treated with RNase-free DNase (DNA-free™, Ambion Inc., Austin, TX). RNA quality and concentration were estimated by the Experion RNA StdSens Analysis Kit (Bio-Rad Laboratories, Hercules, CA). DNA contamination was checked by PCR using RNA as a template.
2.2.5. Reverse transcription (RT)-PCR Reverse transcription (RT) was performed with the Enhanced Avian First Strand synthesis kit (Sigma-Aldrich Co., St Louis, MO) using random nonamers as described previously (Holmes et al., 2004). Two negative controls lacking reverse transcriptase or RNA were included. PCR reac-tions were performed as described above to confirm the transcription to complementary DNA (cDNA) and the negative controls using the RT reaction as a template.
2.2.6. Quantitative PCR analysis Quanititative (qPCR) analyses were performed on a Biorad CFX96TM Real-Time System/C1000 Thermal cycler equipped with CFX ManagerTM Software. Gene copy numbers of the Thaumarchaeota group 1.1a were estimated by using the 16S rRNA gene primers MCGI-391F/MCGI-554R (Coolen et al., 2007). The AOA amoA gene was amplified using the primer com-bination AmoA-ModF/AmoA-ModR (Yakimov et al., 2011). Abundance of AOB 16S rRNA gene was estimated using primers CTO189F/CTO654R as described by Kowalchuk et al. (1997). Gene copy numbers of the AOB amoA gene were estimated using the primer set AOB-amoAF/AOB-amoAR new (Rotthauwe et al., 1997; Hornek et al., 2006). Abundance of the anammox bacteria 16S rRNA gene was estimated using primers Brod541F/Amx820R as described by Li et al. (2010). Additionally, the anammox bacteria hzsA gene was quantified using the primer combination hzsA_1597F/hzsA_1857R as described by Harhangi et al. (2012) (See Table S1 for details). All qPCR reactions were performed in triplicate with standard curves from 100 to 107 molecules per microliter. Standard curves were generated as described before (Pitcher et al.,
27
Material and Methods
2011b). Gene copies were determined in triplicates on diluted DNA extracts (1:10) and on com-plementary DNA (cDNA) extracts. The reaction mixture (25 μL) contained 1 U of PicoMaxx high fidelity DNA polymerase (Stratagene, Agilent Technologies, Santa Clara, CA) 2.5 μL of 10x PicoMaxx PCR buffer, 2.5 μL 2.5 mM of each dNTP, 0.5 μL BSA (20 mg mL–1), 0.02 pmol μL–1 of primers, 10,000 times diluted SYBR Green® (Life Technologies, Carlsbad, CA) (optimized concentration), 0.5 μL 50 mM of MgCl2 and ultra-pure sterile water. All reactions were per-formed in iCycler iQTM 96-well plates with optical tape (Bio-Rad, Hercules, CA). Specificity of the reaction was tested with a gradient melting temperature assay. The cycling conditions for the qPCR reaction were the following: 95°C, 4 min; 40–45 × [95°C, 30 s; melting temperature (Tm), 40 s; 72°C, 30 s]; final extension 80°C, 25 s. Specificity for qPCR reaction was tested on agarose gel electrophoresis and with a melting curve analysis (50°C–95°C; with a read every 0.5°C held for 1 s between each read) in order to identify unspecific PCR products such as primer dimers or fragments with unexpected fragment lengths. Melting temperature, PCR efficiencies (E) and correlation coefficients for standard curves are listed in Table S2.
2.2.7. PCR amplification and cloning Amplifications of the anammox bacteria 16S rRNA gene, AOA and AOB amoA genes were performed with the primer pairs specified above (Table S1). PCR reaction mixture was the fol-lowing (final concentration): Q-solution (PCR additive, Qiagen, Valencia, CA) 1 ×; PCR buffer 1 ×; BSA (200 µg mL–1); dNTPs (20 µM); primers (0.2 pmol µL–1); MgCl2 (1.5 mM); 1.25 U Taq polymerase (Qiagen, Valencia, CA). PCR conditions for these amplifications were the fol-lowing: 95°C, 5 min; 35 × [95°C, 1 min; Tm, 1 min; 72°C, 1 min]; final extension 72°C, 5 min. PCR products were gel purified (QIAquick gel purification kit, Qiagen, Valencia, CA), cloned in the TOPO-TA cloning® kit (Life Technologies, Carlsbad, CA), and transformed in E. coli TOP10 cells following the manufacturer’s recommendations. Recombinant plasmidic DNA was sequenced using M13R (5’-CAG GAA ACA GCT ATG AC-3’) primer by Macrogen Inc. (Am-sterdam, The Netherlands).
2.2.8. Phylogenetic analysis Sequences were analyzed for the presence of chimeras using the Bellerophon tool at the Green-Genes website (http://greengenes.lbl.gov/). Sequences were aligned with Mega5 software (Ta-mura et al., 2011) by using the alignment method ClustalW. Partial sequences of the archaeal amoA gene generated in this study were added to the amoA gene reference tree provided in Pester et al. (2012) using the ARB Parsimony tool (Ludwig et al., 2004). Phylogenetic trees of AOB amoA and the anammox bacterial 16S rRNA genes were computed with the Neigh-bour-Joining method (Saitou and Nei, 1987) in the Mega5 software. The evolutionary distances were estimated using the Jukes-Cantor method (Jukes and Cantor, 1969) with a bootstrap test of 1,000 replicates. Sequences were deposited in NCBI with the following accession numbers: KJ807530–KJ807556 for partial sequences of the archaeal amoA gene, KJ807557–KJ807597 for partial bacterial amoA gene sequences and KJ807598–KJ807609 for partial anammox bacterial 16S rRNA gene sequences.
2.2.9. Statistical analysis Spearman’s rank order correlation coefficient (rs) analysis was performed using the SigmaPlotTM (12.0) Exact Graphs and Data Analysis (Systat Inc., San Jose, CA). Additional multivariate anal-
Chapter 2
28
ysis did not show additional correlations of environmental data with gene and expression data therefore results were not included in this study.
2.3. Results
2.3.1. Physicochemical conditionsOxygen concentrations of the water column corresponding to the sampling time and location of sediment core sampling are shown in Fig. S1. In February, oxygen concentrations decreased throughout the water column from 301.3 to 299 µM (300 µM on average). In May, the oxygen concentration was slightly lower compared to February (282 µM on average) and decreased be-tween 17.8–22.8 m water depth from about 287 to 278 µM. Lowest oxygen concentrations were detected in August compared to February and May (230 µM on average) and decreased between 17.8–24.8 m water depth from 242 to 217.25 µM.
Physicochemical parameters of the bottom water during the cruises of February (winter), May (spring) and August (summer) are shown in Table S3. Bottom water temperatures ranged from 5 to 15.4˚C. Salinity values were stable throughout the year ranging from 34.3–34.7 practical sa-linity units (psu). Ammonia (NH4
+) concentrations in the bottom water ranged between 1.6 and 3 µM with a maximum concentration in February. Bottom water nitrite (NO2
–) concentrations varied from 0.6 µM in February to 0.1 µM in May and August. Highest nitrate (NO3
–) concentra-tions were detected in February (1 µM) and lowest in August (0.5 µM).
Pore water concentrations of NH4+ ranged between 3–53 µM in all three seasons (Fig. 1). The
depth trend of ammonia concentrations in the pore water was similar in all seasons with lower concentrations in the upper 4 cm of the sediment (3–34 µM) compared to increasing concen-trations of the underlying layers (20–53 µM) down to 12 cm sediment depth. Highest NH4
+ concentrations were detected in August (40–53 µM) compared to February and May. Nitrite (NO2
–) concentrations ranged between 0.1–1.2 µM in all seasons (Fig. 1). Depth profiles of pore water nitrite concentrations showed different seasonal trends. In February, nitrite concentrations were relatively low (0.3 µM) in the first 3 cm of the sediment and increased with depth (0.6 µM) whereas in May and August, nitrite concentrations were higher between 1–2 cm sediment depth (0.8 µM) compared to the underlying sediment layers (0.4 and 0.2 µM, respectively). Pore water nitrate (NO3
–) concentrations strongly varied with sediment depth and season (Fig. 1). In Feb-ruary and May, nitrate concentrations were highly variable with depth and reached maximum values between 3−4 cm (38 µM) and 4−5 cm of the sediment (24 µM), while the concentration strongly decreased in the underlying layers. In August, lower nitrate concentrations were detect-ed compared to the other seasons with slightly elevated values in the first 2 cm of the sediment (7.3 µM) and lower concentrations in the underlying layers (1.3 µM). Phosphate concentrations ranged between 1.4–5.2 µM in all seasons (Fig. 1). Pore water phosphate concentrations were stable in the first 4 cm of the sediment (1.7 µM, averaged) in all three seasons. In February and May, phosphate concentrations increased slightly (3.4 µM, averaged) in the underlying sediment layers whereas the depth profile remained stable in August. TOC and TON percentages of the sediment were relatively stable in all seasons (between 0.15–0.38% and 0.02–0.08% respectively), with highest values in May between 1–2 cm and 4–5 cm sediment depth (Table S4).
2.3.2. Abundance, distribution, activity and diversity of AOA and AOBThe abundance of AOA in the sediments was determined by quantification of the 16S rRNA
29
Material and Methods/Results
and amoA gene copies, as well as by quantification of HPH-crenarchaeol (Figs. 2A–C Table S5). The seasonal variations in depth profiles of AOA 16S rRNA and amoA gene abundance were generally similar (Figs. 2A, B). Both AOA gene abundances were higher between 0−5 cm (6 × 106 and 1.4 × 107 gene copies g–1, respectively) compared to 5−12 cm of the sediment (5 × 106 and 8.2 × 106 gene copies g–1, respectively). Gene copy numbers of the AOA amoA gene were higher in August in comparison to the values observed in February and May (1.4-fold and 2.7-fold higher, respectively) for the 0–5 cm interval. HPH-crenarchaeol concentration was variable over the first 5 cm of the sediment (between 3 × 106–17 × 106 r.u. g–1), but stable values (around 5.9 × 106 r.u. g–1) were detected in the layers underneath. No clear seasonal differences were detected (Fig. 2C).
The abundance of AOB was determined by quantifying the AOB 16S rRNA and amoA gene (Figs. 2D, E). Values were relatively stable with depth with seasonal variations between 0–4 cm of the sediment. Abundance of the AOB 16S rRNA gene showed values similar to the AOA 16S rRNA gene abundance in February and August (on average 5.1 × 106 and 5.8 × 106 gene copies g–1, respectively), while in May AOB 16S rRNA gene copy numbers were lower on average com-pared to the AOA 16S rRNA gene copy number (4.0 × 106 gene copies g–1, 1.4-fold lower). The AOB amoA gene abundance followed the same seasonal trends as that of the AOB 16S rRNA gene, AOA 16S rRNA and amoA gene abundances, with higher values in August, but absolute values were one order of magnitude lower than AOA amoA gene copy numbers (2.3 × 105–5.2 × 106 gene copies g–1). AOB amoA gene abundance was highest in the 0−5 cm depth interval except in May when values between 2−5 cm and in the 5−12 cm depth interval were lower than in the surface sediment.
Figure 1: Sediment pore water nutrients: A) NH4+; B) NO2
–; C) NO3– and D) PO4
3+ [µM] with sediment depth [cm] below sea floor [bsf].
Chapter 2
30
The RNA:DNA ratios of the AOA and AOB 16S rRNA and amoA genes were calculated as an indicator of the potential transcriptional activity of the targeted microbial group (Figs. 3A–F).In all three seasons, AOA 16S rRNA gene RNA:DNA ratio showed relatively stable values down core ranging between 0.9–5.0 and 1.2–3.4 in May and August but reached slightly higher values (2.2–8.2) in February (Fig. 3A). AOB 16S rRNA gene RNA:DNA ratio was between 0.1–2.1 with a minimum of 0.1 between 4−5 cm of the sediment in February and 0.1–3.7 with a minimum between 2−3 cm sediment depth in May. The AOB 16S rRNA gene RNA:DNA ratio was slightly higher (1.2–4.1) in August (Fig. 3C). Values were relatively stable with depth in August whereas in February and May values were more variable. Compared to the RNA:DNA ratio of the AOA 16S rRNA gene, the AOB 16S rRNA gene RNA:DNA ratio was lower (5-fold in February, 1.5-fold in May and 1.3-fold lower in August) in all seasons (Figs. 3A, C). AOA amoA gene transcripts (Fig. 3B) were only detected in February in the first 3 cm and in August throughout the core, and were under the detection limit in May. AOB amoA gene RNA:DNA ratio (Fig. 3D) varied between 4 × 10–5–2 × 10–2 in all seasons with a slight decrease with depth and highest values in August.
The diversity of AOA and AOB was evaluated in two selected depth intervals (0–1 and 9–10 cm sediment depth) of the sediment core recovered in August by targeting the AOA amoA gene and the AOB amoA gene, respectively (Figs. S2, S3). Amplified AOA amoA gene sequences were closely related to AOA amoA gene sequences previously isolated from marine and estuarine environments and did not cluster according to depth (Figs. S2A, B). Sequences were mainly affil-iated to the Nitrosopumilus subclusters 12 and 16, also known as the stable marine cluster, or to
Figure 2: Abundance of A) AOA 16S rRNA gene [copy number g–1]; B) AOA amoA gene [copy number g–1]; C) Hexose phosphohexose (HPH)-crenarchaeol [response units g–1], and D) AOB 16S rRNA gene [copy number g–1]; E) AOB amoA gene [copy number g–1] with sediment depth [cm] below sea floor [bsf].
31
Results
the Nitrosopumilus subcluster 4.1, known as the estuarine cluster, according to the phylogenetic classification proposed by Pester et al. (2012). The AOB amoA gene sequences were affiliated to AOB amoA gene sequences previously isolated from estuarine sediments. Sequences were close-ly related to the AOB amoA gene sequences of Nitrospira sp. (accession number X90821) and Nitrosolobus multiformis (accession number AF042171). No clustering of AOB amoA sequences according to depth was observed (Fig. S3).
2.3.3. Abundance, distribution, activity and diversity of anammox bacteriaThe abundance and distribution of anammox bacteria were estimated by quantification of ana-mmox bacteria 16S rRNA and hzsA gene copy number, as well as by quantification of the PC-monoether ladderane (Figs. 4A–C). Depth profiles of anammox bacteria 16S rRNA and hzsA gene abundances followed similar trends. Gene copy numbers of the hzsA gene were one order of magnitude lower (between 3.5 × 105 and 2 × 106 copies g–1) than anammox bacteria 16S rRNA gene copy numbers in all three seasons (Figs. 4 A, B). Values were higher in August compared to those in February and May, especially for the anammox bacteria 16S rRNA gene (3.7-fold higher).
The RNA:DNA ratio for the anammox bacteria 16S rRNA gene varied between 1.6–34.6 (Fig. 3E) with higher values in August compared to February and May (on average 4-fold higher). The hzsA gene RNA:DNA ratio (Fig. 3F) depth profiles showed relatively stable values (between 0.008–0.125) throughout the core without significant seasonal differences. The PC-monoether ladderane concentration (Fig. 4C) was variable over the first 5 cm of the sediment (between 0.25–1.25 ng g–1), while in the underlying sediment layers values decreased slightly to more stable
Figure 3: Transcriptional activity given as RNA:DNA ratio of A) AOA 16S rRNA gene; B) AOA amoA gene; C) AOB 16S rRNA gene, D) AOB amoA; E) Anammox 16S rRNA gene, and F) Anammox bacteria hzsA gene with sediment depth [cm] below sea floor [bsf].
Chapter 2
32
values (approximately 0.36 ng g–1) down to 12 cm sediment depth. There was no clear seasonal difference observed.
The diversity of anammox bacteria was evaluated in two selected depths (0–1 and 9–10 cm) of the sediment core in August by targeting the 16S rRNA gene of anammox bacteria. The sequences were closely related to “Candidatus Scalindua marina” (accession number EF602038) and “Candidatus Scalindua brodae” (accession number AY254883) and to sequences previously detected in waters of marine oxygen minimum zones (Woebken et al., 2008). Anammox bacterial 16S rRNA gene sequences from different depths were closely related to each other (Fig. S4).
2.4. Discussion
2.4.1. Aerobic ammonia oxidizersIn this study, we defined two niches in the Oyster Grounds sediment based on the differences in physicochemical parameters and in the abundance of the target organisms, i.e. the upper 4 cm of the sediment, and the underlying sediment. Ammonia concentration in the pore water of the upper part of the sediment (0–4 cm) was consistently lower than in deeper sediment layers (4–12 cm) (Fig. 1), suggesting ammonia diffusion from below formed by mineralization of or-ganic matter by ammonification or dissimilatory nitrate reduction to ammonium (DNRA). In addition, the abundance of AOA and AOB (as well as anammox bacteria, see below) was higher and more affected by seasonality in the upper part than deeper in the sediment, which apparently is a more stable compartment. The higher variability observed in the upper part of the sediment is in agreement with the seasonal mixing of the bottom water layers and sediment deposition
Figure 4: Abundance of A) Anammox bacteria 16S rRNA gene [copy number g–1]; B) Anammox bacteria hzsA gene [copy number g–1], and C) PC-monoether ladderane [ng g–1] with sediment depth [cm] below sea floor [bsf].
33
Results/Discussion
dynamics in this area (Greenwood et al., 2010). Oxygen availability is expected to play an important role in the dynamics of ammonia oxidiz-
ing microorganisms in marine sediments. In the summer months, water stratification leads to a decrease in the dissolved oxygen concentration in the bottom water in the Oyster Grounds area (Greenwood et al., 2010) (see Fig. S1). Indeed, bottom water hypoxia has been shown to cause a decrease in oxygen penetration depth and oxygen consumption in Oyster Grounds sediments by induced short-term hypoxia in intact sediment cores (Neubacher et al., 2011). Lohse et al. (1996) reported an oxygen penetration depth (OPD) of 1.7 cm in February and 0.5 cm in August in sediment at a station close to the Oyster Grounds using oxygen microelectrodes, suggesting per-manently anoxic conditions from a depth of approximately >2 cm throughout the year. How-ever, the OPD into the sediment must be interpreted with caution because the Oyster Grounds sediment is known to be an area of intense bioturbation by macro- and meiobenthos even in periods of low oxygen concentration in the bottom water (De Wilde et al., 1984; Duineveld et al., 1991), thus the import of oxygen by macrofaunal burrows into the deeper sediment could be relevant (Kristensen, 2000; Meysman et al., 2006). A study by Laverock et al. (2010) has also shown that bioturbation can induce changes in the microbial community composition, resulting in distinct communities within the burrow. However, in our study we did not observe changes in the diversity of amoA gene sequences of AOA or AOB, which might indicate that the changing physicochemical conditions in this system do not select for specific ammonia oxidizing micro-organisms. The depth and seasonal variability for AOB was more pronounced than for AOA in the first 4 cm of the sediment, which is consistent with the fact that the relative abundance of AOB is more significantly affected by bioturbation than AOA according to previous studies (Laverock et al., 2013).
AOA and AOB 16S rRNA and amoA genes and AOA-IPLs and were detected up to 12 cm depth in Oyster Grounds sediments. The detection of aerobic ammonia oxidizing microorgan-isms in marine sediment at depths where the oxygen concentration is expected to be undetect-able seems counterintuitive with their aerobic metabolism. However, the intense bioturbation reported in the Oyster Grounds sediments, as mentioned above, might provide enough oxygen to support the activity of these microbial groups. In fact, Beman et al. (2012) detected AOB and AOA amoA genes up to 10 cm sediment depth as well as readily detectable 15NH4
+ oxidation rates up to 9 cm sediment depth with maxima overlapping with a peak in pore water NO3
– + NO2
– concentrations between 3–7 cm sediment depth in bioturbated sediments of Catalina Island (CA, USA) . Thus, our results, and those of Beman et al. (2012), suggest that aerobic am-monia oxidizers are indeed living and actively involved in the marine sedimentary nitrogen cycle deeper (i.e. up to at least ca. 10 cm) in coastal marine sediments.
The detection of a potential transcriptional activity of the AOA 16S rRNA gene up to 12 cm depth supports that AOA are indeed active deeper in the marine sediment. The potential AOA 16S rRNA gene transcriptional activity was higher during winter, whereas the abundance was slightly higher during summer months. Previous studies showed higher AOA abundance during winter months in the in the North Sea water column (Wuchter et al., 2006; Herfort et al., 2007; Pitcher et al., 2011c) attributed to the higher availability of ammonia and the lack of competition for ammonia with phytoplankton. However, none of these studies targeted the transcriptional activity of AOA. Recently, Bale et al. (2013) observed that the abundance of the benthic Thaumarchaeota (given by HPH crenarchaeol) in the surface sediment (0–1 cm) at the
Chapter 2
34
Oyster Grounds was on average highest in the summer (August) and lowest in the winter (No-vember), which they attributed to the deposition of algal-bloom-derived organic matter taking place in late spring and summer resulting in the formation of ammonia. However, it should also be noted that Bale et al. (2013) did find that transcriptional activity of the AOA 16S rRNA gene was higher during winter in the surface sediment. The disparity in seasonality between the results of these two studies highlights the difference between the seasonal ammonia dynamics at the surface sediment/water interface (Bale et al., 2013) and with depth in the sediment (this study).
To complement the determination of potential transcriptional activity of AOA based on 16S rRNA gene, we also determined the AOA amoA gene RNA:DNA ratio, which was possible for samples from August throughout the core but only in the upper 3 cm depth in February because the quantity of transcripts in the other seasons and depths was under the detection limit of the qPCR assay.
The relationship of amoA gene expression and in situ ammonia oxidation is still unclear (Lam et al., 2007; Nicol et al., 2008; Abell et al., 2011; Vissers et al., 2013). However, recent studies have observed a good correlation between nitrification rates and abundance of AOA amoA gene and transcripts in coastal waters (Urakawa et al., 2014; Smith et al., 2014). Therefore, the detection of AOA amoA transcripts in our setting suggests that AOA were active in the summer throughout the sediment in comparison with the winter in which AOA would be only active in the upper part of the sediment (upper 2 cm).
AOB 16S rRNA gene abundance was in the same order of magnitude than AOA 16S rRNA gene abundance, however, AOB amoA gene abundance was one order of magnitude lower than AOA amoA gene abundance, which can be explained by biases introduced by the primers or by differences in copy number of 16S rRNA and amoA genes per cell. In fact, it is assumed that 3.3 ± 1.6 copies of 16S rRNA can exist per cell in AOB (Větrovský et al., 2013), whereas marine Crenarchaeota seem to contain only one copy per genome (Klappenbach et al., 2001; Laverock et al., 2013). For the amoA gene it is assumed that AOB genomes contain 2 to 3 copies (Arp et al., 2007) while AOA genomes contain only one copy. In addition, the transcriptional activity of the AOB 16S rRNA gene was lower compared to the one of AOA 16S rRNA gene in all seasons.
On the other hand, the abundance of AOB amoA gene transcripts was higher than for AOA and was detected up to 12 cm depth in all seasons which would suggest a higher AOB activity vs AOA. However, a recent study by Urakawa et al. (2014) in water of the Puget Sound Estuary did not observe a correlation between nitrification rates and AOB amoA transcripts. In addition, previous studies have detected the presence of AOB amoA transcripts in non-active starved cells (Bollmann et al., 2005; Geets et al., 2006; Ward et al., 2011) indicating that the AOB amoA tran-scriptional activity is not a good indicator of AOB nitrification activity due to a longer half-life of AOB amoA transcripts than that expected for AOA amoA transcripts.
Taking together the AOA and AOB amoA gene quantification results, AOA have a more im-portant role in the nitrification process in Oyster Grounds sediments than AOB. In addition, all available evidence points to the presence of some oxygen deeper in the sediments of the Oyster Grounds in all seasons probably due to the intense bioturbation in the area, which favors the activity of both AOB and AOA. In the case of AOA, and due to their higher affinity for oxygen (Martens-Habbena et al., 2009), the niche occupancy of AOA could be potentially larger than for AOB.
35
Discussion
Previous studies observed a positive correlation between AOA abundance and low phosphate concentrations and suggested that phosphate plays a role in determining the niches of Thau-marchaeota (Dang et al., 2013; Erguder et al., 2009). In our study, AOA amoA gene transcript copy number and RNA:DNA ratio was negatively correlated with phosphate (rs= –0.745 and –0.739 respectively; both P ≤ 0.005) suggesting a lower expression of the AOA amoA gene with an increase in pore water phosphate concentrations. These results support the assumption that some ecotypes of AOA dominate over AOB in environments with low phosphate availability. Previously, homologues of the pst gene, encoding for the Pst phosphate ABC transporter, which is usually activated in phosphate deficient environments, was found in marine metagenomes of thaumarchaeotal origin (Rusch et al., 2007; Dang et al., 2013) emphasizing the importance of phosphate availability in marine environments. No correlations were found between AOB abundance or transcriptional activity with pore water nitrogen species, but a negative correlation with the sediment depth (rs= –0.646; P ≤ 0.005) was observed indicating that sediment depth is a factor determining the AOB abundance and activity in Oyster Grounds sediments which might be explained by the decreasing oxygen availability with depth.
2.4.2. Anaerobic ammonia oxidizersAnammox bacteria 16S rRNA and hzsA gene abundance was detected throughout the analyzed sediment with more pronounced depth and seasonal differences than those observed for AOA and AOB. This was not reflected in the abundance of PC-monoether ladderane lipid.
It is possible that the PC-monoether ladderane is partly derived from fossil material and thus reflects a long-term presence of anammox bacteria averaged throughout the entire year rath-er than an actively living anammox population. This possibility has been already suggested by Bransdsma et al. (2011) and Bale et al. (2014) who found dissimilarities between the PC-mon-oether ladderane concentration and gene copy numbers in surface sediments of the Gullmar Fjord and the Southern North Sea, respectively.
We also observed an up to 10-fold difference in the quantification of anammox bacteria 16S rRNA and hzsA gene abundance (Figs. 4A, B). This discordance between the anammox bacteria gene markers has been previously observed in environmental samples (Harhangi et al., 2012), and it could be due to primer biases as previously suggested (Bale et al., 2014). Both the anammox 16S rRNA and the hzsA gene revealed a higher abundance in August compared to February and May. This may indicate that anammox bacteria are more active and abundant at higher temperatures (15˚C), which is the anammox bacteria temperature optimum in temperate shelf sediments (Dalsgaard and Thamdrup, 2005). Additionally, the oxygen penetration depth is expected to decrease during water stratification between May and October, which would also favor anammox bacterial growth and activity (Dalsgaard and Thamdrup, 2002). Previous studies by Neubacher et al. (2013) observed an increase in anammox activity up to 82% compared to control treatments in mesocosms under sustained hypoxic conditions, which corresponds well with our findings of high anammox activity during summer stratification associated with lower oxygen concentrations in the bottom water (Fig. S1).
The presence of anammox markers in the upper layers of the sediment (0–4 cm) is remark-able as the metabolism of anammox bacteria is expected to be incompatible with the presence of oxygen. However, some studies have reported that anammox bacteria can cope with low oxygen concentrations (Kalvelage et al., 2011; Yan et al., 2012), and that anammox bacteria can
Chapter 2
36
be present and active at high oxygen levels by being dormant or using anaerobic niches (Kuypers et al., 2005; Woebken et al., 2007). It is also possible that a high activity of AOA and AOB and heterotrophic bacteria inhabiting these marine sediments would rapidly consume the oxygen available and allow the activity of anammox bacteria even in presence of oxygen. Some studies have also concluded that the potential for anammox bacteria activity is indeed not affected by bioturbation or physical mixing (Rooks et al., 2012). On the contrary, bioturbation and mixing can extend the area of nitrate reduction and thus the availability of nitrite, which fuels the ana-mmox process (Meyer et al., 2005). Our results thus suggest that anammox bacteria can tolerate the presence of oxygen and co-exist with aerobic ammonia oxidizers and potentially have an important role in the nitrogen cycle in marine sediments. In fact, the potential transcriptional activity of anammox bacteria 16S rRNA and hzsA gene was observed throughout the sediment in all seasons. The transcriptional activity of anammox bacteria 16S rRNA gene was higher in the summer as observed for the anammox bacteria abundance. A recent study by Bale et al. (2014) observed a good correlation between the rate of anammox and anammox bacteria 16S rRNA gene transcript abundance in North Sea sediments, which suggests that the transcription-al activity of anammox bacteria 16S rRNA gene is a good proxy of anammox bacteria activity, and confirm a higher anammox activity in the summer for the sediments analyzed in our study. Nevertheless, quantification results of anammox bacteria 16S rRNA gene transcripts have to be interpret with caution because there is evidence that the ribosome content does not decrease during the period of starvation (Schmid et al., 2005; Li et al., 2011). However, the increase of anammox bacteria 16S rRNA gene transcriptional activity during summer was not observed for the hzsA gene, which remained stable across sediment depth and also for the different seasons, and gene abundances were generally an order of magnitude lower. The low and constitutive transcriptional activity of the hzsA gene indicates that the hzsA gene transcript abundance does not reflect variations of anammox bacteria activity in environmental sediment samples, thus the hzsA gene transcript abundance does not seem to be an adequate biomarker for the estimation of the activity of anammox bacteria. Further experiments, especially with pure cultures and under controlled physiological conditions, should be performed to clarify the regulation of the expression of the hzsA gene.
No evidence of a niche separation of aerobic and anaerobic ammonia oxidizers was observed in the oxygen transition zone of the marine sediments. Surprisingly, aerobic and anaerobic am-monia oxidizers are present and active throughout the year in oxygenated sediment layers as well as in anoxic layers. These results seem to be counterintuitive with regards to the individual oxygen requirements of the targeted microbial groups. We hypothesize that the presence and activity of aerobic ammonia oxidizers (AOA, AOB) is supported by the oxygen supply in deep-er anoxic layers due to bioturbation. Likewise, the presence and activity of anammox bacteria in these sediments is then possible by the rapid consumption of oxygen by aerobic ammonia oxidizers and/or other groups, as well as the availability of nitrite provided either by ammonia oxidizers or by an active nitrate reduction present in bioturbated sediments (Meyer et al., 2005).
2.5. ConclusionOur study has unraveled the coexistence and metabolic activity of AOA, AOB, and anammox bacteria in bioturbated marine sediments of the North Sea, leading to the conclusion that the metabolism of these microbial groups is spatially coupled based on the rapid consumption of
37
Discussion/Cocnlusion
oxygen that allows the coexistence of aerobic and anaerobic ammonia oxidizers. AOA outnum-bered AOB throughout the year which may be caused by the higher oxygen affinity of AOA compared to AOB. Anammox bacterial abundance and activity were higher during summer, indicating that their growth and activity are favored by higher temperatures and lower oxygen available in the sediments due to summer stratifying conditions in the water column. During the summer, anammox bacteria are probably not in competition with AOA and AOB for ammonia as the concentrations were relatively high in the sediment pore water most likely as a result of ammonification processes and the activity of denitrifiers and DNRA. Further studies are re-quired to get a complete picture of the nature of these interactions in the oxygen transition zone of coastal marine sediments.
Acknowledgements
We thank the captain and crew of the R/V Pelagia for logistic support and E. Panoto, J. van Bleijswijk, H. Witte, and A. Mets for technical support. We thank J. van Oijen and S. Ossebaar for nutrient sample collection and analysis. We thank T. Richter for providing and discussing the CTD data. This work was supported by a grant to J. S. Sinninghe Damsté from the Dutch Orga-nization for Scientific Research (NWO) (NICYCLE; 839.08.331) and a grant to Y.A. Lipsewers (grant number 3062) of the Darwin Center for Biogeosciences.
Chapter 2
38
Figure S1: Oxygen profiles [µM] of the water column in February, May and August.
39
Supplementary Material
Nitrosopumilus subcluster 9 84
uncultured crenarchaeote, Nitrosopumilus cluster, hydrothermal sedimentuncultured crenarchaeote, Nitrosopumilus cluster, marineuncultured crenarchaeote, Nitrosopumilus cluster, marine
Nitrosopumilus subcluster 1 16
uncultured crenarchaeote, Nitrosopumilus cluster, marineuncultured crenarchaeote, Nitrosopumilus cluster, estuary
uncultured crenarchaeote, Nitrosopumilus cluster, estuaryuncultured crenarchaeote, Nitrosopumilus cluster, estuary
uncultured crenarchaeote, Nitrosopumilus cluster, marineuncultured crenarchaeote, Nitrosopumilus cluster, marine
uncultured crenarchaeote, Nitrosopumilus cluster, estuaryuncultured crenarchaeote, Nitrosopumilus cluster, estuaryuncultured crenarchaeote, Nitrosopumilus cluster, marine
uncultured archaeon, Nitrosopumilus cluster, coralNitrosopumilus maritimus SCM1, Nitrosopumilus cluster, marine
uncultured archaeon, Nitrosopumilus cluster, marineuncultured ammonia−oxidizing, Nitrosopumilus cluster, estuaryuncultured crenarchaeote, Nitrosopumilus cluster, estuaryMarine metagenome ctg_1101668569825, Nitrosopumilus clusteruncultured crenarchaeote, Nitrosopumilus cluster, freshwater
uncultured crenarchaeote, Nitrosopumilus clusteruncultured archaeon, Nitrosopumilus cluster, freshwater
uncultured crenarchaeote, Nitrosopumilus cluster, freshwateruncultured archaeon, Nitrosopumilus cluster, estuary
uncultured crenarchaeote, Nitrosopumilus cluster, marineuncultured crenarchaeote, Nitrosopumilus cluster, marine
uncultured crenarchaeote, Nitrosopumilus cluster, marineuncultured crenarchaeote, Nitrosopumilus cluster, spongeuncultured crenarchaeote, Nitrosopumilus cluster, estuary
uncultured crenarchaeote, Nitrosopumilus cluster, marineuncultured crenarchaeote, Nitrosopumilus cluster, marine
uncultured crenarchaeote, Nitrosopumilus cluster, estuaryuncultured crenarchaeote, Nitrosopumilus cluster, hydrothermal sedimentuncultured crenarchaeote, Nitrosopumilus cluster, hydrothermal sediment
uncultured crenarchaeote, Nitrosopumilus cluster, marineuncultured crenarchaeote, Nitrosopumilus cluster, marine
1cm 1uncultured crenarchaeote, Nitrosopumilus cluster, estuary
Nitrosopumilus subcluster 10 5
uncultured archaeon, Nitrosopumilus cluster, marineuncultured crenarchaeote, Nitrosopumilus cluster, marine
uncultured crenarchaeote, Nitrosopumilus cluster, marineuncultured crenarchaeote, Nitrosopumilus cluster, hydrothermal sedimentuncultured crenarchaeote, Nitrosopumilus cluster, hydrothermal sedimentuncultured crenarchaeote, Nitrosopumilus cluster, hydrothermal sediment
uncultured archaeon, Nitrosopumilus cluster, coraluncultured crenarchaeote, Nitrosopumilus cluster, marine
uncultured crenarchaeote, Nitrosopumilus cluster, marineuncultured crenarchaeote, Nitrosopumilus cluster, hydrothermal sediment
uncultured archaeon, Nitrosopumilus cluster, marineuncultured crenarchaeote, Nitrosopumilus clusteruncultured crenarchaeote, Nitrosopumilus cluster
Nitrosopumilus subcluster 11 4
uncultured crenarchaeote, Nitrosopumilus cluster, estuaryuncultured crenarchaeote, Nitrosopumilus cluster, estuaryuncultured crenarchaeote, Nitrosopumilus cluster, estuaryuncultured crenarchaeote, Nitrosopumilus cluster, wastewater
uncultured crenarchaeote, Nitrosopumilus clusteruncultured crenarchaeote, Nitrosopumilus cluster, marine
Nitrosopumilus subcluster 12, Oyster Grounds sediment, 8 seq 1cm, 12 seq 10 cm 25
1cm 31cm 4
uncultured archaeon, Nitrosopumilus cluster, marineuncultured archaeon, Nitrosopumilus cluster, coraluncultured ammonia−oxidizing, Nitrosopumilus cluster, aquarium biofilter
uncultured crenarchaeote, Nitrosopumilus cluster, estuaryNitrosopumilus subcluster 13 4uncultured crenarchaeote, Nitrosopumilus cluster, estuary
Nitrosopumilus subcluster 14 7
Nitrosopumilus subcluster 2 26
Nitrosopumilus subcluster 15 8
Nitrosopumilus subcluster 3 13
uncultured crenarchaeote, Nitrosopumilus cluster, spongeuncultured crenarchaeote, Nitrosopumilus cluster, spongeuncultured crenarchaeote, Nitrosopumilus cluster, sponge
Nitrosopumilus subcluster 16, Oyster Grounds sediment, 1 seq 1 cm 7
Nitrosopumilus subcluster 4, Oyster Grounds sediment 3 seq 1 cm 23
Nitrosopumilus subcluster 5 21
uncultured crenarchaeote, Nitrosopumilus cluster, spongeNitrosopumilus subcluster 6 14
Nitrosopumilus subcluster 7 36
uncultured crenarchaeote, Nitrosopumilus cluster, spongeuncultured crenarchaeote, Nitrosopumilus cluster, marine
uncultured ammonia−oxidizing, Nitrosopumilus cluster, aquarium biofilteruncultured crenarchaeote, Nitrosopumilus cluster, wastewateruncultured crenarchaeote, Nitrosopumilus cluster, wastewater
Nitrosopumilus subcluster 8 28
Nitrosotalea cluster 39
Nitrosocaldus cluster 2
315
Nitrososphaera sister cluster 14
bacterial amoA 8
0.10
Nitrososphaera cluster
Figure S2A: Phylogenetic tree of AOA amoA gene sequences retrieved in this study and closest relatives (Bold: sequences retrieved at 1cm sediment depth and sequences retrieved at 10 cm sediment depth; Au-gust 2011 and clusters containing sequences retrieved in this study, find details in Fig. S2B); the scale bar indicates 10% sequence divergence.
Chapter 2
40
Nitrosopumilus subcluster 4
0.10
Nitrosopumilus subcluster 12
10cm 101cm 61cm 1210cm 31cm 710cm 61cm 210cm 13uncultured crenarchaeote, Nitrosopumilus subcluster 12, marine10cm 21cm 910cm 1410cm 121cm 15
10cm 151cm 1410cm 7
10cm 910cm 1
10cm 111cm 8
uncultured crenarchaeote, Nitrosopumilus subcluster 12, marineuncultured archaeon, Nitrosopumilus subcluster 12, marineuncultured archaeon, Nitrosopumilus subcluster 12, marine
Nitrosopumilus subcluster 16uncultured crenarchaeote, Nitrosopumilus subcluster 16, marineuncultured crenarchaeote, Nitrosopumilus subcluster 16, marineuncultured ammonia−oxidizing, Nitrosopumilus subcluster 16, aquarium biofilter
uncultured archaeon, Nitrosopumilus subcluster 16, marineuncultured crenarchaeote, Nitrosopumilus subcluster 16, marine
10cm 5
1cm 131cm 51cm 1010cm 8uncultured crenarchaeote, Nitrosopumilus subcluster 4.1, marine
uncultured ammonia−oxidizing, Nitrosopumilus subcluster 4.1, estuaryuncultured crenarchaeote, Nitrosopumilus subcluster 4.1, marineuncultured crenarchaeote, Nitrosopumilus subcluster 4.1, marineuncultured crenarchaeote, Nitrosopumilus subcluster 4.1, marineuncultured ammonia−oxidizing, Nitrosopumilus subcluster 4.1, estuaryuncultured ammonia−oxidizing, Nitrosopumilus subcluster 4.1, estuary
uncultured crenarchaeote, Nitrosopumilus subcluster 4.1, marineuncultured crenarchaeote, Nitrosopumilus subcluster 4.1, estuaryuncultured crenarchaeote, Nitrosopumilus subcluster 4.1, estuaryuncultured crenarchaeote, Nitrosopumilus subcluster 4.1, estuaryuncultured crenarchaeote, Nitrosopumilus subcluster 4.1, estuary
uncultured crenarchaeote, Nitrosopumilus subcluster 4.1, estuaryuncultured crenarchaeote, Nitrosopumilus subcluster 4.1, estuary
uncultured crenarchaeote, Nitrosopumilus subcluster 4.1uncultured crenarchaeote, Nitrosopumilus subcluster 4.1, wastewater
uncultured crenarchaeote, Nitrosopumilus subcluster 4.1, estuaryuncultured crenarchaeote, Nitrosopumilus subcluster 4.1, estuary
uncultured crenarchaeote, Nitrosopumilus subcluster 4, estuary
Figure S2B: Phylogenetic tree of AOA amoA gene sequences retrieved in this study and closest relatives (Bold: sequences retrieved at 1cm sediment depth and sequences retrieved at 10 cm sediment depth; Au-gust 2011) the scale bar indicates 10% sequence divergence.
41
Supplementary Material
10cm 10cm 10cm 10cm
10cm 10cm 10cm
10cm 1cm 10cm 10cm 10cm 1cm KC736030.1 Uncultured Nitrosomonadaceae bacterium clone (Yangtze estuary sediments)
HM364248.1 Uncultured bacterium clone (estuary sediments Elkhorn Slough CA)
HM364256.1 Uncultured bacterium clone (estuary sediments Elkhorn Slough CA)
AY736864.1 Uncultured ammonia-oxidizing bacterium clone (Monterrey Bay CA)
10cm HQ247909.1 Uncultured ammonia oxidising bacterium clone (estuarine sediment)
1cm 10cm
1cm 10cm
10cm JQ010925.1 Uncultured beta proteobacterium clone (sediment China East Sea)
EU244548.1 Uncultured bacterium clone (sediments Jiaozhou Bay China)
AB373459.1 Uncultured ammonia-oxidizing bacterium clone (aquarium biofilter)
AB373510.1 Uncultured ammonia-oxidizing bacterium clone (aquarium biofilter)
KC735937.1 Uncultured Nitrosomonadaceae bacterium clone (Yangtze estuary sediments)
1cm JQ638783.1 Uncultured beta proteobacterium clone (estuarine sediment)
1cm 1cm 10cm
10cm AY785983.1 Uncultured beta proteobacterium clone (Guaymas Basin hydrothermal plumes particle attached)
1cm 1cm 1cm
1cm 1cm 10cm 1cm 10cm 1cm
1cm 10cm JQ345981.1 Uncultured bacterium clone (sediment of Chongming eastern tidal flat)
JX465211.1 Uncultured ammonia-oxidizing bacterium clone (Laizhou Bay sediment)
1cm 1cm 10cm
10cm 10cm 10cm
X90821.1 Nitrosospira sp.
AF042171.1 Nitrosolobus multiformis
AJ388578.1 uncultured proteobacterium clone (water column freshwater lake Medemblik)
AF272406.1 Nitrosomonas oligotropha
AF272398.1 Nitrosomonas halophila
U51630.1 Nitrosomonas eutropha
L08050.1 Nitrosomonas europaea
100
99100
97
95
93
86
7884
68
66
65
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56
5150
50
98
65
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55
77
57
100
94
55
96
91
79
79
76
0.05
Figure S3: Phylogenetic tree of AOB amoA gene sequences retrieved in this study; the scale bar indicates 5% sequence divergence.
Chapter 2
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Figu
re S
4: P
hylo
gene
tic tr
ee o
f an
amm
ox b
acte
ria 1
6S rR
NA
gen
e se
quen
ces r
etrie
ved
in th
is st
udy;
the
scal
e ba
r ind
icat
es 0
.2%
sequ
ence
div
erge
nce.
43
Supplementary MaterialTa
ble
S1: P
rimer
pai
rs d
escr
ibed
in th
e te
xt, p
olym
eras
e ch
ain
reac
tion
(PC
R) c
ondi
tions
and
am
plic
on si
ze u
sed
in th
is st
udy.
Ass
ayTa
rget
Prim
er p
air
Tm
Am
plic
on
size
[bp*
]R
efer
ence
qPC
RA
OA
16S
rRN
A ge
neM
CG
I-39
1F (5
’-AA
GG
TTA
RTC
CG
AG
TGRT
TTC
-3’)
qPC
R 61
˚C16
3C
oole
n et
al.
(200
7)M
CG
I-55
4R (5
’-TG
AC
CA
CTT
GA
GG
TGC
TG-3
’)
qPC
R +
PC
R/cl
onin
gA
OA
amo
A g
ene
Am
oA-M
odF
(5’-G
GTC
TGG
YTW
AG
AC
GA
TG-3
’)qP
CR
59.5
˚C62
6Ya
kim
ov e
t al
. (20
11)
Am
oA-M
odR
(5’-G
CC
ATC
CA
TCTG
TAW
GTC
-3’)
PCR
55˚C
qPC
R +
PC
R/cl
onin
gA
nam
mox
bac
teria
16
S rR
NA
gene
Br
od54
1F (5
’-GA
GC
AC
GTA
GG
TGG
GTT
TGT-
3’)
qPC
R 59
˚C27
9Li
et a
l. (2
010)
Am
x820
R (5
’-AA
AA
CC
CC
TCTA
CTT
AG
TGC
CC
-3’)
PCR
58˚C
qPC
RA
nam
mox
bac
teria
hz
sA g
ene
hzsA
_159
7F (5
’-WTY
GG
KTA
TCA
RTA
TGTA
-3’)
qPC
R 51
˚C26
0H
arha
ngi e
t al
. (20
12)
hzsA
_185
7R (5
’-AA
ABG
GYG
AA
TCA
TART
GG
C-3
’)
qPC
RA
OB
16S
rRN
A g
ene
CTO
189F
_A (5
’-GG
AG
RAA
AG
CA
GG
GG
ATC
G-3
’)†
qPC
R 60
˚C46
5K
owal
chuk
et
al.
(199
7)C
TO18
9F_C
(5’-G
GA
GG
AA
AG
TAG
GG
GA
TCG
-3’)†
CTO
654R
(5’-C
TAG
CY
TTG
TAG
TTTC
AA
AC
GC
-3’)
qPC
R +
PC
R/cl
onin
gA
OB
amoA
gen
eA
OB-
amoA
F (5
’-GG
GG
TTTC
TAC
TGG
TGG
T-3’
)qP
CR
61.6
˚C49
1Ro
tthau
we
et a
l. (1
997)
, H
orne
k et
al.
(200
6)A
OB-
amoA
R ne
w (5
’-CC
CC
TCBG
SAA
AVC
CTT
CTT
C-3
’)PC
R 58
˚CPC
R co
nditi
ons:
95˚C
5 m
in; 4
0 ×
[95˚
C 1
min
, mel
ting
tem
pera
ture
(Tm) 4
0 s,
72˚C
1 m
in];
72˚C
5 m
in; q
PCR
cond
ition
s: 95
˚C 4
min
; 40
× [9
5˚C
30
s, T m
40
s, 72
˚C 3
0 s]
; 80˚
C 2
5 s;
* bas
e pa
irs (b
p); † T
he fo
rwar
d pr
imer
con
tain
s an
equi
mol
ar m
ixtu
re o
f th
e re
port
ed fo
rwar
d pr
imer
s.
Chapter 2
44
Tabl
e S2
: Qua
ntita
tive
poly
mer
ase
chai
n re
actio
n (q
PCR)
effi
cien
cies
(E) a
nd c
orre
latio
n co
effic
ient
s (R2 ).
Febr
uary
May
Aug
ust
qPC
R a
ssay
targ
et
mol
ecul
eT
m [˚
C]
E [%
]R
2T
m [˚
C]
E [%
]R
2T
m[˚
C]
E [%
]R
2
AO
A 1
6S rR
NA
gen
eD
NA
61.0
100.
00.
998
61.0
93.5
0.98
861
.094
.30.
999
(MC
GI-
391F
/MC
GI-
554R
)cD
NA
61.0
96.1
1.00
061
.098
.80.
998
61.0
97.2
0.99
9
AO
A a
moA
gen
eD
NA
59.5
100.
70.
998
59.5
99.7
0.98
859
.597
.80.
994
(Am
oA_m
odF/
Am
oA_m
odR)
cDN
A59
.599
.90.
983
59.5
107.
60.
984
59.5
96.4
0.99
5
Ana
mm
ox b
acte
ria 1
6S rR
NA
gen
e D
NA
59.0
99.0
0.99
859
.096
.40.
995
59.0
98.9
0.99
3
(Bro
d541
F/A
mx8
20R)
cDN
A59
.098
.40.
999
59.0
93.7
0.99
659
.010
6.8
0.98
9
Ana
mm
ox b
acte
ria h
zsA
gen
eD
NA
51.0
82.0
0.99
751
.081
.10.
997
51.0
80.1
0.99
7
(hzs
A_1
597F
/hzs
A_1
857R
)cD
NA
51.0
80.0
0.99
851
.080
.20.
997
51.0
80.4
0.99
6
AO
B 16
S rR
NA
gen
eD
NA
60.0
86.6
0.99
860
.086
.60.
998
60.0
86.6
0.99
8
(CTO
189F
/CTO
654R
)cD
NA
60.0
84.0
0.99
860
.084
.00.
998
60.0
84.0
0.99
8
AO
B am
oA g
ene
DN
A61
.685
.40.
994
61.6
85.4
0.99
461
.685
.40.
994
(AO
B-am
oAF/
AO
B-am
oAR
new
)cD
NA
61.6
91.0
0.99
361
.691
.00.
993
61.6
91.0
0.99
3
qPC
R co
nditi
ons:
95˚C
4 m
in; 4
0 ×
[95˚
C 3
0 s,
mel
ting
tem
pera
ture
(Tm) 4
0 s,
72˚C
30
s]; 8
0˚C
25
s
45
Supplementary MaterialTa
ble
S3: P
hysic
al (C
TD) a
nd c
hem
ical
(nut
rient
) pro
pert
ies o
f th
e bo
ttom
wat
er (B
W).
Para
met
er/
Am
mon
ium
N
itrite
Nitr
ate
Phos
phat
eTe
mpe
ratu
reSa
linity
wat
er d
epth
Sedi
men
t dbs
f [c
m]
[µM
][µ
M]
[µM
][µ
M]
[˚C
][p
su]
[m]
Feb-
11
BW
3.0
0.6
6.8
1.0
5.0
34.4
43.0
May
-11
BW
1.9
0.1
2.0
0.7
8.6
34.3
44.0
Aug
-11
BW
1.6
0.1
0.5
0.5
15.4
34.7
45.0
Chapter 2
46
Table S4: Total organic carbon (TOC) and total organic nitrogen (TON).
Parameter/ TOC TONSediment dbsf [cm] [%] [%]
Feb-110.5 0.22 0.021.5 0.22 bdl*2.5 0.21 0.043.5 0.22 0.044.5 0.26 0.036.5 0.20 0.028.5 0.28 0.0311.5 0.37 0.08
May-11 0.5 0.20 0.021.5 0.30 0.052.5 0.25 0.043.5 0.27 0.034.5 0.38 0.086.5 0.25 0.058.5 0.15 0.0311.5 0.21 0.02
Aug-110.5 0.26 0.031.5 0.27 0.052.5 0.23 0.023.5 0.20 0.024.5 0.31 0.066.5 0.25 0.038.5 0.28 0.0311.5 0.22 0.04
*bdl: below detection limit
47
Supplementary MaterialTa
ble
S5a:
Spe
arm
an ra
nk o
rder
cor
rela
tion
of a
ll pa
ram
eter
s obs
erve
d in
this
stud
y. Pa
ram
eter
NH
4+N
O3-
PO4+
TO
NA
OA
16S
rRN
A g
ene
AO
A a
moA
gen
e
[µ
M]
[µM
][µ
M]
[%]
(RN
A:D
NA
ratio
)(D
NA
) [co
pies
g-1]
Sedi
men
t dep
th [c
m]
0.82
2***
0.80
1***
NH
4+ [µ
M]
0.73
4***
NO
3- [µM
]
PO4+
[µM
]
AO
A 16
S rR
NA
gen
e (D
NA
) [co
pies
g-1]
0.69
4***
AO
A 1
6S rR
NA
gen
e (c
DN
A) [
copi
es g
-1]
0.84
6***
AO
A a
moA
gen
e (D
NA
) [co
pies
g-1]
AO
A a
moA
gen
e (c
DN
A) [
copi
es g
-1]
AO
A a
moA
gen
e (R
NA
:DN
A ra
tio)
Cre
narc
haeo
l IPL
s tot
al [a
rea
g-1]
HPH
-cre
narc
haeo
l [ar
ea g
-1]
TOC
[%]
0.65
7***
Ana
mm
ox b
acte
ria 1
6S rR
NA
gen
e (D
NA
) [co
pies
g-1]
Ana
mm
ox b
acte
ria 1
6S rR
NA
gen
e (c
DN
A) [
copi
es g
-1]
Ana
mm
ox b
acte
ria 1
6S rR
NA
gen
e (R
NA
:DN
A ra
tio)
Ana
mm
ox b
acte
ria h
zsA
gen
e (D
NA
) [co
pies
g-1]
Ana
mm
ox b
acte
ria h
zsA
gen
e (c
DN
A) [
copi
es g
-1]
Ana
mm
ox h
zsA
gen
e (R
NA
:DN
A ra
tio)
PC M
onoe
ther
ladd
eran
e [n
g g-1
]
AO
B 16
S rR
NA
gen
e (c
DN
A) [
copi
es g
-1]
AO
B am
oA (D
NA
) gen
e [c
opie
s g-1]
AO
B am
oA (c
DN
A) g
ene
[cop
ies g
-1]
AO
B am
oA g
ene
(RN
A:D
NA
ratio
)
Cor
rela
tion
coef
ficie
nts
r s ≥ 0
.6 a
nd r s ≤
-0.6
with
P-v
alue
s ≤
0.0
5 w
ere
repo
rted
. The
deg
ree
of s
igni
fican
ce w
as in
dica
ted
by u
sing
a sin
gle
aste
risk
for
P-va
lues
≤ 0
.05
and
≥ 0
.01,
two
aste
risks
for P
-val
ues ≤
0.0
1 an
d th
ree
aste
risks
for P
-val
ues ≤
0.0
05.
Chapter 2
48
Tabl
e S5
b: S
pear
man
rank
ord
er c
orre
latio
n of
all
para
met
ers o
bser
ved
in th
is st
udy.
Para
met
erA
OA
am
oA g
ene
AO
A a
moA
gen
eA
nam
mox
16S
rRN
A g
ene
Ana
mm
ox 1
6S rR
NA
gen
e
(c
DN
A) [
copi
es g
-1]
(RN
A:D
NA
ratio
)(D
NA
) [co
pies
g-1]
(cD
NA
) [co
pies
g-1]
Sedi
men
t dep
th [c
m]
NH
4+ [µ
M]
NO
3- [µM
]-0
.647
***
-0.7
43**
*
PO4+
[µM
]-0
.745
***
-0.7
39**
*
AO
A 16
S rR
NA
gen
e (D
NA
) [co
pies
g-1]
AO
A 1
6S rR
NA
gen
e (c
DN
A) [
copi
es g
-1]
AO
A a
moA
gen
e (D
NA
) [co
pies
g-1]
0.72
5***
AO
A a
moA
gen
e (c
DN
A) [
copi
es g
-1]
0.99
4***
0.62
9***
AO
A a
moA
gen
e (R
NA
:DN
A ra
tio)
Cre
narc
haeo
l IPL
s tot
al [a
rea
g-1]
HPH
-cre
narc
haeo
l [ar
ea g
-1]
TOC
[%]
Ana
mm
ox b
acte
ria 1
6S rR
NA
gen
e (D
NA
) [co
pies
g-1]
0.79
7***
Ana
mm
ox b
acte
ria 1
6S rR
NA
gen
e (c
DN
A) [
copi
es g
-1]
Ana
mm
ox b
acte
ria 1
6S rR
NA
gen
e (R
NA
:DN
A ra
tio)
0.71
7***
Ana
mm
ox b
acte
ria h
zsA
gen
e (D
NA
) [co
pies
g-1]
Ana
mm
ox b
acte
ria h
zsA
gen
e (c
DN
A) [
copi
es g
-1]
Ana
mm
ox h
zsA
gen
e (R
NA
:DN
A ra
tio)
PC M
onoe
ther
ladd
eran
e [n
g g-1
]
AO
B 16
S rR
NA
gen
e (c
DN
A) [
copi
es g
-1]
AO
B am
oA (D
NA
) gen
e [c
opie
s g-1]
AO
B am
oA (c
DN
A) g
ene
[cop
ies g
-1]
AO
B am
oA g
ene
(RN
A:D
NA
ratio
)
49
Supplementary MaterialTa
ble
S5c:
Spe
arm
an ra
nk o
rder
cor
rela
tion
of a
ll pa
ram
eter
s obs
erve
d in
this
stud
y.
Para
met
erA
nam
mox
16S
rRN
AA
nam
mox
hzs
AA
nam
mox
hzs
AA
nam
mox
hzs
APC
-ME
ladd
eran
e
(R
NA
:DN
A ra
tio)
(DN
A) [
copi
es g
-1]
(cD
NA
) [co
pies
g-1]
(RN
A:D
NA
ratio
)[n
g g-1
]
Sedi
men
t dep
th [c
m]
-0.6
62**
*
NH
4+ [µ
M]
NO
3- [µM
]
PO4+
[µM
]
AO
A 16
S rR
NA
gen
e (D
NA
) [co
pies
g-1]
AO
A 1
6S rR
NA
gen
e (c
DN
A) [
copi
es g
-1]
AO
A a
moA
gen
e (D
NA
) [co
pies
g-1]
0.66
2***
AO
A a
moA
gen
e (c
DN
A) [
copi
es g
-1]
0.70
8***
AO
A a
moA
gen
e (R
NA
:DN
A ra
tio)
Cre
narc
haeo
l IPL
s tot
al [a
rea
g-1]
0.79
7***
HPH
-cre
narc
haeo
l [ar
ea g
-1]
0.76
0***
TOC
[%]
Ana
mm
ox b
acte
ria 1
6S rR
NA
gen
e (D
NA
) [co
pies
g-1]
0.84
8***
-0.7
51**
*
Ana
mm
ox b
acte
ria 1
6S rR
NA
gen
e (c
DN
A) [
copi
es g
-1]
0.74
8***
0.72
9***
Ana
mm
ox b
acte
ria 1
6S rR
NA
gen
e (R
NA
:DN
A ra
tio)
Ana
mm
ox b
acte
ria h
zsA
gen
e (D
NA
) [co
pies
g-1]
Ana
mm
ox b
acte
ria h
zsA
gen
e (c
DN
A) [
copi
es g
-1]
Ana
mm
ox h
zsA
gen
e (R
NA
:DN
A ra
tio)
PC M
onoe
ther
ladd
eran
e [n
g g-1
]
AO
B 16
S rR
NA
gen
e (c
DN
A) [
copi
es g
-1]
AO
B am
oA (D
NA
) gen
e [c
opie
s g-1]
AO
B am
oA (c
DN
A) g
ene
[cop
ies g
-1]
0.71
3***
AO
B am
oA g
ene
(RN
A:D
NA
ratio
)
Chapter 2
50
Chapter 2 Supplementary MaterialTa
ble
S5d:
Spe
arm
an ra
nk o
rder
cor
rela
tion
of a
ll pa
ram
eter
s obs
erve
d in
this
stud
y.
Para
met
erA
OB
16S
rRN
A
AO
B 1
6S rR
NA
A
OB
16S
rRN
AA
OB
am
oA
AO
B a
moA
(D
NA
) [co
pies
g-1]
(cD
NA
) [co
pies
g-1]
(RN
A:D
NA
ratio
)(c
DN
A) [
copi
es g
-1]
(RN
A:D
NA
ratio
)
Sedi
men
t dep
th [c
m]
-0.6
46**
*
NH
4+ [µ
M]
NO
3- [µM
]
PO4+
[µM
]
AO
A 16
S rR
NA
gen
e (D
NA
) [co
pies
g-1]
AO
A 1
6S rR
NA
gen
e (c
DN
A) [
copi
es g
-1]
AO
A a
moA
gen
e (D
NA
) [co
pies
g-1]
AO
A a
moA
gen
e (c
DN
A) [
copi
es g
-1]
AO
A a
moA
gen
e (R
NA
:DN
A ra
tio)
Cre
narc
haeo
l IPL
s tot
al [a
rea
g-1]
HPH
-cre
narc
haeo
l [ar
ea g
-1]
TOC
[%]
Ana
mm
ox b
acte
ria 1
6S rR
NA
gen
e (D
NA
) [co
pies
g-1]
Ana
mm
ox b
acte
ria 1
6S rR
NA
gen
e (c
DN
A) [
copi
es g
-1]
Ana
mm
ox b
acte
ria 1
6S rR
NA
gen
e (R
NA
:DN
A ra
tio)
Ana
mm
ox b
acte
ria h
zsA
gen
e (D
NA
) [co
pies
g-1]
Ana
mm
ox b
acte
ria h
zsA
gen
e (c
DN
A) [
copi
es g
-1]
0.65
6***
Ana
mm
ox h
zsA
gen
e (R
NA
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53
3. Lack of 13C-label incorporation suggests low turnover rates of thaumarchaeal intact polar tetraether lipids in sediments from the Iceland Shelf
Sabine K. Lengger, Yvonne A. Lipsewers, Henk de Haas, Jaap S. Sinninghe Damsté and Stefan Schouten
Thaumarchaeota are amongst the most abundant microorganisms in aquatic environments, however, their metabolism in marine sediments is still debated. Labeling studies in marine sed-iments have previously been undertaken, but focused on complex organic carbon substrates which Thaumarchaeota have not yet been shown to take up. In this study, we investigated the activity of Thaumarchaeota in sediments by supplying different 13C-labeled substrates which have previously been shown to be incorporated into archaeal cells in water incubations and/or enrichment cultures. We determined the incorporation of 13C-label from bicarbonate, pyruvate, glucose and amino acids into thaumarchaeal intact polar lipid-glycerol dibiphytanyl glycerol tet-raethers (IPL-GDGTs) during 4–6 day incubations of marine sediment cores from three sites on the Iceland Shelf. Thaumarchaeal intact polar lipids, in particular crenarchaeol, were detected at all stations and concentrations remained constant or decreased slightly upon incubation. No 13C incorporation in any IPL-GDGT was observed at stations 2 (clay-rich sediment) and 3 (or-ganic-rich sediment). In bacterial/eukaryotic IPL-derived fatty acids at station 3, contrastingly, a large uptake of 13C label (up to + 80‰) was found. 13C was also respired during the experiment as shown by a substantial increase in the 13C content of the dissolved inorganic carbon. In IPL-GDGTs recovered from the sandy sediments at station 1, however, some enrichment in δ13C (1–4‰) was detected after incubation with bicarbonate and pyruvate. The low incorporation rates suggest a low activity of Thaumarchaeota in marine sediments and/or a low turnover rate of thaumarchaeal IPL-GDGTs due to their low degradation rates. Cell numbers and activity of sedimentary Thaumarchaeota based on IPL-GDGT measurements may thus have previously been overestimated.
Biogeosciences, 11, 201–216, 2014
Chapter 3
54
3.1. IntroductionThaumarchaeota are ubiquitous microorganisms (Hatzenpichler, 2012 and references cited therein) which have recently been discovered to form a separate phylum, the Thaumarchaeota (Brochier-Armanet et al., 2008; Spang et al., 2010). They were initially discovered as the Marine Group I Crenarchaeota in the coastal and open ocean (DeLong, 1992; Fuhrman et al. 1992; Karner et al., 2001) where they are abundantly present in the epipelagic zone (e.g. Francis et al., 2005; Beman et al., 2008) but also in deep water (Fuhrman and Davis, 1997; Herndl et al., 2005; Agogué et al., 2008) where they can be as abundant as the total bacterial population. Thaumar-chaeota have also been detected in marine sediments (Hershberger et al., 1996; Francis et al., 2005).
Before enrichment cultures became available, the metabolism of Thaumarchaeota was unclear. Hoefs et al. (1997) suggested, based on the 13C-enrichment of thaumarchaeal lipids in compari-son to algal biomarkers, the possibility of autotrophic assimilation of dissolved inorganic carbon (DIC) using a different pathway than via Rubisco, or, alternatively, the heterotrophic uptake of small organic molecules. Indeed, 13C-labeling studies with bicarbonate showed the incorporation of 13C-labelled DIC into thaumarchaeal membrane lipids and thus their autotrophic metabolism (Wuchter et al., 2003). Unambiguous proof for the growth of Thaumarchaeota on inorganic carbon came with the first enrichment culture of Nitrosopumilus maritimus, which was growing chemolithoautotrophically on bicarbonate, and gaining energy by the oxidation of ammonia to nitrite (Könneke et al., 2005). It was suggested that 3-hydroxypropionate/4-hydroxybutyrate pathway was used by these microorganisms (Berg et al., 2007), which was supported by genetic analyses of C. symbiosum (Hallam et al., 2006) and N. maritimus (Walker et al., 2010). However, in these two species, also genes involved in heterotrophic metabolisms were detected, which implies their potential for mixotrophy. Furthermore, the uptake of pyruvate into cell material in cultures of a Thaumarchaeote enriched from soil, Nitrososphaera viennensis, was demonstrated (Tourna et al., 2011).
Indeed, there is some environmental evidence for a mixotrophic metabolism of Thaumar-chaeota. Ouverney and Fuhrman (2000) as well as Herndl et al. (2005) showed, via MICRO-CARD-FISH using 3H-labeled amino acids, that thaumarchaeal cells present in sea water take up amino acids. There is also circumstantial evidence for mixotrophy of Thaumarchaeota, such as the radiocarbon values of archaeal lipids in the deep ocean (Ingalls et al., 2006), thaumarchaeal activity (as quantified by uptake of substrate measured by MAR-FISH) being correlated to the presence of urea (Alonso-Sáez et al., 2012), and the possession of genes for urea transporters (Baker et al., 2012). Mußmann et al. (2011) found thaumarchaeal cell numbers in waste reactors that were too high to be supported by the rates of ammonia oxidation, and a lack of incorpo-ration of 13C-labelled DIC into thaumarchaeal lipids during growth, also suggesting heterotro-phy of Thaumarchaeota. Circumstantial evidence, based on the correlation of organic carbon concentration with archaeal biomarker lipids, suggests that Archaea in deep subsurface marine sediments (<1 m) use organic carbon (Biddle et al., 2006; Lipp et al., 2008; Lipp and Hinrichs, 2009), however, this empirical correlation could also be due to preservation factors affecting biomarkers and total organic carbon in a similar way (Hedges et al., 1999; Schouten et al., 2010). These studies thus illustrate the potential for diversity of thaumarchaeal metabolisms.
Cell membranes of Thaumarchaeota consist of glycerol dibiphytanyl glycerol tetraether lip-ids (GDGT) in the form of intact polar lipids (IPL; Schouten et al., 2008; Pitcher et al., 2011a;
55
Introduction/Material and Methods
Sinninghe Damsté et al., 2012; Fig. 1a). They possess GDGTs which are also present in other Archaea (Koga and Nakano, 2008), such as GDGT-0, -1, -2 and -3 (Fig. 1b), but also a specific lipid named crenarchaeol, which up to now has only been found in (enrichment) cultures of Thaumarchaeota (Sinninghe Damsté et al., 2002; de la Torre et al., 2008; Schouten et al., 2008; Pitcher et al., 2011b; Sinninghe Damsté et al., 2012). Stable isotope probing (SIP) experiments targeting the biphytanyl chains contained in crenarchaeol (Fig. 1c), have been undertaken in order to determine the uptake of different substrates. This revealed the incorporation of 13C from bicarbonate into crenarchaeol (Wuchter et al., 2003). Pitcher et al. (2011c) showed that this uptake was dependent on ammonia oxidation in North Sea water, as addition of inhibitors for ammonia oxidation, nitrapyrine (N-serve) or chlorate, resulted in a decreased incorporation of 13C-labelled DIC. Other SIP experiments carried out with organic substrates were less success-ful: Lin et al. (2012) achieved only a 2‰ enrichment in one of the biphytanyl chains of crenar-chaeol, but 2‰ depletion in the other biphytanyl chain when adding 13C -labeled phytodetrital organic carbon to sediment slurries. Takano et al. (2010) and Nomaki et al. (2011) also carried out benthic in situ-labeling experiments and did not find incorporation of 13C in the biphytanyl chains in an incubation experiment with 13C-labeled glucose in sediment from Sagami Bay, Ja-pan, after 405 days, although they noted an initial apparent increase in δ13C of one biphytane by ~10‰. This was in spite of an increase in molecular thaumarchaeal biomarkers within 9 days. Remarkably, however, they did report labeling of the glycerol moieties of the GDGT molecules after 405 days. Thus, not much evidence for substantial incorporation of carbon from organic substrates into thaumarchaeal lipids is observed in SIP experiments performed with sediments. It is possible that the types of substrate used in these studies were not suitable, i.e. not readily taken up by the Thaumarchaeota, and that other organic compounds would result in higher in-corporation. Interestingly, none of the previously conducted labeling studies in sediments used 13C-labelled DIC. Bicarbonate had previously unambiguously been shown to be incorporated by pelagic Thaumarchaeota (Wuchter et al., 2003; Pitcher et al. 2011c) and by Thaumarchaeota enriched from sediments (Park et al., 2010) and soils (Jung et al., 2011; Kim et al., 2012).
To shed further light on the metabolism of sedimentary Thaumarchaeota, we performed labeling experiments using 13C-labeled substrates, i.e. bicarbonate, pyruvate, amino acids and glu-cose in sediment cores from the Iceland shelf and determined the degree of 13C incorporation into the most abundant GDGT-lipids, i.e. crenarchaeol which is specific for Thaumarchaeota and GDGT-0, which can also be produced by other Archaea. All these compounds have pre-viously been shown to be taken up by Thaumarchaeota either in the environment (Ouverney and Fuhrman, 2000; Wuchter et al. 2003; Herndl et al., 2005; Takano et al., 2010; Pitcher et al. 2011c) or enrichment cultures (Park et al., 2010; Jung et al., 2011; Tourna et al., 2011; Kim et al., 2012) and were thus deemed the most suitable substrates and most likely to result in uptake by sedimentary Thaumarchaeota. The results are discussed with respect to the uptake of substrates as well as the turnover rates of thaumarchaeal GDGTs.
3.2. Material and Methods
3.2.1. Sampling stationsSediment cores were sampled at three stations, located on the Iceland Shelf, during the ‘Long Chain Diols’ cruise on the R/V Pelagia in July 2011 (Fig. 2). Station 1 (63°21’N 16°38’W), south of Iceland, was at 240 m water depth and consisted of dark, sandy sediment.
Chapter 3
56
Station 2 (66°18’N 13°58’W) is located north-east of Iceland, at 261 m water depth, and the sediment was sandy-clayish. Sediment at Station 3 (67°13’N 19°07’W), north of Iceland, at 503 m water depth, and further offshore than the other two stations, consisted of dark, soft, black mud. From each station, multicores were retrieved in polycarbonate core tubes. Ten cores from each station were retrieved in tubes of 10 cm diameter with drilled holes downwards, spaced 1 cm apart, and used for incubation. Cores sampled with tubes of 5 cm diameter were used for oxygen microprofiling, pore-water extraction, and four cores from each station were sliced and stored for density and total organic carbon (TOC) analysis.
3.2.2. Core characterizationFor each station, control cores were sliced into 1 cm thick layers from 0–10 cm core depth. The water content of each sediment was determined by weighing prior to and after freeze-drying. To-tal organic carbon was determined from freeze-dried sediments following overnight acidification with 2N HCl, subsequent washes with bidistilled H2O and water removal by freeze-drying. The decalcified sediments were measured on a Flash EA 1112 Series (Thermo Scientific, Waltham, MA) analyzer coupled via a Conflo II interface to a Finnigan Deltaplus mass spectrometer. Stan-dard deviations from three measurements ranged from 0.0 to 0.6% TOC.
Two cores (5 cm diameter) from each cast were used for oxygen microprofiling with an OX-100 Unisense oxygen microelectrode (Unisense, Aarhus, DK; Revsbech, 1989). A two-point
b
a
Crenarchaeol O
O
O
O
HO
OH
c
Monohexose-crenarchaeol
Dihexose-crenarchaeol
Hexose, phosphohexose-crenarchaeol
OO
O
O
O
O
OHO
HO
OHO OH
HOHO OH
O
OO
O
O
O
O
O PO
OO
HOHO
HO OH
OHOH
OH
HO
OO
O
O
O
O
HO
HOHO OH
O
O
O
O
HO
OH
OH
OH
acyclic biphytane
bicyclic biphytane
tricyclic biphytane
HI, ∆
4
GDGT-0
OO
OO
HO
OH
OO
OO
HO
OH
LiAlH , ∆
Figure 1: Structures of crenarchaeol and GDGT-0 (a), IPL-crenarchaeol species (b) and biphytanyl chains released from crenarchaeol and GDGT-0 by chemical degradation (c).
57
Material and Methods
calibration was carried out with bottom water from the same station bubbled with air at 4°C for at least 5 min (100% saturation) and a solution of 0.1 M sodium ascorbate in 0.1 N NaOH in Milli-Q Water (0% saturation) and the electric current measured in pA was converted to mg L–1 O2. The sensor was moved with a micromanipulator one mm at a time.
Pore water was extracted on board from slices of several cores by centrifugation. Five mL from each depth was preserved air-free with added HgCl2 for analysis of the δ13C of the dis-solved inorganic carbon (DIC) at 4°C, and 3 mL were preserved at –20°C for analysis of phos-phate, ammonia, nitrite and nitrate.
Dissolved inorganic phosphate, ammonia, nitrite and nitrate were measured on a Traacs 800 Autoanalyzer (Seal Analytical, Fareham, UK). Ortho-phosphate was measured using potassium antimonyltartrate as a catalyst and ascorbic acid as a reducing reagent which resulted in for-mation of a blue (880 nm) molybdenum phosphate-complex at pH 0.9–1.1 (Murphy and Riley, 1962). Ammonia was measured via formation of the indo-phenol blue-complex (630 nm) with phenol and sodium hypochlorite at pH 10.5 in citrate (Helder and de Vries, 1979). Dissolved inorganic nitrite concentrations were measured after diazotation of nitrite with sulphanilamide and N-(1-naphtyl)-ethylene diammonium dichloride to form a reddish-purple dye measured at 540 nm. Nitrate was first reduced in a copperized Cd-coil using imidazole as a buffer, measured as nitrite and concentrations were calculated by subtraction of nitrite (Grasshoff et al., 1983).
δ13C of DIC was measured in pore water from all stations, and bottom water samples from the experiments, on a Thermo GasBench II coupled to a Thermo Delta Plus and is reported in
Iceland100
500Den
mark S
trait
1000
1000
20 ° 10 °
200060 °
30 °
Iceland Basin
20003000
Faroes
Jan Mayen
Greenland
Iceland2000
100
3000
Station 3
Station 2
Station 1
Figure 2: Map of the sampling stations (1, 2 and 3) on the Iceland shelf.
Chapter 3
58
Lower part of splitable core(upper part removed)
90°
Air in (pipette)
Drilled holes 2.5 mmfilled with silicon
Stopper
Stopper
Yellow tape
Distance 1 cm
Airpump
Filter 0.2 mm
Water bath for optimum temperature (4°C)
Figure 3: Scheme of the incubation set-up of the cores.
the delta notation against the Vienna Pee-Dee Belemnite (V-PDB) standard. To this end, 0.5 mL of each sample was injected into gastight exetainers, containing 0.1 mL of 80% H3PO4, that had been flushed for 15 min each with He. Performance was monitored by analysis of an in-house laboratory standard of Na2CO3 with a δ13C of –0.57‰ after every 12 measurements and an in-house laboratory standard of CaCO3, with a δ13C value of –24.2‰ at the start and the end of every series. Measured values of these standards were usually not deviating by more than 0.5‰ from the calibrated (on NBS-19) values.
3.2.3. Incubation conditionsTen cores from each station were used for incubations (Table 2). For this, splitable polycarbonate core tubes with 10 cm diameter were prepared by drilling two rows of 1 mm holes spaced at distances of 1 cm. The two rows were 90° contorted; holes were filled with silicon and covered with plastic non-permeable tape (see setup in Fig. 3). The cores were, after recovery from the multicorer, transferred as quickly as possible to a temperature-controlled room kept at 4°C, and the bottom water was sampled with a sterile pipette for determination of pH, δ13C of DIC and nutrients as described above. Four whole cores at each station were incubated with 13C-la-belled substrates, i.e. bicarbonate, pyruvate, amino acids and glucose, and one whole core (‘back-ground’) was injected with MilliQ water only. Four more cores were incubated with solutions containing one of the substrates and a nitrification inhibitor, and one (‘background + inhibitor’) with MilliQ water and the nitrification inhibitor. The incubation solutions were injected into
59
Material and Methods
the seven injection ports from the surface downwards, i.e. the first 8 cm were supplied with the labeled substrate. Injection solutions contained 99% 13C-labelled substrates as supplied by Cam-bridge Isotope Laboratories (Andover, MA, USA). The substrates were dissolved in MilliQ-H2O in concentrations of 3.7 mg mL–1 for NaHCO3
– (Bic), 1.01 mg mL–1 for Glucose (Glu), 0.89 mg mL–1 for a mix of 16 algal amino acids (AA; 97–99% labeled; CLM 1548) and 1.24 mg mL–1 of sodium pyruvate (Pyr). 200 μL were delivered to each slice by injection through the two 90° contorted injection ports, which corresponded to a total addition of 1.6 g 13C m–3 sediment for the bicarbonate, and 1.2 g 13C m–3 for the organic compounds. The nitrification inhibitor was Nitrapyrine (N-Serve, Pestanal) at 11.5 μg mL–1, which is known to inhibit archaeal ammonia oxidation (Park et al., 2010; Pitcher et al., 2011c). As Nitrapyrine cannot be dissolved in pure water, 5% of EtOH was added and the solutions were kept at 30°C to prevent precipitation of the Nitrapyrine. Nitrapyrine-free incubation solutions were kept at the same conditions.
After injection, the cores were stored in the dark at 4°C in a water bath - boxes with core holders filled with water for 62 h (38 h for Station 3), after which the bottom water was sampled for 13C-DIC and N- and P-nutrients as described above and re-injected with a fresh solution of the substrates in water, with or without nitrapyrine added. During the incubation time, the cores were covered lightly with a rubber stopper, so that the escape of air was possible, and aerated through a sterile plastic pipette, with air pumped by an aquarium pump and filtered through a 0.2 mm filter for sterilization purposes. After 144 h (96 h for Station 3), bottom water samples for 13C-DIC (dissolved inorganic carbon) and N- and P-nutrients were taken again, and oxygen microprofiles were measured as described above on all cores (except for Station 2, where cores were too short and thus surfaces too low in the core tubes, to allow measurements in more than three cores). Subsequently, the upper 10 cm of the sediment were sliced in 1 cm resolution and each slice mixed thoroughly, split in half and both parts were frozen at –80°C immediately. The incubations at station 3 were shorter due to time constraints.
3.2.4. Lipid extraction, separation and measurementsThe freeze-dried sediments of 0–1 cm, 1–2 cm and 7–8 cm depth intervals of the incubation and background cores were ground and extracted by a modified Bligh-Dyer extraction meth-od (Pitcher et al., 2009). Briefly, they were extracted ultrasonically three times in a mixture of methanol/dichloromethane (DCM)/phosphate buffer (2:1:0.8, v:v:v), centrifuged and the sol-vent phases were combined. The solvent ratio was then adjusted to 1:1:0.9, v:v:v, which caused the DCM to separate. Liquid extraction was repeated two more times, the DCM fractions were combined, the solvent was evaporated and bigger particles were removed over cotton wool. An aliquot of the extracts was stored for high performance liquid chromatography /electron spray ionization tandem mass spectrometry (HPLC/ESI-MS2) analysis, and another aliquot was sepa-rated into core lipid (CL)- and intact polar lipid (IPL)-GDGTs by silica column separation with hexane/ethyl acetate (1:2, v:v) for the CL-fraction and MeOH to elute the IPL-fraction. 0.1 mg C46 internal standard (Huguet et al., 2006) were added to the CL-fractions. The IPL-fraction was split in three aliquots: 5% were used to determine the carry-over of CL-GDGTs into the IPL-fraction and measured directly via HPLC/APCI-MS, 60% were kept for ether cleavage in order to determine the 13C incorporation into the biphytanes (see below), and 35% were subject-ed to acid hydrolysis under reflux for 2 h with 5% HCl in MeOH, followed by addition of water and extraction (3 ×) of the aqueous phase at an adjusted pH of 4–5 with DCM. This yielded the IPL-derived GDGTs which were measured via HPLC/APCI-MS. The C46 internal standard was
Chapter 3
60
used to quantify the IPL-derived GDGTs and the carry over, but was added after the aliquot for 13C analysis was taken in order to prevent any possible interference of alkyl chains released from the internal standard molecule.
3.2.5. δ13C analysis of biphytanes Aliquots (60%) of the IPL-fractions were subjected to chemical treatment in order to cleave GDGTs, releasing the biphytanyl chains (Fig. 1c) according to Schouten et al. (1998). For this, the IPL fraction was refluxed in 57% HI for 1 h to break the ether bonds and produce alkylio-dides and subsequently extracted three times with hexane. The hexane phase was washed with 5% NaS2O7 and twice with water. The alkyliodides were purified over Al2O3 with hexane/DCM (9:1, v:v), hydrogenated with H2/PtO2 in hexane for 1 h (Kaneko et al., 2011) and eluted over Na2O3 with DCM. As the H2/PtO2 hydrogenation-procedure has never been tested for stable carbon isotope analysis, we used four CL-fractions of extracts from Station 1 and Station 2, split them in half and hydrogenated one half with the conventional LiAlH4 reduction method de-scribed by Schouten et al. (1998), the other half with the method described here and by Kaneko et al. (2011). The conventional method consisted of LiAlH4 in 1,4-dioxane for 1 h under reflux, then the remaining LiAlH4 was reacted with ethyl acetate, bidistilled H2O was added and the bi-phytanes were extracted with DCM from the dioxane/H2O mixture. Additional purification was achieved by elution over an Al2O3 column using hexane. The results showed that the δ13C values of the biphytanes were not significantly different when H2/PtO2 treatment and LiAlH4 hydro-genation were compared (Table 1). However, when yields were compared, it was obvious that hydrogenation with H2/PtO2 gave better results. This is probably due to the fact that the H2/PtO2 treatment requires fewer workup procedures after hydrogenation (only one drying step) than the LiAlH4 treatment, which requires two column separations in addition to a drying step.
3.2.6. δ13C of phospholipid-derived fatty acidsIn order to demonstrate that the incubation experiments did result in label uptake by the sedi-mentary microbial community, we determined the uptake of 13C-label by bacteria and eukaryotes by isotopic analysis of polar lipid-derived fatty acids (PLFA). For this, one third of the extract of the 0–1 cm sediment slice from Station 3, from the cores incubated with bicarbonate, glucose, amino acids and the background core (all without nitrapyrine), were used and analyzed for PLFA according to Guckert et al. (1985). Briefly, the aliquots were separated over a silica column with DCM, acetone and methanol, respectively, with the methanol-fraction containing the PLFA. PLFA fractions were saponified in methanolic KOH (2N) and, after adjusting to pH 5, the re-sulting fatty acids were extracted with DCM and methylated with BF3-MeOH (with a δ13C of –25.4 ± 0.2 ‰V-PDB) before measurements by gas chromatography – isotope ratio mass spec-trometry (GC-irMS). The δ13C values for the fatty acids were corrected for the added carbon.
3.2.7. HPLC-APCI-MS and HPLC-ESI-MS2The CL-fractions, hydrolyzed IPL- fractions and the IPL-fractions themselves (to determine the carry-over of CL into the IPL fraction) were analyzed by HPLC-APCI-MS as described previously (Schouten et al., 2007). HPLC-ESI-MS2 in selected reaction monitoring (SRM) mode, as described by Pitcher et al. (2011b), was used to analyze selected IPL-GDGTs. IPL-GDGTs monitored were monohexose (MH)-crenarchaeol, dihexose (DH)-crenarchaeol and hexose, phosphohexose (HPH)-crenarchaeol. Performance was monitored using a lipid extract of sed-
61
Material and Methods
iment known to contain the monitored GDGTs that was injected every 8 runs. Response areas per mL sediment (mL sed) are reported, as absolute quantification was not possible due to a lack of standards. The values reported are the averages of duplicate injections and their standard deviations.
3.2.8. GC-MS and GC-irMSGC-MS was used to identify the biphytanes and phospholipid-derived fatty acid methyl esters (FAME) using a TRACE GC with a DSQ-MS. The gas chromatograph was equipped with a fused silica capillary column (25 m, 0.32 mm internal diameter) coated with CP Sil-5 (film thick-ness 0.12 mm). The carrier gas was helium. The compound specific isotope composition of the biphytanes and fatty acids was measured with an Agilent 6800 GC, using the same GC column conditions, coupled to a ThermoFisher Delta V isotope ratio monitoring mass spectrometer. The isotopic values were calculated by integrating the mass 44, 45 and 46 ion currents of the peaks and that of CO2-spikes produced by admitting CO2 with a known 13C-content into the mass spectrometer at regular intervals. The performance of the instrument was monitored by
Table 1: δ13C values of the acyclic, bicyclic, and tricyclic biphytanes obtained via H2/PtO2 and LiAlH4 reduction of alkyliodides formed via HI ether cleavage.
δ13C (‰)acyclic bicyclic tricyclic
Sample H2/PtO2 LiAlH4 H2/PtO2 LiAlH4 H2/PtO2 LiAlH4
Station 1 0–1 cm –20.3 ± 0.4 –20.2 ± 0.0 –19.7 ± 0.7 –20.0 ± 0.6 –19.5 ± 1.1 –21.2 ± 0.8
Station 1 1-–2 cm –19.9 ± 0.6 –22.0 ± 0.2 –18.4 ± 0.2 –20.2 ± 1.6 –19.0 ± 0.2 –19.8 ± 0.6
Station 2 0–1 cm –22.7 ± 0.7 –22.0 ± 0.4 –24.2 ± 1.0 –22.4 ± 0.3 –22.6 ± 1.6 –22.0 ± 0.4
Station 2 1–2 cm –24.0 ± 1.0 –25.6 ± 0.2 –22.3 ± 1.4 –25.6 ± 0.8 –22.6 ± 0.2 –25.0 ± 0.6
Total amount / μgacyclic bicyclic tricyclic
Sample H2/PtO2 LiAlH4 H2/PtO2 LiAlH4 H2/PtO2 LiAlH4
Station 1 0–1 cm 0.79 0.28 0.27 0.16 0.31 0.18
Station 1 1–2 cm 0.42 0.16 0.14 0.07 0.15 0.08
Station 2 0–1 cm 0.45 0.34 0.17 0.16 0.23 0.23
Station 2 1–2 cm 0.13 0.05 0.04 0.0 0.06 0.0
Chapter 3
62
Table 2: The bottom water NO3– concentrations and δ 13DIC changes over the incubation time (Δt–t0),
as well as oxygen penetration depths measured after the incubations. In brackets, the average values of ox-ygen penetration depth for the cores before incubation. BG: background, Bic: bicarbonate, Pyr: pyruvate, +Inh: nitrification inhibitor nitrapyrine added.
Station IncubationNO3
– Δδ13DICt–t0 O2 Pen depth
[mM] [‰] [mm]t=0h t=62 h t=144h t=62 h t=144h t=144h
(before: 17)
1
BG 17.9 19.1 4.1 0.6 2.8 11
Bic 15.9 16.2 8.2 66.5 156.2 16
Pyr 18.1 19.2 5.9 109.1 457.0 16
BG+Inh 15.5 16.3 13.9 –0.5 2.6 20
Bic+Inh 11.5 12.0 3.8 135.3 275.5 20
Pyr+Inh 25.4 25.6 14.3 72.7 671.1 16
(before: 13)
2
BG 12.14 11.37 0.09 –0.5 2.9 9
Bic 5.55 4.05 0.07 336.5 606.0 6
Pyr 13.77 12.48 0.12 366.6 1570.7 6
BG+Inh 10.72 10.45 0.19 0.1 3.5 5
Bic+Inh 7.22 6.79 0.09 255.4 570.1 6
Pyr+Inh 5.01 3.17 0.06 511.3 1136.4 16
(before: 16)
3
BG 13.84 0.00 0.13 1.5 –2.3 n.d.
Bic 13.83 12.60 0.08 558.2 814.3 n.d.
Pyr 6.45 4.23 0.12 1108.9 1496.3 n.d.
Glu 14.14 12.03 0.11 90.4 194.2 n.d.
AA 15.34 13.55 0.15 82.7 201.9 n.d.
BG+Inh 16.06 13.39 0.11 0.3 4.9 8
Bic+Inh 15.23 14.05 0.18 244.8 520.3 n.d.
Pyr+Inh 8.92 6.68 0.10 682.7 1644.5 8
Glu+Inh 5.86 4.77 0.03 110.8 301.2 10
AA+Inh 14.36 13.41 0.09 62.2 368.2 n.d.
n.d. - could not be determined.
63
Material and Methods
cδ C - DIC [‰]13PO [µmol . L ]
NH [µmol . L ] NO [µmol . L ]-1
2
3
NO [µmol . L ]4-1
-1
-13-
4
-
-+O [mg/L]2
0 2 4 6 8 10 12
Sed
imen
t dep
th [c
m]
0 2 4 6 8 10-2
0
2
4
6
8
10
0 10 20 30 40 50
0.0 0.2 0.4 0.6
0 2 4 6 8 10121416
-4 -3 -2 -1 0 1 2
b δ C - DIC [‰]13PO [µmol . L ]
NH [µmol . L ] NO [µmol . L ]-1
2
3
NO [µmol . L ]4-1
-1
-13-
4
-
-+O [mg/L]0 2 4 6 8 10 12
-2
0
2
4
6
8
10
Sed
imen
t dep
th [c
m]
2
0 2 4 6 8 10 12
0 20 40 60 80
0.0 0.2 0.4 0.6
0 4 8 12 16
-4 -3 -2 -1 0 1 2
O [mg/L]2
0 2 4 6 8 10 12
-2
0
2
4
6
8
10
Sed
imen
t dep
th [c
m]
PO [µmol . L ]0 4 8 12 16
NH [µmol . L ] 0 20 40 60 80
NO [µmol . L ]-1
2
3
δ C - DIC [‰]NO [µmol . L ]0.0 0.2 0.4 0.6
0 10 20 30 40
4-1
-1
-13-
4
-
-+
-4 -3 -2 -1 0 1 2
13a
Figure 4: Oxygen microprofiles and pore water results vs. depth at station 1 (a), 2 (b) and 3 (c).
Chapter 3
64
daily injections of a standard mixture of a C20 and a C24 perdeuterated n-alkane. Two replicate analyses (one in the case of the fatty acids) were carried out and the results were averaged in order to obtain the average and standard deviations. The stable carbon isotope compositions are reported in the delta notation against the V-PDB standard. Some values of the biphytanes could not be determined due to low concentrations, mainly in the background cores at station 2. For calculations of incorporation, the background values from station 1 were used.
3.3. Results
3.3.1. Sediment characteristicsThe sediments at stations 1–3 consisted of sand, sandy clay, and dark and soft mud, respectively. Oxygen penetration depth was on average 17 mm at station 1, while oxygen penetrated slightly less deep at station 2 (13 mm on average) and station 3 (15.5 mm on average; Fig. 4). At station 1, organic carbon contents were low with 0.6 % at 0–1 cm depth and 0.3% at 1–2 cm and 6–7 cm depth. Organic carbon contents were higher at station 2 and amounted to 1.4–1.7% and were highest at station 3 (2.0–2.5%). The pH of the bottom water hardly differed between stations and was typically marine, i.e. 8.2 at station 1, 8.0 at station 2, and 7.9 at station 3.
Pore water concentrations of nutrients, as shown in Fig. 4, showed similar trends with depth at the three stations. Inorganic phosphate concentrations were 1 μM in the bottom water and gen-erally increased with depth up to 7–14 μM. Ammonia concentrations increased as well with sed-iment depth, from 0.19 to 1.3 μM in bottom water to 44–70 μM at depth. Nitrite concentrations were an order of magnitude higher in the pore water (0.32–0.62 μM) than in the bottom water (0.055 μM), and increased with sediment depth. Nitrate concentrations were high in the bottom water, 14 μM, and generally decreased quickly with depth in the sediment to values between 0.6 and 3 μM. The δ13C of the DIC showed also similar profiles at the three stations. It decreased from 1‰ in the bottom water to –3‰ in the pore water. At station 2, δ 13C of the DIC could only be measured in the bottom water and the four uppermost pore water samples, but, in these samples, showed the same decrease with depth as observed at Station 1, from –1.3 ‰ to –2.9 ‰.
3.3.2. GDGT-abundanceGDGT-concentrations averaged over all cores from the incubations (10 per station) are shown with standard deviation in order to give an impression of the range of concentrations found (Fig. 5). GDGT-0 and crenarchaeol were present as a core lipid in concentrations of 0.4 to 0.8 μg mL sed–1, and 0.08 to 0.12 μg mL sed–1 for the minor isoprenoid GDGTs (i-GDGTs; GDGT-1, -2 and -3). Concentrations were similar at all stations and did not show substantial changes with sediment depth. IPL-derived GDGTs were present in lower concentrations and amounted to 0.09 to 0.3 (GDGT-0), 0.07 to 0.18 (crenarchaeol) μg mL sed–1. Concentrations were generally lower at station 1 compared to stations 2 and 3. Direct analysis of individual IPL-crenarchaeol showed that the head groups mainly consisted of monohexose (MH)- and hexose, phospho-hexose (HPH)- headgroups, with only a small contribution of dihexose (DH)- head groups (Fig. 5c). The proportion of HPH- to the total peak area of IPL-crenarchaeol was ca. 80–90% in the surface sediments (0–1 and 1–2 cm) of all stations. At station 1 and 2, this decreased to 10–25% in the deepest sediment slice analyzed, 6–7 cm. At station 3, HPH-crenarchaeol dominated at all sediment depths (Fig. 4).
65
Material and Methods/Results
Tabl
e 3:
Bac
kgro
und
(BG
) val
ues o
fδ 13
C o
f th
e bip
hyta
nes (
BP) m
easu
red
in th
e sed
imen
t (i.e
. δ13
C o
f th
e bi
phyt
anes
that
wer
e inc
ubat
ed ju
st w
ith w
ater
, bu
t und
er th
e sa
me
cond
ition
s). T
hese
val
ues
wer
e us
ed fo
r de
term
inat
ion
of th
e Δ13
C: B
G v
alue
s w
ere
subt
ract
ed fr
om th
e 13
C o
f th
e co
rres
pond
ing
valu
e m
easu
red
from
the
core
s inc
ubat
ed w
ith la
bel (
Fig.
6). N
umbe
rs in
dica
te th
e de
pth
inte
rval
the
sam
ple
was
com
ing
from
, + :
nitri
ficat
ion
inhi
bito
r ni
trapy
rine
adde
d fo
r inc
ubat
ion,
- : n
o in
hibi
tor a
dded
. Val
ues a
t sta
tion
2 co
uld
not b
e de
term
ined
due
to lo
w c
once
ntra
tions
.
Stat
ion
1St
atio
n 2
Stat
ion
3
δ13C
[‰]
δ13C
[‰]
δ13C
[‰]
Sedi
men
t(c
m)
acyc
lic
BP
bicy
clic
B
Ptr
icyc
lic
BP
acyc
lic
BP
bicy
clic
B
Ptr
icyc
lic
BP
acyc
lic
BP
bicy
clic
B
Ptr
icyc
lic
BP
–
0–1
–22.
0 ±
0.1
–20.
5 ±
1.1
–19.
9 ±
0.3
n.d.
*n.
d. *
n.d.
*–2
0.4
± 0
.2–2
0.2
± 1
.2–1
9.8
± 0
.8
1–2
–21.
4 ±
0.5
–20.
7 ±
0.1
–20.
2 ±
0.0
n.d.
*n.
d. *
n.d.
*–1
9.6
± 1
.2–1
8.3
± 1
.4–1
7.7
± 1
.9
6–7
–21.
4 ±
0.2
–22.
4 ±
1.9
–21.
5 ±
2.3
n.d.
*n.
d. *
n.d.
*–2
0.6
± 0
.4–2
0.1
± 0
.4–1
9.2
± 0
.6
+
0–1
n.d.
*n.
d.*
n.d.
*n.
d. *
n.d.
*n.
d. *
–19.
3 ±
0.6
–19.
7 ±
0.6
–19.
4 ±
0.3
1–2
–22.
0 ±
0–2
1.2
± 0
.4–2
1.3
± 0
–22.
9 ±
0.9
–21.
4 ±
1.4
–20.
3 ±
0.9
–19.
4 ±
0.1
–19.
9 ±
0.4
–19.
2 ±
0.2
6–7
–22.
4 ±
0
–20.
0 ±
0.6
–22.
2 ±
0–2
2.0
± 0
.0–2
1.0
± 0
.4–2
0.0
± 0
.4–2
2.4
± 0
.0–2
1.4
± 0
.4–2
0.7
± 0
.1
* n.d
. – c
ould
not
be
dete
rmin
ed.
Chapter 3
66
0-1 cm 1-2 cm 6-7 cm0-1 cm 1-2 cm 6-7 cm0-1 cm 1-2 cm 6-7 cm
0-1 cm 1-2 cm 6-7 cm
0-1 cm 1-2 cm 6-7 cm
0-1 cm 1-2 cm 6-7 cm0-1 cm 1-2 cm 6-7 cm
0-1 cm 1-2 cm 6-7 cm0-1 cm 1-2 cm 6-7 cm
IPL-
cren
arch
aeol
[%]
IPL-
GD
GT
conc
entra
tion
[µg
(mL
sed)
]
-1C
L-G
DG
T co
ncen
tratio
n[µ
g (m
L se
d)
]
Depth interval
-1
0.0
0.1
0.2
0.3
0.4
HPH-crenarchaeol
MH-crenarchaeolDH-crenarchaeol
GDGT-0 Crenarchaeol
Station 3Station 2Station 1
0.0
0.2
0.4
0.6
0.8
1.0
1.2
0
20
40
60
80
100c
b
a
Figure 5: GDGT-0 and crenarchaeol concentrations (averages), for CL-GDGTs (a) and IPL-derived GDGTs (b) at all three stations and core depths. Proportions of head groups of IPL-crenarchaeol at all three stations (c).
67
Results
3.3.3. Incubation experimentsIncubations experiments were started directly after core recovery and initial sampling by injec-tion of solutions, which contained 13C-bicarbonate, pyruvate, glucose , amino acids or just water (incubated for comparison and further called the “background core”) over the first 7 cm of the cores. The cores were incubated at in situ temperatures (4°C) for 6 days (4 days for station 3) and subsequently sliced and stored for analysis of 13C-enrichment in lipids. Oxygen penetration depths were measured and bottom water was sampled at the start of the experiment, after 48 hours (36 for Station 3) and at the end of the incubations. At all stations, nutrient concentrations of the bottom water did not change over the 6 days (5 days for station 3) of incubation, except for nitrate, which generally showed a decrease (Table 2). The bottom water pH remained mostly constant, except at station 1, where it changed during the incubation from 8.2 to 8.0 in all incu-bations, similar to the other sediment cores and perhaps indicating that the initial value of 8.2 might have been due to an error in the measurement. The δ13C of the DIC in the bottom water substantially increased in the cores where 13C-labeled compounds and bicarbonate was added, but not in the background cores (Table 2). In cores from station 2, oxygen penetration depths decreased to 6–9 mm in all incubation experiments except for the core incubated with pyruvate and inhibitor, as well as in cores from station 3, where a decrease in oxygen penetration depth to 8–10 mm was observed (Table 2). In all cores from the three stations, no major differences in IPL-crenarchaeol concentrations upon incubation could be detected (Figs. S1–S3).
The δ13C-values of the biphytanes released from the IPL-GDGTs of the background cores were ranging from –17 to –24‰ at all stations (Table 3), which is within the natural variation observed for biphytanes sourced by Thaumarchaeota in marine sediments (Hoefs et al., 1997; Könneke et al., 2012; Schouten et al., 2013). No substantial 13C enrichment of biphytanes was observed in nearly all of the incubation experiments (Fig. 6). The only exception was the tricy-clic biphytane in some of the incubations at station 1 (with 13C-labelled substrates bicarbonate, bicarbonate and inhibitor, and pyruvate and inhibitor at nearly all depths) and one incubation (with pyruvate and inhibitor at 6–7 cm depth) at station 2 with enrichments ranging from 2 to 4‰. However, due to the large standard deviations in the δ13C values of the background cores, only the enrichment of 2–5 ‰ in the 1–2 cm slices of station 1 is statistically significant at a 95% confidence level (t(2)= 6.6–9.0, P=0.05). To determine whether the added 13C-labelled substrate was incorporated into sedimentary microbial biomass at all, phospholipid-derived fatty
Table 4: δ13C values of fatty acids measured in the 0-1 cm slice in cores from station 3, incubated with-out inhibitor, for 5 days.
δ13C [‰]Fatty acid BG Bic Glu AA
C16:0 –25.5 ± 0.2 –25.3 ± 0.6 20.6 ± 0.5 30.0 ± 3.9
C18:0 –24.6* –24.5 ± 0.2 66.2 ± 0.4 63.1 ± 2.1
* Single measurement
Chapter 3
68
0-1* 1-2 6-7 0-1 1-2 6-7 0-1 1-2 6-7 0-1 1-2 6-7
∆ δ
C
[‰
]
-5
0
5
Acyclic biphytane
Bicyclic biphytaneTricyclic biphytane
13in
c-B
G
Depth [cm]
Experiment
0-1 1-2 6-7 0-1 1-2 6-7 0-1 1-2 6-7* 0-1 1-2* 6-7
0-1 1-2 6-7 0-1 1-2 6-7 0-1 1-2 6-7 0-1 1-2 6-7
0-1 1-2 6-7 0-1 1-2 6-7 0-1 1-2 6-7 0-1 1-2 6-7
∆ δ
C
[‰
]13
inc-
BG
Pyruvate + InhPyruvateBicarbonate + InhBicarbonate
Pyruvate + InhPyruvateBicarbonate + InhBicarbonate
Pyruvate + InhPyruvateBicarbonate + InhBicarbonate
Depth [cm]
Depth [cm]-5
0
5
AA + InhAAGlucose + InhGlucose
∆ δ
C
[‰
]13
inc-
BG
-5
0
5
∆ δ
C
[‰
]13
inc-
BG
Depth [cm]
-5
0
5(d) Station 3
(c) Station 3
(b) Station 2
(a) Station 1
Figure 6: Difference in δ13C-values (Δδ13Cinc-bg) of the acyclic, bicyclic and tricyclic biphytanes in ‰ in the cores incubated with labeled substrate versus the 13C-values in the background cores (incubated with and without inhibitor) at station 1 (a), station 2 (b) and station 3 (c) from the cores incubated with bicarbonate and pyruvate, with and without inhibitor, and the cores incubated with glucose and amino acids with and without inhibitor, at station 3 (d).
69
Results/Discussion
acids, stemming from bacteria or eukaryotes, were analyzed from the surface sediments of the bicarbonate, amino acids and glucose incubation experiments. δ13C values of the most common fatty acids, C16:0 and C18:0 were enriched in 13C by up to 80‰ in the amino acid and glucose incu-bation experiments compared to the background (Table 4). The cores incubated with 13C-labeled bicarbonate that were analyzed showed no 13C-enriched fatty acids.
3.4. Discussion
3.4.1. Biomarkers indicative for live sedimentary ThaumarchaeotaThe only biomarker lipids up to now which are probably indicative for live Thaumarchaeota are crenarchaeol IPLs (Pitcher et al., 2011b). Of these, the ones with a glycosidic head group likely contain a substantial fossil component, while the hexose, phosphohexose (HPH)-crenarchaeol is more labile and its concentration corresponds well to DNA-based thaumarchaeal abundance (Pitcher 2011a and 2011b; Schouten et al., 2012; Lengger et al., 2012a). The presence and dom-inance of HPH-crenarchaeol in the sediments strongly suggests that live Thaumarchaeota were present in sediments at all the stations (Fig. 5). This was expected for the surface sediment, as oxygen and ammonium were present (Martens-Habbena et al., 2009; Erguder et al., 2009; Hat-zenpichler, 2012). The ammonium concentration profiles, with concentrations decreasing up-wards, agree with aerobic ammonia oxidation proceeding in the oxygenated parts, using the am-monium diffusing from below. However, HPH-crenarchaeol was present down to 7 cm depth, below the oxygen penetration depth, which could indicate that either live Thaumarchaeota were present at depth, using a metabolic process different from aerobic ammonia oxidation, or that this HPH-crenarchaeol is not stemming from live Thaumarchaeota at depth and was partly preserved. In any case, it is not yet known what exactly the preferred environment for Thau-marchaeota is, as they have been found to be active in low and high ammonia and low and high oxygen environments (Martens-Habbena et al., 2009; Erguder et al., 2009; Hatzenpichler, 2012).
3.4.2. Activity indicators and label uptake during incubationSeveral parameters can be monitored during the incubation experiments to cast a light on sed-imentary microbial activities stimulated by the addition of substrates. During incubation, a de-crease of oxygen penetration depths would indicate an increased aerobic metabolism at the surface, utilizing oxygen and preventing it from penetrating deeper, which was expected in the slices where organic carbon was added. However, at station 1, this was not observed and oxygen penetration depths only decreased in the background core (Table 2). This could be due to the aeration carried out by bubbling air into the bottom water of the core, and oxygen penetrating deeper into the sandy sediment. However, the cores from station 2 showed a decrease of oxygen penetration depth after incubation, except for the core incubated with pyruvate and inhibitor. Also the cores from station 3, i.e. those where oxygen penetration depth could be measured, showed a decrease, indicating that the oxygen was consumed upon incubation, independent of the type of substrate added to the cores. Ammonia and nitrite concentrations in the bottom water showed no changes during the incubations. No significant differences can be seen if the cores incubated with and without nitrification inhibitor are compared, indicating that either the communities are not affected by it, or potentially that the inhibitor was not as effective in a sedimentary environment as in water incubations (e.g. due to adherence to particles). Nitrate concentrations were, at station 2 and station 3, below detection limit after 6 and 5 days, respec-
Chapter 3
70
tively, suggesting consumption of nitrate (Table 2). This may indicate a strong contribution of denitrification to organic carbon processing in these sediments in the sections below oxygen penetration depth. The increase in δ13C of the DIC in the bottom water of all cores compared to the background cores (Table 2) clearly showed that the organic substrates added were respired. Previous labeling experiments with similar substrates have been successful in detecting uptake of 13C-label into bacterial PLFA (e.g. Guilini et al., 2010), resulting in a highly labeled C16:0, among other PLFAs. Indeed, the strong labeling of the bacterial PLFA C16:0 at station 3 indicated that the organic substrates were readily taken up by bacteria, and potentially non-photosynthetic eukaryotes (PLFA C16:0, C18:0), and incorporated into their biomass. Intriguingly, no incorporation was observed upon labeling with bicarbonate, which is in contrast to other studies with oligotro-phic sediment cores who used similar concentrations (e.g. Guilini et al., 2010). The amount of PLFA generated by chemoautotrophs present might have been too low to allow unambiguous detection of the incorporation in this case.
The most abundant archaeal lipids were crenarchaeol, a lipid specific for Thaumarchaeota (Sinninghe Damsté et al., 2002; de la Torre et al., 2008; Schouten et al., 2008; Pitcher et al., 2011b; Sinninghe Damsté et al., 2012), and GDGT-0, a lipid produced by Thaumarchaeota as well as some other Archaea (cf. Koga and Nakano, 2008). Their concentrations did not substantially change upon incubation, suggesting that Thaumarchaeota abundances did not change (Fig. 5 showing an average of all incubated cores, with standard deviations). However, this could also indicate that the majority of IPLs in these sediments were fossil (cf. Schouten et al., 2010; Logemann et al., 2011; Lengger et al., 2012a) and not part of living Thaumarchaeota, and thus not affected at all by the incubation. This could include HPH-GDGTs as well, though it is also possible that the bias during analysis, i.e. loss during silica column chromatography (cf. Lengger et al., 2012b), resulted in an underrepresentation of HPH- derived GDGTs.
The biphytanes analyzed included a-, bi- and tricyclic biphytane, which are mainly derived from the two most abundant GDGTs: GDGT-0 (acyclic; general archaea), and crenarchaeol (bi- and tricyclic; Thaumarchaeota). Importantly, in nearly all of the incubation experiments, the δ13C values of all measured biphytanes, including those derived from crenarchaeol, changed by less than 2‰ and sometimes even decreased in 13C-content compared to the background val-ues (Fig. 6). In some of the experiments, mainly at station 1, a slight enrichment in the tricyclic biphytane, derived from crenarchaeol, of up to 4 ± 2‰ was observed though this difference is not statistically significant for individual experiments. Furthermore, the bicyclic biphytane, also predominantly derived from crenarchaeol, shows, in general, lower 13C-enrichments than the tricyclic biphytane and also no statistically significant enrichments for individual experiments. Thus, there is no evidence for substantial uptake of 13C-label in archaeal GDGTs, contrary to what is observed for the PLFA.
This apparent lack of uptake could be due to three reasons. Firstly, it is possible that the Thau-marchaeota were active, but the substrates were not taken up. As the metabolism of the different Thaumarchaeota could be diverse, this is possible, but, in case of the bicarbonate incubations, unlikely, as in sea water incubations as well as enrichment cultures – including those of sedimen-tary Thaumarchaeota – 13C from bicarbonate has been shown to be readily incorporated into biphytanes (Wuchter et al., 2003; Park et al., 2010; Pitcher et al., 2011c). Secondly, it is possible that most of the IPLs measured (i.e. MH- and DH-GDGTs, assuming the chromatographic discrimination against the HPH-GDGTs) are fossil, and thus only a small amount of these IPLs
71
Discussion
are part of live and active sedimentary Thaumarchaeota. Finally, it is also possible that a higher proportion of the IPLs are part of sedimentary Thaumarchaeota, but that their metabolism and growth rates are so slow (as opposed to Thaumarchaeota in sea water and enrichment cultures), that no incorporation could be detected over the time scales investigated. Thus, our incubation times of 96–144 h may have been too short. However, longer incubation times inevitably result in spreading of the label over the whole sedimentary food web as e.g. discussed by Radajewski et al. (2003) for stable isotope probing of nucleic acids. This is why this study, and nearly all other incubation studies (e.g. Boschker et al. 1998, Guilini et al. 2010, cf. Middelburg 2013 and references cited therein), including those for sediments (e.g. Middelburg et al. 2000, Moodley et al. 2002), use only a short time interval (mostly just a few days) to avoid this label scrambling. Indeed, our results show that the uptake in bacteria is occurring within a few days suggesting that, if active, microbes rapidly take up label.
3.4.3. Estimating growth rates of Thaumarchaeota and turnover rates of IPL-GDGTsTo investigate whether growth rates as well as degradation rates of IPL-GDGTs were respon-sible for the apparent lack of substantial 13C-labeling, we used data from our experiments to estimate minimal growth rates and the turnover time of IPL-GDGTs. The greatest label in-corporation was found at station 1 in the sandy sediment, indicating that Thaumarchaeota may have been active there. If all IPL-GDGT biphytanes are stemming from living cells, and an enrichment of 2‰ of biphytanes is assumed, this can be converted to growth rates by using a formula used for growth of phytoplankton based on the isotope dilution theory of Laws (1984; Eq. (1)), with µ representing the growth rate, tinc the incubation time, P* the atom%-excess of the product, in our case the biphytane, and A* the atom%-excess of the substrate added (cf. alkenone lipids for eustigmatophyte algae; Popp et al., 2006):
(1)
Unfortunately, as natural concentrations of the added substrates were not determined, A* could not be calculated for the incubation experiments with pyruvate, glucose and amino acids. In the bicarbonate experiments, we calculated A* based on the amount of added 99%-labeled DIC and natural δ13C and concentration of DIC (Table 2). For P* we used the highest enrich-ment observed at 6–7 depth with no inhibitor, i.e. 4‰. This gives an estimate of the maximum µ as 6.3 × 10–4 d–1, corresponding to a generation time of 3 yr. Clearly, for the other bicarbon-ate experiments which resulted in even less label incorporation, generation times will be much higher (e.g. for a 2 ‰ enrichment, 9 yr). Interestingly, growth rates as low as estimated here have been predicted by Valentine (2007), who stated that the archaeal domain, other than bacteria and eukaryotes, has adapted to low energy conditions and is thus characterized by the exceptional ability to live in low energy environments. They are thus not fast in adapting to settings with higher concentrations of available carbon and redox substrates. However, this has not been observed for pelagic Thaumarchaeota as SIP experiments showed a substantial enrichment in 13C in IPL-GDGTs (Wuchter et al., 2003; Pitcher et al., 2011c) in incubation experiments of 168 and 24 h duration, respectively. Indeed, the generation times calculated from enriched North Sea water labeling experiments conducted by Wuchter et al. (2003; A*=5%; P*=0.46% – 400 ‰ enrichment) and Pitcher et al. (2011c; A*=9%; P*=0.07% – 44‰ enrichment) were at least an order of magnitude lower than observed here – 50 and 88 d, respectively. Also sedimentary
Chapter 3
72
Thaumarchaeota have been shown to incorporate 13C from bicarbonate in enrichment cultures (Park et al., 2010). The growth rates reported here might be an underestimation if a large pro-portion of archaeal cells is fossil; and the use of lipid turnover times might be more suitable, as discussed below. Slow growth could potentially be due to the experiments not being carried out in situ on the sea floor. However, incubations were carried out in whole, intact sediment cores, in the dark, immediately after recovery, and at in situ temperatures in order to minimize the devia-tions from in situ conditions, although, admittedly, the pressure was at atmospheric conditions. Therefore, this is unlikely to explain the low growth rates.
The calculations above assume exponential growth of sedimentary Thaumarchaeota and an immediate translation of this signal into the lipid pool. If, on the other hand, steady state con-ditions are assumed, i.e. cell numbers and lipid concentrations are not increasing but remain constant, the turnover time for the sedimentary lipid pool tto can be calculated according to Lin et al. (2012) :
*
*
PtAt inc
to⋅
= (2)
Using Eq. (2), the turnover time of IPL-crenarchaeol in sediments would thus be at least ~4 yrs based on the 4‰ enrichment of the tricyclic biphytane in the bicarbonate incubation experi-ment. Since labeling was not detected in the other sediments, this turnover time estimate is likely to be a minimal estimate. This large turnover time is not an unusual postulate for thaumarchaeal lipids in sediments, as also Lin et al. (2012) found very low 13C incorporation rates of labeled glucose into sugar moieties of glycosidic GDGTs over >400 d in slurry incubations of subsur-face sediments and used these to estimate turnover times of diglycosyl-lipids of 1,700–20,500 years. Similarly, recently published degradation experiments by Xie et al. (2013) using 14C-labeled IPL-diether lipids found very high turnover times and estimated half-lives of up to 310 kyr un-der energy-deprived subsurface conditions. This is in strong contrast to GDGTs in the water column: Using the SIP data of Wuchter et al. (2003) and Pitcher et al. (2011c) from incubations of North Sea water, we obtained tto of 76 and 128 d, respectively, for the thaumarchaeal GDGTs.
Our results are similar to those obtained by in situ-incubations carried out by Takano et al. (2010) and Nomaki et al. (2011), i.e. they did not observe significant incorporation after 405 days into the biphytanyl chains either (even though one single data point after 9 days does show a 10‰ enrichment), though they did observe incorporation into the glycerol moiety. A possibility, as suggested earlier, is that biphytanyl chains are not or hardly produced by sedimentary Thau-marchaeota, but recycled, and the sugar headgroups and/or the glycerol are only newly gener-ated and 13C-labeled. In this case, isotope ratios of whole ether lipids instead of the biphytanes would enable detection of the label, but this involves laborious clean-up of the isolated ether lipids (Takano et al., 2010). However, as also the incorporation into the sugar headgroups of GDGTs, as reported by Lin et al. (2012), is similarly low, it suggests that there is indeed a lack of, or only a very slow 13C-uptake into IPL-GDGTs.
It seems that stable carbon isotope probing using biphytanes is most likely not the method of choice for thaumarchaeal activity measurements in sediments, where conditions are favorable for preservation of fossil GDGTs, thus creating a large background signal. In the water column, however, where growth of Thaumarchaeota is faster and lipids are likely degraded on shorter time scales, due to the abundant presence of oxygen and lack of mineral matrix protection (Keil
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Discussion/Conclusion
et al., 1994; Hedges and Keil, 1995), stable isotope incubations are useful for determining ac-tivities of Thaumarchaeota. In sediments that contain a high proportion of fossil IPL-GDGTs which are not part of live Archaea, the incorporation of 13C into the lipids of the few active Thaumarchaeota is probably not enough to change the δ13C of the IPL-GDGTs to a significant degree over the commonly used time scales of SIP experiments.
3.5. ConclusionIncubations of sediment cores from the Iceland Shelf were used in order to determine the me-tabolism of sedimentary Thaumarchaeota. Thaumarchaeal IPLs were present in sediment cores recovered from the Iceland Shelf and the presence of labile IPL-biomarkers for Thaumarchae-ota, such as HPH-crenarchaeol, suggested the presence of living Thaumarchaeota. However, incubations with 13C-labeled substrates bicarbonate, pyruvate, glucose and amino acids did not result in any substantial incorporation of the 13C into the biphytanyl chains of these lipids. Turn-over times and generation times of thaumarchaeal lipids were estimated to be at least several years, suggesting slow growth of sedimentary Thaumarchaeota in contrast to other sedimentary organisms, and/or a slow degradation of IPL-GDGTs, in contrast to bacterial or eukaryotic PLFAs.
Acknowledgements
We thank Dr. Y. Takano and one anonymous reviewer for their useful comments which greatly improved the manuscript. The authors would like to thank the Master and crew of the R/V Pelagia and the participants of the Long Chain Diols Cruise 64PE341, in particular M. Baas, S. Rampen, M. Besseling, L. Handley and W. Lenthe, as well as the NIOZ technical department (Y. Witte, J. Schilling). We would also like to thank L. Moodley, H.T.S. Boschker, L. Pozzato, J. Mid-delburg, G. Duineveld and M. Lavaleye for helpful advice in planning the experiments and K. Koho / Utrecht University and L. Stal and N. Bale for providing equipment. We are grateful for analytical assistance to J. van Ooijen, S. Crayford, A. Mets, M. Verweij and J. Ossebaar. S.K.L. was funded by a studentship from the Darwin Center for Biogeosciences to S. S. This is a publication nr. DW-2013-1007 of the Darwin Center for Biogeosciences.
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Figure S1: IPL-crenarchaeol profiles of the incubated cores (station 1) - background (BG), bicarbonate (Bic) and pyruvate (Pyr) without (left plot) and with nitrification inhibitor (right plot). Top graphs shows the values in SRM area . mL–1 from 0–1 cm depth, graphs in the middle the profiles from 1–2 cm depth and at the bottom the profiles from 6–7 cm depth
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MH DH HPHMH DH HPH MH DH HPHMH DH HPH MH DH HPHMH DH HPH
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Figure S2: IPL-crenarchaeol profiles of the incubated cores (station 2) - background (BG), bicarbonate (Bic) and pyruvate (Pyr) without (left plot) and with nitrification inhibitor (right plot). Top graphs shows the values in SRM area. mL–1 from 0–1 cm depth, graphs in the middle the profiles from 1–2 cm depth and at the bottom the profiles from 6–7 cm depth.
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Chapter 3 Supplementary Material
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79
4. Abundance and diversity of denitrifying and anammox bacteria in seasonally hypoxic and sulfidic sediments of the saline Lake Grevelingen
Yvonne A. Lipsewers, Ellen C. Hopmans, Filip J.R. Meysman, Jaap S. Sinninghe Damsté, and Laura Villanueva
Denitrifying and anammox bacteria are involved in the nitrogen cycling in marine sediments but the environmental factors that regulate the relative importance of these processes are not well constrained. Here, we evaluated the abundance, diversity and potential activity of denitri-fying, anammox, and sulfide-dependent denitrifying bacteria in the sediments of the seasonally hypoxic saline Lake Grevelingen, known to harbor an active microbial community involved in sulfur oxidation pathways. Depth distributions of 16S rRNA gene, nirS gene of denitrifying and anammox bacteria, aprA gene of sulfur-oxidizing and sulfate-reducing bacteria, and ladderane lipids of anammox bacteria were studied in sediments impacted by seasonally hypoxic bottom waters. Samples were collected down to 5 cm depth (1 cm resolution) at three different locations before (March) and during summer hypoxia (August). The abundance of denitrifying bacteria did not vary despite of differences in oxygen and sulfide availability in the sediments, whereas anammox bacteria were more abundant in the summer hypoxia but in those sediments with lower sulfide concentrations. The potential activity of denitrifying and anammox bacteria as well as of sulfur-oxidizing, including sulfide-dependent denitrifiers and sulfate-reducing bacteria, was potentially inhibited by the competition for nitrate and nitrite with cable and/or Beggiatoa-like bacteria in March and by the accumulation of sulfide in the summer hypoxia. The simultaneous presence and activity of organoheterotrophic denitrifying bacteria, sulfide-dependent denitrifi-ers and anammox bacteria suggests a tight network of bacteria coupling carbon-, nitrogen- and sulfur cycling in Lake Grevelingen sediments.
Frontiers in Microbiology 7, 1661, 2016
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4.1. IntroductionNitrogen availability is a major factor controlling primary production in temperate coastal ma-rine environments with high anthropogenic nitrogen input (Herbert, 1999). Denitrification is a key process in the nitrogen cycle of coastal sediments releasing gaseous end products, nitric ox-ide (NO), nitrous oxide (N2O) and dinitrogen gas (N2) to the atmosphere. This nitrogen removal can result in a decrease of nitrogen availability for primary producers and thereby controlling the rate of eutrophication in coastal marine systems (Seitzinger 1988; Herbert 1999). Multiple microbial mediated pathways result in the removal of nitrogen in anoxic sediments (see Devol, 2015 for a detailed review). Here we focus on (1) denitrification, the stepwise conversion of nitrate/nitrite to dinitrogen gas which is mainly performed by facultative organoheterotrophic anaerobic bacteria and some archaea (Zumft, 1997); (2) anaerobic ammonium oxidation (ana-mmox), the oxidation of ammonium with nitrite to dinitrogen gas carried out by anammox bacteria (Kuypers et al., 2003); and (3) sulfide-dependent denitrification, the oxidation of sulfide with nitrate performed by autotrophic members of α-, β-, γ- and ε-proteobacteria, which could contribute to denitrification and to the removal of sulfide in the oxygen transition zone of coast-al marine sediments (Shao et al., 2010).
Numerous environmental factors, such as the availability of nitrogen speciation and concen-tration, temperature, oxygen concentrations, organic matter quality and quantity, bioturbation and other sediment characteristics have been suggested to affect the distribution and abundance of denitrifying and anammox bacteria (Thamdrup and Dalsgaard 2002; Meyer et al., 2005; Jen-sen et al., 2008; Dang et al., 2010; Laverock et al., 2013; Prokopenko et al., 2013; Babbin et al., 2014; Zhang et al., 2014). In this study, we assessed the effects of hypoxia and elevated sulfide concentration on the abundance and activity of denitrifiers and anammox bacteria in marine sediments as these factors have been previously suggested as potential limiting factors in denitri-fication processes (Brunet and Garcia-Gil, 1996; Burgin and Hamilton, 2007; Aelion and Wart-tinger, 2010; Neubacher et al., 2011; 2013; Bowles et al., 2012). Seasonal hypoxia is an increasing phenomenon that occurs in coastal areas causing a decrease in the electron acceptors (O2, NO3
–) in the bottom waters (Diaz & Rosenberg 2008). Besides, sulfide inhibition can decrease denitri-fication rates as the enzyme catalyzing the reduction of nitrous oxide to N2 is sensitive to sulfide (e.g. Porubsky et al., 2009). In addition, several studies have provided putative evidence indicat-ing that sulfide inhibits the anammox reaction. For example, Dalsgaard et al. (2003) reported a decrease in anammox activity in the sulfidic waters of the anoxic basin of Golfo Dulce (Costa Rica). Also Jensen et al. (2008) showed that sulfide had a direct inhibiting effect on the activity of anammox bacteria in the Black Sea.
In this study, we evaluated the impact of environmental factors, such as oxygen and free sulfide concentrations in the diversity, abundance, activity, and spatial distribution of bacteria involved in N2 removal pathways in sediments of Lake Grevelingen (The Netherlands), a sea-sonally hypoxic saline reservoir. Here, we determined the diversity, abundance and potential activity of denitrifying bacteria, anammox bacteria and sulfur-oxidizing bacteria (SOB), includ-ing sulfide-dependent denitrifiers, and sulfate-reducing (SRB), in three different stations within the lake both in March (before hypoxia) and August (i.e. during hypoxia). In order to determine changes in the diversity, abundance and activity of denitrifiers, we targeted the nirS gene, en-coding for the cytochrome cd1 nitrite reductase, catalyzing nitrite reduction to nitric oxide (NO) (Braker et al., 1998; Smith et al., 2007; Huang et al., 2011). Here, we focused on the cytochrome
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cd1-containing nitrite reductase (nirS gene), as it has been found to be more widespread in the bacterial communities compared to the copper-containing nitrite reductase (nirK) in various sed-iments (Braker 1998; Priemé et al. 2002; Liu et al. 2003; Throbäck et al. 2004; Tiquia et al. 2006; Oakley et al. 2007; Dang et al. 2009; Huang et al. 2011). For anammox bacteria, the nirS gene was also quantified as it has been recently suggested to be a functional biomarker anammox bacteria (Li et al., 2011). Both, denitrifying and anammox bacteria harbor one copy of the nirS gene, indicating that the nirS gene might be a suitable marker to compare the abundance and distribu-tion of nirS-type denitrifiers and anammox bacteria in coastal sediments. The potential activity of denitrifying and anammox bacteria was also determined by estimating the gene expression of those metabolic genes as in previous studies (Smith et al., 2007; Lam et al., 2009; Bale et al., 2014; Bowen et al., 2014; Zhang et al., 2014; Chapter 2). Besides functional genes, the abundance of anammox bacteria was also determined by the quantification of ladderane lipids, which are specific lipid biomarkers for this microbial group (Sinninghe Damsté et al., 2002; Jaeschke et al., 2009; Russ et al., 2013). Finally, the diversity and abundance of sulfur-oxidizing and sulfate-re-ducing bacteria in marine sediments was estimated by targeting the aprA gene encoding the adenosine-5’-phosphosulfate (APS) reductase (Lenk et al., 2011; Blazejak and Schippers, 2011; Dyksma et al., 2016). The APS reductase is operating in in SOB, oxidizing sulfite to APS, as well as in SRB, operating in reverse direction, converting APS to adenosine monophosphate (AMP) and sulfite (SO3
2–) (Meyer and Kuever, 2007b). Our starting hypothesis is that the abundance and potential activity of organoheterotrophic
denitrifiers and anammox bacteria would decrease upon increase of the sulfide concentration found in the sediments during the summer hypoxia. Moreover, recent studies point out that sulfide-dependent denitrifiers play a relevant role in the sulfide transition zone of intertidal sedi-ments (Dyksma et al., 2016). Therefore, we hypothesize that their abundance and activity would be higher in hypoxic and sulfidic conditions, thus contributing more to the general N2 removal in comparison to organoheterotrophic denitrifying and anammox bacteria and eventually being involved in sulfide detoxification which could promote anammox activity.
4.2. Material and Methods
4.2.1. Study site and sampling Lake Grevelingen is a former estuary within the Scheld- Rhine- Meuse delta, and was formed by the construction of the Grevelingendam on the landside in 1964 and the Brouwersdam on the seaward side in 1971. The lake (surface area: 108 km2, mean water depth 5.3 m) mainly consists of shallow water areas with the exception of the former tidal gullies, that have a water depth of up to 48 m (Keldermann 1984; Nienhuis and De Bree, 1984). After its closure, the lake transformed into a freshwater body, but in 1979, the connection with the North Sea was par-tially re-established, and since then, Lake Grevelingen has a high and relatively constant salinity (29−32). Within Lake Grevelingen, the Den Osse basin forms a deeper basin within the main gully, and experiences a regular seasonal stratification leading to oxygen depletion in the bottom water (summer hypoxia) (Wetstejn, 2011). Due to sediment focusing, the Den Osse basin (max-imum water depth 34 m) also experiences a rapid accumulation of fine-grained, organic rich sediments (sediment accumulation rate ~2 cm yr–1; Donders, 2012).
Sediment cores were collected along a depth gradient in Den Osse basin during two cruises March and August 2012 on board of the RV Luctor. Sampling took place at three different sta-
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tions: S1 was located in the deepest point of the basin at 34 m water depth (51.747°N, 3.890°E), S2 at 23 m (51.749°N, 3.897°E) and S3 at 17 m (51.747°N, 3.898°E). Sediment was collected with single core gravity corer (UWITEC) using transparent PVC core liners (6 cm inner diam-eter, 60 cm length). Four sediment cores were collected at each station in March and in August. The cores were sliced with a 1 cm resolution until 5 cm depth, and sediment samples were collected for lipid and DNA/RNA analysis and kept at –80ºC until further processing. In each sampling campaign, a water column depth profile of temperature, salinity and oxygen (O2) con-centration was recorded at S1 using an YSI 6600 CTD instrument (for details see Hagens et al., 2015). Oxygen concentrations recorded by the CTD instrument were calibrated based on dis-crete water samples using an automated Winkler titration procedure (Knap et al., 1996). Bottom water concentrations of ammonium (NH4
+), nitrite (NO2–) and nitrate (NO3
–) were measured colometrically on a SEAL QuAAtro segmented flow nutrient analyzer. Monitoring data at Lake Grevelingen (Wetstejn, 2011) shows that the water column is laterally homogenous over the Den Osse basin scale, which allows estimation of the bottom water parameters at S2 and S3 from corresponding depths in the measured CTD profiles at station S1.
4.2.2. Sediment geochemistry High-resolution depth profiles of O2 and sulfide (H2S) were measured in intact sediment cores to determine the oxygen penetration depth (OPD) and the sulfide appearance depth (SAD), using commercial micro-electrodes (Unisense A.S., Denmark) operated with a motorized micromanip-ulator (for details on the procedure see Malkin 2014). The oxygen penetration depth (OPD) is operationally defined as the depth below which [O2] < 1 µM, while the sulfide appearance depth (SAD) is operationally defined as the depth below which [H2S] > 1 µM (Seitaj et al., 2015).
Sediment cores were sectioned in increments of 0.5 cm from the sediment-water interface to 5 cm depth, and pore water was extracted by centrifugation, and analyzed following the proce-dure of (Sulu-Gambari et al., 2016). After filtration through 0.22 µm cellulose filters (Chromafil Xtra), pore water samples were analyzed for total free sulfide (∑H2S) via spectrophotometry (Cline, 1969; standard deviation ± 0.4 µM), whereas ammonium (NH4
+) was determined by a SEAL QuAAtro segmented flow analyzer (Aminot et al., 2009) after a 25 times dilution with a low nutrient seawater matrix solution (standard deviation ± 3.5%).
The free sulfide and ammonium concentration depth profiles of the sediment pore water were averaged to provide a 1 cm resolution down to 5 cm sediment depth to enable a direct comparison with results of the DNA/RNA and lipid analysis. The total organic carbon (TOC) content of the sediment was determined on sediment samples that were freeze-dried, ground to a fine powder and analyzed by an a Thermo Finnigan Delta plus isotope ratio monitoring mass spectrometer (irmMS) connected to a Flash 2000 elemental analyzer (Thermo Fisher Scientific, Milan). Before the analysis, samples were first acidified with 2N hydrogen chloride (HCl) to re-move the inorganic carbon (Nieuwenhuize et al., 1994). Concentrations of TOC are expressed as mass % of dry sediment.
4.2.3. DNA/RNA extraction DNA and RNA from sediments (previously centrifuged to remove excess of water thus values are given as grams of wet weight; S1, S2 and S3; 0–5 cm sediment depth; 1 cm resolution) were extracted by using the DNA and RNA PowerSoil® Total Isolation Kit, respectively (Mo Bio Laboratories, Inc., Carlsbad, CA). Nucleic acid concentrations were quantified spectrophoto-
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Material and Methods
metrically (Nanodrop, Thermo Scientific, Wilmington, DE) and checked by agarose gel electro-phoresis for integrity. Extracts were kept frozen at –80°C. The RNA extracts were treated with RNase-free DNase (DNA-free™, Ambion Inc., Austin, TX), and RNA quality and concentration were estimated by the Experion RNA StdSens Analysis Kit (Bio-Rad Laboratories, Hercules, CA). DNA contamination was checked by PCR using RNA as a template. Reverse transcription was performed as specified in Chapter 2.
4.2.4. PCR amplification and cloning Amplifications of the nirS gene of denitrifying bacteria (S1, S2, S3, March and August, 0–1 cm), and anammox bacteria 16S rRNA gene (S2, March, 1–2 cm), specific nirS genes of Scalindua sp. (S3, August, 0–1 cm) and the aprA gene (S2, August, 0–1 cm) were performed with the primer pairs specified in Table S1. The PCR reaction mixture consisted of (final concentration): Q-solu-tion (PCR additive, Qiagen, Valencia, CA) 1 ×; PCR buffer 1 ×; BSA (200 µg mL–1); dNTPs (20 µM); primers (0.2 pmol µL–1); MgCl2 (1.5 mM); 1.25 U Taq polymerase (Qiagen, Valencia, CA). PCR conditions for these amplifications were: 95°C, 5 min; 35 × [95°C, 1 min; Tm, 1 min; 72°C, 1 min]; final extension 72°C, 5 min. PCR products were gel purified (QIAquick gel purifi-cation kit, Qiagen, Valencia, CA) and cloned in the TOPO-TA cloning® kit (Life Technologies, Carlsbad, CA) and transformed in E. coli TOP10 cells following the manufacturer’s recommen-dations. In addition, in order to test the specificity of the quantitative PCR reaction we repeated the reactions of anammox bacteria 16S rRNA gene (Broc541F - Amx820R) with DNA extract of S2, March, 0–1 cm, nirS gene of heterotrophic denitrifying bacteria (nirS1F - nirS3R) with cDNA of S2, March, 0–1 cm, and aprA gene (Apr1F- Apr5R) with cDNA of S2, August, 0–1 cm, which were then treated to add 3’-A-overhangs and then cloned with the TOPO-TA cloning® kit as indicated above. Recombinant plasmid DNA was sequenced using the M13R primer by Macrogen Inc. (Amsterdam, The Netherlands).
4.2.5. Phylogenetic analysis Sequences were analyzed for the presence of chimeras using the Bellerophon tool at the Green-Genes website (http://greengenes.lbl.gov/). Sequences were aligned with MEGA6 software (Tamura, 2013) by using the alignment method ClustalW. The phylogenetic trees of the nirS and aprA genes were computed with the Neighbour-Joining method (Saitou and Nei, 1987) using the Poisson model with a bootstrap test of 1,000 replicates. The phylogenetic affiliation of the partial anammox bacteria 16S rRNA gene sequences was compared to release 123 of the SILVA NR SSU Ref database (http://www. arb-silva.de/; Quast et al., 2013) using the ARB software package (Ludwig et al., 2004). Sequences were added to the reference tree supplied by the SILVA database using the ARB Parsimony tool. Sequences were deposited in NCBI with the following accession numbers: KP886533–KP886678 for nirS gene sequences of denitrifiers, KP886679–KP8866700 for 16S rRNA gene sequences of anammox bacteria, KP886701–KP886721 for nirS gene sequences of anammox bacteria and KP886722–KP886804 for aprA gene sequences of SOB and SRB.
4.2.6. Quantitative PCR (qPCR) analysis qPCR analyses were performed on a Biorad CFX96TM Real-Time System/C1000 Thermal cycler equipped with the CFX ManagerTM software for sediment DNA/RNA extracts (S1, S2 and S3; 0–5 cm sediment depth; 1 cm resolution). Detailed information about the primers used in this
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study are summarized in Table S1. The abundance of denitrifying bacteria specific nirS gene was quantified using the primer set nirS1F/nirS3R as described by Braker et al. (1998). The abun-dance of anammox bacteria 16S rRNA gene was estimated using primers Brod541F/Amx820R as described by Li et al. (2010). Additionally, a fragment of the Scalindua sp. specific nirS gene, which codes for the cytochrome cd1-containing nitrite reductase, was quantified using the primer combination Scnir372F/Scnir845R as described by Lam et al. (2009). The abundance of SOB and SRB including sulfide dependent denitrifiers was estimated by targeting the dissimilatory adenosine-5’-phosphosulfate (APS) reductase (aprA gene) involved in the APS reduction of sul-fur-oxidizing bacteria and in the sulfite oxidation of sulfate-reducing bacteria by using the primer combination Apr-1-FW/Apr-5-RW as described by Meyer and Kuever (2007a) (see Table S1 for details). Gene abundances are expressed as copies g–1 sediment of wet weight.
All qPCR amplifications were performed in triplicate with standard curves ranging from 100 to 107 molecules per microliter. Standard curves and qPCR amplifications were performed as pre-viously described in Chapter 2. Coefficients of determination (R2) for standard curves ≥ 0.998 and qPCR efficiencies (E) ≥ 80% were accepted.
4.2.7. Anammox bacteria ladderane lipid analysis Intact polar lipids (IPLs) were extracted with the Bligh and Dyer extraction method (Bligh 1959; mod. by Pitcher et al., 2011) as described in detail by Bale et al. (2014). Intact ladderane phos-pholipids specific for anammox bacteria, the C20-[3]-monoether ladderane attached to a phos-phatidylcholine (PC) headgroup (PC-monoether ladderane) was analyzed by HPLC-MS/MS following Jaeschke et al. (2009) and quantified using an external standard consisting of isolated PC-monoether ladderane. Sediment samples between 0–5 cm depth (1 cm resolution) were an-alyzed and PC-monoether ladderane lipid concentrations were expressed per nanogram of dry weight sediment (ng g–1). In order to determine the fatty acid composition of the ladderane lip-ids, aliquots of the Bligh and Dyer extracts (BDE) obtained from the 0–1 and 4–5 cm sediment layers were saponified by reflux with aqueous KOH (in 96% MeOH) for 1 h. Fatty acids were obtained by acidifying the saponified samples to a pH of 3 with 1N HCl in MeOH and extracted using dichloromethane (DCM). The fatty acids were converted to their corresponding fatty acid methyl esters (FAMEs) by methylation with diazomethane (CH2N2) as described by Rush et al. (2012a). Polyunsaturated fatty acids (PUFAs) were removed by eluting the sample over a silver nitrate (AgNO3) (5 %) impregnated silica column with DCM and air-dried at room temperature. The fatty acid fractions were dissolved in acetone, filtered through a 0.45 μm polytetrafluoroeth-ylene (PTFE) filters (4 mm diameter), and analyzed by high performance liquid chromatography coupled to positive ion atmospheric pressure chemical ionization tandem mass spectrometry (HPLC/APCI-MS/MS) in selective reaction monitoring (SRM) mode following Hopmans et al. (2006) including the recent modifications described by Rush et al. (2012b). Ladderane lipids were quantified using external calibration curves of three standards of isolated methylated ladderane fatty acids (C20-[3]-ladderane fatty acid, and C20-[5]-ladderane fatty acid) (Hopmans et al., 2006; Rush et al., 2011).
4.3. Results Sediment samples were collected along a depth gradient in Den Osse basin (Lake Grevelingen) during two cruises March (before summer hypoxia) and August (during summer hypoxia) 2012. Sampling took place at three different stations: S1 was located in the deepest point of the basin
85
Material and Methods/Results
at 34 m water depth, S2 at 23 m and S3 at 17 m.
4.3.1. Environmental conditionsThe temperature of the bottom water at station S1 (Fig. S1) showed a regular seasonal cycle with lowest values in late winter (1.5 °C in February) and highest values in late summer (16.9 °C in September). During the spring campaign (March 2012), the water column was only partially stratified and showed a limited surface-to-bottom temperature gradient. In contrast, during the summer campaign (August 2012), the water column was thermally stratified. The yearly pattern of the bottom water oxygenation at station S1 was inversely correlated the temperature, with greatest oxygenation levels in winter and fall, and lowest concentrations in summer (Fig. S1). In March 2012, the bottom water oxygenation was similar for all three stations, whereas in August 2012, the bottom water at S1 and S2 were anoxic (< 1 µM), while the bottom water at S3 still had 88 µM of O2 (36% air saturation). Bottom water ammonium (NH4
+) concentrations in station S1 ranged from 3 µM in March to 11.5 µM in August; nitrite (NO2
–) concentrations were relatively constant (0.7–1 µM) in March and August. Nitrate concentrations ranged from 28 µM in March to <2 µM in August in station S1 (Fig. S1) whereas in stations S2 and S3 values varied between 28 µM in March to ~10 µM in August.
The OPD in the sediment was seasonally variable and increased from S1 to S3, i.e. in S1 in March OPD was 1.5 mm and in August the sediment was completely anoxic. In S2, OPD was between 1.7–2.5 mm in March and in August ca. 0.5 mm (hypoxic) and in S3, the OPD was be-tween 1.5–2.2 mm in March and ca. 1.0 mm (hypoxic) in August. (Table 1). The sulfide appear-ance depth (SAD) varied between March and August in all stations. The SAD moved towards the sediment surface between March and August in all stations. In March, the SAD in stations S1 and S2 was at 18.4 and 21.3 mm respectively, whereas in S3, the SAD was detected at 41.8 mm sediment depth. However, in August, SAD in stations S1 and S2 was at 0.4 and 0.6 mm, respec-tively. In station S3, the sulfide was detected at 4.2 mm sediment depth (Table 1). At station S2, white mats of Beggiatoa sp.-like microorganisms covered the sediment surface in March. Small polychaetes were observed in the sediment at station S3 in March, suggesting some bioturbation. Sulfide (∑H2S) concentrations in the sediment pore water were low in March in all three stations, i.e. ranging from 0 to 0.007 mM, whereas in comparison, all three stations showed high sulfide concentrations in August, i.e. 0.15 to 1.6 mM (Table 1) (see Seitaj, 2015 for detailed geochemical profiles of station S1). Ammonium concentrations were low in March, i.e. ranging from 0.24 to 0.63 mM on average, in comparison with August when NH4
+ concentrations reached higher values, i.e. 0.7 to 1.2 mM on average (Table 1). The TOC content of the sediments varied slightly between stations and seasons, ranging between 1.8 and 4.4% (Table S2).
4.3.2. Diversity, abundance and potential activity of nirS-type denitrifiers In our study, we focused on heterotrophic and autotrophic bacteria that are able to perform the dissimilatory reduction of nitrite to nitric oxide. This reaction forms an intermediate step in the complete denitrification of nitrate to N2 and is catalyzed by the cytochrome cd1-contain-ing nitrite reductase encoded by the nirS gene (Braker et al., 2000). The diversity of nirS-type denitrifiers was evaluated for the surface sediment layer (0–1 cm) at the three stations in March and August by phylogenetic analysis targeting the nirS gene (Figs. 1 A, B). In general, the nirS sequences obtained (147 sequences in total) were closely related to nirS sequences of uncultured organisms found in coastal marine environments with a high input of organic matter such as
Chapter 4
86
Tabl
e 1:
Sed
imen
t por
ewat
er a
mm
onia
(NH
4+) a
nd su
lfide
(HS– )
conc
entra
tions
(1 c
m re
solu
tion)
, oxy
gen
pene
tratio
n de
pth
(OPD
) and
sul
fide
appe
ar-
ance
dep
th (S
AD
) det
erm
ined
by
mic
ro-s
enso
r pro
filin
g.
Stat
ion
Sedi
men
t dep
th
[cm
]H
S- [μM
]N
H4+
[μM
]O
PD [m
m]
SAD
[mm
]
Mar
chA
ugus
tM
arch
Aug
ust
Mar
chA
ugus
tM
arch
Aug
ust
1
0–1
081
027
965
6
1.5
018
.40.
4
1–2
015
0341
010
71
2–3
016
3963
613
22
3–4
019
6283
315
67
4–5
3320
6397
917
68
2
0–1
011
5716
555
0
1.7
2.5
21.3
0.6
1–2
080
245
583
6
2–3
010
0852
610
27
3–4
212
3859
211
38
4–5
2711
9067
112
28
3
0–1
021
173
537
1.5
2.2
41.8
4.2
1–2
017
715
469
4
2–3
014
623
673
6
3–4
010
933
374
9
4–5
093
408
746
* Dat
a ar
e av
erag
ed to
reac
h a
1 cm
reso
lutio
n; d
ata
prov
ided
by
Fatim
ah S
ulu-
Gam
bari
(201
6; u
npub
lishe
d da
ta),
**da
ta p
rovi
ded
by D
orin
a Se
itaj,
2015
; unp
ublis
hed
data
).
87
Results
estuarine sediments and eutrophic bay sediments (Braker et al., 2000, Zhang et al., 2014). The phylogenetic analysis of protein sequences of the nirS gene revealed two distinct clusters (Fig. 1A; cluster 1 and 2), where most (ca. 95%) of the sequences clustered in cluster 1 (ca. 95%). Within cluster 1, approximately 90% of the nirS gene sequences were grouped into subcluster 1.1 and 10% into subcluster 1.2 (Figs. 1 A, B; Fig. S2). Within subcluster 1.1 sequences were affiliated to nirS sequences of members of α-, β- and γ-proteobacteria able to perform autotro-phic denitrification coupled to sulfide oxidation (Thiobacillus denitrificans) and heterotrophic de-nitrification (Azospirillum brasilense, Marinobacter hydrocarbonoclasticus, Kangiella aquamirina, Halomonas sp.). Sequences grouped in subcluster 1.2 were affiliated to the nirS gene sequences of divers α- proteobacteria able to perform autotrophic denitrification coupled to sulfide or iron oxida-tion (Paracoccus denitrificans, Sideroxidans lithotrophicus), as well as heterotrophic denitrification (e.g. Aromatoleum aromaticum, Azocarus toluclasticus, Acidovorax delafieldii). Sequences grouped into cluster 2 were affiliated to nirS gene sequences of uncultured bacteria detected in coastal marine and estuarine sediments (Braker et al., 2000; Zhang et al., 2014). In order to determine the specificity of the qPCR assay, sequences of nirS cDNA (complementary DNA of nirS mRNA) generated during the qPCR reaction were cloned and sequenced (28 sequences in total) and also added to the protein-coding nirS sequences phylogenetic tree showing that those sequences were grouped in the clusters described before (Figs. 1 A, B).
The abundance and distribution of nirS-type denitrifiers was estimated through quantification of the nirS gene copy number in the upper 5 cm (1 cm resolution) of the sediments at the three sampling sites in March and August (Fig. 2). The nirS gene abundance was relatively stable with depth with slightly higher values in station S1 (6.4 × 107 copies g–1 on average) compared to sta-tions S2 and S3 (5.7 × 107 and 5.2 × 107 copies g–1 on average, respectively). Overall, nirS gene abundance was slightly higher in March compared to August in S2 and S3, and this difference was especially evident in station S1.
To estimate the potential transcriptional activity of nirS-type denitrifiers, nirS transcripts (mRNA copy numbers) were quantified (data reported in Table S3) and the RNA:DNA ratio was calculated. In station S1, transcripts were only detectable in March in the upper 2 cm of the sediment, 5.6 × 103 copies g–1on average, whereas in August, nirS gene transcripts could only be detected within the 2–3 cm depth layer (102 copies g–1). In station S2, nirS gene transcripts were only detectable in March in the upper 3 cm and numbers varied between 1.9 × 102–1.5 × 103 copies g–1 with the highest value within the 1–2 cm zone. In station S3, the nirS gene transcripts could be detected in March in the upper cm of the sediment (1.5 × 102 copies g–1) and in August for 1–2 cm and for 3–4 cm sediment (1.1 × 102 and 1.8 × 103 copies g–1, respectively ) (Table S3). The ratio of nirS gene and transcript copies (RNA:DNA ratio) was ≤ 0.00013 in all stations in March and August.
4.3.3. Diversity, abundance and potential transcriptional activity of anammox bacteria Most of the anammox bacterial nirS gene sequences obtained in this study (20 sequences out of 21) were part of one cluster (cluster 1, Fig. 3) closely related to nirS sequences of “Candidatus Scalindua profunda” (Van de Vossenberg et al., 2013), and of uncultured bacteria obtained from continental margin sediment of the Arabian Sea (Sokoll et al., 2012) and surface sediments of the South China Sea (Li et al., 2013).
Chapter 4
88
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89
Results
The diversity of the 16S rRNA gene sequences of anammox bacteria (Fig. S3) obtained from surface sediments (0–1 cm) revealed that most of the sequences (21 sequences derived from PCR plus cloning, and 23 gene sequences obtained from the qPCR assay and further cloning to check the specificity of the qPCR assay) were closely related to “Candidatus Scalindua” bro-dae and “Candidatus Scalindua marina” obtained from surface sediments of the Gullmar Fjord (Brandsma et al., 2011), and to sequences detected in OMZ waters of the Arabian Sea, Peru and Namibia (Woebken et al., 2008) and Peruvian coastal margin (Henn, unpublished). Two 16S rRNA sequences were more distantly related to the other sequences, and were closely related to the 16S rRNA sequence of “Candidatus Scalindua wagneri” obtained from a bioreactor (Woeb-ken et al., 2008) (Fig. S3).
We also quantified the C20-[3]-ladderane monoether-PC (for 0–5 cm sediment depth) and ladderane core lipids (for 0–1 and 4–5 cm sediment depth) (Table S4 and S5) as markers for the presence of anammox bacteria. Abundance of PC-monoether ladderane ranged between 0.9–20.4 ng g–1 with highest values in station S1 in March (between 3.4–20.4 and 2.4–7 ng g–1, respectively). PC-monoether ladderane values were relatively constant with depth in August in all stations (between 0.9–7 ng g–1; Table S4). On the other hand, PC-monoether ladderane abun-dance was always higher in March in the upper 2 cm of the sediment and decreased four-fold between 2 and 5 cm in all stations (on average from 10.7 to 2.5 ng g–1). The summed concen-tration of the ladderane fatty acids was on average lowest in station S1 (13 ng g–1), with slightly
Figure 2: Depth profiles of anammox bacteria 16S rRNA gene abundance [copies g–1] (circle); anammox bacteria nirS gene abundance [copies g–1] (triangle), denitrifying bacteria nirS gene abundance [copies g–1] (square); SOB and SRB aprA gene abundance [copies g–1] (diamond); A) Station 1; B) Station 2; C) Station 3; black symbol: March; white symbol: August.
Chapter 4
90
uncultured bacterium, Peruvian OMZ seawater (ACR07885)uncultured Scalindua sp., Black Sea waterCandidatus (AFO85870)Station 3, August; Lake Grevelingen 0-1 cm sediment depth (15)
uncultured bacterium, Peruvian OMZ seawater (ACR07884)Kuenenia stuttgartiensisCandidatus (CT573071)
Anaerolinea thermophila (WP013561145)uncultured bacterium, Peruvian OMZ seawater (ACR07901)
uncultured Scalindua sp., Pacific marine water column, USACandidatus (AGM49043)2 sequences subseafloor sediment, South China Sea (ACV84553; ACV84614)2 sequences water column (AFO85813; AFO85819)Black Sea OMZ
uncultured bacterium, Peruvian OMZ seawater (ACR07879)uncultured bacterium, Peruvian OMZ seawater (ACR07891)
uncultured bacterium,Peruvian OMZ seawater(ACR07882)uncultured bacterium, Peruvian OMZ seawater (ACR07881)uncultured bacterium, Peruvian OMZ seawater (ACR07877)
uncultured bacterium, Peruvian OMZ seawater (ACR07883)uncultured bacterium, Peruvian OMZ seawater (ACR07890)
uncultured bacterium, Peruvian OMZ seawater (ACR07889)Uncultured bacterium, Peruvian OMZ seawater (ACR07875)
uncultured Scalindua sp.Candidatus Black Sea water (AFO85831)uncultured Scalindua sp.Candidatus Black Sea water (AFO85849)Candidatus Scalindua (scal02098)profundauncultured bacterium, sediment, South China Sea (ACV84622)uncultured Scalindua sp.Candidatus Black Sea water (AFO85782)uncultured bacterium, surface sediment, South China Sea (AEJ85669)uncultured bacterium, sediment, Arabian Sea (AFZ84060)Station 3, August; Lake Grevelingen 0-1 cm sediment depth (20)Station 3, August; Lake Grevelingen 0-1 cm sediment depth (5)Station 3, August; Lake Grevelingen 0-1 cm sediment depth (7)Station 3, August; Lake Grevelingen 0-1 cm sediment depth (4)Station 3, August; Lake Grevelingen 0-1 cm sediment depth (18)
15 x Station 3, August; Lake Grevelingen 0-1 cm sediment depth
5473
50
65
58
0.25
clu
ste
r 1
Figure 3: Phylogenetic tree of partial nirS gene sequences of anammox bacteria retrieved in this study and closest relatives (S3; 0–1 cm Lake Grevelingen sediment; bold: sequences retrieved in March and se-quences of known relatives); the scale bar indicates 25% sequence divergence.
higher average values in S2 (27 ng g–1), and the highest average values in S3 (41 ng g–1) (Table S5). The summed ladderane fatty acid concentrations were comparable to the abundance of anammox bacteria determined by the 16S rRNA gene quantification in the first centimeter of the sediment obtained in different stations and seasons, whereas the PC-monoether ladderane revealed a different trend compared to the 16S rRNA gene abundance, i.e., was more abundant in March compared to August (Table S4).
The abundance of anammox bacteria was determined by the quantification of the 16S rRNA gene copy number of anammox bacteria as well as of the nirS gene copy number of members of the genus “Candidatus Scalindua” (Figure 2) (Strous et al., 2006; Li et al., 2011). Copy numbers of the anammox bacteria 16S rRNA gene ranged between 9.5 × 105 and 8.1 × 107 copies g–1 with highest values in S3 (between 2 × 106 and 8.1 × 107 copies g–1). The abundance of the ana-mmox bacterial 16S rRNA gene was slightly higher in August compared to March in all stations. The “Candidatus Scalindua” nirS gene abundance followed the same depth trend but values were 2 – 3 orders of magnitude lower (between 1.1 × 104 and 9.9 × 104 copies g–1) compared to the anammox bacteria 16S rRNA gene copy numbers.
The anammox bacterial 16S rRNA transcript, used as a proxy for the potential transcriptional activity, varied between 1.3 × 103 – 5.1 × 106 copies g–1 of sediment (Table S3). The anammox 16S rRNA transcript copy number varied slightly and reached highest values in S2 and S3 in August between 2–4 cm sediment depth (2.7 × 106 copies g–1 on average). The ratio between 16S rRNA gene and transcript (RNA:DNA ratio) was ≤ 0.32 in all stations in March and August.
91
Results
Anammox bacteria nirS transcript copies were below detection level of the qPCR assay.
4.3.4. Diversity, abundance and potential transcriptional activity of bacteria involved in sulfur cycling Here, we focused on bacteria involved in sulfur cycling, performing dissimilatory sulfur oxida-tion or sulfate reduction. The dissimilatory APS reductase encoded by the aprA gene is operating in SRB, converting APS to adenosine monophosphate (AMP) and sulfite (SO3
2–), as well as in SOB, operating in reverse direction, oxidizing sulfite to APS (Meyer and Kuever, 2007b). The diversity of the microorganisms harboring the aprA gene was evaluated in the first centimeter of the sediment core at S2 in August as the observation of Beggiatoa mats on top indicated the occurrence of sulfide oxidation at this station. The protein sequences (86 sequences PCR + cloning) coded by the aprA gene grouped in two clusters (Fig. 4; cluster I (66%) and II (34%)). Within cluster I, sequences clustered in three distinct subclusters. Sequences of the aprA gene included in subcluster 1.1 (36%) were affiliated to heterotrophic SRB of the δ-proteobacteria class (e.g. Desulfosarcina sp., Desulfofaba gelida, Desulfobulbus propionicus) and to aprA gene sequences of uncultured bacteria found in environments such as in Black Sea sediments and associated with benthic organisms (Blazejak and Schippers, 2011; Ruehland et al., 2008). In subcluster 1.2 (21%), sequences were closely affiliated to β- and γ-proteobacteria involved in autotrophic sul-fur-dependent denitrification (Thiobacillus denitrificans and Sulfuricella denitrificans) or in phototro-phic sulfur oxidation (Lamprocystis purpurea) and to the aprA gene sequence of an uncultured bacterium associated with the sea urchin Asterechinus elegans (Quast et al., 2009). Sequences clus-tering in subcluster 1.3 (9%) were affiliated with aprA gene sequences of bacteria of the phylum Firmicutes (i.e. Desulfotomaculum sp.) known to perform heterotrophic sulfate reduction, and to sequences of uncultured bacteria obtained in various sediments such as hydrothermal seep sedi-ments, Peru margin sediments and salt lake sediments (Blazejak and Schippers, 2011; Meyer and Kuever, 2007c; Kleindienst et al., 2012). Cluster II contained sequences (34%) closely related to obligately chemolithoautotrophic members of the β-proteobacteria class (Thiobacillus thioparus) able to perform nitrate reduction to nitrite with thiocyanate, and to aprA gene sequences of uncultured bacteria retrieved in salt lake sediments or associated with benthic organisms (Becker et al., 2009). In addition, to assess the specificity of the aprA gene qPCR assay, aprA gene tran-scripts (cDNA of aprA mRNA) generated during the qPCR assay (21 sequences in total) were cloned, sequenced and added to the aprA phylogenetic tree, where they were classified in the clusters previously described (Fig. 4).
The abundance and the potential activity of SOB including sulfide-dependent denitrifiers and SRB were determined by the quantification of the aprA gene and its gene transcripts (Fig. 2, Table S3). The copy number of the aprA gene was relatively constant with varying sediment depth and season. Gene copy numbers of the aprA gene were of the same order of magnitude as observed for the denitrifiers nirS (on average 3.1 × 108 copies g–1) and reached highest val-ues in S2 in March and August (on average 3.3 × 108 copies g–1). At station S1, the aprA gene transcript (Table S3) was detectable at 2–3 cm sediment depth in March (5.4 × 102 copies g–1 on average), whereas in August the nirS transcript was detectable at 0–1 cm (3.8 × 103 copies g–1) and 2–4 cm (1.8 × 104 copies g–1 on average) sediment depth. In S2 and S3, aprA gene transcripts were detectable at 1–4 cm sediment depth in March and August (on average 4.7 × 103 copies g–1 in March and 4.4 × 103 copies g–1 in August). The ratio between aprA gene and transcript (RNA:DNA ratio) was ≤ 0.000088 in all stations in March and August.
Chapter 4
92
23 sequences Station 2, August; 0-1 cm Lake Grevelingen sediment (including 3 x cDNA) closely related to sequences of uncultured bacteria and δ-Proteobacteria Desulfatibacillum alkenivorans, Desulfofaba gelida and Desulfobacter curvatus
41 sequences Station 2, August; 0-1 cm Lake Grevelingen sediment (including 12 x cDNA) closely related to sequences of uncultured bacteria and the ɣ-Proteobacterium Thiobacillus thioparus (WP018507768)
Station 2, August; 0-1 cm Lake Grevelingen sediment (45) Olavius algarvensis endosymbiont; marine sediment (CAJ81243)
Station 2, August; 0-1 cm Lake Grevelingen sediment (44) Station 2, August; 0-1 cm Lake Grevelingen sediment (79)
Station 2, August; 0-1 cm Lake Grevelingen sediment (57) Station 2, August; 0-1 cm Lake Grevelingen sediment; cDNA (18)
uncultured bacterium; mud vulcano (AFV48087) Station 2, August; 0-1 cm Lake Grevelingen sediment (56) Station 2, August; 0-1 cm Lake Grevelingen sediment (63) Station 2, August; 0-1 cm Lake Grevelingen sediment; cDNA (9) Station 2, August; 0-1 cm Lake Grevelingen sediment (39) Station 2, August; 0-1 cm Lake Grevelingen sediment; cDNA (19)
Station 2, August; 0-1 cm Lake Grevelingen sediment (59) Station 2, August; 0-1 cm Lake Grevelingen sediment; cDNA (1)
Station 2, August; 0-1 cm Lake Grevelingen sediment (65) uncultured δ-Proteobacterium; surface of crab (ABY89711) Desulfobulbus propionicus; δ-Proteobacterium (YP004194237) Station 2, August; 0-1 cm Lake Grevelingen sediment; cDNA (23)
uncultured Desulfofustis sp.; δ-Proteobacterium (WP023406400)uncultured bacterium; marine sponge (AFK76428)
Station 2, August; 0-1 cm Lake Grevelingen sediment (1) Station 2, August; 0-1 cm Lake Grevelingen sediment (33)
Station 2, August; 0-1 cm Lake Grevelingen sediment (74) uncultured bacterium; marine sediment Gulf of Mexico (CCB84484)
Station 2, August; 0-1 cm Lake Grevelingen sediment (37) Station 2, August; 0-1 cm Lake Grevelingen sediment (67)
uncultured bacterium; Black Sea sediment (CCC58324) Desulfotomaculum alcoholivorax; Firmicutes (WP027366015)
Station 2, August; 0-1 cm Lake Grevelingen sediment (13) Station 2, August; 0-1 cm Lake Grevelingen sediment (52)
Station 2, August; 0-1 cm Lake Grevelingen sediment (50) Station 2, August; 0-1 cm Lake Grevelingen sediment (69)
uncultured bacterium; Peru margin sediment (CCC58328) Desulfotomaculum thermocisternum; Firmicutes (WP027356136)
Station 2, August; 0-1 cm Lake Grevelingen sediment (14) Station 2, August; 0-1 cm Lake Grevelingen sediment (64)
uncultured bacterium; salt lake sediment (ACM47772) δ-Proteobacterium NaphS2 (WP006420559)
Archaeoglobus sulfaticallidus; Archaeoglobi (YP007908062) Station 2, August; 0-1 cm Lake Grevelingen sediment; cDNA (13)
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23 sequences Station 2, August; 0-1 cm Lake Grevelingen sediment (including 5 x cDNA) closely related to sequences of uncultured bacteria and β-ProteobacteriaThiobacillus denitrificans and Sulfuricella denitrificans and ɣ-Proteobacterium Lamprocystis purpurea
clu
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su
bclu
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Figure 4: Phylogenetic tree of partial aprA gene sequences of sulfur-oxidizing and sulfate-reducing bac-teria (SOB and SRB) retrieved in this study (86 DNA sequences recovered by amplification (PCR) and 21 cDNA sequences recovered by amplification (qPCR) and cloning from sediments (0–1 cm) of station S2 in August) and closest relatives (bold: our sequences and closest known relatives); the scale bar indicates 5% sequence divergence.
93
Discussion
4.4. DiscussionThe phylogenetic analysis of the nirS gene sequences amplified from Lake Grevelingen sed-iments revealed a substantial diversity of autotrophic and heterotrophic denitrifiers (Fig. 1). Most of the sequences obtained in this study were affiliated to α-, β- and γ-proteobacteria able to perform denitrification coupled to the oxidation of reduced sulfur compounds. Sequences of the nirS gene (~30%) and the aprA gene (21%) (Fig. 4) were closely related to sequences of Thiobacillus denitrificans, able to couple the oxidation of inorganic sulfur species such as sulfide with denitrification (Shao et al., 2010). Sulfide-dependent denitrifiers couple nitrogen and sulfur cycling and their presence point to an important denitrification potential in these sediments. In order to determine differences in abundance, and therefore of denitrification potential, be-tween sediments and with depth, in our study we quantified the abundance of the nirS gene. The nirS gene abundance was relatively constant with increasing sediment depth, suggesting a stable community of heterotrophic and autotrophic denitrifying bacteria in Lake Grevelingen sediments. NirS gene abundance (in the order of 107 copies g–1) was slightly higher in March in all three stations, but the difference was especially notable in station S1, most likely explained by the lower free sulfide concentrations in March compared to August (Table 1). Lower sulfide concentrations in March could favor the proliferation of heterotrophic denitrifiers not coupled with sulfide oxidation as sulfide has been seen to impair denitrification by inhibition of NO and N2O reductases (Sørensen et al., 1980). In addition, the nirS gene abundance (Fig. 2) determined in Lake Grevelingen sediments (between 107–108 copies g–1) was one to three orders of mag-nitude higher compared to the values previously detected in other marine sediments such as in sediments of open estuaries with permanently oxygenated bottom water (104–107 copies g–1 on average) (Smith et al., 2007; Zhang et al., 2013). The nirS gene abundance has previously been shown to correlate positively with potential denitrification rates (Mosier and Francis, 2010), and therefore, we can conclude that the sediments of the marine Lake Grevelingen harbor a stable community of heterotrophic and autotrophic denitrifiers, which can be actively involved in the denitrification process independent of season and sediment depth.
Besides quantifying the nirS gene as an indicator of the denitrification potential of these sedi-ments, we also estimated the presence of nirS gene transcripts as a measure of potential activity (Table S3). Unfortunately, there is a lack of in situ studies correlating nirS gene expression with denitrification rates, and some studies have even shown a lack of direct relationship between nirS gene expression and modeled rates of denitrification in marine surface sediments (Bowen et al., 2014). On the other hand, other studies have observed a correlation between a decrease of nirS gene transcripts and reduction of denitrification rates together with declining concentrations of nitrate in estuarine sediment (Dong et al., 2000, 2002; Smith et al., 2007), which would justify the use of nirS gene transcripts as a proxy for potential denitrification performed by nirS-type denitrifiers. In this study, the copy number of denitrifier nirS transcripts was two to three orders of magnitude lower compared to values previously reported for estuarine sediments (Smith et al., 2007), suggesting a low denitrification rate in surface sediments of all stations in March and in deeper sediment layers in August. Gene expression of the nirS gene was detected in surface sediments in March (all stations) and in deeper sediment layers in August (stations S1 and S3), which is most likely explained by the availability of nitrate/nitrite in the water-sediment interface (bottom water).
Chapter 4
94
Apart from nirS-containing denitrifiers, also anammox bacteria were detected in Lake Grev-elingen sediments by applying both DNA and lipid-based biomarkers. The phylogenetic analysis of the anammox 16S rRNA gene amplified from the sediments pointed to an anammox com-munity dominated by “Candidatus Scalindua” (Fig. S3). In order to estimate the abundance of anammox bacteria in the sediments and their potential role in the nitrogen cycle in this system, we estimated the abundance of the “Candidatus Scalindua” nirS gene. In contrast to nirS-type denitrifiers, anammox bacteria showed a clear seasonal contrast in their nirS gene abundance with higher copy numbers in August (summer hypoxia) compared to March (Fig. 2). However, this seasonal trend was not reflected in the abundance of the anammox bacteria lipid biomarker PC-monoether ladderane lipid (Table S4). Previous studies have suggested that this biomarker lipid could be partly preserved in the sediment due to a relatively low turnover rate (Brandsma et al., 2011; Bale et al., 2014; Chapter 2). On the other hand, the concentration of ladderane lipid fatty acids (Table S5) correlated with the anammox bacteria abundance given by 16S rRNA gene quantification, i.e. with the lowest values in station S1 and highest values in station S3. This suggests that the abundance of ladderane lipid fatty acids could be interpreted as a proxy for anammox bacteria abundance together with specific gene quantification. It is also worth notic-ing that a difference of three to four orders of magnitude was detected between abundances of anammox 16S rRNA gene and the “Candidatus Scalindua” nirS gene (Fig. 2). This discordance between anammox 16S rRNA genes and functional genes has been previously observed and is possibly linked to primer biases attributed to the anammox bacteria 16S rRNA gene primers that would amplify 16S rRNA gene fragments of bacteria other than anammox bacteria (Li et al., 2010; Harhangi et al., 2012; Bale et al., 2014; Chapter 2). However, in our study we have ruled out the possibility of the anammox bacteria 16S rRNA gene primers amplifying bacteria other than anammox by cloning and sequencing of the product generated during the qPCR reaction as shown in Fig. S3. Therefore, further studies should address the causes of this discordance.
Factors other than hypoxia and sulfide concentration could have also contributed to the dif-ferences in abundance and activity of anammox bacteria. For example, both the anammox bac-teria 16S rRNA and nirS gene abundances were higher in August in comparison to March (Fig. 2). This may indicate that anammox bacteria are more abundant at higher temperatures (15°C), which is the anammox bacteria temperature optimum in temperate shelf sediments (Dalsgaard et al., 2005). This seasonality of anammox bacteria abundance has been reported before in sandy and as well in muddy, organic rich sediments of the North Sea (Bale et al., 2014; Chapter 2). Ad-ditionally, oxygen penetration depth in the sediments decreased and the sediment even became entirely anoxic during summer stratification (Table 1), which would also favor the anaerobic metabolism of anammox bacteria (Dalsgaard and Thamdrup, 2002). Anammox bacterial abun-dance was highest in station S3, which could also be related to elevated bioturbation activity that was observed in this station, as bioturbation and mixing extends the area of nitrate reduction, which might fuel the anammox process (Meyer et al., 2005; Laverock et al., 2013). Another factor determining anammox and denitrification pathways in sediments is the organic carbon content. Anammox and denitrification have been suggested to be more important nitrogen removal path-ways in sediments of low carbon input compared to sulfide-dependent denitrification which seem to be more important in sulfidic sediments with high carbon input (Burgin and Hamilton, 2007). The TOC content in Lake Grevelingen sediments is high, i.e. in the order of 2.5–4.5% (Malkin et al., 2014), which is hence consistent with the low activity of anammox bacteria. More-
95
Discussion
over in station S1, fresh organic-rich sediment rapidly accumulates (> 2 cm yr–1; Malkin et al., 2014), which might inhibit the activity of anammox bacteria and denitrifying bacteria.
Overall, the nirS gene abundance of denitrifiers was three to four orders of magnitude higher compared to the anammox bacteria ‘Scalindua’ nirS gene values, suggesting that nirS-type denitri-fiers have a more prominent role in the overall denitrification activity in Lake Grevelingen sed-iments in comparison with anammox bacteria (Fig. 2). This is also supported by the anammox bacteria nirS gene transcript abundance, which remained below detection limit. On the other hand, anammox bacteria 16S rRNA gene transcripts were detected throughout the sediment (Table S3). A recent study by Bale et al. (2014) observed a good correlation between the 16S rRNA gene abundance, 16S rRNA gene transcript abundance and anammox rates in North Sea sediments, which suggests that the transcriptional activity of anammox bacteria 16S rRNA gene is a suitable proxy of anammox bacteria activity. However, the anammox bacteria 16S rRNA gene RNA:DNA ratio was low (0.01–1) compared to the values previously reported in sediments of the southern North Sea (1.6–34.6) (Chapter 2), further supporting a low anammox activity in the Lake Grevelingen sediments.
Although denitrification was more relevant than anammox process as suggested by the gene abundance and potential activity (Fig. 2, Table S3), the measured denitrification rates (between 36–96 µM m–2 d–1; D. Seitaj, personal communication) in Lake Grevelingen are low in compar-ison with other marine sediments. For example, denitrification rates were reported to vary be-tween 30–270 µM m–2 d–1 in marine Arctic sediments (Rysgaard et al., 2004), while denitrification rates of 270±30 µmol N2 m
−2 d−1 were measured in sediments of the Lower St. Lawrence Estu-ary (Crowe et al., 2012). The lower denitrification and anammox potential in Lake Grevelingen sediments could be explained by the effect of high concentrations of sulfide (potentially inhib-iting both heterotrophic denitrification and anammox). In our study, the abundance of nirS-type denitrifiers did not vary substantially for the different stations however the highest anammox bacterial abundance was observed in station S3 where lowest sulfide concentration was reported (Fig. 2, Table 1). Besides, these sediments harbor an important population of sulfide-dependent denitrifiers (as indicated by aprA gene values comparable to those found in sediments of the Black Sea; Blazejak and Schippers, 2011), which could alleviate the inhibitory effect of sulfide on other microbial groups such as anammox bacteria. For example, a study by Russ et al. (2014) observed the coexistence and interaction of sulfide-dependent denitrifying and anammox bacte-ria in a co-culture in which anammox bacteria remained active. Also a study by Wenk et al (2013) provided evidence for the coexistence of anammox bacteria and sulfide-dependent denitrifiers in the stratified water column of Lake Lugano, and reported that the addition of sulfide in incu-bation studies enhanced both processes. They speculated that anammox bacteria in this system would rely on nitrite released as intermediate during sulfide-dependent denitrification and that they would overcome inhibiting or toxic effects of sulfide by creating a sulfide-free microenvi-ronments in aggregates as previously proposed by Wenk et al (2013). However, in the case of Lake Grevelingen sediments the potential detoxification of sulfide and a source of nitrite by sulfide-dependent denitrifiers did not translate in significant anammox potential. Another expla-nation for the low denitrification potential of these sediments can be found in the interactions of anammox and heterotrophic denitrifiers with sulfur oxidizers also involved in the nitrogen
Chapter 4
96
cycle. For example in Lake Grevelingen, cable bacteria have been detected in stations S1 and S3 in March, whereas station S2 was dominated by Beggiatoaceae down to ~3 cm, but both groups were hardly detectable in subsurface sediments (0.5 cm downwards) during summer hypoxia (Seitaj et al., 2015; Seitaj, unpublished data). In fact, the analysis of aprA gene of SOB/SRB in our study showed that up to 36% of the aprA gene sequences were closely related to the aprA se-quences of Desulfobulbus propionicus (Fig. 4), which has been identified as closest known relative of cable bacteria (Pfeffer et al., 2012). Cable bacteria perform a novel ‘electrogenic’ form of sulfur oxidation, in which the oxidation of the electron donor and the reduction of the electron accep-tor are separated over centimeter-scale distances, and the necessary redox coupling is ensured by long-distance electron transport (Nielsen et al., 2010; Pfeffer et al., 2012). Cable bacteria use ox-ygen as terminal electron acceptor (Nielsen et al., 2010; Meysman et al., 2015) and recent studies also indicate that nitrate (Marzocchi et al., 2014) and nitrite (Risgaard-Petersen et al., 2014) can be utilized, suggesting that cable bacteria can also play a role in bioavailable nitrogen removal. In addition, marine Beggiatoa spp. couple the oxidation of sulfide to nitrate reduction resulting in N2 and/or NH4
+ (Mußmann et al., 2003). Previous studies have observed that both denitrification and anammox in anoxic sediments can be supported by intracellular nitrate transport performed by sulfide-oxidizing bacteria like Thioploca and Beggiatoa (Prokopenko et al., 2013; Muβmann et al., 2007; Jørgensen et al., 2010) down to deeper sediment layers and possibly supplying anammox bacteria with nitrite and/or ammonia produced by DNRA (Teske and Nelson, 2006, Prokopen-ko et al., 2011).The nrfA gene, encoding a nitrite reductase catalyzing the conversion of nitrite to ammonia (Smith et al., 2007), could not be detected in our sediment samples (data not shown) by using general nrfA primers (Mohan et al., 2004), however we cannot rule out completely the presence of microorganisms performing DNRA as the primers used could be not the most ap-propriate ones for this system. Therefore, the presence of sulfide-dependent denitrifiers (such as Thiobacillus denitrificans), cable bacteria and Beggiatoa-like bacteria present in Lake Grevelingen sediments could potentially support denitrification and anammox processes in March. However, the nitrate and nitrite concentrations in the bottom water in March were reported to be relatively low (28 and 0.7 μM on average, respectively, Fig. S1), which is expected to induce a strong com-petition for nitrate, nitrite and sulfide with Beggiatoaceae, cable bacteria and other nitrate-reduc-ing bacteria (e.g. Thiobacillus thioparus), explaining the limited denitrification potential observed in the Lake Grevelingen sediments.
4.5. Conclusion Our study has unraveled the coexistence and potential activity of heterotrophic and autotrophic denitrifiers, anammox bacteria as well as SOB/SRB in seasonally hypoxic and sulfidic sediments of Lake Grevelingen. Our starting hypothesis was that the abundance and activity of denitrifiers and anammox bacteria would decrease upon increase of the sulfide concentration found in the sediments during the summer hypoxia. However, nirS-type heterotrophic denitrifiers were a sta-ble community regardless of changes in oxygen and sulfide concentrations in different seasons and with a similar abundance to that detected in other sediments not exposed to high sulfide concentrations.
Besides, nirS-type denitrifiers outnumbered anammox bacteria leading to the conclusion that anammox does not contribute significantly to the N2 removal process in Lake Grevelingen sed-iments. Apart from that, the anammox bacteria population seemed to be affected by the phys-
97
Discussion/Conclusion
icochemical changes between seasons. For example, their abundance and activity was higher in lower sulfide concentrations and low carbon input, also supporting a possible inhibition of anammox bacteria by sulfide. The sulfide-dependent denitrifiers in Lake Grevelingen sediments have proven to be abundant and expected to contribute significantly to the N2-removal in these sediments. Their activity of sulfide oxidation is intuitively expected to reduce the concentration of sulfide, which is in turn toxic for organoheterotrophic denitrifiers and anammox bacteria. However, in this system the detoxification mediated by sulfide-dependent denitrifiers is either not sufficient or other factors are contributing to the low denitrification potential observed in the sediments of Lake Grevelingen.
Recent studies have also reported the presence of cable bacteria and sulfide-oxidizers of the Beggiatoaceae family in the Lake Grevelingen sediments. Both denitrifiers and anammox bacte-ria activity could be inhibited by the competition with cable bacteria and Beggiatoaceae for elec-tron donors and acceptors (such as sulfide, nitrate and nitrite) before summer hypoxia (March). During summer hypoxia (August), sulfide inhibition and low nitrate and nitrite concentrations seem to limit the activity of heterotrophic and autotrophic (sulfide-dependent) denitrifiers and anammox bacteria. Further studies also involving denitrification rate determinations will be re-quired to further assess the effects of hypoxia and high sulfide concentrations in the sediments of Lake Grevelingen.
Acknowledgements
We thank the captain and crew of the R/V Luctor (Peter Coomans and Marcel Kristalijn) for support during sampling. We thank Eric Boschker for support and discussions during the sam-pling campaigns, and Diana Vasquez, Dorina Seitaj, Fatimah Sulu-Gambari and Anton Tramper for assistance with the collection and analysis of water column and pore water data. We thank Pieter van Rijswijk, Silvia Hidalgo Martinez, Marcel van der Meer and Sandra Heinzelmann for assistance during sediment sampling. Analytical support was provided by Anchelique Mets, De-nise Dorhout, Irene Rijpstra and Elda Panoto. We thank Prof. Stefan Schouten for constructive comments on the manuscript. This work was supported by grants from the Darwin Center for Biogeosciences (grant numbers 3062 and 142.16.3092) and ERC Grant 306933 to FM. This Re-search was supported by the SIAM Gravitation Grant 024.002.002 from the Dutch Ministry of Education, Culture, and Science (OCW).
Chapter 4
98
Figure S1: Bottom water temperature [°C] (red square) and concentrations of oxygen [μM] (blue square), ammonium [μM] (dark green triangle), nitrite [μM] (pink triangle) and nitrate [μM] (light green triangle).
Figure S2: A) Relative percentage of nirS sequences of denitrifying bacteria in cluster 1 and 2 and B) in subcluster 1.1 and 1.2 according to the three stations in March and August.
99
Supplementary Material
0.1
uncultured bacterium, ocean sediment, 5306 m water depth (FJ746210)uncultured bacterium, Manantial del Toro hypersaline groundwater (JF747691)
17 x Station 2, March, 0-1cm Lake Grevelingen sediment (qPCR)8 x Station 2, March, 1-2 cm Lake Grevelingen sediment (cloning)
Candidatus Scalindua brodae, anaerobic ammonium oxidizer enrichment reactor (EU142948)Candidatus Scalindua brodae (JRYO01000256)Candidatus Scalindua brodae, Black Sea (AY257181) uncultured bacterium, seafloor lavas from the East Pacific Rise (EU491842)uncultured planctomycete, Barrow Canyon sediment, Alaskan margin (DQ869385)uncultured bacterium, sediment from the Kings Bay, Svalbard, Arctic (EU050867)
uncultured planctomycete, Saanich Inlet, 200 m depth (HQ163732)uncultured planctomycete, seawater (DQ534740)uncultured Planctomycetales bacterium, Peruvian OMZ; Station 4; 35 m
uncultured Planctomycetales bacterium, Peruvian OMZ; Station 4; 35 m (EU478646)uncultured Planctomycetales bacterium, Peruvian OMZ; Station 4; 35 m (EU478653)uncultured Planctomycetales bacterium, Peruvian OMZ; Station 4; 35 m (EU478687)uncultured planctomycete, seawater (DQ534739)uncultured Planctomycetales bacterium, Peruvian OMZ; Station 4; 35 m (EU478684)uncultured Planctomycetales bacterium, Peruvian OMZ; Station 4; 35 m (EU478669)uncultured planctomycete, seawater (DQ534742)
uncultured Planctomycetales bacterium, Peruvian OMZ; Station 4; 35 m (EU47869)uncultured Planctomycetales bacterium, Black Sea, 100 m (EU478626)uncultured Planctomycetales bacterium, Namibian OMZ; Station 202; 52 m (EU478632)uncultured Planctomycetales bacterium, Namibian OMZ; Station 202; 52 m (EU478631)uncultured planctomycete, Saanich Inlet, 120 m depth (GQ349291)uncultured Planctomycetales bacterium, Namibian OMZ; Station 202; 52 m (EU478645)uncultured Planctomycetales bacterium, Namibian OMZ; Station 202; 52 m (EU478634)uncultured Planctomycetales bacterium, Namibian OMZ; Station 202; 52 m (EU478633)uncultured planctomycete, Saanich Inlet, 120 m depth (GQ349285) uncultured planctomycete, Saanich Inlet, 120 m depth (GQ349247)uncultured planctomycete, Barrow Canyon sediment, Alaskan margin (DQ869384)
uncultured Planctomycetales bacterium, low temperature hydrothermal oxides (South West Indian Ridge) (JN860309)Candidatus Scalindua marina, surface sediment under a water column of 118 m (EF602039)Candidatus Scalindua marina, surface sediment under a water column of 118 m (EF602038)uncultured planctomycete, sea water from Gullmarsfjorden (DQ386151)Candidatus Scalindua sp. anaerobic ammonium oxidizer enrichment reactor (EU142947)uncultured Planctomycetales bacterium (AB573102)
uncultured Candidatus Scalindua sp., estuarine sediment, 0−1 cm depth (FM992882) uncultured bacterium, Yellow Sea continental shelf sediment (GQ143789)uncultured bacterium, Manantial del Toro hypersaline groundwater (JF747652)
Station 2, March, 1-2 cm Lake Grevelingen sediment (1) Station 2, March, 1-2 cm Lake Grevelingen sediment (8)
Candidatus Scalindua wagneri, rotating biological contactor (AY25488)uncultured Candidatus Scalindua sp., estuarine sediment, 0−1 cm depth (FM992881)
uncultured planctomycete, intertidal sand bank (AB300486)uncultured Candidatus Scalindua sp., laboratory−scale bioreactor (AB822932) uncultured Candidatus Scalindua sp., enrichment culture from marine sediment (AB811947) anaerobic ammonium−oxidizing planctomycete JMK−2, anammox bioreactor (AB281489)
uncultured planctomycete, marine sediment ca. 50 m (EU373086) uncultured bacterium, Manantial del Toro hypersaline groundwater (JF747633)
uncultured bacterium, subseafloor sediment of the South China Sea (EU386010)uncultured bacterium, deep−sea sediments from different depths (AB015552)
uncultured Planctomycetales bacteria, Peruvian OMZ; Station 4; 35 m
uncultured bacteria Arabian Sea; Xisha Trough (South China Sea); OMZ of Chile; hypersaline grondwater
6 x Station 2, March, 0-1 cm Lake Grevelingen sediment (qPCR) 11 x Station 2, March, 1-2 cm Lake Grevelingen sediment (cloning)
uncultured bacteria Xisha Trough (South China Sea); Manantial del Toro hypersaline grondwater
Can
did
atu
s S
calin
du
a
Figure S3: Phylogenetic tree of anammox bacteria partial 16S rRNA gene sequences retrieved in this study (21 DNA sequences recovered by amplification (PCR) and cloning and 21 DNA sequences recov-ered by amplification (qPCR) and cloning from sediments (0–1 cm) of station S2 in March) and closest relatives (bold: our sequences and closest known relatives); the scale bar indicates 10% sequence diver-gence.
Chapter 4
100
Tabl
e S1
: Prim
er p
airs
des
crib
ed in
the
text
, PC
R co
nditi
ons a
nd a
mpl
icon
size
use
d in
this
stud
y.
Ass
ayTa
rget
Prim
er p
air
Tm
[°C
]A
mpl
icon
si
ze [b
]R
ef.
qPC
R +
PC
R/cl
onin
gA
nam
mox
bac
teria
16
S rR
NA
gen
e
Brod
541F
(5’-G
AG
CA
CG
TAG
GTG
GG
TTTG
T-3’
)qP
CR
59/
PCR
5827
9Li
et a
l.,
2010
Am
x820
R (5
’-AA
AA
CC
CC
TCTA
CTT
AG
TGC
CC
-3’)
qPC
R +
PC
R/cl
onin
gSc
alind
ua sp
. nirS
gen
e
Scni
r372
F (5
’-TG
TAG
CC
AG
CA
TTG
TAG
CG
T-3’
)qP
CR/
PCR
5747
4La
m e
t al.,
20
09Sc
nir8
45R
(5’-T
CA
AG
CC
AG
AC
CC
ATT
TGC
T-3’
)
qPC
R +
PC
R/cl
onin
gD
enitr
ifyin
g ba
cter
ia
nirS
gen
e
nirS
1F (5
’-CC
TAY
TGG
CC
GC
CRC
ART
-3’)
qPC
R/PC
R 60
222
Brak
er e
t al
., 19
98ni
rS3R
(5’-G
CC
GC
CG
TCRT
GVA
GG
AA
-3’)
qPC
R+cl
onin
gSu
lfide
oxi
dizi
ng
bact
eria
apr
A g
ene
Apr
1F (5
’TG
GC
AG
ATC
ATG
ATY
MAY
GG
-3’)
qPC
R/PC
R 56
359
Mey
er &
K
ueve
r, 20
07A
pr5R
(5’-G
CG
CC
AA
CYG
GRC
CRT
A-3
’)
PCR
cond
ition
s: 95
°C 5
min
; 40×
[95°
C 1
min
, Tm
40
s, 72
°C 1
min
]; 72
°C 5
min
. qPC
R co
nditi
ons:
95°C
4 m
in; 4
0× [9
5°C
30
s, Tm
40
s, 72
°C 3
0 s]
; 80
°C 2
5 s.
101
Supplementary Material
Table S2: Total organic carbon (TOC) after acidification of freeze dried sediment.
Station Sediment depth [cm]
TOC [%]
March August
1
0–1 2.86 1.81
1–2 3.67 2.47
2–3 3.83 3.52
3–4 3.98 3.11
4–5 4.28 3.66
2
0–1 3.11 2.38
1–2 3.62 3.29
2–3 3.77 3.24
3–4 3.49 3.5
4–5 3.85 3.52
3
0–1 2.87 3.04
1–2 4.02 3.9
2–3 3.89 3.56
3–4 4.01 4.39
4–5 3.63 3.73
Chapter 4
102
Tabl
e S3
: Tra
nscr
ipt (
cDN
A; m
RNA
cop
y) a
bund
ance
det
ecte
d in
sedi
men
ts o
f al
l sta
tions
in M
arch
and
Aug
ust.
Stat
ion
Sedi
men
t de
pth
[cm
]
nirS
gen
ede
nitr
ifyin
g ba
cter
ia16
S rR
NA
gen
ean
amm
ox b
acte
riaap
rA g
ene
SOB
and
SR
B
cDN
A [c
opy
g-1]
cDN
A [c
opy
g-1]
cDN
A [c
opy
g-1]
Mar
chA
ugus
tM
arch
Aug
ust
Mar
chA
ugus
t
1
0–1
1.8
× 1
02n.
d.1.
9 ×
105
8.1
× 1
05n.
d.3.
8 ×
103
1–2
1.1
× 1
04n.
d.1.
8 ×
105
1.3
× 1
03n.
d.n.
d.
2–3
n.d.
1.0
× 1
021.
0 ×
105
2.8
× 1
055.
4 ×
102
2.5
× 1
04
3–4
n.d.
n.d.
6.5
× 1
046.
9 ×
105
n.d.
1.1
× 1
04
4–5
n.d.
n.d.
2.5
× 1
042.
3 ×
105
n.d.
n.d.
2
0–1
1.9
× 1
02n.
d.8.
5 ×
104
3.0
× 1
05n.
d.n.
d.
1–2
1.5
× 1
03n.
d.6.
0 ×
105
1.1
× 1
067.
0 ×
103
7.4
× 1
02
2–3
6.7
× 1
02n.
d.9.
6 ×
105
1.7
× 1
061.
4 ×
104
3.4
× 1
03
3–4
n.d.
n.d.
1.9
× 1
051.
3 ×
105
1.6
× 1
035.
9 ×
102
4–5
n.d.
n.d.
4.8
× 1
045.
5 ×
104
n.d.
n.d.
3
0–1
1.5
× 1
02n.
d.4.
9 ×
106
2.9
× 1
05n.
d.n.
d.
1–2
n.d.
1.1
× 1
023.
1 ×
106
5.1
× 1
063.
5 ×
103
1.8
× 1
04
2–3
n.d.
n.d.
4.1
× 1
053.
1 ×
106
5.0
× 1
024.
3 ×
102
3–4
n.d.
1.8
× 1
032.
2 ×
105
1.3
× 1
051.
4 ×
103
3.7
× 1
03
4–5
n.d.
n.d.
8.5
× 1
043.
7 ×
104
n.d.
n.d.
qPC
R co
nditi
ons:
95°C
4 m
in; 4
0 ×
[95°
C 3
0 s,
Tm 4
0 s,
72°C
30
s]; 8
0°C
25
s. nd
: non
det
ecta
ble,
i.e. v
alue
s wer
e un
der t
he d
etec
tion
limit
of th
e qP
CR
appr
oach
.
103
Supplementary Material
Table S4: Results of anammox bacteria PC-monoether ladderane lipid analysis at all stations in March and August (0−5 cm sediment depth).
PC-monoether ladderane lipid [ng g−1]Station Sediment depth [cm] March August
1
0–1 20.4 2.4
1–2 13.3 3.4
2–3 6.1 2.8
3–4 3.4 7
4–5 5 7
2
0–1 10.8 6.2
1–2 4.7 1.9
2–3 2 1.9
3–4 1 1.4
4–5 1 1.4
3
0–1 8.6 2.4
1–2 6.1 1.2
2–3 1.6 1.2
3–4 1.1 0.9
4–5 1.4 1.4
Chapter 4
104
Tabl
e S5
: Res
ults
of
anam
mox
bac
teria
FA
ME
ana
lysis
of
all s
tatio
ns in
Mar
ch a
nd A
ugus
t (0−
1 an
d 4−
5 cm
sedi
men
t dep
th).
long
cha
in F
AM
Es
[ng
g-1]
sum
Stat
ion
mon
thde
pth
C20
-[3]
C20
-[5]
C18
-[3]
C18
-[5]
C20
-[3]
–C18
-[5]
Stat
ion
1
Mar
ch0.
53.
63.
84.
05.
516
.8
Mar
ch4.
53.
55.
42.
05.
015
.8
Aug
ust
0.5
2.5
1.5
5.1
3.9
13.1
Aug
ust
4.5
1.8
1.8
1.4
2.8
7.8
Stat
ion
2
Mar
ch0.
56.
14.
76.
97.
825
.4
Mar
ch4.
54.
89.
14.
44.
422
.7
Aug
ust
0.5
5.3
5.7
19.3
8.4
38.7
Aug
ust
4.5
3.1
8.2
4.4
4.1
19.8
Stat
ion
3
Mar
ch0.
518
.916
.332
.139
.310
6.5
Mar
ch4.
53.
67.
94.
04.
019
.5
Aug
ust
0.5
4.7
4.1
8.9
9.7
27.4
Aug
ust
4.5
2.8
3.2
1.6
3.0
10.6
107
5. Impact of seasonal hypoxia on activity and community structure of chemolithoautotrophic bacteria in a coastal sediment
Yvonne A. Lipsewers, Diana Vasquez-Cardenas (equal contributors), Dorina Seitaj, Regina Schauer, Silvia Hidalgo Martinez, Jaap S. Sinninghe Damsté,
Filip J.R. Meysman, Laura Villanueva, and Henricus T.S. Boschker
Seasonal hypoxia in coastal systems drastically changes the availability of electron acceptors in bottom water, which alters the sedimentary reoxidation of reduced compounds. However, the effect of seasonal hypoxia on the chemolithoautotrophic community that catalyze these reoxi-dation reactions, is rarely studied. Here we examine the changes in activity and structure of the sedimentary chemolithoautotrophic bacterial community of a seasonally hypoxic saline basin under oxic (spring) and hypoxic (summer) conditions. Combined 16S rRNA gene amplicon sequencing and analysis of phospholipid derived fatty acids indicated a major temporal shift in community structure. Aerobic sulfur-oxidizing Gammaproteobacteria (Thiotrichales) and Epsi-lonproteobacteria (Campylobacterales) were prevalent during spring, whereas Deltaproteobac-teria (Desulfobacterales) related to sulfate reducing bacteria prevailed during summer hypoxia. Chemolithoautotrophy rates in the surface sediment were three times higher in spring compared to summer. The depth distribution of chemolithoautotrophy was linked to the distinct sulfur oxidation mechanisms identified through microsensor profiling, i.e., canonical sulfur oxidation, electrogenic sulfur oxidation by cable bacteria, and sulfide oxidation coupled to nitrate reduction by Beggiatoaceae. The metabolic diversity of the sulfur-oxidizing bacterial community suggests a complex niche partitioning within the sediment probably driven by the availability of reduced sulfur compounds (H2S, S0, S2O3
2−) and electron acceptors (O2, NO3−) regulated by seasonal
hypoxia. Chemolithoautotrophic microbes in the seafloor are dependent on electron acceptors like ox-ygen and nitrate that diffuse from the overlying water. Seasonal hypoxia however drastically changes the availability of these electron acceptors in the bottom water, and hence, one expects a strong impact of seasonal hypoxia on sedimentary chemolithoautotrophy. A multidisciplinary in-vestigation of the sediments in a seasonally hypoxic coastal basin confirms this hypothesis. Our data show that bacterial community structure and the chemolithoautotrophic activity varied with the seasonal depletion of oxygen. Unexpectedly, the dark carbon fixation was also dependent on the dominant microbial pathway of sulfur oxidation occurring in the sediment (i.e., canonical sulfur oxidation, electrogenic sulfur oxidation by cable bacteria, and sulfide oxidation coupled to nitrate reduction by Beggiatoaceae). These results suggest that a complex niche partitioning within the sulfur-oxidizing bacterial community additionally affects the chemolithoautotrophic community of seasonally hypoxic sediments.
Applied and Environmental Microbiology 83, e03517-16, 2017
Chapter 5
108
5.1. Introduction The reoxidation of reduced intermediates formed during anaerobic mineralization of organic matter is a key process in the biogeochemistry of coastal sediments (Soetaert et al., 1996, Jør-gensen and Nelson, 2004). Many of the microorganisms involved in the reoxidation of reduced compounds are chemolithoautotrophs, which fix inorganic carbon using the chemical energy derived from reoxidation reactions (dark CO2 fixation). In coastal sediments, sulfate reduction forms the main respiration pathway, accounting for 50% to 90% of the organic matter min-eralization (Soetaert et al., 1996). The reoxidation of the pool of reduced sulfur compounds produced during anaerobic mineralization (dissolved free sulfide, thiosulfate, elemental sulfur, iron monosulfides and pyrite) hence forms the most important pathway sustaining chemolitho-autotrophy in coastal sediments (Jørgensen and Nelson, 2004, Howarth, 1984).
Various lineages from the Alpha-, Gamma-, Delta- and Epsilonproteobacteria, including re-cently identified groups, such as particle-associated Gammaproteobacteria and large sulfur bac-teria, couple dark CO2 fixation to the oxidation of reduced sulfur compounds in oxygen defi-cient marine waters and sediments, in coastal marine sediments and in lake sediments (Brüchert et al., 2003; Lavik et al., 2009; Sorokin et al., 2011; Grote et al., 2012; Jessen et al., 2016; Ye et al., 2016). Both chemolithoautotrophic sulfur-oxidizing Gammaproteobacteria and sulfur dis-proportionating Deltaproteobacteria have been identified to play a major role in the sulfur and carbon cycling in diverse intertidal sediments (Lenk et al., 2010; Boschker et al., 2014; Dyksma et al., 2016). Hence, chemolithoautotrophic sulfur-oxidizing communities vary between sediment environments, but it is presently not clear as to which environmental factors are actually deter-mining the chemolithoautotrophic community composition at a given site.
Seasonal hypoxia is a natural phenomenon that occurs in coastal areas around the world (Diaz and Rosenberg, 2008) and provides an opportunity to study the environmental factors con-trolling sedimentary chemolithoautotrophy. Hypoxia occurs when bottom waters become de-pleted of oxygen (< 63 µmol O2 L
–1), and has a large impact on the biogeochemical cycling and ecological functioning of the underlying sediments (Diaz and Rosenberg, 2008). The reduced availability or even absence of suitable soluble electron acceptors (O2, NO3
–) in the bottom water during part of the year should in principle result in a reduction or complete inhibition of sedimentary sulfur reoxidation, and hence, limit chemolithoautotrophy. At present, the preva-lence and temporal variations of chemolithoautotrophy have not been investigated in coastal sediments of seasonal hypoxic basins.
Likely, the availability of soluble electron acceptors (O2, NO3–) in the bottom water is not
the only determining factor of chemolithoautotrophy. A recent study conducted in a seasonally hypoxic saline basin (Lake Grevelingen, The Netherlands) indicated that the intrinsic structure and composition of the sulfur oxidizing microbial community also determined the biogeochem-istry of the sediment (Seitaj et al., 2015). In this study, three distinct microbial sulfur oxidation mechanisms were observed throughout a seasonal cycle: (1) electrogenic sulfur oxidation by heterotrophic cable bacteria (Desulfobulbaceae); (2) canonical aerobic oxidation of free sulfide at the oxygen-sulfide interface and, (3) sulfide oxidation coupled to nitrate reduction by filamen-tous members of the Beggiatoaceae family that store nitrate intracellularly. The consequences of these three mechanisms on the chemolithoautotrophic community have however not been studied. The first sulfur oxidizing mechanism has been shown to affect the chemolithoauto-trophic community in sediments only under laboratory conditions (Vasquez-Cardenas et al.,
109
Introduction/Material and Methods
2015) while the third mechanisms may directly involve chemolithoautotrophic Beggiatoaceae as some species are known to grow autotrophically (Nelson and Jannasch, 1983). Accordingly, we hypothesize that the presence of these sulfur oxidation regimes as well as the depletion of O2 and NO3
– will result in a strong seasonality in both the chemolithoautotrophic activity and community structure under natural conditions.
To examine the above-mentioned hypothesis, we conducted a multidisciplinary study with intact sediments of Lake Grevelingen, involving both geochemistry and microbiology. Field sampling was conducted during spring (oxygenated bottom waters) and summer (oxygen deplet-ed bottom waters). The dominant sulfur oxidation mechanism was geochemically characterized by sediment microsensor profiling (O2, H2S, pH) whereas the abundance of cable bacteria and Beggiatoaceae was performed with fluorescence in situ hybridization (FISH). General bacterial diversity was assessed by 16S rRNA gene amplicon sequencing and the analysis of phospholipid derived fatty acids (PLFA). PLFA analysis combined with 13C stable isotope probing (PLFA-SIP) provided the activity and community composition of chemolithoautotrophs in the sediment. This approach was complemented by the analysis of genes involved in dark CO2 fixation, i.e., characterizing diversity and the abundance of the genes cbbL and aclB that code for key enzymes in Calvin-Benson Bassham (CBB) and reductive tricarboxylic acid (rTCA) carbon fixation path-ways. This multidisciplinary research showed strong temporal and spatial shifts of the chemo-lithoautotrophic composition and activity in relation to the seasonal hypoxia and the main sulfur oxidation mechanisms present in the sediments of the marine Lake Grevelingen.
5.2. Material and methods
5.2.1. Study site and sediment sampling Lake Grevelingen is a former estuary located within the Rhine-Meuse-Scheldt delta area of the Netherlands, which became a closed saline reservoir (salinity ~30) by dam construction at both the land side and sea side in the early 1970s. Due to an absence of tides and strong currents, Lake Grevelingen experiences a seasonal stratification of the water column, which in turn, leads to a gradual depletion of the oxygen in the bottom waters (Hagens et al., 2015). Bottom water oxygen at the deepest stations typically starts to decline in April, reaches hypoxic conditions by end of May (O2 < 63 µM), further decreasing to anoxia in August (O2 <0.1 µM), while the re-ox-ygenation of the bottom water takes place in September (Seitaj et al., 2015).
To study the effects of the bottom water oxygenation on the benthic chemolithoautotrophic community we performed a field sampling campaign on March 13th, 2012 (before the start of the annual O2 depletion) and August 20th, 2012 (at the height of the annual O2 depletion). Detailed water column, pore water and solid sediment chemistry of Lake Grevelingen over the year 2012 have been previously reported (Seitaj et al., 2015; Hagens et al., 2015; Sulu-Gambari et al., 2016). Sediments were recovered at three stations along a depth gradient within the Den Osse basin, one of the deeper basins in Marine Lake Grevelingen: Station 1 (S1) was located in the deepest point (34 m) of the basin (51.747°N, 3.890°E), Station 2 (S2) at 23 m depth (51.749°N, 3.897°E) and Station 3 (S3) at 17 m depth (51.747°N, 3.898°E). Intact sediment cores were retrieved with a single core gravity corer (UWITEC) using PVC core liners (6 cm inner diameter, 60 cm length). All cores were inspected upon retrieval and only cores with a visually undisturbed surface were used for further analysis.
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Thirteen sediment cores for microbial analysis were collected per station and per time point: two cores for phospholipid-derived fatty acid analysis combined with stable isotope probing (PLFA-SIP), two cores for nucleic acid analysis, four cores for 13C-bicarbonate labeling, three cores for microelectrode profiling, one core for quantification of cable bacteria (see supple-ment), and one core for quantification of Beggiatoaceae (see supplement). Sediment cores for PLFA extractions were sliced manually on board the ship (5 sediment layers; sectioning at 0.5, 1, 2, 4, and 6 cm depth). Sediment slices were collected in Petri dishes, and replicate depths were pooled and thoroughly mixed. Homogenized sediments were immediately transferred to centrifuge tubes (50 mL) and placed in dry ice until further analysis. Surface sediments in August consisted of a highly porous “fluffy” layer that was first left to settle after core retrieval. After-wards, the top 1 cm thick layer was recovered through suction (rather than slicing). Sediment for nucleic acid analysis was collected by slicing manually at a resolution of 1 cm up to 5 cm depth. Sediment samples were frozen in dry ice, transported to the laboratory within a few hour and placed at −80°C until further analysis.
5.2.2. Microsensor profiling Oxygen depth profiles were recorded with commercial microelectrodes (Unisense, Denmark; tip size: 50 µm) at 25−50 µm resolution. For H2S and pH (tip size: 50 and 200 µm), depth profiles were recorded at 200 µm resolution in the oxic zone, and at 400 or 600 µm depth resolution be-low. Calibrations for O2, pH and H2S were performed as previously described (Seitaj et al., 2015; Malkin et al., 2014). ΣH2S was calculated from H2S based on pH measured at the same depth using the R package AquaEnv (Hofmann et al., 2010). The oxygen penetration depth (OPD) is operationally defined as the depth below which [O2] < 1 µM, while the sulfide appearance depth (SAD) is operationally defined as the depth below which [H2S] > 1 µM. The diffusive oxygen uptake (DOU) was calculated from the oxygen depth profiles as previously described in detail (Vasquez-Cardenas et al., 2015).
5.2.3. DNA extraction and 16S rRNA gene amplicon sequencing DNA from 0 cm to 5 cm sediment depth (in 1 cm resolution) was extracted using the DNA PowerSoil® Total Isolation Kit (Mo Bio Laboratories, Inc., Carlsbad, CA). Nucleic acid con-centrations were quantified spectrophotometrically (Nanodrop, Thermo Scientific, Wilmington, DE) and checked by agarose gel electrophoresis for integrity. DNA extracts were kept frozen at –80°C.
Sequencing of 16S rRNA gene amplicons was performed on the first cm of the sediment (0–1 cm depth) in all stations in March and August as described before (Moore et al., 2015). Further details are provided in the SI. The 16S rRNA gene amplicon reads (raw data) have been deposited in the NCBI Sequence Read Archive (SRA) under BioProject number PRJNA293286. The phylogenetic affiliation of the 16S rRNA gene sequences was compared to release 119 of the SILVA NR SSU Ref database (http://www. arb-silva.de/; Quast et al., 2013) using the ARB software package (Ludwig et al., 2004). Sequences were added to a reference tree generated from the Silva database using the ARB Parsimony tool.
5.2.4. Sediment incubations and PLFA-SIP analysis Sediment cores were labeled with 13C-bicarbonate to determine the chemolithoautotrophic activ-ity and associated bacterial community by tracing the incorporation of 13C into bacterial PLFA.
111
Material and Methods
To this end, four intact cores were sub-cored with smaller core liners (4.5 cm inner diameter; 20 cm height). In situ bottom water was kept over the sediment and no gas headspace was pres-ent. Cores were kept inside a closed cooling box during transport to the laboratory.
Stock solutions of 80 mM of 13C-bicarbonate (99% 13C; Cambridge Isotope Laboratories, Andover, Ma, USA) were prepared as previously described (Boschker et al., 2014). 13C-bicarbon-ate was added to the sediment from 3 cm above the surface to 8 cm deep in the sediment cores in aliquots of 100 μL through vertically aligned side ports (0.5 cm apart) with the line injection method (Jørgensen, 1978). March sediments were incubated at 17±1°C in the dark for 24 h and continuously aerated with 13C-saturated air to maintain 100% saturated O2 conditions as those found in situ, but avoiding the stripping of labeled CO2 from the overlying water (Vasquez-Carde-nas et al., 2015). In August, sediments were incubated at 17±1°C in the dark for 40 h to ensure sufficient labeling as a lower activity was expected under low oxygen concentrations. In August, oxygen concentrations in the overlying water were maintained near in situ O2 levels measured in the bottom water (S1: 0−4% saturation, S2: 20−26%, S3: 35−80%). A detailed description of aeriation procedures can be found in the SI.
At the end of the incubation period, sediment cores were sliced in five depth intervals (as described for PLFA sediment cores sliced on board) thus obtaining two replicate slices per sedi-ment depth and per station. Sediment layers were collected in centrifuge tubes (50 mL) and wet volume and weight were noted. Pore water was obtained by centrifugation (4500 rpm for 5 min) for dissolved inorganic carbon (DIC) analysis, and sediments were lyophilized for PLFA analysis. Biomarker extractions were performed on freeze dried sediment as described before (Guckert et al., 1985) and 13C-incorporation into PLFA was analyzed as previously reported (Boschker et al., 2014). Nomenclature of PLFA can be found in the SI. Detailed description of the PLFA calcu-lations can be found in the literature (Vasquez-Cardenas et al., 2015; Boschker and Middelburg, 2002). Total dark CO2 fixation rates (mmol C m–2 d–1) are the depth-integrated rates obtained from the 0−6 cm sediment interval.
5.2.5. Quantitative PCR To determine the abundance of chemolithoautotrophs we quantified the genes coding for two enzymes involved in dark CO2 fixation pathways: the large subunit of the RubisCO enzyme (ribulose 1,5-bisphosphate carboxylase/oxygenase) cbbL gene, and the ATP citrate lyase aclB gene. Abundance of the RubisCO cbbL gene was estimated by using primers K2f/V2r, specific for the forms IA and IC of the RuBisCO form I large subunit gene cbbL which is present in obligately and facultatively lithotrophic bacteria (Nanba et al., 2004; Nigro and King, 2007). The abundance of ATP citrate lyase aclB gene was quantified by using the primer set aclB_F/aclB_R, which is based on the primers 892F/1204R (Campbell et al., 2003), specific for the ATP citrate lyase β gene of chemoautotrophic bacteria using the rTCA pathway, with several nucleotide differences introduced after aligning n=100 sequences of aclB gene fragments affiliated to Epsi-lonproteobacteria (See Table S1 for details).
The quantification of cbbL and aclB genes via quantitative PCR (qPCR) was performed in 1 cm resolution for the sediment interval between 0–5 cm depth in all stations in both March and August. qPCR analyses were performed on a Biorad CFX96TM Real-Time System/C1000 Thermal cycler equipped with CFX ManagerTM Software. All qPCR reactions were performed in triplicate with standard curves from 100 to 107 molecules per microliter. Standard curves and
Chapter 5
112
qPCR reactions were performed as previously described (Chapter 2). Melting temperatures (Tm) are listed in Table S1, qPCR efficiencies (E) for aclB gene and cbbL gene amplifications were 70 and 82%, respectively. Correlation coefficients for standard curves were ≥ 0.994 for aclB gene and ≥ 0.988 for cbbL gene amplification.
5.2.6. PCR amplification and cloning Amplifications of the RubisCO cbbL gene and the ATP citrate lyase aclB gene were performed with the primer pairs specified in Table S1. The PCR reaction mixture was the following (final concentration): Q-solution (PCR additive, Qiagen, Valencia, CA) 1 ×; PCR buffer 1 ×; BSA (200 µg mL–1); dNTPs (20 µM); primers (0.2 pmol µL–1); MgCl2 (1.5 mM); 1.25 U Taq poly-merase (Qiagen, Valencia, CA). PCR conditions for these amplifications were the following: 95°C, 5 min; 35 × [95°C, 1 min; Tm, 1 min; 72°C, 1 min]; final extension 72°C, 5 min. PCR products were gel purified (QIAquick gel purification kit, Qiagen, Valencia, CA) and cloned in the TOPO-TA cloning® kit (Life Technologies, Carlsbad, CA) and transformed in E. coli TOP10 cells following the manufacturer’s recommendations. Recombinant plasmid DNA was sequenced using M13R primer by BASECLEAR (Leiden, The Netherlands).
Sequences were aligned with MEGA5 software (Tamura et al., 2011) by using the alignment method ClustalW. The phylogenetic trees of the cbbL and aclB genes were computed with the Neighbour-Joining method (Saitou and Nei, 1987). The evolutionary distances were estimated using the Jukes-Cantor method (Jukes and Cantor, 1969) for DNA sequences and with the Poisson correction method for protein sequences (Zuckerkandl and Pauling, 1965) with a boot-strap test of 1,000 replicates. Sequences were deposited in NCBI with the following accession numbers: KT328918–KT328956 for cbbL gene sequences and KT328957–KT329097 for aclB gene sequences. Further details on experimental procedures and methods are found in the Sup-plementary Information.
5.3. Results
5.3.1. Geochemical characterization The seasonal variation of the bottom water oxygen concentration in Lake Grevelingen strongly influenced the porewater concentrations of O2 and H2S. In March, bottom waters were fully oxygenated at all stations (299–307 μM), oxygen penetrated 1.8–2.6 mm deep in the sediment, and no free sulfide was recorded in the first few centimeters (Table 1). The width of the suboxic zone, operationally defined as the sediment layer located between the oxygen penetration depth (OPD) and the sulfide appearance depth (SAD), varied between 16–39 mm across the three stations in March 2012. In contrast, in August, oxygen was strongly depleted in the bottom waters at S1 (< 0.1 μM) and S2 (11 μM), and no O2 could be confidently detected by microsen-sor profiling in the surface sediment at these two stations. At station S3, the bottom water O2 remained higher (88 μM), and oxygen penetrated down to 1.1 mm. In August, free sulfide was present near the sediment-water interface at all three stations, and the accumulation of sulfide in the pore water increased with water depth (Fig. 1a). Depth pH profiles showed much larger variation between stations in March compared to August (Fig. 1a). The pH profiles in S1 and S3 in March were similarly characterized by highest values in the oxic zone and low pH values (pH < 6.5) in the suboxic zone. The pH depth profile in S2 showed an inverse pH profile with a pH minimum in the oxic layer and a subsurface maximum below. The pH profiles at S1 and S3
113
Material and Methods/Results
in August 2012 showed a gradual decline of pH with depth, while the pH profile at S2 in August was more or less constant with depth.
5.3.2. Bacterial diversity by 16S rRNA gene amplicon sequencingThe general diversity of bacteria was assessed by 16S rRNA gene amplicon sequencing anal-ysis, which was applied to the surface sediments (0−1 cm) of all stations in both March and August. Approximately 50% of the reads were assigned to three main clades: Gamma, Delta-, and Epsilonproteobacteria (Fig. 2). The remaining reads were distributed amongst the orders Bacteroidetes (14%), Planctomycetes (6%), Alphaproteobacteria (3%), other orders (20%), the candidate phylum WS3 (2%) and unassigned (5%) (given as the average of the three stations and both seasons).
Reads classified within the Gammaproteobacteria were more abundant in March during ox-ygenated bottom water conditions than in August (Fig. 2). The majority of these reads were assigned to the orders Alteromonadales, Chromatiales and Thiotrichales. The first order includes chemoheterotrophic bacteria that are either strict aerobes or facultative anaerobes (Bowman and McMeekin, 2005). Phylogenetic comparison revealed that the reads assigned to the Chromatiales group were closely related to the Granulosicoccaceae, Ectothiorhodospiraceae, and Chroma-tiaceae families (Fig. S1). Reads falling in the Thiotrichales group were closely related to sul-fur-oxidizing bacteria from the Thiotrichaceae family with 30% of the sequences related to the genera “Candidatus Isobeggiatoa”, “Ca. Parabeggiatoa” and Thiomargarita (Fig. S2). It has been recently proposed that the genera Beggiatoa, Thiomargarita and Thioploca should be reclassified into the originally published monophyletic family of Beggiatoaceae (Salman et al., 2011, 2013), and so here, these genera will be further referred to as Beggiatoaceae. Most of the reads assigned to the Beggiatoaceae came from station S2 in spring, whereas the percentage of reads assigned to sulfur oxidizers from the order Thiotrichales decreased in August when oxygen concentrations in the bottom water were low.
Within the Deltaproteobacteria, reads were assigned to the orders Desulfarculales and Desul-fobacterales (Fig. S3). Reads within the order of Desulfobacterales were mainly assigned to the families Desulfobacteraceae (between 10−20%) and Desulfobulbaceae (~5%) (Fig. 2). Addition-al phylogenetic comparison revealed that within the Desulfobulbaceae, 60% of reads, obtained from the three stations in both seasons, clustered within the genus Desulfobulbus, of which 30% were related to the electrogenic sulfur-oxidizing cable bacteria (Fig. S4). Overall, the relative abundance of reads assigned to the Desulfobulbaceae family was similar between the two sea-sons in S2 and S3, whereas in S1 the percentage of reads was approximately 4.5-fold higher in March compared to August (Fig. 2). In contrast, the relative abundance of reads assigned to the Desulfarculales and Desulfobacteraceae increased in August during hypoxia (Fig. 2), and phylogenetic comparison revealed typical sulfate reducer genera Desulfococcus, Desulfosarcina, and Desulfobacterium, indicative of anaerobic metabolism (Figs. S5a–c).
All Epsilonproteobacteria reads were assigned to the order Campylobacterales, such as the Campylobacteraceae and Helicobacteraceae families. Phylogenetic comparison showed that the reads were closely related to the genera Sulfurovum, Sulfurimonas, Sulfurospirillum, Arcobacter (Figs. S6a–d), all capable of sulfur oxidation with oxygen or nitrate (Campbell et al., 2006). The per-centage of reads assigned to the Epsilonproteobacteria in August was lower than those in March, with highest numbers present in S2 in March (~6%), (Fig. 2).
Chapter 5
114
Tabl
e 1:
Geo
chem
ical
cha
ract
eriz
atio
n, c
hem
oaut
otro
phy
rate
s, an
d qu
antifi
catio
n of
cab
le b
acte
ria a
nd B
eggi
atoa
ceae
in th
e th
ree
stat
ions
in L
ake
Gre
velin
gen
for s
prin
g (M
arch
) and
sum
mer
(Aug
ust).
Mon
th/
Stat
ion
Bot
tom
wat
er *
con
c.
[μM
]D
OU
OPD
SA
DSu
boxi
c zo
ne**
pH
sign
atur
e***
Che
mol
itho-
auto
trop
hy
[mm
ol C
m-2
d-1]
Cab
le
biov
olum
e
[mm
3 cm
-2]
Beg
giat
oa
biov
olum
e
[mm
3 cm
-2]
°CO
2 N
O3–
[mm
ol O
2 m
-2 d
-1]
[mm
][m
m]
[mm
]
M
15
299
(oxi
c)28
.218
.2±
1.7
1.8±
0.04
17.5
±0.
716
e-SO
x3.
1±0.
52.
550.
02
25
301
(oxi
c)27
.915
.8±
3.1
2.6±
0.65
21.3
±2.
519
Nitr
ate-
stor
ing
Begg
iato
a1.
9±0.
1N
D0.
11
35
307
(oxi
c)27
.717
.1±
5.7
2.4±
0.4
41.8
±8.
639
e-SO
x1.
4±0.
32.
080.
05
A
117
0(a
noxi
c)1.
70
00.
9±1.
10.
9
Sulfa
te
redu
ctio
n/
cano
nica
l su
lfur
oxid
atio
n
0.2±
0.1
0.11
0.00
1
217
12(h
ypox
ic)
11.6
00
0.6±
00.
60.
8±0.
3N
D3.
24
319
88(h
ypox
ic)
10.6
13.9
±2.
11.
1±0.
14.
2±2.
73
1.1±
0.5
0.00
30.
004
M -
Mar
ch, A
- A
ugus
t, D
OU
: diss
olve
d O
2 up
take
; OPD
: O2
pene
tratio
n de
pth;
SA
D: ∑
H2S
app
eara
nce
dept
h; e
-SO
x: e
lect
roge
nic
sulfu
r oxi
datio
n;
ND
: not
det
erm
ined
. *Bo
ttom
wat
er is
cla
ssifi
ed a
s ano
xic
with
O2
conc
entra
tion
belo
w 1
μM
and
hyp
oxic
bel
ow 6
3 μM
. **T
he th
ickn
ess o
f th
e su
boxi
c zo
ne is
defi
ned
as t
he a
vera
ge S
AD
min
us t
he a
vera
ge O
PD. *
**pH
sig
natu
re s
erve
s to
indi
cate
the
sul
fur
oxid
izin
g m
echa
nism
tha
t do
min
ates
the
po
rew
ater
che
mist
ry a
s des
crib
ed b
y Se
itaj e
t al.
(201
5). C
able
- ca
ble
bact
eria
.
115
Results
Figu
re 1
: Geo
chem
ical
fing
erpr
int,
(b) c
hem
oaut
otro
phy
dept
h pr
ofile
s, (c
) bio
volu
me
of fi
lam
ento
us B
eggi
atoa
ceae
(bla
ck) a
nd c
able
bac
teria
(blu
e)
in se
dim
ent o
f La
ke G
reve
linge
n fo
r Mar
ch a
nd A
ugus
t in
all t
hree
stat
ions
(not
e ch
ange
in sc
ale
for B
eggi
atoa
ceae
bet
wee
n M
arch
and
Aug
ust).
S1:
st
atio
n 1
(34
m),
S2: s
tatio
n 2
(23
m),
S3: s
tatio
n 3
(17
m).
Chapter 5
116
5.3.3. Bacterial community structure by phospholipid derived fatty acid analysis The relative concentrations of phospholipid derived fatty acid (PLFA) were determined to a depth of 6 cm and were analyzed by principal component analysis (PCA) to determine differ-ences in bacterial community structure (Fig. 3). A total of 22 individual PLFA, each contributing more than 0.1% to the total PLFA biomass, were included in this analysis. Samples with low total PLFA biomass (less than one standard deviation below the mean of all samples) were excluded. The PCA analysis indicated that 73% of the variation within the dataset was explained by the first two principal components (PC). While PC1 correlated with sediment depth (particularly for the March samples), PC2 clearly exposed differences in the bacterial community structure between seasons (Fig. 3a). Surface sediments (0–1 cm) were characterized by high relative con-centrations of C16 and C18 monounsaturated PLFA. In contrast, ai15:0, i17:1ω7c, and 10Me16:0 were more abundant in deeper sediments (Fig. S7a). The surface sediment showed an increased contribution of iso, anteiso and branched PLFAs in August relative to March, and this was more similar to the deeper sediments from March (Fig. 3a). Nonetheless, August sediments also showed a higher abundance of 16:0, 14:0, and 18:1ω9c compared to the deeper sediment layers in March (Fig. S7a).
5.3.4. Chemolithoautotrophic activity and community by 13C-phospholipid fatty acids analysisIncorporation of 13C-labeled dissolved inorganic carbon was found in bacterial PLFAs after 24 to 40 hours of incubation (Fig. S7b). Depth integrated dark CO2 fixation rates based on 13C-in-corporation (Table 1) showed a significant difference between seasons and stations (p = 0.0005). In March, chemolithoautotrophy increased with water depth, while in August, the opposite trend was observed. The dark CO2 fixation rate in March for S1 was the highest across all seasons and stations, but dropped by one order of magnitude in August. In contrast, at the intermediate station (S2), the dark CO2 fixation rate was only two times higher in March compared to August, while in the shallowest station (S3) the depth integrated rates were not significantly different between seasons (p = 0.56).
The depth distribution of the chemolithoautotrophic activity also differed between seasons (p = 0.02; Fig. 1b). In August, the chemolithoautotrophic activity was restricted to the upper cm of the sediment at all stations while in March, chemolithoautotrophic activity was measured deep into the sediment (up to 4 cm). In stations S1 and S3 during March, the activity depth profile showed high activities down to 4 cm, whereas at S2 chemolithoautotrophy only extended down to 2 cm with highest activity in the top 1 cm. This distinction between the depth distri-butions of chemolithoautotrophy at S2 versus S1/S3 in March correlated with the distinct pH profiles observed for S2 versus S1/S3 (Fig. 1c).
The PLFA 13C-fingerprints were analyzed by PCA to identify differences in chemolithoauto-trophic community. Only PLFA that contributed more than 0.1% to the total 13C-incorporation and sediment layers that showed chemolithoautotrophy rates higher than 0.01 μmol C cm–3 d–1 were taken into account in this analysis. Because chemolithoautotrophy rates were low in Au-gust, the PCA analysis mainly analyzed the chemolithoautotrophic communities in March (Fig. 3b). Within the dataset, 64% of the variation was explained by two principal components. PC1 revealed a clear differentiation between station S2, and stations S1 and S3 (Fig. 3b) in agreement with the distinct pH profiles described for March (Fig. 1a). S2 sediment horizons showed a
117
Results
Figure 2: Percentages of total bacterial 16S rRNA gene reads in stations S1 (yellow), S2 (blue) and S3 (red) in March (filled) and August (hatched). Classified bacterial phyla, classes and orders > 3% of the total bacteria reads (in March or August) are reported (exception: family Thiotrichaceae < 3%), *including cable bacteria, **including Beggiatoaceae.
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higher contribution of monounsaturated C16 and C18 fatty acids, whereas sediments from S1 and S3 revealed an increased 13C-incorporation into fatty acids with iso and anteiso C15 and saturated C14 PLFA (Fig. S7c), together these results indicate distinct chemolithoautotrophic microbial assemblages between S2 and S1/S3. On the contrary, the three sediment samples from August (that had sufficient 13C-incorporation for the analysis) did not cluster in the PCA analysis and exhibited divergent PLFA profiles, thus the chemolithoautotrophic bacterial community for Au-gust could not be characterized further based on PLFA analysis.
5.3.5. Chemolithoautotrophic carbon fixation pathways Various CO2 fixation pathways are used by autotrophic bacteria (for detailed reviews see Berg, 2011, Hügler and Sievert, 2011). The CBB pathway is utilized by cyanobacteria and many aerobic or facultative aerobic proteobacteria of the alpha, beta and gamma subgroups whereas the rTCA pathway operates in anaerobic or microaerobic members of phyla such as Chlorobi, Aquificae, proteobacteria of the Delta- and Epsilon- subgroups and Nitrospirae (Berg, 2011). The spatial and temporal distribution of bacteria possessing these two autotrophic carbon fixation pathways was studied by quantifying the abundance of cbbL gene (CBB pathway) (Nigro and King, 2007) and aclB gene (rTCA pathway) (Campbell et l., 2006, modified in this study) by quantitative PCR down to 5 cm sediment depth (Fig. 4).The diversity of cbbL and aclB gene sequences obtained from the surface sediments (0–1 cm) was analyzed (Figs. 5a, b).
Significant differences were found in the abundance of cbbL and aclB genes (p = 5.7 × 10–7) and between season (p = 0.002), but not between stations (Fig. 4). The abundance of the cbbL gene copies was at least 2-fold higher than that of the aclB gene in March and August in all sta-tions (p = 5×10–5). In March, the depth profiles of cbbL gene showed a similar trend in stations
Figure 3: Principal component analysis (PCA) of relative PLFA concentrations (a) and of 13C-incorpora-tion into PLFA (b) in sediments from the three stations in March (no border) and August (black border). The percentage of variability explained by the first two principal components (PC) is indicated on each axis. Red: station S1, Yellow: S2, Blue S3. Symbols indicate sediment depth as seen in plot.
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S1 and S3 with a decreasing gene abundance from the surface towards deeper layers, but depth integrated abundance of the cbbL gene was more than two-fold higher in S1 than in S3 (Fig. 4a). The depth distribution of the cbbL gene in the deepest station (S1) differed between seasons (p = 0.004), with lower gene copy abundances in the top 4 cm in August (Fig. 4a). In contrast, in the shallow station (S3), which experiences less seasonal fluctuations in bottom water O2, the cbbL gene copy number did not differ significantly between seasons (p = 0.4), except for a sharp decrease in the top cm of the sediment. In station S2, abundance and depth distribution of cbbL gene copies was similar between the two seasons (p = 0.3). All detected cbbL gene sequences clustered with uncultured Gammaproteobacteria clones (Fig. 5a), assigned to the orders Chro-matiales and Thiotrichales (both cbbL1 and cbbL2 clusters) reported in intertidal sediment from Lowes Cove, Maine (Nigro and King, 2007).
The abundance of the aclB gene significantly differed between months (p = 0.0004) and sta-tions (p = 0.04). Similar depth profiles of the aclB gene were detected in stations S1 and S3, with subsurface maxima in deeper sediments (at 3–4 cm and 2–3 cm deep for S1 and S3 respectively, Fig. 4b). Station S2 showed the highest aclB gene abundance in March, which remained constant with sediment depth (p = 0.86). In August, aclB gene abundance decreased substantially in S2 (p < 0.001). All stations showed a uniform distribution of the aclB gene abundance with depth in August. Bacterial aclB gene sequences in surface sediments (0−1 cm) of all stations were predominantly related to aclB sequences of Epsilonproteobacteria (Fig. 5b). Within the Epsi-lonproteobacteria, sequences clustered in six different subclusters and were mainly affiliated to bacteria in the order of Campylobacterales, i.e., to the genera Sulfuricurvum, Sulfurimonas, Thiovu-
Figure 4: Abundance [copy g−1] of two carbon fixation pathway genes with sediment depth [cm] for S1 (left), S2 (middle) and S3 (right) (a) RuBisCO cbbL gene (b) ATP citrate lyase aclB gene (black: March, white: August). The error bars represent the standard deviations of qPCR replicates.
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Station 1 August (seq19); 0-1 cm Lake Grevelingen sedimentStation 3 August (seq19); 0-1 cm Lake Grevelingen sediment
uncultured proteobacterium clone LCS147; intertidal marine surface sediment (DQ683601)Station 2 August (seq4); 0-1 cm Lake Grevelingen sediment
Station 3 August (seq18); 0-1 cm Lake Grevelingen sedimentStation 3 August (seq16); 0-1 cm Lake Grevelingen sedimentuncultured proteobacterium clone LCB16; intertidal marine sediment, burrow (DQ683650)
uncultured proteobacterium clone LCS69; intertidal marine surface sediment, (DQ683590)uncultured proteobacterium clone LCS120; intertidal marine surface sediment, (DQ683598)
Station 1 March (seq4); 0-1 cm Lake Grevelingen sedimentStation 2 March (seq27); 0-1 cm Lake Grevelingen sediment
Station 2 March (seq20); 0-1 cm Lake Grevelingen sedimentStation 2 March (seq22); 0-1 cm Lake Grevelingen sediment
uncultured proteobacterium clone LCS15; intertidal marine surface sediment, (DQ683585)uncultured proteobacterium clone LCSS223; intertidal marine subsurface sediment, (DQ683644)
Station 3 August (seq13); 0-1 cm Lake Grevelingen sedimentStation 2 March (seq15); 0-1 cm Lake Grevelingen sediment
uncultured proteobacterium clone LCSS; intertidal marine subsurface sediment, (DQ683627)uncultured proteobacterium clone LCSS21; intertidal marine subsurface sediment, (DQ683641)
Station 3 August (seq20); 0-1 cm Lake Grevelingen sedimentuncultured proteobacterium clone LCB173; intertidal marine sediment, burrow (DQ683661)Station 1 August (seq16); 0-1 cm Lake Grevelingen sediment
Station 2 March (seq23); 0-1 cm Lake Grevelingen sedimentStation 3 March (seq23); 0-1 cm Lake Grevelingen sediment
Station 2 August (seq24); 0-1 cm Lake Grevelingen sedimentStation 3 August (seq17); 0-1 cm Lake Grevelingen sediment
Station 1 March (seq26); 0-1 cm Lake Grevelingen sedimentuncultured proteobacterium clone LCSS9 (intertidal marine subsurface sediment (DQ683619)Station 2 March (seq18); 0-1 cm Lake Grevelingen sediment
Station 1 August (seq17); 0-1 cm Lake Grevelingen sedimentuncultured proteobacterium clone LCS155 (intertidal marine surface sediment (DQ683603)
Station 3 August (seq14); 0-1 cm Lake Grevelingen sedimentuncultured proteobacterium clone LCS42 (intertidal marine surface sediment (DQ683588)
Station 3 August (seq15); 0-1 cm Lake Grevelingen sedimentStation 3 March (seq19); 0-1 cm Lake Grevelingen sediment
Station 2 March (seq21); 0-1 cm Lake Grevelingen sedimentStation 2 March (seq26); 0-1 cm Lake Grevelingen sediment
Station 2 March (seq17); 0-1 cm Lake Grevelingen sedimentStation 2 March (seq19); 0-1 cm Lake Grevelingen sediment
strain ALJD (AY914807)Thioalkalivibrio denitrificansstrain Hl17 (EF199949)Thioalkalivibrio halophilus
sp. K90mix (CP001905)Thioalkalivibriostrain Arh2 (AY914804)Thioalkalivibrio thiocyanoxidans
strain Al2 (AY914800)Thioalkalivibrio versutusThioploca ingrica (AP014633)
sp. PS (ABBZ01000395)Beggiatoastrain HL 5 cbbL-1 gene (DQ390451)Thiomicrospira halophila
sp. Lilliput-1 (AM404076)ThiomicrospiraXCL-2 (CP000109)Thiomicrospira crunogena
cbbL-1 gene (DQ272534)Thiomicrospira crunogenacbbL-1 gene (DQ272531)Thiomicrospira kuenenii
cbbL-1 gene (D43621)Hydrogenovibrio marinusHydrogenovibrio marinus (AB122069)
Station 2 March (seq25); 0-1 cm Lake Grevelingen sedimentStation 3 March (seq24); 0-1 cm Lake Grevelingen sediment
Station 2 March (seq16); 0-1 cm Lake Grevelingen sedimentuncultured proteobacterium clone LCSS153; intertidal marine subsurface sediment (DQ683632)
Station 1 August (seq18); 0-1 cm Lake Grevelingen sedimentStation 1 March (seq28); 0-1 cm Lake Grevelingen sedimentStation 2 August (seq24); 0-1 cm Lake Grevelingen sedimentStation 2 March (seq24); 0-1 cm Lake Grevelingen sediment
Station 1 August (seq15); 0-1 cm Lake Grevelingen sedimentuncultured proteobacterium clone LCS90 (intertidal marine surface sediment (DQ683592)Station 3 March (seq21); 0-1 cm Lake Grevelingen sediment Station 3 March (seq25); 0-1 cm Lake Grevelingen sediment
Station 1 March (seq27); 0-1 cm Lake Grevelingen sedimentStation 2 March (seq18); 0-1 cm Lake Grevelingen sediment
strain HL 5 cbbL-2 gene (DQ390452)Thiomicrospira halophilastrain Arh1 (AY914806)Thioalkalivibrio paradoxus
XCL-2 (CP000109)Thiomicrospira crunogenacbbL-2 gene (DQ272533)Thiomicrospira crunogena
cbbL-2 gene (DQ272532)Thiomicrospira kueneniisp. Lilliput-1 (AM404077)Thiomicrospira
cbbL-2 gene (AB122070)Hydrogenovibrio marinuscbbL-2 gene (D43622)Hydrogenovibrio marinus
Thiomicrospira pelophila (DQ272530)sp. V2501 cbbL-2 gene (AB634593)Thiomicrospira
Al3 (CP007030)Thioalkalimicrobium aerophilumALM1 (CP002776)Thioalkalimicrobium cyclicum
Thioalkalimicrobium sibiricum (DQ272529)Thioalkalimicrobium aerophilum (DQ272527)
Thioalkalimicrobium cyclicum (DQ272528)
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Figure 5a: Phylogenetic tree (amino acid-based) of cbbL gene sequences retrieved in this study and closest relatives. The scale bar indicates 2% sequence divergence.
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Station 2 March (seq14); 0-1 cm Lake Grevelingen sedimentStation 2 March (seq26); 0-1 cm Lake Grevelingen sedimentStation 2 March (seq3); 0-1 cm Lake Grevelingen sediment
uncultured bacterium; epibiota hydrothermal vent shrimp (CBJ18443) Station 2 March (seq21); 0-1 cm Lake Grevelingen sedimentStation 2 March (seq4); 0-1 cm Lake Grevelingen sediment
Station 3 March (seq10); 0-1 cm Lake Grevelingen sediment
Station 1 March (seq7); 0-1 cm Lake Grevelingen sedimentStation 2 August (seq11); 0-1 cm Lake Grevelingen sedimentuncultured bacterium; epibiota hydrothermal vent shrimp (CBJ18444)
Station 2 March (seq9); 0-1 cm Lake Grevelingen sedimentuncultured bacterium; hydrothermal vent (CBH30829)
uncultured bacterium; epibiota hydrothermal vent shrimp (CBJ19314)uncultured bacterium;epibiota hydrothermal vent shrimp (CBJ19314)
Sulfuricurvum kujiense (YP004059532)Station 2 August (seq9); 0-1 cm Lake Grevelingen sediment
Sulfurimonas denitrificans (WP011372203)Thiovulum sp. ES (WP008352685)
Station 1 March (seq9); 0-1 cm Lake Grevelingen sedimentStation 1 August (seq3); 0-1 cm Lake Grevelingen sedimentStation 1 March (seq13); 0-1 cm Lake Grevelingen sedimentuncultured bacterium; hydrothermal vent (CBH30846)
Arcobacter sulfidicus (AAQ76339)Candidatusuncultured bacterium; hydrothermal vent (CBH30845)Station 1 March (seq3); 0-1 cm Lake Grevelingen sedimentStation 2 March (seq25); 0-1 cm Lake Grevelingen sedimentStation 1 August (seq11); 0-1 cm Lake Grevelingen sedimentuncultured bacterium; deep sea hydrothermal vent (CBH30818)uncultured episymbiont of Alvinella pompejana (AAQ76330) Station 2 March (seq28); 0-1 cm Lake Grevelingen sedimentStation 2 August (seq17); 0-1 cm Lake Grevelingen sedimentStation 3 August (seq3); 0-1 cm Lake Grevelingen sedimentStation 2 August (seq8); 0-1 cm Lake Grevelingen sedimentStation 1 August (seq5); 0-1 cm Lake Grevelingen sediment
Station 1 March (seq5); 0-1 cm Lake Grevelingen sedimentStation 1 March (seq12); 0-1 cm Lake Grevelingen sedimentStation 1 August (seq10); 0-1 cm Lake Grevelingen sedimentStation 3 August (seq14); 0-1 cm Lake Grevelingen sedimentStation 3 August (seq6); 0-1 cm Lake Grevelingen sediment
Station 1 March (seq21); 0-1 cm Lake Grevelingen sedimentStation 1 March (seq24); 0-1 cm Lake Grevelingen sedimentStation 3 March (seq3); 0-1 cm Lake Grevelingen sedimentStation 3 March (seq13); 0-1 cm Lake Grevelingen sedimentStation 1 March (seq7); 0-1 cm Lake Grevelingen sedimentStation 3 March (seq16); 0-1 cm Lake Grevelingen sediment
Station 3 March (seq15); 0-1 cm Lake Grevelingen sedimentStation 1 March (seq4); 0-1 cm Lake Grevelingen sedimentStation 1 March (seq25); 0-1 cm Lake Grevelingen sedimentStation 3 March (seq8); 0-1 cm Lake Grevelingen sediment
Sulfurimonas gotlandica (WP008336361)Station 2 August (seq2); 0-1 cm Lake Grevelingen sediment
Station 1 August (seq18); 0-1 cm Lake Grevelingen sedimentStation 1 August (seq15); 0-1 cm Lake Grevelingen sediment
Station 2 August (seq6); 0-1 cm Lake Grevelingen sedimentStation 3 August (seq11); 0-1 cm Lake Grevelingen sediment1
Station 1 August (seq22); 0-1 cm Lake Grevelingen sedimentSulfurimonas autotrophica (WP013327378)
Station 3 August (seq7); 0-1 cm Lake Grevelingen sedimentuncultured bacterium; deep sea hydrothermal vent (AAS01105)
sp. AR (WP008245184)SulfurovumStation 3 March (seq7); 0-1 cm Lake Grevelingen sediment
Station 2 March (seq15); 0-1 cm Lake Grevelingen sedimentStation 2 August (seq16); 0-1 cm Lake Grevelingen sedimentStation 2 March (seq27); 0-1 cm Lake Grevelingen sedimentStation 3 March (seq9); 0-1 cm Lake Grevelingen sediment
Station 2 March (seq1); 0-1 cm Lake Grevelingen sedimentStation 2 March (seq8); 0-1 cm Lake Grevelingen sedimentStation 1 August (seq16); 0-1 cm Lake Grevelingen sedimentStation 2 August (seq3); 0-1 cm Lake Grevelingen sediment
Station 1 March (seq2); 0-1 cm Lake Grevelingen sedimentStation 1 March (seq29); 0-1 cm Lake Grevelingen sedimentStation 2 March (seq22); 0-1 cm Lake Grevelingen sedimentStation 3 March (seq4); 0-1 cm Lake Grevelingen sedimentStation 1 March (seq20); 0-1 cm Lake Grevelingen sedimentStation 1 March (seq17); 0-1 cm Lake Grevelingen sedimentStation 3 March (seq12); 0-1 cm Lake Grevelingen sediment
Station 1 March (seq15); 0-1 cm Lake Grevelingen sedimentStation 2 March (seq2); 0-1 cm Lake Grevelingen sedimentStation 1 March (seq14); 0-1 cm Lake Grevelingen sedimentStation 1 March (seq19); 0-1 cm Lake Grevelingen sedimentStation 3 March (seq16); 0-1 cm Lake Grevelingen sediment
Station 3 August (seq15); 0-1 cm Lake Grevelingen sedimentuncultured episymbiont of Alvinella pompejana (AAQ76323)uncultured episymbiont of Alvinella pompejana (AAQ76331)uncultured episymbiont of Alvinella pompejana (AAQ76305)
Nautilia profundicola (WP012663645)Caminibacter mediatlanticus (WP007475383)
uncultured episymbiont of Alvinella pompejana (AAQ76296)uncultured episymbiont of Alvinella pompejana (AAQ76291)
Station 1 March (seq8); 0-1 cm Lake Grevelingen sedimentStation 2 March (seq5); 0-1 cm Lake Grevelingen sediment
Nitratifractor salsuginis (WP013553540)Station 3 March (seq22); 0-1 cm Lake Grevelingen sediment
sp. TC5-1 (WP022847029)Desulfurobacteriumuncultured sp. (ABW04211)Sulfurihydrogenibium
Persephonella marina (WP012676068)Desulfurobacterium thermolithotrophum (WP013638724)Desulfurobacterium crinifex (ABI50077)Thermovibrio ammonificans (WP013537775)Thermovibrio ruber (ABI50082)
Station 2 August (seq23); 0-1 cm Lake Grevelingen sedimentStation 2 August (seq24); 0-1 cm Lake Grevelingen sediment
Station 2 August (seq22); 0-1 cm Lake Grevelingen sedimentStation 2 August (seq25); 0-1 cm Lake Grevelingen sediment
Station 1 August (seq13); 0-1 cm Lake Grevelingen sedimentStation 1 August (seq14); 0-1 cm Lake Grevelingen sedimentStation 1 August (seq9); 0-1 cm Lake Grevelingen sedimentStation 1 August (seq20); 0-1 cm Lake Grevelingen sediment
Station 1 August (seq21); 0-1 cm Lake Grevelingen sedimentStation 1 August (seq8); 0-1 cm Lake Grevelingen sediment
Thermoplasmatales archaeon (WP008441970)Station 3 August (seq8); 0-1 cm Lake Grevelingen sediment
Methanosaeta harundinacea (WP014587073)Station 3 March (seq20); 0-1 cm Lake Grevelingen sediment
Station 2 August (seq21); 0-1 cm Lake Grevelingen sedimentStation 2 August (seq18); 0-1 cm Lake Grevelingen sediment
Station 2 August (seq20); 0-1 cm Lake Grevelingen sediment
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Figure 5b: Phylogenetic tree (amino acid-based) of aclB gene sequences retrieved in this study and closest relatives. The scale bar indicates 5% sequence divergence.
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lum, Arcobacter, and macrofaunal endosymbionts. As observed for the cbbL gene, no clustering of sequences was observed according to station or season (Fig. 5b).
5.3.6. Quantification of cable bacteria and filamentous Beggiatoaceae We performed a detailed microscopy-based quantification of the biovolume of sulfur oxidizing cable bacteria and filamentous Beggiatoaceae because both groups have been reported to govern the sediment geochemistry and sulfur cycling in sediments of Lake Grevelingen (Seitaj et al., 2015), and thus are likely to influence the chemolithoautotrophic community. Biovolume data of both filamentous bacteria for S1 have been reported before (Seitaj et al., 2015) whereas data for S2 and S3 are novel results from the 2012 campaign. In March, high biovolumes of cable bacteria were detected in S1 and S3 (Table 1) with filaments present throughout the suboxic zone until a maximum depth of 4 cm (Fig. 1c). At the same time, cable bacteria were absent in S2 (Fig. 1c). In August, cable bacteria were only detected between 1 and 2 cm deep at the deepest station (S1), albeit at abundances that were close to the detection limit of the technique. Beggiatoaceae were found in all three stations in March, although the biovolume at S2 was one order of magni-tude higher than in the other two stations (Table 1). In station S2, Beggiatoaceae were uniformly distributed up to the sulfide appearance depth (Fig. 1c). In August, Beggiatoaceae were no longer detectable in stations S1 and S3 (Table 1), while at S2, filaments were no longer found in deeper sediment, but formed a thick mat at the sediment-water interface (Fig. 1c).
5.4. Discussion
5.4.1. Temporal shifts of chemolithoautotrophy and the associated bacterial assemblages Together, our geochemical and microbiological characterization of the sediments of Lake Grev-elingen indicates that the availability of electron acceptors (O2, NO3
–) constitutes the main en-vironmental factor controlling the activity of the chemolithoautotrophic bacterial community. In the deeper basins of Lake Grevelingen (below water depth of 15 m), the electron acceptor availability changes on a seasonal basis due to the establishment of summer hypoxia (Seitaj et al., 2015; Sulu-Gambari et al., 2016). In March, when high oxygen levels are found in the bottom waters, the chemolithoautotrophy rates were substantially higher than in August when oxygen in the bottom water was depleted to low levels (Fig. 1b; Table 1). Moreover in August, the chemo-lithoautotrophy rates showed a clear decrease with water depth (from S3 to S1) in line with the decrease of the bottom water oxygen concentration over depth.
The 16S rRNA gene amplicon sequencing analysis in our study reveals that the response of the chemolithoautotrophic bacterial community in the surface sediments of Lake Grevelingen is associated with the seasonal changes in bottom water oxygen (Fig. 2). Generally, Lake Grevelin-gen surface sediments harbor a distinct microbial community compared to other surface sedi-ments such as coastal marine (North Sea), estuarine and Black Sea sediments (Jessen et al., 2016; Ye et al., 2016; Dyksma et al., 2016) studied by 16S rRNA gene amplicon sequencing analysis.
In March, with oxic bottom waters, the microbial community in the top centimeter of the sediment at all three stations was characterized by high abundances of Epsilon- and Gammapro-teobacteria, which are known chemolithoautotrophic sulfur-oxidizers (e.g. capable of oxidizing sulfide, thiosulfate, elemental sulfur and polythionates) using oxygen or nitrate as electron ac-ceptor (Campbell et al., 2006; Sorokin et al., 2001; Takai et al., 2006; Labrenz et al., 2013). In
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August, the lack of electron acceptors (O2, NO3–) in the bottom water was accompanied by a
decrease in the relative abundance of these Gammaproteobacteria and Epsilonproteobacteria. At the same time, the numbers of reads related to the Desulfobacteraceae family increased in the top centimeter of the sediment, and a shift in the microbial community structure towards sul-fate reducing bacteria related to the genera Desulfococcus and Desulfosarcina was evident. In coastal sediments, these genera are characteristic in deeper sediment layers experiencing anaerobic min-eralization (Llobet-Brossa et al., 2002; Miyatake, 2011; Muyzer and Stams, 2008), and thus, they are not unexpected in surface sediments during strongly hypoxic (S2) and anoxic (S1) conditions encountered in August.
Shifts in PLFA patterns are in agreement with the temporal difference in the bacterial com-munity (Fig. 3a), with more PLFAs found in Gammaproteobacteria and Epsilonproteobacteria in March (i.e., 16:1ω7c and 18:1 ω7c; Vestal and White, 1989) as opposed to more PLFAs found in sulfate reducing bacteria in the Deltaproteobacteria in August (i.e., ai15:0, i17:1ω7c, 10Me16:0; Boschker and Middelburg, 2002; Taylor and Parkes, 1983, Edlund et al., 1985). However, sedi-ments below the OPD in March have PLFA patterns that are more similar to those of surface sediments in August, in agreement with the observation that anaerobic metabolism such as sul-fate reduction prevail in deeper anoxic sediments also in March.
5.4.2. Spring: Activity and diversity of chemolithoautotrophic bacteriaAlthough the availability of soluble electron acceptors (O2, NO3
–) in the bottom water is import-ant, our data show that it cannot be the only structuring factor of the chemolithoautotrophic communities. In March 2012, all the three stations examined experienced similar bottom water O2 and NO3
– concentrations (Table 1), but still substantial differences were observed in the composition of the chemolithoautotrophic communities as determined by PLFA-SIP (Fig. 3b), as well as in the depth distribution of the chemolithoautotrophy rates in the sediment (Fig. 1b). We attribute these differences to the presence of specific sulfur oxidation mechanisms that are active in the sediments of Lake Grevelingen (Seitaj et al., 2015). In March 2012, based on FISH counts and microsensor profiles two separate sulfur oxidation regimes were active at the sites investigated: sites S1 and S3 were impacted by electrogenic sulfur oxidation by cable bacteria, while site S2 was dominated by sulfur oxidation via nitrate-storing, filamentous Beggiatoaceae. Each of these two regimes is characterized by a specific sulfur-oxidizing microbial community and a particular depth distribution of the chemolithoautotrophy. We now discuss these two re-gimes separately in more detail.
Electrogenic sulfur oxidationIn March, stations S1 and S3 (Fig. 1a) showed the geochemical fingerprint of electrogenic
sulfur oxidation (e-SOx) consisting of a centimeter-wide suboxic zone that is characterized by acidic pore waters (pH < 7) (Nielsen et al., 2010; Meysman et al., 2015). Electrogenic sulfur oxidation is attributed to the metabolic activity of cable bacteria (Pfeffer et al., 2012), which are long filamentous bacteria related to the sulfate reducing genus Desulfobulbus that extend centi-meters deep into the sediment (Schauer et al., 2014). The observed depth-distribution of cable bacteria at S1 and S3 (Fig. 1c) was congruent with the geochemical fingerprint of e-SOx. Cable bacteria couple the oxidation of sulfide in deeper layers to the reduction of oxygen near the sediment-water interface, by channeling electron along their longitudinal axis (long-distance elec-tron transport). Note that stations S1 and S3 also contained some Beggiatoaceae. However, they
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attained low biovolumes and were only found at certain depths, suggesting that they did not play a significant role in sulfur oxidation.
When e-SOx was present in the sediment (sites S1 and S3 in March), the chemolithoautotro-phic activity penetrated deeply into the sediment and was evenly distributed throughout the su-boxic zone (Fig. 1b). These field observations confirm previous laboratory incubations in which cable bacteria were induced under oxic conditions in homogenized sediments, and a highly simi-lar depth pattern of deep chemolithoautotrophy was noted (Vasquez-Cardenas et al., 2015). This deep dark CO2 fixation is unexpected in two ways. Firstly, cable bacteria are likely not responsible for the deep CO2 fixation although they do perform sulfur oxidation, as cable bacteria from Lake Grevelingen have been shown to incorporate organic carbon rather than inorganic carbon (Vasquez-Cardenas et al., 2015). Secondly, chemolithoautotrophy is generally dependent on re-oxidation reactions, but there is no transport of oxygen or nitrate to centimeters depth in these cohesive sediments, and so the question is: how can chemolithoautotrophic reoxidation occur in the absence of suitable electron acceptors?
To reconcile these observations, it was proposed that in incubated electro-active sediments from Lake Grevelingen, heterotrophic cable bacteria can form a sulfur-oxidizing consortium with chemolithoautotrophic Gamma- and Epsilonproteobacteria throughout the suboxic zone
Figure 6: Schematic representation of the main sulfur oxidation mechanisms by chemoautotrophic bac-teria under oxic conditions in spring (left) and hypoxic conditions in summer (right) in marine Lake Grevelingen (single-celled and filamentous sulfur-oxidizing bacteria are shown as follows, Epsilonproteo-bacteria (yellow), Gammaproteobacteria (green), Deltaproteobacteria (red), grey arrows represent possible reoxidation processes by chemoautotrophic bacteria and the color of the reaction indicates the bacterial group involved, blue arrow: trajectory of filamentous Beggiatoaceae (thick green lines) from the surface to the sulfide horizon and back up to the surface, black arrow: long-distance electron transport by cable bacteria (red broken lines).
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(Vasquez-Cardenas et al., 2015). The results obtained in our study provide various lines of evi-dence that support the existence of such a consortium in intact sediment cores. The PLFA-SIP patterns in S1 and S3 (Fig. 3b) showed major 13C-incorporation in PLFA which are present in sulfur-oxidizing Gamma- and Epsilonproteobacteria (Takai et al., 2006; Inagaki et al., 2003; Donachie et al., 2005; Zhang et al., 2005), and this occurred throughout the top 5 cm of the sediment corresponding to the zone of e-SOx activity. In addition, the depth profiles of genes involved in dark CO2 fixation (Fig. 4) revealed chemolithoautotrophic Gammaproteobacteria using the CBB cycle as well as Epsilonproteobacteria using the rTCA cycle, which confirms the potential dark CO2 fixation by both bacterial groups deep in the sediment. The higher abun-dance of cbbL genes in S1 compared to S3 indicates a greater chemolithoautotrophic potential of Gammaproteobacteria, which may explain the two-fold higher total chemolithoautotrophy rate encountered in S1. Moreover, the peak in aclB gene abundance found in deeper sediment suggests that Epsilonproteobacteria could play an important role in sulfur oxidation in the deep-er suboxic zone in both stations. Clearly, a consortium could sustain the high rates of chemolith-oautotrophy throughout the suboxic zone. It has been speculated that chemolithoautotrophs use the cable bacteria as an electron sink in the absence of an electron acceptor like O2 or NO3
– in centimeter deep sediments (Vasquez-Cardenas et al., 2015). However the question still remains as to how the Gamma- and Epsilonproteobacteria are metabolically linked to the cable bacteria (Fig. 6).
In March, stations S1 and S3 also showed a higher contribution of fatty acids occurring in the sulfate reducing Deltaproteobacteria (Boschker et al., 2014; Taylor and Parkes, 1983; Webster et al., 2006) compared to the PLFA-SIP profiles in station S2 (Fig. 3b). Deltaproteobacteria such as Desulfobacterium autotrophicum and Desulfocapsa sp., as identified by 16S rRNA gene sequencing, are known to grow as chemolithoautotrophs by performing H2 oxidation or S0-disproportion-ation (Finster et al., 1998, Böttcher et al., 2005; Fig. 6), and are important contributors to the chemolithoautotrophic activity in coastal sediments (Boschker et al., 2014; Thomsen and Kris-tensen, 1997). However, a further identification of the chemolithoautotrophic Deltaproteobac-teria through the functional genes related to carbon fixation pathways was not performed in this study. Although it is known that autotrophic Deltaproteobacteria mainly use the reverse TCA cycle or the reductive acetyl-CoA pathway (Hügler and Sievert, 2011), further development of the functional gene approach, by designing specific primers is necessary to determine and clarify the diversity of Deltaproteobacteria involved in the chemolithoautotrophic activity.
Overall, we hypothesize that such a diverse assemblage of chemolithoautotrophic bacteria in the presence of cable bacteria is indicative of a complex niche partitioning between these sulfur-oxidizers (Gamma-, Epsilon-, and Deltaproteobacteria). In sulfidic marine sediments found in tidal and deep sea habitats, complex S0 niche partitioning have been proposed where uncultured sulfur-oxidizing Gammaproteobacteria mainly thrive on free sulfide, the epsilonproteobacterial Sulfurimonas/Sulfurovum group oxidizes elemental sulfur, and members of the deltaproteobacterial Desulfobulbaceae family may perform S0-disproportionation (Pjevac et al., 2014).
Nitrate-storing filamentous Beggiatoaceae Nitrate-storing filamentous Beggiatoaceae glide through the sediment transporting their electron acceptor (intracellular vacuoles filled with high concentrations of NO3
–) into deeper sediment
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and electron donor (intracellular granules of elemental sulfur) up to the surface, and in doing so, they oxidize free sulfide to sulfate in a two-step process that creates a wide suboxic zone (Seitaj et al., 2015; Mußmann et al., 2003; Sayama et al., 2005; Fig. 6). In March, the microsensor depth profiles at S2 (Fig. 1a) revealed a cm-thick suboxic zone with a subsurface pH minimum at the OPD followed by a pH maximum at SAD, which is the characteristic geochemical fingerprint of sulfur oxidation by nitrate-storing Beggiatoaceae (Seitaj et al., 2015; Sayama et al., 2005). At the same time, microscopy revealed high biovolumes of Beggiatoaceae that were uniformly distrib-uted throughout the suboxic zone (Fig. 1c), and more than half the filaments found were thicker than 15 μm indicating potential nitrate storage. Together these results corroborate the indica-tions of the dominant sulfur-oxidation mechanism suggested by the geochemical fingerprint.
The chemolithoautotrophy depth profile at S2 in March (Fig. 1b) recorded higher activities in the top 1 cm and chemolithoautotrophic activity penetrated down only to 2 cm (at the sulfide appearance depth). The similar depth distribution of Beggiatoaceae and chemolithoautotrophic activity suggests that dark CO2 fixation was primarily carried out by the nitrate-storing Beggia-toaceae. Beggiatoaceae can indeed grow as obligate or facultative chemolithoautotrophs de-pending on the strain (Hagen and Nelson DC, 1996). The PLFA-SIP analysis further supported chemolithoautotrophy by Beggiatoaceae as the PLFA patterns obtained at S2 resembled those of Beggiatoa mats encountered in sediments associated with gas hydrates (Zhang et al., 2005).
However, the CO2 fixation by Beggiatoaceae could be complemented by the activity of other chemolithoautotrophs. Beggiatoaceae have previously been reported to co-occur with chemo-lithoautotrophic nitrate-reducing and sulfur-oxidizing Epsilonproteobacteria (Sulfurovum and Sul-furimonas) in the deep sea Guyamas basin (Bowles et al., 2012). Interestingly, station S2 in March showed the highest abundance of aclB gene copies of all stations and seasons (Fig. 4b), and in addition, had the highest relative percentage of 16S rRNA gene read sequences assigned to the Epsilonproteobacteria (Fig. 2). Therefore, the dark CO2 fixation at station S2 is likely caused by both the motile, vacuolated Beggiatoaceae as well as the sulfur-oxidizing Epsilonproteobacteria. Yet, as was the case of the cable bacteria above, the metabolic link between Beggiatoaceae and the Epsilonproteobacteria remains currently unknown. However, it seems possible that internal-ly stored NO3
– is released into the sediment once Beggiatoa filaments lyse, allowing sulfur-oxida-tion with NO3
– by Epsilonproteobacteria.
5.4.3. Summer: Activity and diversity of chemolithoautotrophic bacteria In August, when the O2 levels in the bottom water decreased substantially, a third geochemi-cal regime was observed at all stations, which was different from the regimes associated with cable bacteria or nitrate-storing Beggiatoaceae. The microsensor profiling revealed an upward diffusive transport of free sulfide to the top millimeters of the sediment, which was produced in deeper sediment horizons through sulfate reduction (Fig. 1a). The uniform decrease in pH with depth is consistent with sediments dominated by sulfate reduction (Meysman et al., 2015). As noted above, the chemolithoautotrophy rates strongly decreased compared to March and were restricted to the very top of the sediment. Chemolithoautotrophic activity showed a close relation with the bottom water oxygen concentration. The number of gene copies of the two carbon fixation pathways investigated (CBB and rTCA) also decreased under hypoxic conditions (Fig. 4), suggesting a strong dependence of subsurface chemolithoautotrophy on the availability of oxygen in bottom waters.
127
Discussion/Conclusion
The highest chemolithoautotrophy rate was recorded at the shallower station (S3), which was the only station in August where O2 was found to diffusive into the sediment (Table 1), thus supporting aerobic sulfur oxidation at a shallow oxic-sulfidic interface in the sediment (Meysman et al., 2015). Several studies have shown that chemolithoautotrophy ceases in the absence of oxygen in the overlying water column (Vasquez-Cardenas et al., 2015; Miyatake, 2011; Thomsen and Kristensen, 1997). Such full anoxia occurred in the deepest station (S1), but still limited chemolithoautotrophic activity was recorded in the top layer of the sediment. A possible ex-planation is that some residual aerobic sulfur oxidizing bacteria were supported by the very low oxygen levels. Alternatively, cable bacteria activity at S1 in spring leads to a buildup of iron (hydr)oxides (FeOOH) in the top of the sediments, which prevents sulfide diffusion to the bottom water during summer anoxia (3H2S + 2FeOOH → 2FeS + S0 + 4H2O) (Seitaj et al., 2015). The elemental sulfur formed in this reaction may support chemolithoautotrophic sulfur dispropor-tionating bacteria (Finster et al., 1998). At station S2, Beggiatoaceae were found forming a mat at the sediment surface in S2 (Fig. 1b) and chemolithoautotrophy rates were limited to this mat (Fig. 6). Beggiatoaceae can survive hypoxic periods by using stored nitrate as electron acceptor (Schulz and Jørgensen, 2001), which is thought to be a competitive advantage that leads to their proliferation in autumn in S1 (Seitaj et al., 2015). Such survival strategies may be used to produce energy for maintenance rather than growth under hypoxic conditions which would in combina-tion with the low oxygen concentrations explain the low chemolithoautotrophy to biovolume ratio observed in S2 in August compared to March.
5.5. Conclusion Coastal sediments harbor a great potential for chemolithoautotrophic activity given the high anaerobic mineralization, which produce a large pool of reduced sulfur in these organic rich sediments. In this study, two environmental factors were identified to regulate the chemolith-oautotrophic activity in coastal sediments: seasonal hypoxia and the dominant sulfur oxidation mechanism. In sediments where oxygen, the main electron acceptor for chemolithoautotrophs, is depleted because of seasonal hypoxia, chemolithoautotrophy was strongly inhibited. In addi-tion, it is clear that the different sulfur oxidation mechanism (e.g. canonical sulfur oxidation, elec-trogenic sulfur oxidation, or sulfur oxidation mediated by vacuolated Beggiatoaceae) observed in the sediment also determine the magnitude and depth distribution of the dark CO2 fixation, as well as the chemolithoautotrophic bacterial community structure. The seasonal variations in electron acceptors and potentially reduced sulfur species suggest complex niche partitioning in the sediment by the sulfur-oxidizing bacterial community. An in depth study on the availability of different sulfur species in the sediment could shed light on the sulfur preferences by the dif-ferent bacterial groups. Likewise, the potential mechanism used to metabolically link filamentous sulfur-oxidizers and chemolithoautotrophic bacteria remains presently unresolved and requires further study. These tight metabolic relationships may ultimately regulate the cycling of sulfur, carbon and even nitrogen in coastal sediments, including (but not limited to) sediments affected by seasonal hypoxia.
Acknowledgments
We thankfully acknowledge the crew of the R/V Luctor (Peter Coomans and Marcel Kristalijn) and Pieter van Rijswijk for their help in the field during sediment collection, Marcel van der
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Meer and Sandra Heinzelmann for support onboard and assistance with incubations, Peter van Breugel and Marco Houtekamer for their assistance with stable isotope analysis, Elda Panoto for technical support and Alexandra Vasquez Cardenas for designing Figure 6. This work was finan-cially supported by several grants from Darwin Centre for Biogeosciences to HTSB (grant no: 3061), LV (grant no: 3062) and FJRM (grant no: 3092), FJRM received funding from the Euro-pean Research Council under the European Union’s Seventh Framework Program (FP7/2007–2013) via ERC grant agreement n°[306933], and RS received support from Danish Council for Independent Research-Natural Sciences.
129
Supplementary Material
Supplementary information
Experimental procedures
Aeration of 13C- incubations
To maintain the low oxygen levels found in August at S2 and S3, 30 ml of in situ overlying water was removed and cores were closed with rubber stoppers. Headspace was then flushed with N2 through a needle inserted between the core liner and the rubber stopper without disturbing the water surface. After several minutes, N2 flushing was stopped and 10 and 35% of the headspace was replaced with air using a syringe for S2 and S3, respectively. No air was added to S1 cores. All cores were gently mixed (0.2 rpm) on a shacking plate to homogenize oxygen concentration in headspace with those in overlying water. At the end of the experiment oxygen saturation in overlying water were verified with oxygen optodes (PreSens Fibox 3 LCD) obtaining anoxic conditions for S1 (0−4% air saturation), hypoxic for S2 (20−26%) and S3 (35−80%).
PLFA nomenclature The shorthand nomenclature used for phospholipid derived fatty acids is as follows. The num-ber before the colon indicates the number of carbon atoms, while the number after represents the number of double carbon bonds in the fatty acids chain. The position of the initial double bond is then indicated by the last number after the number of carbons from the methyl end (ω). The double bond geometry is designated by cis (c) or trans (t). Methyl branching is described as being in the second carbon iso (i), third carbon anteiso (a) or a number followed by Me is used to indicate the position relative to the carboxyl end (e.g. 10Me16:0). Further details can be found in the literature (Vestal and White, 1989).
PCR 16S rRNA gene amplicon library preparation and analysis PCR reactions were performed with the universal (Bacteria and Archaea) primers S-D-Arch-0519-a-S-15 (5’-CAG CMG CCG CGG TAA-3’) and S-D-Bact-0785-a-A-21 (5’-GAC TAC HVG GGT ATC TAA TCC-3’) (Klindworth et al., 2013) adapted for pyrosequencing by the ad-dition of sequencing adapters and multiplex identifier (MID) sequences. To minimize bias three independent PCR reactions were performed containing: 16.3 µL H2O, 6 µL HF Phusion buffer, 2.4 µL dNTP (25 mM), 1.5 µL forward and reverse primer (10 µM; each containing an unique MID tail), 0.5 µL Phusion Taq and 2 µL DNA (6 ng/µL). The PCR conditions were following: 98ºC, 30 s; 25 × [98ºC, 10 s; 53 ºC, 20 s; 72ºC, 30 s]; 72 ºC, 7 min and 4ºC, 5 min.
The PCR products were loaded on a 1% agarose gel and stained with SYBR® Safe (Life technologies, Netherlands). Bands were excised with a sterile scalpel and purified with Qiaquick Gel Extraction Kit (QIAGEN, Valencia, CA) following the manufacturer’s instructions. PCR purified products were quantified with Quant-iTTM PicoGreen® dsDNA Assay Kit (Life Tech-nologies, Netherlands). Equimolar concentrations of the barcoded PCR products were pooled and sequenced on GS FLX Titanium platform (454 Life Sciences) by Macrogen Inc. Korea.
Samples were analyzed using the QIIME pipeline (Caporaso et al., 2010). Raw sequences were demultiplexed and then quality-filtered with a minimum quality score of 25, length between 250−350, and allowing maximum two errors in the barcode sequence. Sequences were then clustered into operational taxonomic units (OTUs, 97% similarity) with UCLUST (Edgar, 2010). Reads were aligned to the Greengenes Core reference alignment (DeSantis et al., 2006) using
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the PyNAST algorithm (Caporaso et al., 2010). Taxonomy was assigned based on the Green-genes taxonomy and a Greengenes reference database (version 12_10) (McDonald et al., 2012; Werner et al., 2012). Representative OTU sequences assigned to the specific taxonomic groups were extracted through classify.seqs and get.lineage in Mothur (Schloss et al., 2009) by using the greengenes reference and taxonomy files.
In order to determine a more accurate taxonomic classification of the bacterial groups with high percentage of reads and known to contain members with chemolithoautotrophic metabo-lism, sequence reads of the order Chromatiales and Thiotrichales (Fig. S1, S2), reads of the order Desulfarculales (Fig. S3), the family of Desulfobulbaceae (Fig. S4a) and the genus Desulfubulbus (Fig. S4b), reads of the family Desulfobacteraceae (Fig. S5a–c), and additionally reads of the or-der Campylobacterales (Fig. S6a–d) were extracted from the dataset and added to a phylogenetic tree as described in the supplementary experimental procedures.
Quantification of cable bacteria and Beggiatoaceae Microscopic identification of cable bacteria was achieved by fluorescence in situ hybridization (FISH), using a Desulfobulbaceae-specific oligonucleotide probe (DSB706; 5′-ACC CGT ATT CCT CCC GAT-3′), according to (Schauer et al., 2014). Cable bacteria biovolume per unit of sediment volume (mm3 cm−3) was calculated based on measured filament length and diameter. The areal biovolume of cable bacteria (mm3 cm−2) was obtained by depth integration over all sediment layers analyzed.
The minimum limits of quantification via FISH for single cells were 1.5 × 106 cells cm−3, taken as the FISH count with the negative control probe NON338; a minimum of 1000 DAPI (4,6-diamidino-2-phenylindole) stained cells was evaluated for this count. The FISH detection limit for cable bacteria was lower than for single cells, and was calculated to be 10 cm filament cm−3 (corresponding to <1 filament in 0.1 mL of sediment).
Filamentous Beggiatoaceae were identified via inverted light microscopy (Olympus IM) within 24 h of sediment retrieval. Intact sediment cores were sectioned at 5 mm intervals over the top 4 cm from which subsamples (20−30 mg) were used to count living Beggiatoaceae (Seitaj et al., 2015). The biovolume was determined by measuring length and width of all filaments found in the subsample, following the counting procedure described in (Jørgensen et al., 2010).
Statistical analysis All statistical analyses were performed using the CRAN: stats package in the open source soft-ware R. A two-way ANOVA (aov) was used to test the effect of station, season, and sediment depth on bacterial biomass, chemolithoautotrophic activity, and gene abundances. PLFA con-centrations and 13C-incorporation values were expressed as a fraction of the total bacterial bio-mass and 13C-incorporation (respectively) per sediment sample. These relative PLFA values were first log-transformed (log (x+1)) and subsequently analyzed with Principal Component Analysis (PCA: prcomp) to distinguish different bacterial and chemolithoautotrophic communities in the sediment.
131
Supplementary Material
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AB681900, Granulosicoccus antarcticusEF495228, Granulosicoccus antarcticus, seawater
KC160719, Granulosicoccus sp. SS10.26, Antarctic sea sedimentFJ535355, Granulosicoccus coccoides, leaves of sea grass in Troitza Bay, Gulf of Peter the Great, Sea of Japan
GU451354, uncultured bacterium, macroalgal surfaceJF344155, uncultured gamma proteobacterium, petroleum spot over marine sediments from figueiras beach
ARB_EFBD0A28, denovo1856 GI2.1_972JX559163, uncultured bacterium, antarctic aerosol
FJ905714, uncultured bacterium, iron oxide sediments, Volcano 1, Tonga ArcGQ119472, uncultured proteobacterium
ARB_E6BF6C65, denovo119 GI1.1_2739Hq153883, uncultured bacterium, shallow hydrothermal vent 189.1 m
EU246808, uncultured gamma proteobacterium, Calcinus obscurus abdominal floraARB_5B178E07, denovo1043 GI1.1_895
JF344255, uncultured gamma proteobacterium, petroleum spot over marine sediments from figueiras beachEU050785, uncultured gamma proteobacterium, sediment from the Kings Bay, Svalbard, Arctic
GU234740, uncultured marine bacterium, Antarctic sea water collected from 5mARB_62B26A19, denovo3300 GII3.1_6302
AB099937, uncultured bacterium, inactive deep−sea hydrothermal vent chimneysDQ269113, uncultured gamma proteobacterium, surface of marine macro−alga
GQ274231, uncultured gamma proteobacterium, heat exchange system using biocides to inhibit biofilm formationARB_BB7219C4, denovo505 GII2.1_2624ARB_97A6CE1, denovo309 GI2.1_1401
EU491486, uncultured bacterium, seafloor lavas from Hawai’i South Point X4JN606989, uncultured bacterium, white microbial mat from lava tube wall
EU491392, uncultured bacterium, seafloor lavas from Hawai’i South Point X3JX226828, uncultured bacterium, nodule collected from station WS0904 in the Clarion−Clipperton Fracture Zone
EU287407, uncultured bacterium, arctic surface sedimentKC861163, uncultured bacteriumEU652530, uncultured bacterium, Yellow Sea sediment
ARB_6609E7D9, denovo1802 GI1.1_2332JF266091, uncultured bacterium, white microbial mat lava tube wall
HQ397072, uncultured gamma proteobacterium, haloalkaline soilJF344181, uncultured gamma proteobacterium, petroleum spot over marine sediments from figueiras beach
AB476263, uncultured bacterium, ventral setae of Shinkaia crosnieriARB_BBCD0639, denovo969 GI1.1_2370
Hq153957, uncultured bacterium, white filamentous microbial mat in the photic zone of a shallow hydrothermal ventEF092205, uncultured gamma proteobacterium
FR744557, uncultured bacterium, nitrate−amended injection water from the Halfdan oil fieldEU491601, uncultured bacterium, seafloor lavas from the East Pacific Rise
HQ379738, gamma proteobacterium S−1(2010)JX391088, uncultured bacterium, marine sediment
JF344304, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beachARB_9C00EB59, denovo1294 GII1.1_8935ARB_9C00EB59, denovo2723 GI1.1_3081
JF344362, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beachJF344419, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beach
JF344330, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beachJF344428, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beach
FM242303, uncultured gamma proteobacterium, sedimentAM176842, uncultured bacterium, mangrove sediment
HQ916536, uncultured bacterium, Lei−Gong−Huo mud volcanoAB278144, uncultured bacterium, obtained from Mariana Trough
HF558592, uncultured bacterium, tailing material
Chromatiales_
Granulosico
ccace
ae_Granulosico
ccus
0.05
DQ498828, Thiocapsa imhoffiiJX521203, uncultured bacterium, terrestrial sulfidic spring
AJ223235, Lamprocystis purpureaAJ006063, Lamprocystis roseopersicina
Y12366, Lamprocystis purpureaAb478670, uncultured Chromatiaceae bacterium, submerged biofilm mats wetland
DQ676347, uncultured gamma proteobacterium, suboxic freshwater−pond bacterioplanktonARBC01000182, Lamprocystis purpurea DSM 4197AJ006057, phototrophic bacterium
DQ676296, uncultured gamma proteobacterium, suboxic freshwater−pond bacterioplanktonFN396696, uncultured marine bacterium, Arctic marine surface sediment
ARB_DB9D716A, denovo836 GI3.1_1527Am882544, uncultured gamma proteobacterium, sediment from oil polluted water
ARB_3ED72159, denovo2717 GI2.1_4916ARB_4D38CEFC, denovo3368 GII2.1_10913
ARB_2E607D92, denovo759 GII1.1_1362
Lamprocystis
AJ831752, uncultured bacterium, chemoclineJX521262, uncultured bacterium, terrestrial sulfidic spring
AJ224430, Isochromatium buderi
uncultured 16
ARB_A2F14DB, denovo674 GII3.1_6959Jn479885, uncultured organism, Guerrero Negro Hypersaline Mat
Jn461133, uncultured organism, Guerrero Negro Hypersaline Mat ARB_528E7DEA, denovo59 GI1.1_4285
Jn450999, uncultured organism, Guerrero Negro Hypersaline Mat Jn458696, uncultured organism, Guerrero Negro Hypersaline Mat
Jn459399, uncultured organism, Guerrero Negro Hypersaline Mat DQ330804, uncultured proteobacterium, hypersaline microbial mat: Guerrero Negro
Jn469059, uncultured organism, Guerrero Negro Hypersaline Mat Am882535, uncultured gamma proteobacterium, sediment from oil polluted water
Am882566, uncultured gamma proteobacterium, sediment from oil polluted water DQ330805, uncultured proteobacterium, hypersaline microbial mat: Guerrero Negro
HQ877095, Lamprobacter modestohalophilusX93472, Halochromatium glycolicumX98597, Halochromatium salexigensAm283535, Halochromatium roseum
Haloch
romatium
KF799054, uncultured bacterium, gutARB_C9137E14, denovo4029 GII3.1_8926
KF513141, uncultured Thiohalocapsa sp., pink berry consortia from Sippewissett salt marshAVFP01004244, microbial mat metagenome, pink berry consortia of the Sippewissett salt marsh
Am491592, Thiohalocapsa marina
Thiohalocapsa
JQ738932, uncultured bacterium, Lonar sediment surface rocks
Chromatiales_Chromatiaceae
0.05
JX138882, uncultured bacterium, marine sedimentsJF809744, uncultured bacterium, Medea hypersaline basin, Mediterranean Sea
EU373841, uncultured gamma proteobacterium, canyon and slope sedimentARB_38DFA738, denovo886 GI3.1_648
JX138600, uncultured bacterium, marine sedimentsEU491667, uncultured bacterium, seafloor lavas from the East Pacific Rise
KC471275, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa TroughDQ289918, uncultured gamma proteobacterium, South Atlantic Bight Permeable Shelf Sediment
ARB_7A35AA84, denovo1280 GI1.1_178HE817849, uncultured bacterium, tissue of sponge Vaceletia crypta
ARB_D868D57F, denovo435 GI3.1_117GU119047, uncultured bacterium
FJ205275, uncultured gamma proteobacterium, active hydrothermal field sediments, depth:1922mJQ347472, uncultured bacterium, Da Ya Bay
ARB_C8883AA2, denovo18 GII3.1_3781ARB_120B20A, denovo2400 GII3.1_10467
ARB_B82136A6, denovo1971 GII2.1_2927ARB_639358B4, denovo3330 GII3.1_10833
ARB_B3D72EEA, denovo473 GI2.1_3560JQ062714, uncultured bacterium, sponge tissue
ARB_57D58DCA, denovo51 GI2.1_107ARB_83FE435B, denovo2355 GI3.1_549
FJ937838, uncultured gamma proteobacterium, coastal waters of Lingshui Bay of Hainan Island in the South China SeaFJ937834, uncultured bacterium, coastal waters of Lingshui Bay of Hainan Island in the South China Sea
JF344578, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beachARB_66261C8C, denovo2664 GII3.1_1805
EF208706, uncultured bacterium, sandy carbonate sedimentEU652575, uncultured bacterium, Yellow Sea sediment
KF741570, uncultured bacterium, Talbert salt marsh sedimentJF727679, uncultured gamma proteobacterium, petroleum−contaminated saline−alkali soilsJQ347371, uncultured bacterium, Da Ya Bay
ARB_C634BA31, denovo1128 GI3.1_3820ARB_9441BCE4, denovo1555 GII2.1_57GU118309, uncultured bacterium
JX280354, uncultured bacterium, marine spongeDQ513032, uncultured bacterium, ridge flank crustal fluid
FJ535071, uncultured gamma proteobacterium, cave wall biofilmAF317768, unidentified bacterium wb1_P19
EF125399, uncultured bacterium, naked tidal flat sediment near mangroveARB_37CE9830, denovo1458 GI1.1_565
FJ905747, uncultured bacterium, iron oxide sediments, Volcano 1, Tonga ArcFJ205285, uncultured gamma proteobacterium, active hydrothermal field sediments, depth:1922m
JF272102, uncultured bacterium, biofilmsGU061300, uncultured gamma proteobacterium, Yellow Sea intertidal beach seawater at 20 m depth
ARB_78A3E9B6, denovo818 GI1.1_1073JF344260, uncultured gamma proteobacterium, petroleum spot over marine sediments from figueiras beachHQ191094, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden Sea
ARB_8F2AAD3A, denovo1907 GI3.1_2023JQ579854, uncultured gamma proteobacterium, sediments from Figueiras BeachJF344662, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beach
GQ246358, uncultured bacterium, North Yellow Sea sedimentsDQ867047, uncultured bacterium, natural gas field
M96398, Nitrosococcus oceaniAY690336, Nitrosococcus oceani
AF508987, Nitrosococcus oceaniAF363287, Nitrosococcus oceani
CP000127, Nitrosococcus oceani ATCC 19707CP000127, Nitrosococcus oceani ATCC 19707AF508994, Nitrosococcus oceaniCP002086, Nitrosococcus watsonii C−113CP002086, Nitrosococcus watsonii C−113
CP001798, Nitrosococcus halophilus Nc 4AJ298727, Nitrosococcus oceaniCP001798, Nitrosococcus halophilus Nc 4
AJ298748, Nitrosococcus halophilusJX240761, uncultured proteobacterium, coastal soil
HF558562, uncultured bacterium, tailing material
Chromatia
les_
Chromatia
ceae_Nitroso
cocc
us
AM882518, uncultured gamma proteobacterium, sediment from oil polluted water from petrochemical treatment plantAF170421, sulfur−oxidizing bacterium OBII5
AJ810552, uncultured gamma proteobacterium, superficial sedimentsARB_334A7441, denovo4022 GII3.1_923
ARB_BB6DFFA9, denovo421 GI1.1_601ARB_516EEF6C, denovo342 GII3.1_5432
uncultured
DQ351800, uncultured gamma proteobacterium, marine sedimentsHQ191097, uncultured sediment bacterium, Dangast muddy intertidal sediment; German Wadden Sea
GQ246364, uncultured bacterium, North Yellow Sea sedimentsAF223297, uncultured gamma proteobacterium B2M28ARB_AB5216C3, denovo3247 GII2.1_612
AF223299, uncultured gamma proteobacterium B2M60JQ586305, uncultured bacterium, arctic marine sediment
HQ191062, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden SeaHQ191090, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden Sea
KF624106, uncultured bacterium, anoxic pyrite−particle colonization experiment, Janssand tidal flat, Wadden SeaAY193138, uncultured proteobacterium, marine sedimentDQ394966, uncultured gamma proteobacterium, harbor sediment
ARB_57253D3A, denovo1419 GI1.1_2310ARB_1DF4361C, denovo2934 GII2.1_7000
FJ545494, uncultured bacterium, North Yellow Sea sedimentGU061176, uncultured gamma proteobacterium, Yellow Sea intertidal beach surface seawater
EU491687, uncultured bacterium, seafloor lavas from the East Pacific RiseEU491530, uncultured bacterium, seafloor lavas from the East Pacific Rise
HQ191065, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden SeaFJ712412, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains, East Mediterranean Sea
AM889168, uncultured gamma proteobacterium, SedimentsFM211768, uncultured gamma proteobacterium, sediment of Bizerte lagoon
HQ191095, uncultured sediment bacterium, Dangast muddy intertidal sediment; German Wadden SeaKF799091, uncultured bacterium, gutHQ190975, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden SeaHQ190997, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden Sea
HF922366, uncultured bacterium, high pressure reactorHF922334, uncultured bacterium, high pressure reactor
KF624415, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden SeaEU491232, uncultured bacterium, seafloor lavas from the Loi’hi Seamount Pisces Peak X2
Gu369920, uncultured epsilon proteobacterium, white microbial film shallow hydrothermal vent ARB_97962E3E, denovo2892 GI3.1_431
DQ351779, uncultured gamma proteobacterium, marine sedimentsGU061213, uncultured gamma proteobacterium, Yellow Sea intertidal beach seawater at 5 m depth
JF344014, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from rodas beachDQ351744, uncultured gamma proteobacterium, marine sediments
ARB_9A36BE2D, denovo2926 GII3.1_4245Gu302450, uncultured bacterium, marine sediments (900 m water depth, Gulf of Mexico
EU491337, uncultured bacterium, seafloor lavas from Hawai’i South Point X3KC470886, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough
FJ416116, uncultured bacterium, sediment from station NEC5 in the Northern Bering SeaFN396751, uncultured marine bacterium, Arctic marine surface sediment
DQ351776, uncultured gamma proteobacterium, marine sedimentsJQ580264, uncultured gamma proteobacterium, sediments from Rodas Beach polluted with crude oil
FJ264585, uncultured bacterium, methane seep sedimentFJ358865, uncultured gamma proteobacterium, marine reef sandy sediment
ARB_B77AF6B7, denovo2435 GI1.1_1585JX504392, uncultured bacterium, oolitic sand
JF344659, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beachJX193397, uncultured bacterium, intertidal surface sediment
JF344391, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beachDQ395021, uncultured gamma proteobacterium, harbor sediment
ARB_781E2AD4, denovo2106 GI2.1_4886ARB_C0B550B5, denovo551 GII1.1_195ARB_C0B550B5, denovo1651 GI1.1_51
HQ203959, uncultured bacterium, seawaterFM211764, uncultured gamma proteobacterium, sediment of Bizerte lagoon
DQ351781, uncultured gamma proteobacterium, marine sedimentsARB_AD855E3B, denovo1086 GII3.1_4940ARB_42D76043, denovo2199 GI2.1_788
ARB_6192704D, denovo1940 GI2.1_2314AB530205, uncultured bacterium, marine sediment
GQ500735, uncultured bacterium, Charon’s Cascade, sandy clastic sedimentsHm598244, uncultured bacterium, surface sediment Xisha Trough, China Sea
ARB_754734E8, denovo507 GI2.1_2211EF999373, uncultured bacterium, Pearl River Estuary sediments at 22cm depth
DQ395015, uncultured gamma proteobacterium, harbor sedimentAM889166, uncultured gamma proteobacterium, Sediments
DQ395051, uncultured gamma proteobacterium, harbor sedimentJN977193, uncultured bacterium, Jiaozhao Bay sediment
JF344480, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beachDQ394926, uncultured gamma proteobacterium, harbor sediment
FJ545485, uncultured bacterium, North Yellow Sea sedimentGQ246283, uncultured bacterium, North Yellow Sea sedimentsAB530211, uncultured bacterium, marine sedimentGU230357, uncultured gamma proteobacterium, coastal sediment
JF344616, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beachAM889165, uncultured gamma proteobacterium, Sediments
JN977291, uncultured bacterium, Jiaozhao Bay sedimentAM889164, uncultured gamma proteobacterium, Sediments
DQ394995, uncultured gamma proteobacterium, harbor sedimentDQ395062, uncultured gamma proteobacterium, harbor sediment
KF463825, uncultured gamma proteobacterium, Marine coastal sedimentARB_800DD24B, denovo2123 GI1.1_1928GQ246321, uncultured bacterium, North Yellow Sea sediments
GU230358, uncultured gamma proteobacterium, coastal sedimentGU061255, uncultured gamma proteobacterium, Yellow Sea intertidal beach seawater at 5 m depth
GU061303, uncultured gamma proteobacterium, Yellow Sea intertidal beach seawater at 20 m depthJN038904, uncultured gamma proteobacterium, Chongxi wetland soil
FJ786140, uncultured bacterium, prawn farm sedimentARB_BA77D3F2, denovo1553 GII2.1_8765
ARB_E4ED143B, denovo942 GII2.1_8839ARB_136300C8, denovo2859 GI1.1_837
ARB_E7A49636, denovo132 GII2.1_1684ARB_5E12BDAE, denovo3289 GII3.1_10675
ARB_47DF8362, denovo147 GI2.1_4282ARB_429AAAE0, denovo1745 GI2.1_3679Am882524, uncultured gamma proteobacterium, sediment from oil polluted water
FJ416094, uncultured bacterium, sediment from station NEC5 in the Northern Bering SeaARB_2EDF208B, denovo2396 GII3.1_9109
ARB_87D422D8, denovo2963 GII3.1_3051ARB_BB3E52D1, denovo907 GI2.1_2633
ARB_65268B1C, denovo1635 GII2.1_5704AB722093, uncultured bacterium, subseafloor massive sulfide depositFn553610, uncultured sediment bacterium, Logatchev hydrothermal vent depth = 3224 m
ARB_82B8D5B4, denovo910 GI2.1_3635Fn553597, uncultured sediment bacterium, Logatchev hydrothermal vent 3224 m
EU491112, uncultured bacterium, seafloor lavas from the Loi’hi Seamount Pisces Peak X2FJ497654, uncultured gamma proteobacterium, Vailulu’u SeamountAB722101, uncultured bacterium, subseafloor massive sulfide deposit
ARB_F3CD46EB, denovo3941 GII2.1_7119AB294934, uncultured gamma proteobacterium, microbial mat at a shallow submarine hot spring
Fr670375, uncultured gamma proteobacterium, microbial mat from Eiffel Tower edifice in Lucky Strike EU652533, uncultured bacterium, Yellow Sea sediment
JN977309, uncultured bacterium, Jiaozhao Bay sedimentARB_6DE0F30B, denovo2739 GI3.1_126
EU330397, uncultured gamma proteobacterium, mangrove forest mudARB_910196BD, denovo1551 GI3.1_1932
Hq153920, uncultured bacterium, white microbial film shallow hydrothermal ventEU491810, uncultured bacterium, seafloor lavas from the East Pacific Rise
DQ431906, uncultured gamma proteobacterium, Gulf of Mexico sedimentHQ191077, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden Sea
GU061216, uncultured gamma proteobacterium, Yellow Sea intertidal beach seawater at 5 m depthARB_8B4C06BD, denovo3718 GII1.1_5285ARB_8B4C06BD, denovo1901 GI1.1_3043HQ588368, uncultured bacterium, Amsterdam mud volcano sedimentGQ246407, uncultured bacterium, North Yellow Sea sedimentsFJ497635, uncultured bacterium, Vailulu’u Seamount
Fj712561, uncultured bacterium, Kazan Mud VolcanoKc682690, uncultured bacterium, hydrothermal sulfide chimney, Lau Basin
EU491101, uncultured bacterium, seafloor lavas from the Loi’hi Seamount Pisces Peak X2Fj640811, uncultured bacterium, hydrothermal vent chimney Juan de Fuca Ridge 2267m
GQ903353, uncultured bacterium, ODP Hole 896A basalt crust formation fluidEF999348, uncultured bacterium, Pearl River Estuary sediments at 6cm depth
HQ003527, uncultured gamma proteobacterium, Carrizo shallow lake
Chromatia
les_
Ectothiorhodosp
irace
ae
0.05
Figure S1: Bacterial 16S rRNA gene amplicon sequences assigned to the class of Gammaproteobacteria, order: Chromatiales (black bold: sequences retrieved in this study and closest relatives).
133
Supplementary Material
AM176844, uncultured bacterium, mangrove sedimentHQ203915, uncultured bacterium, seawater
FJ497639, uncultured gamma proteobacterium, Vailulu’u SeamountARB_3553A2D9, denovo1695 GII2.1_1026
Fr670408, uncultured gamma proteobacterium, microbial mat from Eiffel Tower Lucky Strike vent area Ef687244, uncultured bacterium, iron−oxidizing mat, Chefren mud volcano
KC682859, uncultured bacterium, surface of a basalt collected from Kilo Moana vent field, Lau BasinAB476269, uncultured bacterium, ventral setae of Shinkaia crosnieriHq153952, uncultured bacterium, white filamentous microbial mat in the photic zone of a shallow hydrothermal vent
FJ787300, uncultured bacterium, gas hydrate sediments of the Kazan Mud Volcano, East Mediterranean SeaKF624162, uncultured bacterium, oxic pyrite−particle colonization experiment, Janssand tidal flat, Wadden Sea
HQ191073, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden SeaARB_9F2BCD1A, denovo2124 GI1.1_1929AB015250, uncultured gamma proteobacterium, deepest cold−seep area of the Japan Trench
ARB_27D9B048, denovo3381 GII3.1_4329Fn553471, uncultured sediment bacterium, Logatchev hydrothermal vent field,oceanic sediment
AB476207, uncultured bacterium, ventral setae of Shinkaia crosnieriAB476206, uncultured bacterium, ventral setae of Shinkaia crosnieriAB530202, uncultured bacterium, marine sediment
HQ191082, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden SeaAM882552, uncultured gamma proteobacterium, sediment from oil polluted water from petrochemical treatment plantKF624159, uncultured bacterium, oxic pyrite−particle colonization experiment, Janssand tidal flat, Wadden Sea
ARB_17F65DD9, denovo2929 GII1.1_4344ARB_17F65DD9, denovo1483 GI1.1_747
KF624231, uncultured bacterium, suboxic pyrite−particle colonization experiment, Janssand tidal flat, Wadden SeaJQ287244, uncultured bacterium, East Pacific RiseJQ287289, uncultured bacterium, East Pacific Rise
ARB_585E8CC4, denovo2756 GI3.1_2429FJ905708, uncultured bacterium, iron oxide sediments, Volcano 1, Tonga Arc
KF624156, uncultured bacterium, oxic pyrite−particle colonization experiment, Janssand tidal flat, Wadden SeaARB_83A518EC, denovo2486 GI1.1_92ARB_83A518EC, denovo1329 GII3.1_629
FJ205286, uncultured gamma proteobacterium, active hydrothermal field sediments, depth:1922mEf687482, uncultured bacterium, sediment underneath an iron−oxidizing mat, Chefren mud volcano
ARB_8F6B21AE, denovo413 GI1.1_285AM882574, uncultured gamma proteobacterium, sediment from oil polluted water from petrochemical treatment plant
FJ712538, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains, East Mediterranean SeaFn397820, uncultured gamma proteobacterium, GeoB 9072−1 anoxic sub−surface mud volcano
AJ535246, uncultured gamma proteobacterium, marine sediment above hydrate ridgeAM745138, uncultured gamma proteobacterium, marine sediments
Fn553607, uncultured sediment bacterium, Logatchev hydrothermal vent sediment at 3224 mAF154089, uncultured hydrocarbon seep bacterium BPC036FJ712588, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains, East Mediterranean Sea
ARB_71C0FE2D, denovo2398 GII3.1_2072ARB_DFAE6D84, denovo669 GI2.1_13
FJ264668, uncultured bacterium, methane seep sedimentJN977166, uncultured bacterium, Jiaozhao Bay sediment
EU652548, uncultured bacterium, Yellow Sea sedimentARB_1103BE8F, denovo1699 GI2.1_3700
ARB_2C6B48A0, denovo576 GI1.1_851ARB_40FFFC75, denovo472 GI1.1_1416
Hq153917, uncultured bacterium, white microbial film shallow hydrothermal ventHq153955, uncultured bacterium, white filamentous microbial mat shallow hydrothermal vent
ARB_97098AEA, denovo2230 GI2.1_1696HQ191071, uncultured sediment bacterium, Janssand intertidal sediment; German Wadden SeaEF644802, uncultured bacterium, MAR Logatchev hydrothermal vent system, 3000m water depth, sulfide sample
Jf344197, uncultured gamma proteobacterium, petroleum spot over marine sediments ARB_6C6887C4, denovo1420 GI1.1_961
KF268708, uncultured bacterium, marine sedimentJf344186, uncultured gamma proteobacterium, petroleum spot over marine sediments
AB271125, Oligobrachia mashikoi endosymbiont GAB271122, Oligobrachia mashikoi endosymbiont D
AB271124, Oligobrachia mashikoi endosymbiont FAB271120, Oligobrachia mashikoi endosymbiont B
AB252051, Oligobrachia mashikoi endosymbiont AEU491817, uncultured bacterium, seafloor lavas from the East Pacific Rise
JF344283, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beachJQ580274, uncultured gamma proteobacterium, sediments from Rodas Beach polluted with crude oil
Fn397817, uncultured gamma proteobacterium, GeoB 9072−1 anoxic sub−surface mud volcanoDQ925898, uncultured bacterium, hydrothermal vent chimneys of Guaymas Basin
AB476202, uncultured bacterium, ventral setae of Shinkaia crosnieriFn397818, uncultured gamma proteobacterium, GeoB 9072−1 anoxic sub−surface mud volcano
FJ497576, uncultured gamma proteobacterium, Vailulu’u SeamountFJ497611, uncultured gamma proteobacterium, Vailulu’u Seamount
FJ497565, uncultured gamma proteobacterium, Vailulu’u SeamountFJ497622, uncultured gamma proteobacterium, Vailulu’u Seamount
ARB_F1FB6017, denovo1531 GI2.1_1865ARB_BF291963, denovo1853 GII2.1_888
KF624239, uncultured bacterium, suboxic pyrite−particle colonization experiment, Janssand tidal flat, Wadden SeaARB_2B841FB1, denovo642 GI3.1_474
FJ712548, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains, East Mediterranean SeaFJ264584, uncultured bacterium, methane seep sediment
JF344299, uncultured gamma proteobacterium, hydrocarbon polluted marine sediments from figueiras beachFJ905702, uncultured bacterium, iron oxide sediments, Volcano 1, Tonga Arc
ARB_D102CB76, denovo2637 GI1.1_1578ARB_8C35E7C7, denovo309 GII3.1_11763
EU491119, uncultured bacterium, seafloor lavas from the Loi’hi Seamount Pisces Peak X2Fn553445, uncultured sediment bacterium, Logatchev hydrothermal vent field,oceanic sediment
JQ579946, uncultured gamma proteobacterium, sediments from Figueiras Beach
uncu
lture
d
JX559252, uncultured bacterium, antarctic aerosolARB_D18874D7, denovo1457 GI2.1_998ARB_D18874D7, denovo3229 GII2.1_12387
JX570601, endosymbiont of Ridgeia piscesaeKC682827, uncultured bacterium, surface of a basalt collected from Kilo Moana vent field, Lau Basin
Fr670405, uncultured gamma proteobacterium, microbial mat from Eiffel Tower Lucky Strike JQ200201, uncultured bacterium, seawater; next to dolphin Y
AB495251, Cocleimonas flava, marine molluskJn662081, uncultured gamma proteobacterium, particulate detritus
Eu107481, uncultured Leucothrix sp., Okinawa Trough at depth of 1309 metersAB476220, uncultured bacterium, ventral setae of Shinkaia crosnieri
EU555124, uncultured bacterium, Dudley hydrothermal vent
Cocle
imonas
Thio
tric
hale
s_T
hio
tric
hace
ae
0.05
AF532775, Candidatus Isobeggiatoa divolgata, marine sedimentAF532769, Candidatus Isobeggiatoa divolgata, Wadden Sea sedimentARB_D11B76E1, denovo3026 GII2.1_578ARB_D11B76E1, denovo976 GI2.1_627
AB108786, Candidatus Isobeggiatoa divolgata, marine sedimentARB_D764416C, denovo1446 GI2.1_519FJ875195, uncultured Beggiatoa sp., marine sediment underlying a salmon farm
FN561862, Candidatus Isobeggiatoa divolgata, marine sedimentAF532771, uncultured Beggiatoa sp., marine sediment
ARB_6BD95FAD, denovo1168 GI2.1_4524
Candidatus Isobeggiatoa
ARB_9D6DFEEE, denovo3057 GII2.1_5949AF532773, Candidatus Parabeggiatoa communis, marine sediment
AF532772, Candidatus Parabeggiatoa communis, marine sedimentARB_C4375616, denovo1726 GI1.1_3844
JN793555, uncultured Beggiatoa sp., hydrothermal seep at Guaymas BasinFJ875199, uncultured Beggiatoa sp., marine sediment underlying a salmon farm
Candidatus Parabeggiatoa
FR847872, Candidatus Halobeggiatoa sp. HMW−W562, white microbial matFr847873, Candidatus Halobeggiatoa sp. HMW−W572, white microbial matFR847870, Candidatus Halobeggiatoa sp. HMW−W520, white microbial mat
FR847871, Candidatus Halobeggiatoa sp. HMW−S2528, white microbial matARB_9D825299, denovo578 GI1.1_2396
FN811663, Thiomargarita namibiensis, sediment surfaceFr690927, Candidatus Thiomargarita nelsonii, sedimentFR690929, Candidatus Thiomargarita nelsonii, sediment
FR690966, Candidatus Thiomargarita nelsonii, sedimentFR690953, Candidatus Thiomargarita nelsonii, sediment T
hio
marg
arita
ARB_4BFED579, denovo1545 GII2.1_7825FR690945, Candidatus Thiomargarita nelsonii, sediment
FR690946, Candidatus Thiomargarita nelsonii, sedimentFR690961, Candidatus Thiomargarita nelsonii, sediment
ARB_330D7B34, denovo283 GII2.1_1879ARB_330D7B34, denovo347 GI2.1_475
FR690894, Thiomargarita namibiensis, sedimentFR827866, Thiomargarita namibiensis, intertidal mud flat
JN793554, uncultured Beggiatoa sp., hydrothermal seep at Guaymas BasinARB_9FCD4774, denovo879 GI3.1_3565
Thio
tric
hale
s_T
hio
tric
hace
ae
0.05Thio
marg
arita
Figure S2: Bacterial 16S rRNA gene amplicon sequences assigned to the class of Gammaproteobacte-ria, order: Thiotrichales, family: Thiotrichaceae (black bold: sequences retrieved in this study and closest relatives).
Chapter 5
134
EU592480, uncultured bacterium, hypersaline sedimentARB_7060483C, denovo2020 GI3.1_5100
GQ500708, uncultured bacterium, Charon’s Cascade, sandy clastic sedimentsFq658834, uncultured soil bacterium, PAH−contaminated soil
DQ137968, uncultured bacterium, wetlandARB_10DE197D, denovo40 GI2.1_3162FJ516989, uncultured Desulfobacteraceae bacterium, upper sediment
GU208294, uncultured prokaryote, Dongping Lake sedimentHM243855, uncultured bacterium, middle sediment from Honghu Lake
HQ003578, uncultured delta proteobacterium, Carrizo shallow lakeKF268888, uncultured bacterium, marine sediment
ARB_7004B897, denovo93 GII2.1_1855ARB_7004B897, denovo1972 GI3.1_386AB530221, uncultured bacterium, marine sediment
AB694469, uncultured bacterium, Deep−sea sediment at a depth 7111m.Jn511815, uncultured organism, Guerrero Negro Hypersaline Mat
Jn537626, uncultured organism, Guerrero Negro Hypersaline MatGQ246439, uncultured bacterium, North Yellow Sea sediments
ARB_6181BE0B, denovo348 GI1.1_2389FJ716464, uncultured bacterium, Frasassi cave system, anoxic lake water
ARB_8D6EA0F6, denovo3241 GII3.1_2770JQ925081, uncultured bacterium, cold seep sediment from oxygen mimimum zone in Pakistan Margin
JQ580439, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oilJN207182, uncultured delta proteobacterium, Namako−ike surface sediment (0−1 cm)
JQ036264, uncultured bacterium, Eel River Basin sediment 2688Gu302479, uncultured bacterium, marine sediments Mississippi CanyonHQ691991, uncultured delta proteobacterium, stratified lagoon
AF029045, benzene mineralizing consortium clone SB−21DQ394937, uncultured Desulfobacterium sp., harbor sediment
GQ246425, uncultured bacterium, North Yellow Sea sedimentsEF125430, uncultured bacterium, mangrove soilDQ811822, uncultured delta proteobacterium, mangrove soil
ARB_5BA65306, denovo2937 GI3.1_931ARB_7BD0700F, denovo1902 GII1.1_5946
FN396676, uncultured marine bacterium, Arctic marine surface sedimentARB_666D9846, denovo1315 GI2.1_3389
ARB_D6FD159, denovo3965 GII2.1_38FJ485073, uncultured delta proteobacterium, biomat in El Zacaton at 114m depthGu127072, uncultured delta proteobacterium, sediment; anoxic zone
DQ831550, uncultured delta proteobacterium, marine sedimentARB_D788D99F, denovo2296 GII3.1_7171
ARB_3535E826, denovo1384 GI2.1_3008HQ178897, uncultured bacterium, sediment treated with Mr. Frosty slow freeze method
Gu302445, uncultured bacterium, marine sediments Mississippi Canyon Jf344708, uncultured delta proteobacterium, hydrocarbon polluted marine sediments
GU362957, uncultured bacterium, marine sediment from the South China SeaARB_AB57ED2D, denovo1051 GII3.1_1604
JQ816986, uncultured bacterium, subseafloor sediment at the Good Weather RidgeDQ811813, uncultured delta proteobacterium, mangrove soil
ARB_8F5D807B, denovo60 GII3.1_7337KC470953, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough
Jn518898, uncultured organism, Guerrero Negro Hypersaline Mat DQ811811, uncultured delta proteobacterium, mangrove soil
EU385682, uncultured bacterium, subseafloor sediment of the South China SeaFJ628273, uncultured bacterium, brackish water from anoxic fjord Nitinat Lake at depth 50
AJ241002, uncultured delta proteobacterium Sva0516Jf344210, uncultured delta proteobacterium, petroleum spot over marine sediments
ARB_E20D5C9D, denovo188 GI1.1_278FJ437826, uncultured bacterium, Green Lake chemocline at 20.5 m water depth
AY216442, uncultured bacterium, temperate estuarine mudJQ580448, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil
ARB_4EA6FD94, denovo1367 GII1.1_529AJ430774, delta proteobacterium EbS7, sediment
ARB_A61B58E9, denovo3408 GII2.1_14147FJ437866, uncultured bacterium, Green Lake at 25 m water depth
ARB_A26C8AD9, denovo3152 GII2.1_5152HQ003580, uncultured delta proteobacterium, Carrizo shallow lake
HQ691995, uncultured delta proteobacterium, stratified lagoonJQ580482, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil
ARB_39E47D34, denovo2286 GI1.1_833Hm598151, uncultured bacterium, 1400 m depth surface sediment Xisha Trough, China Sea
ARB_F317CBC0, denovo1489 GII3.1_3131ARB_B01D0B7D, denovo988 GI3.1_3020
JF495321, uncultured bacterium, sediment from anoxic fjordAF154102, uncultured hydrocarbon seep bacterium GCA017
JQ580472, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oilARB_5B4D5DA9, denovo2879 GI1.1_2108
AY542227, uncultured delta proteobacterium, Gulf of Mexico seafloor sedimentsJQ580206, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil
ARB_56A14516, denovo843 GII2.1_2149ARB_56A14516, denovo558 GI2.1_1507
Jn534265, uncultured organism, Guerrero Negro Hypersaline MatJf344192, uncultured delta proteobacterium, petroleum spot over marine sediments
ARB_85297555, denovo2583 GI2.1_230Jn515097, uncultured organism, Guerrero Negro Hypersaline Mat
FJ484510, uncultured delta proteobacterium, wall biomat sample in El Zacaton at 53m depthARB_EA0946DA, denovo2630 GII2.1_2303
JQ817357, uncultured bacterium, subseafloor sediment at the Formosa RidgeJQ925098, uncultured bacterium, cold seep sediment from oxygen mimimum zone in Pakistan Margin
ARB_170270B2, denovo244 GII1.1_367HQ588498, uncultured bacterium, Amsterdam mud volcano sedimentJN977161, uncultured bacterium, Jiaozhao Bay sediment
HM231166, uncultured bacterium, coconut husk retting soilEU592498, uncultured bacterium, hypersaline sediment
HQ174924, uncultured bacterium, Cherokee Road Extension Blue HoleJQ816148, uncultured bacterium, subseafloor sediment at the Deep Basin
AM745154, uncultured delta proteobacterium, marine sedimentsJQ580310, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oilARB_68DB4272, denovo228 GII2.1_2567Jn518931, uncultured organism, Guerrero Negro Hypersaline Mat
FJ437756, uncultured bacterium, Green Lake chemocline at 20.5 m water depthAB630766, uncultured bacterium, aquatic moss pillarsFJ716322, uncultured bacterium, Sawmill Sink water column, at 10.3 m water depth
ARB_9AE7AD4E, denovo2234 GI1.1_2318ARB_364C0C47, denovo3678 GII1.1_6861ARB_5D22E99, denovo730 GI1.1_3588
AJ237601, Desulfobacterium aniliniDQ394914, uncultured Desulfobacterium sp., harbor sediment
AF121886, bacterium 2BP−6Ab763347, Desulfobacterium sp. DS, a river sediment contaminated chlorinated volatile organic compounds
GQ354966, uncultured delta proteobacterium, springFJ517129, uncultured Desulfobacteraceae bacterium, water
FJ516988, uncultured Desulfobacteraceae bacterium, upper sedimentHM066266, uncultured bacterium, Texas state well #DX 68−23−616A
JQ245553, uncultured bacterium, mud volcanoEU245563, uncultured organism, hypersaline microbial mat
Jn497298, uncultured organism, Guerrero Negro Hypersaline Mat ARB_1537C093, denovo32 GII3.1_1946
Jn529954, uncultured organism, Guerrero Negro Hypersaline Mat ARB_9B500F68, denovo614 GII3.1_2698
FR682646, uncultured delta proteobacterium, hydrothermal sedimentsFJ485020, uncultured delta proteobacterium, biomat in El Zacaton at 114m depthFJ485340, uncultured delta proteobacterium, wall biomat sample in El Zacaton at 273m depthJn532040, uncultured organism, Guerrero Negro Hypersaline Mat
ARB_E828CF31, denovo3306 GII3.1_6873FM164951, uncultured Desulfobacterium sp., hot spring
AF026998, unidentified delta proteobacterium OPB16EF205578, uncultured delta proteobacterium, geothermal spring mat
FR682638, uncultured delta proteobacterium, hydrothermal sediments
uncu
lture
d
DQ415831, uncultured bacterium, Frasassi sulfidic cave stream biofilmJN397733, uncultured bacterium, river bankARB_9F80C0F0, denovo460 GII2.1_6145
AJ576343, uncultured bacterium, hindgut homogenate of Pachnoda ephippiata larva
Desulfarculus
ARB_2EB6DECF, denovo3036 GII2.1_284ARB_2EB6DECF, denovo38 GI2.1_214
ARB_986F247C, denovo2054 GII3.1_553EU487879, uncultured bacterium, siliciclastic sedment from Thalassia sea grass bed
ARB_783FDF21, denovo1576 GII3.1_1060FM242399, uncultured delta proteobacterium, sediment
ARB_FA468FAA, denovo730 GII3.1_1182KF697533, uncultured bacterium, activated sludge from inclined plate membrane bioreactor
ARB_740BDBE3, denovo1219 GI1.1_1259
uncultured
De
sulfa
rcu
lale
s_D
esu
lfarc
ula
cea
e
0.05
Figure S3: Bacterial 16S rRNA gene amplicon sequences assigned to the class of Deltaproteobacteria, order: Desulfarculales (black bold: sequences retrieved in this study and closest relatives).
135
Supplementary Material
133 sequences (seq), uncultured bacteria, including 8 seq obtained by Pfeffer et al., 2012,and Lake Grevelingen surface sediments, August, station 3 (3 seq),Lake Grevelingen surface sediments, August, station 1 (1 seq)
85 seq, uncultured bacteria related to Desulforhopalus sp.,Lake Grevelingen surface sediments, March and August, station 1 (2 seq),Lake Grevelingen surface sediments, March and August, station 2 (2 seq)Lake Grevelingen surface sediments, August, station 3 (4 seq)
9 seq, uncultured bacteria, including Lake Grevelingen surface sediments, August, station 3 (2 seq)
12 seq, uncultured bacteria, including Lake Grevelingen surface sediments, August, station 3 (2 seq)
Am176855, uncultured bacterium, mangrove sediment
131 seq, uncultured Desulfopila sp.,including Lake Grevelingen surface sediments, March, station 1 (1 seq),Lake Grevelingen surface sediments, August, station 2 (1 seq), Lake Grevelingen surface sediments, August, station 3 (2 seq)
30 seq, uncultured bacteria related to Desulfotalea sp.,including Lake Grevelingen surface sediments, March, station 1 (1 seq),Lake Grevelingen surface sediments, August, station 3 (1 seq),
43 seq, uncultured bacteria (SEEP−SRB4),including Lake Grevelingen surface sediments, March and August, station 2 (2 seq),
2 seq, uncultured bacteria, sediments from Gulf of Mexico and Peru Margin
59 seq, uncultured bacteria,including Lake Grevelingen surface sediments, March, station 1 (1 seq) and 3 (2 seq),Lake Grevelingen surface sediments, August, station 2 (5 seq)
35 seq, uncultured bacteria related to Desulfofustis sp.
2 seq, uncultured bacteria
273 seq, uncultured bacteria related to Desulfocapsa sp.including Lake Grevelingen surface sediments, March, station 1 (1 seq) and 2 (2 seq),Lake Grevelingen surface sediments, August, station 2 (2 seq) and 3 (1 seq),
2 seq, uncultured bacteria, microbial mat and muddy salt marsh sediment
70 seq, uncultured bacteria related to Desulfocapsa sp.,including Lake Grevelingen surface sediments, March, station 1 (1 seq) and 2 (1 seq),Lake Grevelingen surface sediments, August, station 1 (1 seq)
14 seq, uncultured bacteria, including Lake Grevelingen surface sediments, August, station 2 (1 seq)
16 seq, uncultured bacteria, subsurface aquifer sediment and volcanic soil
Jx223964, uncultured bacterium, subsurface aquifer sediment
30 seq, uncultured bacteria, including 1 seq obtained by Pfeffer et al., 2012,Lake Grevelingen surface sediments, August, station 2 (1 seq) and station 3 (4 seq)
5 seq, uncultured bacteria,
2 seq, uncultured bacteria, subsurface aquifer sediments
6 seq, uncultured bacteria, including Lake Grevelingen surface sediments, March, station 1 (1 seq) and station 2 (1 seq), and August, station 2 (1 seq)
478 seq, uncultured bacteria related to Desulfobulbus sp.(see Desulfobulbus tree; following figure)
44 seq, uncultured bacteria related to Desulfurivibrio sp.
42 seq, uncultured bacteria, including 2 seq obtained by Malkin et al., 2014, 1 seq by Pfeffer et al., 2012, Lake Grevelingen surface sediments, March, station 1 (2 seq) and station 3 (2 seq),and August, station 2 (2 seq) and station 3 (2 seq)
7 seq, uncultured bacteria, including 5 seq obtained by Pfeffer et al., 2012
2 seq, uncultured bacterium, marine sediment (1 seq) and Lake Grevelingen surface sediments, August, station 3 (1 seq)
0.10
including Lake Grevelingen surface sediments, March and August, station 1 (2 seq)
De
sulfo
ba
cte
rale
s_D
esu
lfob
ulb
ace
ae
Figure S4a: Bacterial 16S rRNA gene amplicon sequences assigned to the class of Deltaproteobacteria, order: Desulfobacterales, family: Desulfobulbaceae (black bold: sequences retrieved in this study and clos-est relatives).
Chapter 5
136
group 1: 18 sequences uncultured bacteria
group 2: 7 sequences uncultured bacteria
group 3: 3 sequences uncultured bacteria
group 4: 24 sequences uncultured bacteria
Dq676284, uncultured delta proteobacterium, suboxic freshwater−pond sedimentCp002364, Desulfobulbus propionicus DSM 2032, freshwater mudAy548789, Desulfobulbus propionicusCp002364, Desulfobulbus propionicus DSM 2032, freshwater mud
Ay160859, uncultured bacterium, Cubitermes orthognathusAb189697, uncultured bacterium, Termes comis
Af482433, uncultured bacterium, granular sludgeX95180, Desulfobulbus elongatusDq831531, uncultured Desulfobulbus sp., brackish sedimentJq815615, uncultured Desulfobulbus sp., Tinto River sediment (extreme acid environment)
KF020725, Desulfomicrobium sp. enrichment culture clone LDC−, soilGq133652, uncultured bacterium, ASBR reactor treating swine waste
Eu104773, uncultured delta proteobacterium, anaerobic biofilm reactorGq138460, uncultured bacterium, ASBR reactor treating swine waste
Gq138956, uncultured bacterium, ASBR reactor treating swine wasteKC260892, uncultured bacterium, bottlenose dolphin mouthEu488160, uncultured bacterium, siliciclastic sediment from Thalassia sea grass bed
Hm069062, uncultured bacterium, sediment of Rupa LakeAb546247, Desulfobulbus rhabdoformis, sludge sample of crude−oil storage tankU12253, Desulfobulbus rhabdoformis
Ef442993, Desulfobulbus sp. DSM 2033Jn688053, Desulfobulbus sp. S4, microbial consortium enriched from mangrove soilHM750216, Desulfobulbus alkaliphilusAJ866934, Desulfobulbus mediterraneus, tidal flat sedimentEU142055, uncultured bacterium, methane seep sediment
AF354663, Desulfobulbus mediterraneusAUCW01000075, Desulfobulbus mediterraneus DSM 13871Eu528183, uncultured bacterium, sedimentAF099055, psychrophilic sulfate−reducing bacterium LSv55AM404380, uncultured delta proteobacterium, marine sedimentFj716980, uncultured bacterium, marine sediment from Cullercoats, Northumberland, United Kingdom Am882629, uncultured delta proteobacterium, sediment from oil polluted water from petrochemical treatment plantAb110550, Desulfobulbus japonicus, harbor sediment in JapanAB110549, Desulfobulbus japonicus, harbor sediment in Japan
U85473, Desulfobulbus sp. BG25JQ209390, uncultured bacterium, bottlenose dolphin mouthJQ211736, uncultured bacterium, bottlenose dolphin mouthJQ215032, uncultured bacterium, bottlenose dolphin mouth
Gq134058, uncultured bacterium, ASBR reactor treating swine wasteAB243815, uncultured bacterium, Niigata oil well
FJ792164, uncultured bacterium, carbonate chimney in Lost City Hydrothermal FieldFr853023, uncultured bacterium, active hydrothermal chimney, Juan de Fuca Ridge
Aj969450, uncultured delta proteobacterium, rock fragments, Rainbow, deep sea hydrothermal vent fieldFr852968, uncultured bacterium, active hydrothermal chimney, Dudley, Juan de Fuca Ridge
Fr853007, uncultured bacterium, active hydrothermal chimney, Dudley, Juan de Fuca RidgeAy672535, uncultured bacterium, hydrothermal vent, East Pacific Rise, Pacific OceanAy672502, uncultured bacterium, hydrothermal vent, East Pacific Rise, Pacific Ocean
AM404330, uncultured delta proteobacterium, marine sedimentAF420336, uncultured proteobacteriumAy592579, uncultured bacterium, Napoli mud volcano, Eastern Mediterranean, sediment layer 0−8 cmGU584659, uncultured bacterium, marine hydrocarbon seep sedimentJQ287080, uncultured bacterium, East Pacific RiseFj5746, uncultured bacterium, iron oxide sediments, Tonga Arc
EU555141, uncultured bacterium, Dudley hydrothermal ventLake Grevelingen surface sediments, March, station 3 AM268767, uncultured prokaryote, hot fluid vent, site Irina II
group 5: 6 sequences uncultured bacteria
Jn874112, uncultured bacterium, TrapR1, East Pacific RiseAY327886, uncultured delta proteobacterium, surface of vent snail footJn873947, uncultured bacterium, TrapR1, East Pacific Rise
Fr852967, uncultured bacterium, active hydrothermal chimney, Dudley, Juan de Fuca Ridge
group 6: 41 seq, mainly uncultured bacteria and 2 seq obtained by Pfeffer et al., 2012 (JX091042.2; JX091026.1)
Ay531563, uncultured bacterium, Indian Ocean hydrothermal ventAY531586, uncultured bacterium, Indian Ocean hydrothermal ventKc682614, uncultured bacterium, inactive hydrothermal sulfide chimney, Tui Malila vent field, Lau Basin
Lake Grevelingen surface sediments, August, station 3Lake Grevelingen surface sediments, August, station 3Lake Grevelingen surface sediments, August, station 3
JX224538, uncultured bacterium, subsurface aquifer sedimentJX225752, uncultured bacterium, subsurface aquifer sedimentJX225113, uncultured bacterium, subsurface aquifer sedimentLake Grevelingen surface sediments, March, station 3 Lake Grevelingen surface sediments, August, station 2
Lake Grevelingen surface sediments, March, station 1 KF624269, uncultured bacterium, anoxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea
Lake Grevelingen surface sediments, March, station 1 HM992531, uncultured Desulfobacteraceae bacterium, oil sands tailings settling basin
AB525452, uncultured bacterium, deep−sea methane seep sediment off Joetsu, Japan SeaFn554116, uncultured sediment bacterium, Logatchev hydrothermal vent field,Anya’s GardenJn662305, uncultured delta proteobacterium, particulate detritus, c tubeworm Ridgeia piscesae
Lake Grevelingen surface sediments, March, station 2 Lake Grevelingen surface sediments, August, station 3
HQ588389, uncultured bacterium, Amsterdam mud volcano sedimentHq153922, uncultured bacterium, white microbial film on pebble substrate in the aphotic zone of a shallow hydrothermal vent
group 7: 5 sequences uncultured bacteria, carbonate chimney in Lost City hydrothermal vent
Hq153967, uncultured bacterium, white filamentous microbial mat in the photic zone of a shallow hydrothermal ventKC682422, uncultured bacterium, substrate mineral chips
JF738104, uncultured bacterium, Lau Basin hydrothermal sulfide chimneyFR852988, uncultured bacterium, active hydrothermal chimney collected from the Dudley site of Juan de Fuca Ridge
group 8: 40 seq; including 17 seq obtained by Schauer et al., 2014; 11 seq by Pfeffer et al. 2012; 7 seq by Malkin et al., 2014; 4 seq uncultured bacteria obtained from marine sediment
JF268391, uncultured bacterium, Hikurangi margin, Wairarapa − Takahae, station 309; SO191_3_309Gu302481, uncultured bacterium, marine sediments (0−24 m sediment depth) from Mississippi Canyon 118, Gulf of Mexico
GU208270, uncultured prokaryote, Dongping Lake sedimentFQ658831, uncultured soil bacterium, PAH−contaminated soil; retention systems which treat road runoffs
group 9 : 59 sequences, including Lake Grevelingen surface sediments, i.e. 3 seq station 1, March; 1 seq station 1, August; 1 seq station 2, March; 2 seq station 2, August; 2 seq station 3, March; 3 seq station 3, August
FJ264588, uncultured bacterium, methane seep sedimentFJ712577, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains, East Mediterranean SeaFJ264787, uncultured bacterium, methane seep sedimentGU180162, uncultured bacterium, sediment and soil slurryHQ153843, uncultured bacterium, white microbial film on pebble substrate in the aphotic zone of a shallow hydrothermal vent, Volcano 1, South Tonga Arc at a depth of 189.1 m
group 10: 9 seq, uncultured bacteria, marine sediment
FJ358873, uncultured delta proteobacterium, marine reef sandy sedimentFR744613, uncultured bacterium, production water from the Halfdan oil fieldAj535237, uncultured delta proteobacterium, marine sediment above hydrate ridge
Lake Grevelingen surface sediments, August, station 2 JN256008, uncultured delta proteobacterium, surface of pereopod of new species of Yeti crab from mound 12JN662199, uncultured delta proteobacterium, particulate detritus collected from grabs of the vestimentiferan tubeworm Ridgeia piscesae in low−flow environmentAY355303, uncultured bacterium, epibiontic
group 11: 113 seq, including Lake Grevelingen surface sediments, i.e. 7 seq station 1, March; 6 seq station 2, March; 8 seq station 2, August; 1 seq station 3, March; 11 seq station 3, August
FJ813526, uncultured bacterium, marine sedimentLake Grevelingen surface sediments, August, station 2
KF596661, uncultured bacterium, soilFM179887, uncultured delta proteobacterium, marine sediments
AY771956, uncultured delta proteobacterium, marine surface sedimentHQ588373, uncultured bacterium, Amsterdam mud volcano sediment
Lake Grevelingen surface sediments, March, station 1 Lake Grevelingen surface sediments, August, station 2
JN977397, uncultured bacterium, Jiaozhao Bay sedimentDQ831546, uncultured delta proteobacterium, marine sedimentDQ831536, uncultured delta proteobacterium, freshwater sedimentLake Grevelingen surface sediments, August, station 3Lake Grevelingen surface sediments, March, station 2 Lake Grevelingen surface sediments, August, station 2 Lake Grevelingen surface sediments, March, station 1 HQ857627, uncultured delta proteobacterium, hydrocarbon contaminated saline alkaline soils
JN860370, uncultured Desulfobulbus sp., low temperature hydrothermal oxides at the South West Indian RidgeAB722257, uncultured bacterium, freshwater iron−rich microbial matAB754135, uncultured bacterium, lake waterHM141864, uncultured bacterium, in situ samplers incubated in the Mahomet aquifer
JX434192, uncultured bacterium, gold mine boreholeJX434246, uncultured bacterium, gold mine borehole
AB188785, uncultured Desulfobulbus sp., cold seep sedimentJF344301, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beach
Lake Grevelingen surface sediments, August, station 3Lake Grevelingen surface sediments, August, station 1
GQ246446, uncultured bacterium, North Yellow Sea sedimentsLake Grevelingen surface sediments, March, station 2 JN977170, uncultured bacterium, Jiaozhao Bay sedimentJN977290, uncultured bacterium, Jiaozhao Bay sedimentLake Grevelingen surface sediments, August, station 2
KC682706, uncultured bacterium, inner conduit of inactive hydrothermal sulfide chimney, ABE vent field, Lau BasinJQ287075, uncultured bacterium, East Pacific Rise
KC682691, uncultured bacterium, inner conduit of inactive hydrothermal sulfide chimney, ABE vent field, Lau BasinKC470997, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough
Lake Grevelingen surface sediments, August, station 3Lake Grevelingen surface sediments, March, station 3Lake Grevelingen surface sediments, August, station 3
AM882608, uncultured delta proteobacterium, sediment from oil polluted water from petrochemical treatment plantLake Grevelingen surface sediments, March, station 3
Lake Grevelingen surface sediments, March, station 1Lake Grevelingen surface sediments, August, station 3DQ833475, uncultured bacterium, sediment of Guanting ReservoirAB722237, uncultured bacterium, freshwater iron−rich microbial matAB754082, uncultured bacterium, lake waterAB240495, uncultured bacterium, PCR−derived sequence from root−tip (0 to 40 mm) of Phragmites at Sosei River in Sappro, Japan
group 12: 9 seq, uncultured bacteria, marine sediment, hydrothermal vents
Desulfobulb
us
0.1
Figure S4b: Bacterial 16S rRNA gene amplicon sequences assigned to the class of Deltaproteobacteria, order: Desulfobacterales, family: Desulfubulbaceae, genus: Desulfubulbus (black bold: sequences retrieved in this study and closest relatives).
137
Supplementary Material
Kc471241, uncultured bacterium, marine sediment Okinawa TroughARB_7212B3B6, denovo1556 GII2.1_787
AY771938, uncultured delta proteobacterium, marine surface sedimentJf344655, uncultured delta proteobacterium, hydrocarbon polluted marine sediments
Am882597, uncultured delta proteobacterium, sediment from oil polluted water Gu302441, uncultured bacterium, marine sediments Mississippi Canyon
Jf344367, uncultured delta proteobacterium, hydrocarbon polluted marine sediments Jf344621, uncultured delta proteobacterium, hydrocarbon polluted marine sediments Fn396669, uncultured marine bacterium, Arctic marine surface sediment
KF741562, uncultured bacterium, Talbert salt marsh sedimentJf344336, uncultured delta proteobacterium, hydrocarbon polluted marine sediments
AB250573, uncultured bacterium, microbial matGQ259292, uncultured bacterium, deep sedimentARB_9B5D30FB, denovo2586 GII3.1_7180
Jq580293, uncultured delta proteobacterium, sediments Rodas Beach with crude oilDQ394998, uncultured delta proteobacterium, harbor sediment
JQ586318, uncultured bacterium, arctic marine sedimentFN600637, Olavius sp. associated proteobacterium Delta 1
Jf344583, uncultured delta proteobacterium, hydrocarbon polluted marine sediments ARB_E4F47108, denovo2691 GI3.1_2447
DQ831553, uncultured Desulfosarcina sp., marine sedimentARB_3BDC7AF5, denovo1926 GI3.1_5119
JQ579984, uncultured delta proteobacterium, sediments from Figueiras BeachFJ264667, uncultured bacterium, methane seep sediment
ARB_E6ACD753, denovo1584 GII3.1_4528AY222311, uncultured delta proteobacterium, host hindgut caecum
Am882638, uncultured delta proteobacterium, sediment from oil polluted water AXXK01000236, delta proteobacterium PSCGC 5451
ARB_AFCDBB4E, denovo2464 GI1.1_733EU925915, uncultured bacterium, sediment from station DBS1, northern Bering Sea
ARB_527A343A, denovo125 GII3.1_1095ARB_CFF4FC25, denovo2734 GII3.1_1621
ARB_5666EC06, denovo2457 GII3.1_1313ARB_35A5F4CB, denovo3527 GII3.1_3458
ARB_60341410, denovo2446 GII2.1_510ARB_7E58A22C, denovo1560 GI2.1_4724
Jf344664, uncultured delta proteobacterium, hydrocarbon polluted marine sediments DQ395018, uncultured delta proteobacterium, harbor sediment
AASZ01000534, metagenome, gutless worms collected in the Mediterranean SeaAJ620511, Olavius crassitunicatus delta−proteobacterial endo, marine sedimentJq580141, uncultured delta proteobacterium, sediments from Rodas Beach crude oil
FJ786116, uncultured bacterium, prawn farm sedimentARB_64DE2518, denovo1514 GI1.1_1793
JQ586291, uncultured bacterium, arctic marine sedimentARB_2308CAA0, denovo1932 GI1.1_3278
ARB_92BF177B, denovo3292 GII3.1_5475ARB_8199C09B, denovo1844 GII3.1_1277
Jf344447, uncultured delta proteobacterium, hydrocarbon polluted marine sediments ARB_21640F45, denovo2946 GII2.1_7360
ARB_B959CA3E, denovo1101 GI3.1_326AXXL01000032, delta proteobacterium PSCGC 5342
KC470928, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa TroughJf344436, uncultured delta proteobacterium, hydrocarbon polluted marine sediments ARB_2375B3D7, denovo2041 GII2.1_1621ARB_2375B3D7, denovo2116 GI1.1_1921
FM242225, uncultured delta proteobacterium, sedimentARB_DCA38B18, denovo2024 GII2.1_3527
AM040123, uncultured delta proteobacterium, sandy sedimentsARB_BAC5426A, denovo3444 GII2.1_5360
Jn495286, uncultured organism, Guerrero Negro Hypersaline Mat Jf344372, uncultured delta proteobacterium, hydrocarbon polluted marine sediments
ARB_70856E3C, denovo2194 GI2.1_783Jf344690, uncultured delta proteobacterium, hydrocarbon polluted marine sediments
FN396636, uncultured marine bacterium, Arctic marine surface sedimentJf344696, uncultured delta proteobacterium, hydrocarbon polluted marine sediments
ARB_44DC591A, denovo2386 GI2.1_2938ARB_35BFAC0E, denovo1701 GI2.1_3256
GQ472418, uncultured bacterium, lake sedimentFJ516927, uncultured Desulfobacteraceae bacterium, upper sediment
FJ716475, uncultured bacterium, Frasassi cave system, anoxic lake waterGU208253, uncultured prokaryote, Dongping Lake sediment
GU208215, uncultured prokaryote, Dongping Lake sedimentFj485545, uncultured delta proteobacterium, wall biomat sample in El Zacaton
AJ620510, Olavius crassitunicatus delta−proteobacterial endo, marine sedimentJQ712425, uncultured delta proteobacterium, hydrothermal vent fluids
ARB_2FDA25E1, denovo2589 GII3.1_649ARB_923AE546, denovo3737 GII2.1_1274
ARB_5F670FDF, denovo3450 GII2.1_2063Fm165241, uncultured bacterium, tubeworm Lamellibrachia sp. from cold seeps
ARB_B59ABBF4, denovo2404 GII2.1_6581ARB_BBF73459, denovo2912 GI1.1_3098
ARB_4DE6ABCD, denovo560 GII3.1_3361EF125388, uncultured bacterium, naked tidal flat sediment near mangrove
JF428822, uncultured delta proteobacterium, zero water exchange shrimp pond sedimentGQ246372, uncultured bacterium, North Yellow Sea sediments
Jf344682, uncultured delta proteobacterium, hydrocarbon polluted marine sedimentsARB_8BA374D8, denovo1060 GII2.1_1391ARB_8BA374D8, denovo1625 GI1.1_2788
EF999398, uncultured bacterium, Pearl River Estuary sediments at 50cm depthARB_17225923, denovo35 GI1.1_4513
JX221943, uncultured bacterium, subsurface aquifer sedimentJX225840, uncultured bacterium, subsurface aquifer sediment
ARB_7896FCD9, denovo3335 GII3.1_131HQ697836, uncultured bacterium, hydrocarbon contaminated saline−alkali soil
JX240710, uncultured delta proteobacterium, coastal soilGU289732, Desulfonatronobacter acidivorans, soda lake
Desulfonatronobacter
Jf268373, uncultured bacterium, Hikurangi marginAJ704684, uncultured delta proteobacterium, marine sediment
ARB_242A7D9D, denovo1494 GII1.1_2254ARB_F85668AB, denovo305 GII3.1_161
ARB_222F3CA4, denovo584 GII3.1_2561ARB_3E5AFB8D, denovo1509 GII3.1_3622
ARB_3367F4DF, denovo977 GII3.1_2082ARB_242A7D9D, denovo2742 GI1.1_1973
ARB_5F9B7D1E, denovo1873 GII3.1_5804ARB_46062F0A, denovo791 GI3.1_1456
ARB_8C59A6BA, denovo1742 GII3.1_2529GU291339, uncultured bacterium, acid mine drainage contaminated salt marsh sedimentsFJ497421, uncultured delta proteobacterium, Vailulu’u Seamount
ARB_F6791D49, denovo1990 GII3.1_998DQ394951, uncultured delta proteobacterium, harbor sediment
Hq405625, bacterium enrichment culture clone AOM−SR−B8, enrichment anaerobic oxidation of methaneAM176871, uncultured bacterium, mangrove sediment
GQ259270, uncultured bacterium, deep sedimentAJ704683, uncultured delta proteobacterium, marine sediment
ARB_579A7566, denovo2160 GI2.1_3055ARB_42D72CEA, denovo486 GI2.1_275
Fn554099, uncultured sediment bacterium, Logatchev hydrothermal vent HQ691980, uncultured delta proteobacterium, stratified lagoon
ARB_B5B2E1EF, denovo1135 GI2.1_2083ARB_42D72CEA, denovo1053 GII1.1_751
HM141895, uncultured bacterium, in situ samplers incubated in the Mahomet aquiferARB_3B3150E, denovo2691 GII3.1_3664
HQ174942, uncultured bacterium, Cherokee Road Extension Blue HoleARB_70290A1B, denovo94 GI2.1_1300
ARB_4B1EF6D, denovo1731 GI2.1_342ARB_DBAFDA21, denovo2860 GII2.1_5120
ARB_A6EACD9, denovo1419 GII3.1_8756ARB_128F1521, denovo1842 GII2.1_12592
FM242223, uncultured delta proteobacterium, sedimentAm882554, uncultured gamma proteobacterium, sediment from oil polluted water
ARB_E2F92A82, denovo2276 GI1.1_1174Am882618, uncultured delta proteobacterium, sediment from oil polluted water
ARB_61BA32E3, denovo2873 GI3.1_134ARB_39A85234, denovo716 GII3.1_1509
ARB_E2B4FFB0, denovo287 GII2.1_10006Am882636, uncultured delta proteobacterium, sediment from oil polluted water
ARB_768D549B, denovo2723 GII3.1_9116ARB_ED8C662E, denovo3475 GII2.1_540
ARB_F56DA353, denovo3774 GII2.1_8690ARB_942E6C15, denovo717 GII3.1_5336
DQ394899, uncultured delta proteobacterium, harbor sedimentARB_1C79E7C1, denovo123 GII3.1_4596
ARB_97748389, denovo525 GI2.1_2980ARB_87BD5B07, denovo2143 GII3.1_1826
EU542429, uncultured bacterium, sediment and soil slurryHQ190518, uncultured bacterium, Zhongyuan oil fieldAm882592, uncultured delta proteobacterium, sediment from oil polluted water
Jn539400, uncultured organism, Guerrero Negro Hypersaline Mat ARB_40933119, denovo1876 GI1.1_500ARB_40933119, denovo411 GII1.1_601
AB530178, uncultured bacterium, marine sedimentAm882593, uncultured delta proteobacterium, sediment from oil polluted water
uncu
lture
d
AY851292, Algorimarina butyricaARB_C3823A0C, denovo2233 GII3.1_11024
ARB_62175954, denovo1151 GII1.1_5521ARB_62175954, denovo639 GI1.1_635
Jn493110, uncultured organism, Guerrero Negro Hypersaline Mat Jn509712, uncultured organism, Guerrero Negro Hypersaline Mat
FJ813564, uncultured bacterium, marine sedimentJn533073, uncultured organism, Guerrero Negro Hypersaline Mat
Jq580317, uncultured delta proteobacterium, sediments from Rodas Beach crude oilJf344658, uncultured delta proteobacterium, hydrocarbon polluted marine sedimentsARB_AB025D00, denovo2174 GII3.1_2112
FJ517135, uncultured Desulfobacteraceae bacterium, waterJf344433, uncultured delta proteobacterium, hydrocarbon polluted marine sediments
DQ811834, uncultured delta proteobacterium, mangrove soilDQ811835, uncultured delta proteobacterium, mangrove soil
FJ873366, uncultured bacterium, sediments from the Okhotsk SeaARB_2B982B23, denovo78 GII3.1_1891
EU488132, uncultured bacterium, siliciclastic sedment from Thalassia sea grass bedEU385712, uncultured bacterium, subseafloor sediment of the South China Sea
Ab177130, uncultured bacterium, ethane hydrate bearing subseafloor sediment at the Peru margin ARB_8376DD2A, denovo2689 GII2.1_12013
FN820322, uncultured bacterium, marine sediment, mud volcanoJN977360, uncultured bacterium, Jiaozhao Bay sedimentGQ357013, uncultured bacterium, methane seep sediment
ARB_609A165E, denovo1706 GII3.1_4850ARB_276A6BD5, denovo3922 GII3.1_9884
EU181465, uncultured bacterium, marine sedimentsGU982811, uncultured bacterium, marine sediment from the Western Pacific Ocean
JX138851, uncultured delta proteobacterium, marine sedimentsARB_A42CEBFC, denovo210 GI2.1_484JQ817421, uncultured bacterium, subseafloor sediment at the Formosa Ridge
JF495316, uncultured bacterium, sediment from anoxic fjordARB_CA3EC558, denovo365 GII2.1_11472
GU553724, uncultured bacterium, subseafloor sediment at the Yung−An RidgeARB_D98560D6, denovo3652 GII2.1_1870
JN469616, uncultured organism, Guerrero Negro Hypersaline Mat Jn495515, uncultured organism, Guerrero Negro Hypersaline Mat
Fj416106, uncultured bacterium, sediment fNorthern Bering SeaARB_F2527D65, denovo2119 GII3.1_5230
EU287209, uncultured bacterium, arctic surface sedimentARB_ACA31ABA, denovo1320 GI1.1_4519
AY771936, uncultured delta proteobacterium, marine surface sedimentARB_FC6CBA6, denovo2741 GI1.1_105ARB_7F8C1CB7, denovo3949 GII2.1_7114
ARB_47DE09C, denovo2094 GII3.1_9138DQ811820, uncultured delta proteobacterium, mangrove soilFN396758, uncultured marine bacterium, Arctic marine surface sediment
KF624243, uncultured bacterium, suboxic pyrite−particle colonization experiment, Janssand tidal flat, Wadden SeaARB_DECA4E83, denovo514 GI1.1_1612
ARB_21531FCD, denovo1023 GI1.1_2208HM245653, uncultured bacterium, pockmark sediments
DQ811797, uncultured delta proteobacterium, mangrove soilARB_5498C7B, denovo1552 GI2.1_1268
ARB_F96C7440, denovo3157 GII2.1_2571JF344653, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beachFJ716454, uncultured bacterium, Frasassi cave system, anoxic lake water
JF344629, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beachEU266854, uncultured delta proteobacterium, tar−oil contaminated aquifer sediments
AM882620, uncultured delta proteobacterium, sediment from oil polluted water from petrochemical treatment plantARB_89F1B619, denovo3034 GII3.1_5660
Jn533825, uncultured organism, Guerrero Negro Hypersaline Mat ARB_C183B8DF, denovo1811 GII3.1_3650
ARB_F53E48CB, denovo1126 GI3.1_3827ARB_F53E48CB, denovo2039 GII1.1_3417
KF741416, uncultured bacterium, Talbert salt marsh sedimentARB_BC7F083C, denovo345 GI2.1_712
KC358194, uncultured bacterium, large−discharge carbonate springsHQ691983, uncultured delta proteobacterium, stratified lagoon
AM404371, uncultured delta proteobacterium, marine sedimentJQ580124, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oilARB_FBF16789, denovo2108 GII3.1_2264ARB_FBF16789, denovo2361 GI2.1_1158
EU048693, uncultured bacterium, marine sediment, South Slope, South China SeaARB_49159E95, denovo2425 GII3.1_9745
GQ261770, uncultured delta proteobacterium, deep sea sediment associated with whale fallsARB_8ADD6B04, denovo2164 GII3.1_4296ARB_857E05F1, denovo1899 GII2.1_12697
EU652612, uncultured bacterium, Yellow Sea sedimentGQ348508, uncultured delta proteobacterium, Saanich Inlet, 200 m depth
EU386062, uncultured bacterium, subseafloor sediment of the South China SeaJf344630, uncultured delta proteobacterium, hydrocarbon polluted marine sediments
FJ517136, uncultured Desulfobacteraceae bacterium, waterARB_AF14643E, denovo783 GII1.1_4238
ARB_88ACEA80, denovo2073 GI3.1_2120ARB_24074B89, denovo2258 GII3.1_4875
EU488487, uncultured bacterium, siliciclastic sedment from Thalassia sea grass bedDQ811826, uncultured delta proteobacterium, mangrove soil
Jn506728, uncultured organism, Guerrero Negro Hypersaline Mat JN512076, uncultured organism, Guerrero Negro Hypersaline Mat
Jn535830, uncultured organism, Guerrero Negro Hypersaline Mat ARB_C0585716, denovo1150 GII2.1_2398
ARB_6DECB96F, denovo1068 GII2.1_4639FJ746161, uncultured bacterium, ocean sediment, 5306 m water depth, during Cruise Knox02rrAB858610, uncultured bacterium, subseafloor massive sulfide deposit
ARB_11D292FD, denovo839 GII1.1_186Jn449287, uncultured organism, Guerrero Negro Hypersaline Mat
Jn461602, uncultured organism, Guerrero Negro Hypersaline Mat ARB_BC1B7B7C, denovo2903 GII1.1_4184
ARB_DE50BAE, denovo2728 GII2.1_7574ARB_E97A75AA, denovo3575 GII3.1_6200
JN672650, uncultured bacterium, surface layer sediment of the East China seaARB_8D6E9E8D, denovo264 GII2.1_2368
EU246034, uncultured organism, hypersaline microbial matAJ620501, Olavius ilvae Delta 3 endosymbiont, marine sediment
JQ580056, uncultured delta proteobacterium, sediments from Figueiras BeachARB_3CB8B01, denovo822 GII2.1_5065AM493254, Olavius algarvensis associated proteobacterium Del, marine sediment
ARB_3A6149F0, denovo438 GI1.1_1942AB188777, uncultured delta proteobacterium, cold seep sediment
ARB_53E34389, denovo597 GI2.1_641ARB_BEC97052, denovo2382 GI2.1_1911
ARB_5769CAF9, denovo1696 GII2.1_8379Fr853018, uncultured bacterium, active hydrothermal chimney Juan de Fuca Ridge
Fn553934, uncultured sediment bacterium, Logatchev hydrothermal vent fieldFJ535333, uncultured bacterium, sediment
ARB_7EEB8DA1, denovo1999 GI2.1_157ARB_BD08D4DA, denovo2785 GII2.1_4055ARB_7171ABDD, denovo2495 GI3.1_1328AM889193, uncultured delta proteobacterium, Sediments
Jn860325, uncultured Desulfobacteraceae bacterium, low temperature hydrothermal oxides South West Indian RidgeAJ535249, uncultured delta proteobacterium, marine sediment above hydrate ridge
ARB_F2B93C6B, denovo3181 GII3.1_3701ARB_742457D2, denovo3235 GII3.1_3463
Gu302438, uncultured bacterium, marine sediments Mississippi CanyonARB_EC6D159F, denovo3009 GII2.1_4940
ARB_86E2CFD9, denovo1535 GI2.1_196HQ588558, uncultured bacterium, Amsterdam mud volcano sediment
FN820295, uncultured bacterium, marine sediment, mud volcanoFn421323, uncultured delta proteobacterium, marine sediments
ARB_EC6B3962, denovo1757 GII3.1_527ARB_1132C70D, denovo666 GII3.1_2969
JF344558, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beachFJ712476, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains, East Mediterranean Sea
JQ036271, uncultured bacterium, Hydrate Ridge carbonate 2518JF344483, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beach
HQ588578, uncultured bacterium, Amsterdam mud volcano sedimentARB_47DF84C1, denovo133 GI2.1_1635ARB_47DF84C1, denovo1667 GII3.1_7440
JF344359, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beachHQ003583, uncultured Desulfobacteraceae bacterium, Carrizo shallow lake
JQ816993, uncultured bacterium, subseafloor sediment at the Good Weather RidgeFJ716406, uncultured bacterium, Frasassi cave system, anoxic lake water
EU385687, uncultured bacterium, subseafloor sediment of the South China Sea
SE
EP
−S
RB
1
Jn474717, uncultured organism, Guerrero Negro Hypersaline Mat ARB_FCD1073C, denovo1850 GII3.1_2677DQ154853, uncultured bacterium, hypersaline microbial mat
HM141837, uncultured bacterium, in situ samplers incubated in the Mahomet aquiferJQ580445, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil
ARB_C2FCF446, denovo1290 GII2.1_8359ARB_DFC45A49, denovo1961 GI3.1_4202AJ937690, uncultured bacterium, mud from a terrestrial volcano
Hq622295, bacterium enrichment culture clone Oil_45, polluted estuarine sediment PalestineCp000859, Desulfococcus oleovorans Hxd3
FJ712452, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains, East Mediterranean SeaARB_DE12A1A0, denovo106 GII3.1_8455
ARB_8A60CE22, denovo2792 GI2.1_115ARB_9DAF10FF, denovo1830 GI2.1_2003
Jn427089, uncultured organism, Guerrero Negro Hypersaline MatJn513553, uncultured organism, Guerrero Negro Hypersaline Mat
ARB_EE004B84, denovo1007 GII1.1_6352ARB_B4C116D9, denovo2961 GII1.1_74
Ay592356, uncultured bacterium, Amsterdam mud volcano, Eastern MediterraneanDQ395063, uncultured delta proteobacterium, harbor sediment
ARB_565A6172, denovo168 GI1.1_583ARB_715AC8A9, denovo1506 GII3.1_5149
ARB_A58971EA, denovo1416 GI3.1_1406ARB_E30E2486, denovo2288 GII3.1_7373
Jf344183, uncultured delta proteobacterium, petroleum spot over marine sediments from AJ241022, uncultured delta proteobacterium Sva0405DQ394892, uncultured delta proteobacterium, harbor sediment
KF741487, uncultured bacterium, Talbert salt marsh sedimentAF286034, saltmarsh clone LCP−80
AM176857, uncultured bacterium, mangrove sedimentARB_231AEC8D, denovo1538 GII1.1_7681ARB_2DE56776, denovo1282 GII3.1_6573
ARB_26FE5501, denovo1968 GII3.1_510EU488125, uncultured bacterium, siliciclastic sedment from Thalassia sea grass bed
JF344657, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beachARB_2CB6E1DA, denovo2662 GII2.1_13512ARB_DC9284AB, denovo3677 GII3.1_10827
ARB_8D032F64, denovo159 GII1.1_1709ARB_E5FB189, denovo22 GI2.1_3017
ARB_890E687C, denovo491 GII3.1_7669ARB_9BF6A65E, denovo1751 GI2.1_3671
ARB_809B64D8, denovo303 GII2.1_13944ARB_7CA9BAA1, denovo1264 GII2.1_466
ARB_9B8D811B, denovo3373 GII1.1_2350ARB_F5D39F51, denovo89 GII3.1_2169
FJ264783, uncultured bacterium, methane seep sedimentDQ831539, uncultured delta proteobacterium, marine sedimentAM745163, uncultured delta proteobacterium, marine sediments
JF344689, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beachEU290703, uncultured bacterium, sediment 4−6cm depth
JF344569, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beachAB530218, uncultured bacterium, marine sediment
EU592471, uncultured bacterium, hypersaline sedimentJQ580328, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil
JF344202, uncultured delta proteobacterium, petroleum spot over marine sediments from figueiras beachFJ712547, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains, East Mediterranean Sea
Desu
lfoco
ccus
ARB_A55FD4F6, denovo374 GI2.1_643JQ580337, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil
JF344676, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beachAy592214, uncultured bacterium, Kazan mud volcano, Eastern Mediterranean
GU553709, uncultured bacterium, subseafloor sediment at the Yung−An RidgeJQ816985, uncultured bacterium, subseafloor sediment at the Good Weather RidgeJQ580267, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil
ARB_ED592767, denovo91 GII2.1_7106JQ580366, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oilAy592199, uncultured bacterium, Kazan mud volcano, Eastern Mediterranean
ARB_180B36CB, denovo816 GI3.1_1982Hq405618, bacterium enrichment culture clone AOM−SR−B34, enrichment anaerobic oxidation of methane
FJ813588, uncultured bacterium, marine sedimentFN820352, uncultured bacterium, marine sediment, mud volcano
FN820349, uncultured bacterium, marine sediment, mud volcanoFN820318, uncultured bacterium, marine sediment, mud volcano
AF354163, uncultured delta proteobacterium, marine methane seepAJ535248, uncultured delta proteobacterium, marine sediment above hydrate ridge
JQ580408, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oilFn553961, uncultured sediment bacterium, Logatchev hydrothermal vent field
Fm165265, uncultured bacterium, chitineous tube of the vestimentiferan tubeworm Lamellibrachia sp. JQ580515, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oilHQ711383, uncultured delta proteobacterium, marine sediment
uncu
lture
d
JQ925093, uncultured bacterium, cold seep sediment from oxygen mimimum zone in Pakistan MarginARB_AC5CC84B, denovo3507 GII3.1_47
ARB_D2CDF56A, denovo3569 GII3.1_1966JF428850, uncultured bacterium, zero water exchange shrimp pond sediment
Desulfosarcina
Figure S5a: Bacterial 16S rRNA gene amplicon sequences assigned to in the class of Deltaproteobac-teria, order: Desulfobacterales, family: Desulfobacteraceae (black bold: sequences retrieved in this study and closest relatives).
Chapter 5
138
GU584771, uncultured bacterium, marine hydrocarbon seep sedimentFM242377, uncultured delta proteobacterium, sediment
ARB_7BB7CC2B, denovo1528 GI2.1_1861ARB_D1E9F9BC, denovo1688 GII2.1_1597
ARB_A0038697, denovo3562 GII3.1_6063ARB_18096835, denovo477 GII3.1_5967ARB_20167A57, denovo1173 GI1.1_1953
ARB_6E8E107, denovo1703 GII1.1_5238ARB_D0A2A25A, denovo3037 GII3.1_8560
He648188, uncultured delta proteobacterium, mercury contaminated sedimentsARB_DC50913D, denovo2564 GI2.1_308
AY177788, uncultured Desulfosarcina sp., Antarctic sedimentARB_1A22C78C, denovo2306 GII3.1_8988KF741381, uncultured bacterium, Talbert salt marsh sediment
AM745205, uncultured delta proteobacterium, marine sedimentsAJ237603, Desulfosarcina cetonicaHE797782, uncultured bacterium, anoxic brackish photosynthetic biofilms
M34407, Desulfosarcina variabilisM26632, Desulfosarcina variabilisFJ516893, uncultured Desulfobacteraceae bacterium, upper sediment
Y17286, Desulfosarcina ovataAB587702, delta proteobacterium 28bB2TJn532272, uncultured organism, Guerrero Negro Hypersaline Mat
FM242231, uncultured delta proteobacterium, sedimentARB_F37E9CA4, denovo1201 GII3.1_9072ARB_713AB900, denovo1352 GII2.1_5864
FN396663, uncultured marine bacterium, Arctic marine surface sedimentARB_CB5BEF9B, denovo2020 GII2.1_2856
JQ214259, uncultured bacterium, bottlenose dolphin mouthARB_2B785AAB, denovo3244 GII3.1_1828
EU290724, uncultured bacterium, sediment 4−6cm depthJQ215139, uncultured bacterium, bottlenose dolphin mouth
ARB_8D28BB07, denovo302 GI2.1_5299Am882600, uncultured delta proteobacterium, sediment from oil polluted water
De
sulfo
sarc
ina
ARB_48683D96, denovo1131 GI2.1_2394ARB_48683D96, denovo432 GII2.1_7718
Jf344673, uncultured delta proteobacterium, hydrocarbon polluted marine sediments ARB_DCF3EA7D, denovo3912 GII3.1_6692ARB_902EB904, denovo2089 GI1.1_200ARB_9896FE39, denovo774 GII2.1_5886
Jf344442, uncultured delta proteobacterium, hydrocarbon polluted marine sediments DQ630712, uncultured delta proteobacterium, salt marshARB_E400D27A, denovo2526 GI2.1_3217
KF925363, Candidatus Magnetananas sp. Rongcheng CityHq857738, Candidatus Magnetananas tsingtaoensis
ARB_8B4B91B, denovo1795 GII1.1_3318ARB_AB672D1F, denovo4081 GII1.1_4099
ARB_A41502C5, denovo1324 GI1.1_3580Jn438841, uncultured organism, Guerrero Negro Hypersaline Mat
ARB_B521EEA2, denovo1656 GII2.1_1288ARB_E0A88F1, denovo2036 GI3.1_1767
ARB_E0DCFAF3, denovo1979 GI2.1_798ARB_DBAEF3D1, denovo2878 GII2.1_13288
Jn484364, uncultured organism, Guerrero Negro Hypersaline Mat JN463006, uncultured organism, Guerrero Negro Hypersaline Mat
Jn482322, uncultured organism, Guerrero Negro Hypersaline Mat Ef077226, uncultured delta proteobacterium, Gulf of Mexico, gas seep sedimen
HQ588478, uncultured bacterium, Amsterdam mud volcano sedimentFR823373, uncultured delta proteobacterium, associated sedimentFR823363, uncultured delta proteobacterium, gas seep sediment
AXAM01000010, Desulfosarcina sp. BuS5HG513093, uncultured delta proteobacterium, marine sediments
ARB_5888730, denovo1188 GII3.1_10608ARB_F0E82616, denovo420 GII2.1_2648
FR823364, uncultured delta proteobacterium, gas seep sedimentEU570889, uncultured bacterium, Nitinat Lake at a depth of 50 m
ARB_3CE6694D, denovo1374 GI2.1_1017ARB_92706565, denovo2432 GII2.1_422
ARB_B99B5F84, denovo2534 GII2.1_1677Jn520563, uncultured organism, Guerrero Negro Hypersaline Mat Jn528692, uncultured organism, Guerrero Negro Hypersaline Mat
ARB_4101ED26, denovo1240 GI3.1_2030ARB_E852A741, denovo3862 GII2.1_3081AB630474, uncultured bacterium, aquatic moss pillars
Fj712404, uncultured bacterium, Kazan Mud Volcano, Anaximander MountainsKF268892, uncultured bacterium, marine sediment
AJ620497, Olavius algarvensis Delta 4 endosymbiont, marine sedimentFj712498, uncultured bacterium, Kazan Mud Volcano, Anaximander Mountains,
Jn387434, uncultured microorganism, Zodletone spring sedimentARB_28682B51, denovo2197 GI2.1_784
Am882623, uncultured delta proteobacterium, sediment from oil polluted water ARB_76C9EFC4, denovo149 GII1.1_819ARB_76C9EFC4, denovo2253 GI2.1_1760
ARB_8FFDF050, denovo208 GII3.1_7256ARB_19CA1269, denovo3467 GII3.1_7023
JF344320, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beachARB_87AB5B4E, denovo1028 GII3.1_1044
ARB_C029BEB9, denovo2068 GII3.1_3423JF344560, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beach
ARB_85F032BD, denovo3750 GII2.1_1454ARB_DF16678C, denovo386 GII3.1_11802
FR823365, uncultured delta proteobacterium, gas seep sedimentFR823374, uncultured delta proteobacterium, associated sediment
JQ580521, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oilFM242228, uncultured delta proteobacterium, sediment
JN387432, uncultured microorganism, Zodletone spring source sedimentEU290686, uncultured bacterium, sediment 10−12cm depth
FJ802207, denitrifying bacterium enrichment culture clone NO, Ebro River Delta sedimentARB_C7FB7BD3, denovo4038 GII2.1_5507
FJ802214, denitrifying bacterium enrichment culture clone NO, Ebro River Delta sedimentAB630477, uncultured bacterium, aquatic moss pillarsKC662297, uncultured bacterium, shrimp sediment
EU266914, uncultured Desulfobacteraceae bacterium, tar−oil contaminated aquifer sedimentsDQ146482, Desulfatirhabdium butyrativoransAUCU01000039, Desulfatirhabdium butyrativorans DSM 18734
ARB_34FBA2FC, denovo2748 GII3.1_5675ARB_1216BFC8, denovo523 GII3.1_10002
ARB_FC4CC3BF, denovo1568 GII3.1_8534ARB_C45E6319, denovo1783 GII3.1_3436
Jf344627, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from figueiras beachARB_D6AA1912, denovo1579 GI2.1_4294
ARB_B02A7801, denovo3004 GII3.1_6642FJ485367, uncultured delta proteobacterium, wall biomat sample in El Zacaton at 273m depth
ARB_D7DF1E65, denovo183 GII3.1_662ARB_3B67EA53, denovo1846 GI1.1_44
FJ502253, uncultured bacterium, Lake Cadagno chemocline; 12.5mKF741543, uncultured bacterium, Talbert salt marsh sediment
JF268407, uncultured bacterium, Hikurangi margin, Wairarapa − Takahae, station 309; SO191_3_309ARB_118B74EC, denovo680 GII2.1_440
HQ174906, uncultured bacterium, Cherokee Road Extension Blue HoleJf344612, uncultured delta proteobacterium, hydrocarbon polluted marine sediments
JX504502, uncultured bacterium, oolitic sandAB530220, uncultured bacterium, marine sediment
KF596671, uncultured bacterium, soilARB_19855F1B, denovo18 GI2.1_3831
AM086163, uncultured bacterium, lake profundal sediment
De
sulfa
tirh
ab
diu
m
Jn446846, uncultured organism, Guerrero Negro Hypersaline Mat Jn455820, uncultured organism, Guerrero Negro Hypersaline Mat
Gu302437, uncultured bacterium, marine sediments Mississippi Canyon ARB_566A0BD4, denovo661 GII3.1_2960
ARB_D9F5669B, denovo10 GI2.1_3947ARB_7581FAA0, denovo3528 GII1.1_2970
ARB_4D3AC268, denovo1169 GI2.1_1067FM242402, uncultured delta proteobacterium, sediment
Am882622, uncultured delta proteobacterium, sediment from oil polluted water FM242376, uncultured delta proteobacterium, sediment
Am882604, uncultured delta proteobacterium, sediment from oil polluted water AJ237607, Desulfobacterium indolicum
FJ813595, uncultured bacterium, marine sedimentARB_3A7EB538, denovo512 GII3.1_4964
HQ178881, uncultured bacterium, sediment treated with Mr. Frosty slow freeze methodFQ659849, uncultured soil bacterium, PAH−contaminated soil; retention systems which treat road runoffs
EU385675, uncultured bacterium, subseafloor sediment of the South China SeaAY851291, Algidimarina propionicaGQ356960, uncultured bacterium, methane seep sediment
De
sulfo
ba
cte
riu
m
ARB_69CF1588, denovo3217 GII2.1_765ARB_4D5BC411, denovo2235 GII1.1_8125EF125422, uncultured bacterium, mangrove soil
JN038987, uncultured delta proteobacterium, Chongxi wetland soilDQ811793, uncultured delta proteobacterium, mangrove soil
DQ811836, uncultured delta proteobacterium, mangrove soilAY216453, uncultured bacterium, temperate estuarine mud
ARB_E9C88F6B, denovo45 GII2.1_6638ARB_B6B3A7A9, denovo3493 GII1.1_310
JX222415, uncultured bacterium, subsurface aquifer sedimentARB_A67B6D71, denovo2403 GII3.1_10460
ARB_6E5ADDED, denovo3435 GII2.1_1449ARB_6E5ADDED, denovo408 GI3.1_2254
EU290687, uncultured bacterium, sediment 10−12cm depthARB_BF175B5A, denovo2686 GII1.1_64Jn521333, uncultured organism, Guerrero Negro Hypersaline Mat
ARB_4BCB9692, denovo2286 GII1.1_1807ARB_1C9EAE25, denovo1438 GII3.1_1
AM745219, uncultured delta proteobacterium, marine sedimentsARB_B8B5FD8, denovo1541 GII2.1_6936
ARB_EC4D5ED7, denovo1034 GII3.1_1420ARB_5FE96A7F, denovo1725 GII3.1_11421AB121109, uncultured delta proteobacterium, cold seep sediment
ARB_8270E60B, denovo4084 GII2.1_2351ARB_EA29AB53, denovo1053 GI2.1_3353
JX222455, uncultured bacterium, subsurface aquifer sedimentEF999346, uncultured bacterium, Pearl River Estuary sediments at 6cm depth
Jn530486, uncultured organism, Guerrero Negro Hypersaline Mat ARB_E9534EC3, denovo248 GI2.1_3488
Am882642, uncultured delta proteobacterium, sediment from oil polluted water ARB_2869D04F, denovo1318 GII3.1_720
JQ245689, uncultured bacterium, mud volcanoDQ811807, uncultured delta proteobacterium, mangrove soil
JQ516448, uncultured Desulfobacteraceae bacterium, healthy tissueARB_350E391, denovo2371 GI2.1_3686
JQ739023, uncultured bacterium, Lonar sediment surface rocksAF177428, delta proteobacterium S2551
AB614135, Desulfatitalea tepidiphila, tidal flat sedimentJQ245513, uncultured bacterium, mud volcano
Desulfatitalea
AY222313, uncultured delta proteobacterium, host hindgut caecumDQ004679, uncultured bacterium, marine hydrocarbon seep sedimentARB_7FED19F4, denovo57 GII1.1_2044Jn662198, uncultured delta proteobacterium, tubeworm Ridgeia piscesae in low−flow environment
Jn442364, uncultured organism, Guerrero Negro Hypersaline Mat ARB_D6DE1887, denovo2591 GII2.1_5313
Jn451747, uncultured organism, Guerrero Negro Hypersaline Mat Jn456653, uncultured organism, Guerrero Negro Hypersaline Mat
ARB_67DDF75D, denovo1296 GII1.1_1741Jn438994, uncultured organism, Guerrero Negro Hypersaline Mat
JN511301, uncultured organism, Guerrero Negro Hypersaline Mat Jn522159, uncultured organism, Guerrero Negro Hypersaline Mat Jn451253, uncultured organism, Guerrero Negro Hypersaline Mat
Jn453804, uncultured organism, Guerrero Negro Hypersaline Mat JN450823, uncultured organism, Guerrero Negro Hypersaline Mat
JN534382, uncultured organism, Guerrero Negro Hypersaline Mat Jn501880, uncultured organism, Guerrero Negro Hypersaline Mat
ARB_1CA67942, denovo3200 GII1.1_9293Jn451179, uncultured organism, Guerrero Negro Hypersaline Mat
ARB_3AE4005F, denovo2475 GII3.1_4668ARB_FF2383AD, denovo2345 GII3.1_2479
ARB_54481FDD, denovo2635 GII2.1_3097Jn459735, uncultured organism, Guerrero Negro Hypersaline Mat
Jn454132, uncultured organism, Guerrero Negro Hypersaline Mat Jn510800, uncultured organism, Guerrero Negro Hypersaline Mat
Fj712416, uncultured bacterium, Kazan Mud Volcano, Anaximander MountainsARB_4C2031DA, denovo1511 GI3.1_613
Jn522209, uncultured organism, Guerrero Negro Hypersaline MatJN452209, uncultured organism, Guerrero Negro Hypersaline Mat
ARB_2EB5FAA4, denovo2738 GII3.1_6817Jn458684, uncultured organism, Guerrero Negro Hypersaline Mat
Jn459841, uncultured organism, Guerrero Negro Hypersaline Mat JN450773, uncultured organism, Guerrero Negro Hypersaline Mat
Jn442849, uncultured organism, Guerrero Negro Hypersaline Mat Jn450721, uncultured organism, Guerrero Negro Hypersaline Mat
JN460649, uncultured organism, Guerrero Negro Hypersaline Mat U45991, Desulfonema ishimotoniiU45992, Desulfonema ishimotoniiARB_A7DF0EB4, denovo3805 GII3.1_11577
JQ036269, uncultured bacterium, Eel River Basin sediment 2688ARB_1DFD6BEC, denovo952 GII1.1_2275
JN038818, uncultured delta proteobacterium, Chongxi wetland soilJX521572, uncultured bacterium, terrestrial sulfidic spring
Jn440228, uncultured organism, Guerrero Negro Hypersaline Mat ARB_D6FCA9F0, denovo1736 GII3.1_2524
ARB_85BA90CD, denovo2250 GI1.1_2008ARB_85BA90CD, denovo400 GII2.1_7007
U45990, Desulfonema limicolaARB_782235F9, denovo3920 GII2.1_7847
JQ215065, uncultured bacterium, bottlenose dolphin mouth
De
sulfo
ne
ma
ARB_14DE0EB5, denovo764 GII3.1_1091FJ814756, uncultured Desulfobacterales bacterium, Carmel Canyon
ARB_EB7F7EB9, denovo37 GII1.1_11048U45989, Desulfonema magnum
ARB_138F9ACC, denovo158 GII2.1_13064ARB_860FB93E, denovo844 GII3.1_3379
Jn485046, uncultured organism, Guerrero Negro Hypersaline Mat ARB_CD61D4ED, denovo1166 GII1.1_241ARB_CD61D4ED, denovo2718 GI1.1_256
ARB_82AEB832, denovo3766 GII3.1_7784Jn432947, uncultured organism, Guerrero Negro Hypersaline Mat Jn436445, uncultured organism, Guerrero Negro Hypersaline Mat
ARB_86F3D39D, denovo1322 GII3.1_5031Am882643, uncultured delta proteobacterium, sediment from oil polluted water Jn470593, uncultured organism, Guerrero Negro Hypersaline Mat
ARB_3847EEB8, denovo1986 GI1.1_4326ARB_385A98C2, denovo944 GII2.1_698
JX224716, uncultured bacterium, subsurface aquifer sedimentJX224719, uncultured bacterium, subsurface aquifer sediment
ARB_F6EFB277, denovo1388 GII3.1_8824ARB_1B95CE8A, denovo1016 GII3.1_5381
AM882627, uncultured delta proteobacterium, sediment from oil polluted water ARB_7BDF5E2E, denovo3523 GII3.1_3456
ARB_C4BDFDE5, denovo667 GI3.1_271ARB_9709B744, denovo2912 GII3.1_10066
ARB_B470EE51, denovo659 GII3.1_2742ARB_61518FF, denovo3305 GII3.1_9312
ARB_4E1BBC63, denovo1224 GI2.1_837JX223505, uncultured bacterium, subsurface aquifer sediment
AB237683, uncultured bacterium, deep subsurface groundwater from sedimentary rock milieuJX222865, uncultured bacterium, subsurface aquifer sediment
JX225750, uncultured bacterium, subsurface aquifer sedimentARB_8DA8F9E5, denovo433 GI2.1_3360
AB355075, uncultured bacterium, sediment, Manzallah LakeEf999366, uncultured bacterium, Pearl River Estuary sediments
DQ415752, uncultured bacterium, Frasassi sulfidic cave stream biofilmARB_7E558345, denovo924 GII3.1_3115
ARB_BC245D35, denovo1031 GII3.1_2710Fq659033, uncultured soil bacterium, PAH−contaminated soil
ARB_EA44E0C5, denovo1195 GI1.1_2747ARB_77B1D6BD, denovo1947 GII2.1_1107
ARB_F9FC6349, denovo1840 GII3.1_9728ARB_369D1854, denovo601 GI1.1_2578
FJ516891, uncultured Desulfobacteraceae bacterium, upper sedimentARB_D0E35DBE, denovo1637 GII2.1_5707
AB525467, uncultured bacterium, deep−sea methane seep sediment off Joetsu, Japan SeaJN454071, uncultured organism, Guerrero Negro Hypersaline Mat
ARB_7CB39937, denovo3870 GII2.1_5347Jn486306, uncultured organism, Guerrero Negro Hypersaline Mat
Jn443588, uncultured organism, Guerrero Negro Hypersaline Mat Cu925954, uncultured bacterium, mesophilic anaerobic digester wastewater sludge
ARB_A049BE09, denovo1909 GII3.1_1493ARB_E0A335A9, denovo2058 GI2.1_966
AF154058, Eubostrichus dianae epibacterium 2_25DQ415749, uncultured bacterium, Frasassi sulfidic cave stream biofilm
EU246060, uncultured organism, hypersaline microbial matARB_8F55C3F4, denovo2751 GII2.1_6026
DQ415820, uncultured bacterium, Frasassi sulfidic cave stream biofilmDQ133938, uncultured bacterium, limestone−corroding stream biofilm
DQ415847, uncultured bacterium, Frasassi sulfidic cave stream biofilmJn537551, uncultured organism, Guerrero Negro Hypersaline Mat Jn512532, uncultured organism, Guerrero Negro Hypersaline Mat
ARB_42A2A09C, denovo2685 GII2.1_2390AM086154, uncultured bacterium, lake profundal sediment
DQ133936, uncultured bacterium, limestone−corroding stream biofilmDQ133911, uncultured bacterium, limestone−corroding stream biofilm
DQ133934, uncultured bacterium, limestone−corroding stream biofilmJn522187, uncultured organism, Guerrero Negro Hypersaline Mat ARB_988C1618, denovo3179 GII3.1_3268
AF099065, Desulfofrigus fragileARB_29F48A4E, denovo655 GI3.1_4246
HE600063, uncultured Desulfofrigus sp., marine sedimentARB_A5B339C9, denovo2168 GII2.1_7178
AF099064, Desulfofrigus oceanenseAB015240, uncultured delta proteobacterium, deepest cold−seep area of the Japan Trench
EU052250, uncultured delta proteobacterium, anode from microbial fuel cell fed with marine planktonEU052237, uncultured delta proteobacterium, anode from microbial fuel cell fed with marine plankton
AB530175, uncultured bacterium, marine sedimentARB_1EFDF7DA, denovo1912 GI1.1_3304
ARB_F38F9C78, denovo438 GII3.1_9848ARB_B3F8690C, denovo3171 GII2.1_2892
ARB_C3BF8B7, denovo3566 GII2.1_13654Jf344495, uncultured delta proteobacterium, hydrocarbon polluted marine sediments
ARB_972BEFDB, denovo2749 GI1.1_3156ARB_972BEFDB, denovo831 GII1.1_1216
ARB_EDD81177, denovo4017 GII2.1_4348ARB_824ACC52, denovo1977 GII3.1_7096ARB_CEB514CF, denovo327 GII3.1_2683
ARB_5499095F, denovo3967 GII2.1_121ARB_EA25DAB2, denovo301 GI1.1_5383
KC471130, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa TroughKC471154, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough
ARB_230591CA, denovo2332 GII1.1_5560KC471196, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough
ARB_E3CF55F2, denovo3886 GII3.1_9557ARB_875F4162, denovo3943 GII3.1_12311
KC471054, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa TroughHQ703812, uncultured bacterium, Lianyungang marine sediment
ARB_5366F7CC, denovo2113 GII3.1_12485KC471037, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa TroughKC471011, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa TroughKC471046, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough
AF321820, Desulfofaba hanseniiJX222073, uncultured bacterium, subsurface aquifer sediment
Desulfofaba_1
ARB_42DA9ED8, denovo1976 GI1.1_1431ARB_FAF7585E, denovo2155 GII3.1_6836ARB_700BB89E, denovo2433 GI2.1_1599
ARB_B43CC987, denovo87 GII2.1_481Ay592706, uncultured bacterium, Napoli mud volcano, Eastern Mediterranean,
ARB_6CB546A4, denovo3222 GII3.1_3868AY268891, Desulfofaba fastidiosa
EU487968, uncultured bacterium, siliciclastic sedment from Thalassia sea grass bed
Desulfofaba_2
JX222769, uncultured bacterium, subsurface aquifer sedimentDQ415842, uncultured bacterium, Frasassi sulfidic cave stream biofilm
ARB_7A94311A, denovo1579 GII3.1_3316ARB_102BDE9A, denovo1602 GI2.1_1649
HE613444, Desulfatiferula sp. BE2801, estuary sedimentFR667781, uncultured bacterium, iron snow from acidic coal mining−associated Lake 77
Jf344222, uncultured delta proteobacterium, petroleum spot over marine sediments DQ826724, Desulfatiferula olefinivorans
ARB_E11A1166, denovo399 GI2.1_871JX222822, uncultured bacterium, subsurface aquifer sediment
JX223240, uncultured bacterium, subsurface aquifer sedimentARB_2CD45AD4, denovo2141 GI2.1_1838
JX222458, uncultured bacterium, subsurface aquifer sedimentJX223512, uncultured bacterium, subsurface aquifer sediment
JX457247, uncultured bacterium, gutGQ866071, uncultured bacterium, gut
ARB_3A4D20D7, denovo2746 GII3.1_2705
Desulfatiferula
Figure S5b: Bacterial 16S rRNA gene amplicon sequences assigned to in the class of Deltaproteobac-teria, order: Desulfobacterales, family: Desulfobacteraceae (black bold: sequences retrieved in this study and closest relatives).
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Supplementary Material
Jn452561, uncultured organism, Guerrero Negro Hypersaline Mat ARB_5E38B580, denovo3953 GII1.1_1602
JX391346, uncultured bacterium, marine sedimentKf623992, uncultured bacterium, Janssand tidal flat, Wadden Sea
KF799406, uncultured bacterium, gutKF268874, uncultured bacterium, marine sediment
JX391709, uncultured bacterium, marine sedimentJX391368, uncultured bacterium, marine sediment
FJ949149, uncultured Desulfobacteraceae bacterium, calcareous sandy sedimentJX391090, uncultured bacterium, marine sedimentARB_9E2E722F, denovo2789 GII1.1_7427
JX391589, uncultured bacterium, marine sedimentFj716993, uncultured bacterium, marine sediment from Cullercoats, NorthumberlandARB_9D945629, denovo867 GII1.1_234
U51844, delta proteobacterium WNARB_B6C76362, denovo522 GII3.1_7062
ARB_8AA8018, denovo3096 GII2.1_5852JQ212736, uncultured bacterium, bottlenose dolphin mouth
Fj717001, uncultured bacterium, marine sediment from Cullercoats, NorthumberlandAF099054, Desulfobacter sp. ASv25GQ261762, uncultured delta proteobacterium, deep sea sediment associated with whale falls
GQ356938, uncultured bacterium, methane seep sedimentGQ356949, uncultured bacterium, methane seep sedimentFR733673, Desulfobacter hydrogenophilus
DQ057079, Desulfobacter psychrotoleransFJ717003, uncultured bacterium, marine sediment from Cullercoats, Northumberland
Fj716965, uncultured bacterium, marine sediment from Cullercoats, NorthumberlandJF343993, uncultured delta proteobacterium, hydrocarbon polluted marine sediments from rodas beach
Fj716962, uncultured bacterium, marine sediment from Cullercoats, NorthumberlandU85469, Desulfobacter sp. BG8KF268856, uncultured bacterium, marine sediment
ARB_DD288351, denovo2652 GI2.1_4358JX225079, uncultured bacterium, subsurface aquifer sediment
ARB_7BB6FB78, denovo2419 GI3.1_4466ARB_A58E3C3B, denovo3178 GII3.1_10337
JX120461, uncultured bacterium, subsurface aquifer sedimentJX120460, uncultured bacterium, subsurface aquifer sediment
JX125449, uncultured bacterium, subsurface aquifer sedimentJX120466, uncultured bacterium, subsurface aquifer sediment
AF418180, Desulfobacter postgateiM26633, Desulfobacter postgateiAGJR02000005, Desulfobacter postgatei 2ac9, anaerobic sediment of brackish water ditch near Jadebusen
Eu864440, uncultured bacterium, Xiao River EU864484, uncultured bacterium, Xiao River receiving treated oxytetracycline production wastewater
JX120459, uncultured bacterium, subsurface aquifer sedimentJX225700, uncultured bacterium, subsurface aquifer sediment
Jx271977, uncultured bacterium, activated sludge in lab−scale reactor EU234252, uncultured bacterium, downstream of Wang Yang River, receiving penicillin G production wastewater
AGJR02000008, Desulfobacter postgatei 2ac9, anaerobic sediment of brackish water ditch near JadebusenFJ716310, uncultured bacterium, Sawmill Sink water column, at 10.3 m water depth
KF933845, Desulfobacula sp. TS−7ARB_68E1E8F6, denovo1052 GII3.1_1606
AY222309, uncultured delta proteobacterium, host hindgut caecumARB_55128A66, denovo3319 GII2.1_11393
EF442984, sulfate−reducing bacterium JHA1AY177795, uncultured Desulfobacula sp., Antarctic sediment
FR823371, uncultured delta proteobacterium, gas seep sedimentJF514280, uncultured bacterium, sea
ARB_691E454A, denovo157 GI2.1_919ARB_BCB1D27F, denovo1223 GII3.1_11648
EU290701, uncultured bacterium, sediment 0−2cm depthAY177800, uncultured Desulfobacula sp., Antarctic sedimentKF268860, uncultured bacterium, marine sediment
JQ753193, uncultured bacterium, Antarctic sea iceGU197423, uncultured bacterium, intertidal sediment, depth 0−15 cmAy922192, uncultured delta proteobacterium, grey whale bone, Pacific Ocean, Santa Cruz Basin
FR823375, uncultured delta proteobacterium, associated sedimentFR823376, uncultured delta proteobacterium, associated sediment
JF344268, uncultured delta proteobacterium, petroleum spot over marine sediments from figueiras beachKC471161, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa TroughKC471246, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough
KC471078, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa TroughARB_9E645E6E, denovo210 GII3.1_1506
ARB_AD101018, denovo343 GII2.1_4906ARB_9900558E, denovo1638 GII2.1_10513
ARB_ADF00A92, denovo796 GII3.1_7275KC471244, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa Trough
KC471084, uncultured bacterium, marine sediment at Yonaguni Knoll in the Okinawa TroughARB_4A9FE3FF, denovo1772 GII2.1_879
ARB_2423619F, denovo2566 GI2.1_305ARB_18F285C2, denovo2618 GII2.1_3476
ARB_E1D7A46E, denovo1731 GII1.1_2949KC492863, uncultured Desulfobacula sp., Baltic Sea redoxcline, 119 m depthAY177803, uncultured Desulfobacula sp., Antarctic sediment
AJ937698, uncultured bacterium, mud from a terrestrial volcanoARB_A9ED3C90, denovo127 GII3.1_1097
ARB_C5D21D56, denovo1906 GII3.1_607ARB_752C5DFE, denovo3090 GII3.1_10845
ARB_56BD7EAD, denovo3258 GII2.1_9782Fj628185, uncultured bacterium, brackish water from anoxic fjord
ARB_C5116C1C, denovo1634 GII2.1_4094ARB_A9D2324B, denovo1307 GI1.1_2919ARB_7BB990DB, denovo1697 GII3.1_8393
FJ628265, uncultured bacterium, brackish water from anoxic fjord Nitinat Lake at depth 22GU145490, uncultured bacterium, Black Sea, potential density 15.81
KC545723, uncultured Desulfobacula sp., oxycline region of a coastal marine water columnKC545728, uncultured Desulfobacula sp., oxycline region of a coastal marine water column
AM774314, delta proteobacterium JS_SRB50Hy, tidal flat sedimentAJ237606, Desulfobacula phenolicaGQ261767, uncultured delta proteobacterium, deep sea sediment associated with whale fallsGQ348356, uncultured delta proteobacterium, Saanich Inlet, 200 m depthGU197424, uncultured bacterium, intertidal sediment, depth 0−15 cm
DQ831540, uncultured Desulfobacula sp., marine sedimentARB_CB393774, denovo2285 GII1.1_285
ARB_831C7D25, denovo1192 GII1.1_11241ARB_F227D1D4, denovo344 GII3.1_2379
ARB_FE2B548D, denovo2584 GI2.1_237ARB_F4D910C0, denovo2876 GII2.1_5307
Kc000940, unidentified marine bacterioplankton, surface seawater samples from South China SeaARB_8741E9EF, denovo551 GI1.1_5282
ARB_6AAFAFB, denovo1020 GII1.1_1771ARB_E6C2968D, denovo1222 GI1.1_1092
HQ405662, bacterium enrichment culture clone AOM−SR−B24, enrichment mediating the anaerobic oxidation of methaneARB_8921930, denovo1642 GI3.1_5066
EU570896, uncultured bacterium, Nitinat Lake at a depth of 13 mARB_FE450D44, denovo2673 GII2.1_270
Dq925890, uncultured bacterium, hydrothermal vent Guaymas BasinAB189365, uncultured Desulfobacterium sp., cold seep sediment
AJ704693, uncultured delta proteobacterium, marine sedimentAJ704685, uncultured delta proteobacterium, marine sediment
ARB_7FCB72A1, denovo1108 GI1.1_3343ARB_844A3AFA, denovo994 GII3.1_5707
JF268367, uncultured bacterium, Hikurangi margin, Wairarapa − Takahae, station 309; SO191_3_309KF624105, uncultured bacterium, anoxic pyrite−particle colonization experiment, Janssand tidal flat, Wadden Sea
JF344167, uncultured delta proteobacterium, petroleum spot over marine sediments from figueiras beachFN820309, uncultured bacterium, marine sediment, mud volcanoJQ580395, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oil
ARB_F3E53A99, denovo2676 GII3.1_2047AY197397, uncultured bacterium, Guaymas Basin hydrothermal vent sediments
ARB_B802BE9, denovo1369 GII3.1_343FJ497571, uncultured delta proteobacterium, Vailulu’u Seamount
ARB_4BCB0690, denovo2794 GII1.1_6932JX225725, uncultured bacterium, subsurface aquifer sediment
JX224838, uncultured bacterium, subsurface aquifer sedimentARB_38687E91, denovo1775 GII3.1_357
JX224531, uncultured bacterium, subsurface aquifer sedimentKF059938, uncultured Desulfobacula sp., oil well water
JX224964, uncultured bacterium, subsurface aquifer sedimentARB_90F03020, denovo418 GI3.1_3548
Desu
lfobacu
la
ARB_903AB4BE, denovo400 GI1.1_2096ARB_E811D690, denovo2159 GII3.1_4428
ARB_6E68406, denovo3323 GII3.1_11303ARB_2658D044, denovo736 GI2.1_1998
Ef687285, uncultured bacterium, sediment underneath a sulfide−oxidizing mat, Chefren mud volcanoARB_5E2AC7C5, denovo2114 GII1.1_9836
ARB_B40486E4, denovo3407 GII1.1_957ARB_BDBAEB51, denovo2557 GII2.1_2691
ARB_7F4AC00D, denovo2965 GII2.1_4835ARB_5AFBF727, denovo3032 GII3.1_1347
ARB_99C327D9, denovo3509 GII2.1_3753ARB_F6FC891D, denovo2989 GII3.1_6268
HQ405610, bacterium enrichment culture clone AOM−SR−B20, enrichment mediating the anaerobic oxidation of methaneEf687314, uncultured bacterium, sediment underneath a sulfide−oxidizing mat, Chefren mud volcano, Nile Deep Sea Fan
FR823370, uncultured delta proteobacterium, gas seep sedimentAM883182, uncultured bacterium, host trophosome tissue
AY177799, uncultured Desulfobacteraceae bacterium, Antarctic sedimentJn455195, uncultured organism, Guerrero Negro Hypersaline Mat
EU570886, uncultured bacterium, Nitinat Lake at a depth of 50 mARB_1852A786, denovo4080 GII1.1_371
ARB_E77D75, denovo2622 GII3.1_3718ARB_138286CE, denovo2476 GI2.1_431ARB_138286CE, denovo3966 GII3.1_12408
ARB_12774C80, denovo2714 GII2.1_11932AY197376, uncultured proteobacterium, Guaymas Basin hydrothermal vent sediments
DQ925877, uncultured bacterium, hydrothermal vent chimneys of Guaymas BasinARB_6BE57BCD, denovo466 GI2.1_3816
ARB_51E6D082, denovo2560 GII1.1_904ARB_4D98103A, denovo590 GI1.1_2711
ARB_F2CADC85, denovo1645 GII2.1_320ARB_8DA9F1F2, denovo2813 GI3.1_4146
AY197389, uncultured proteobacterium, Guaymas Basin hydrothermal vent sedimentsCP001087, Desulfobacterium autotrophicum HRM2AF099056, Desulfobacterium sp. LSv25GQ261805, uncultured delta proteobacterium, deep sea sediment associated with whale falls
ARB_85D093E0, denovo3220 GII1.1_3563U85474, Desulfobacterium sp. BG33U85471, Desulfobacterium sp. BG18
FR733668, Desulfococcus niaciniEF442983, Desulfobacterium zeppelinii
AF418178, Desulfobacterium vacuolatumARB_DCBB76E5, denovo3877 GII1.1_2385ARB_3CD31A93, denovo1687 GI3.1_2927
ARB_42406D1, denovo1081 GI3.1_4342
Desu
lfobact
erium
_2
ARB_F4D45108, denovo1094 GII1.1_537ARB_F23C63C1, denovo2424 GII2.1_6963
JN252194, Candidatus Desulfamplus magnetomortis BW−1EU047537, uncultured sulfate−reducing bacterium, benzene−degrading, sulfate−reducing enrichment culture
Candidatus Desulfamplus
ARB_D6D2D42B, denovo157 GII3.1_9438ARB_45B9A382, denovo999 GII3.1_1990AB530188, uncultured bacterium, marine sediment
ARB_B33F233E, denovo1250 GII3.1_11390ARB_3811BEBC, denovo272 GI2.1_266ARB_B99FC159, denovo735 GII2.1_4119
ARB_217ED137, denovo1265 GII3.1_6977ARB_6F53D9A2, denovo941 GII2.1_6606
ARB_6CFF573D, denovo1362 GII1.1_9507ARB_6CFF573D, denovo289 GI2.1_1883
ARB_C7AE2C97, denovo2652 GII3.1_3409ARB_7D646BD3, denovo593 GI2.1_647
ARB_4AFD410D, denovo1138 GI2.1_2087ARB_12CB3B73, denovo3860 GII3.1_10456
GQ348489, uncultured delta proteobacterium, Saanich Inlet, 200 m depthARB_1BD1B139, denovo185 GII1.1_842
ARB_AE84C44F, denovo827 GII2.1_8140EU885094, uncultured bacterium, GI tract
JQ216349, uncultured bacterium, bottlenose dolphin mouthARB_843ECF4E, denovo2893 GII3.1_8486
JX391413, uncultured bacterium, marine sedimentARB_BE36ACE0, denovo3825 GII3.1_3441
ARB_DFC8E39B, denovo3243 GII2.1_7317KF268778, uncultured bacterium, marine sediment
ARB_9BF7C65, denovo232 GI3.1_3136GQ259286, uncultured bacterium, deep sediment
ARB_F7DCEB29, denovo227 GII2.1_2296ARB_14204A90, denovo1504 GII2.1_6800ARB_13808028, denovo2840 GI3.1_827
GU127076, uncultured bacterium, sediment; anoxic zone; tucurui hydroeletric power plant reservoirARB_51EF3CEE, denovo718 GII3.1_4007
HM243869, uncultured bacterium, middle sediment from Honghu LakeFJ485347, uncultured delta proteobacterium, wall biomat sample in El Zacaton at 273m depth
JQ580417, uncultured delta proteobacterium, sediments from Rodas Beach polluted with crude oilARB_6F8CC735, denovo624 GII2.1_730
KF548223, uncultured bacterium, aerobic tank of a full−scale produced water treatment plantARB_57B3B254, denovo617 GI1.1_920
AB530187, uncultured bacterium, marine sedimentARB_BFBB7707, denovo738 GII3.1_701
Figure S5c: Bacterial 16S rRNA gene amplicon sequences assigned to in the class of Deltaproteobac-teria, order: Desulfobacterales, family: Desulfobacteraceae (black bold: sequences retrieved in this study and closest relatives).
Chapter 5
140
Ay280427, uncultured epsilon proteobacterium, hydrothermal vent sulfide chimney, Juan de Fuca RidgeJn662023, uncultured epsilon proteobacterium, ubeworm Ridgeia piscesae
AB278151, uncultured bacterium, obtained from Mariana TroughAY531599, uncultured bacterium, Indian Ocean hydrothermal vent
JQ712438, uncultured epsilon proteobacterium, hydrothermal vent fluidsJn662026, uncultured epsilon proteobacterium, tubeworm Ridgeia piscesae AJ441211, uncultured epsilon proteobacterium, Paralvinella palmiformis mucus secretionsAJ576002, uncultured epsilon proteobacterium, deep sea hydrothermal vent
Jn874168, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific RiseJn873951, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise
AY672507, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific OceanAY672537, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean
EU555121, uncultured bacterium, Dudley hydrothermal ventAF449232, uncultured epsilon proteobacterium, Riftia pachyptila’s tube
JQ611095, uncultured bacterium, biofilm near white vent off Kueishan IslandJQ611085, uncultured bacterium, biofilm near white vent off Kueishan Island
Ay280407, uncultured epsilon proteobacterium, hydrothermal vent sulfide chimney, Juan de Fuca RidgeARB_64F4AD65, denovo915 GI2.1_384
ARB_305B8363, denovo513 GII1.1_682Jn662076, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae
ARB_EA631019, denovo1504 GI2.1_3731AY672526, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean
AY672530, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific OceanAY672521, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean
AY672520, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific OceanAJ441209, uncultured epsilon proteobacterium, Paralvinella palmiformis mucus secretions
Gu369886, uncultured epsilon proteobacterium, shallow hydrothermal vent region
uncultured 32
AF449253, uncultured epsilon proteobacterium, Riftia pachyptila’s tube
uncultured 37
AJ431222, proteobacterium BHI80−16AF420345, uncultured proteobacterium
Jn874159, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific RiseJQ712462, uncultured epsilon proteobacterium, hydrothermal vent fluids
Jn662191, uncultured epsilon proteobacterium, tubeworm Ridgeia piscesae AP009179, Sulfurovum sp. NBC37−1AP009179, Sulfurovum sp. NBC37−1AP009179, Sulfurovum sp. NBC37−1
JQ611086, uncultured bacterium, biofilm near white vent off Kueishan IslandJQ611159, uncultured bacterium, core sediment at 0−3 cm depth in yellow vent off Kueishan Island
AJ431221, proteobacterium BHI60−14AB091292, Sulfurovum lithotrophicum, deep−sea hydrothermal vent environmentsJn873995, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise
FR853000, uncultured bacterium, active hydrothermal chimney collected from the Dudley site of Juan de Fuca RidgeJQ712487, uncultured epsilon proteobacterium, hydrothermal vent fluidsJn662247, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae
uncultured (9 sequences)
AY531576, uncultured bacterium, Indian Ocean hydrothermal ventAF449235, uncultured epsilon proteobacterium, Riftia pachyptila’s tube
Jn874207, uncultured bacterium, TrapR2 located 115 m southwest of Ty/Io vents, East Pacific RiseJn874109, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise
Jn874231, uncultured bacterium, TrapR2 located 115 m southwest of Ty/Io vents, East Pacific RiseAY672533, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific OceanJQ611145, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan Island
JQ611112, uncultured bacterium, biofilm near yellow vent off Kueishan IslandHq153866, uncultured bacterium, white microbial film shallow hydrothermal vent
Jn662036, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae Jn662064, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae
FJ535344, uncultured bacterium, sedimentFJ535271, uncultured bacterium, iron matJn662133, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae
AF449231, uncultured epsilon proteobacterium, Riftia pachyptila’s tubeJQ611132, uncultured bacterium, core sediment at 0−5 cm depth in white vent off Kueishan Island
JQ611123, uncultured bacterium, core sediment at 21−24 cm depth in white vent off Kueishan IslandJQ712402, uncultured epsilon proteobacterium, hydrothermal vent fluids
AB842288, uncultured bacterium, gut of S.crosnieri
182
JF747909, uncultured bacterium, Frasassi cave system sulfidic springJF747989, uncultured bacterium, Frasassi cave system sulfidic spring
GQ355039, uncultured bacterium, springEF444740, uncultured bacterium, Thermopiles hot springs
Dq295592, uncultured epsilon proteobacterium, microbial mat from sulfidic spring Dq295601, uncultured epsilon proteobacterium, microbial mat from sulfidic spring Dq295602, uncultured epsilon proteobacterium, microbial mat from sulfidic spring
AF121887, bacterium 2BP−7GQ227834, uncultured bacterium, ground swab in mangrove forest
GQ355011, uncultured epsilon proteobacterium, springJn662280, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae
EF061978, uncultured epsilon proteobacterium, mangrove sedimentGU583971, uncultured bacterium, mangrove soilGU583970, uncultured bacterium, mangrove soilJX403047, uncultured bacterium, bitumen
GU180159, uncultured bacterium, sediment and soil slurryGU180158, uncultured bacterium, sediment and soil slurry
EU488101, uncultured bacterium, siliciclastic sedment from Thalassia sea grass bedKC009865, uncultured Campylobacteraceae bacterium, shallow fluidized muds off the French Guiana coast
KF465256, uncultured Sulfurovum sp., Alang−Sosiya ship breaking yardARB_5E9258CC, denovo3386 GII3.1_7847
ARB_482679F6, denovo1298 GII1.1_1746KC763867, uncultured bacterium, oil−contaminated soilGU120550, uncultured epsilon proteobacterium, inside erupting mud volcano, temperature = 27.7 C
GU056082, uncultured bacterium, soil sample above gas and oil fieldDQ394915, uncultured epsilon proteobacterium, harbor sediment
JQ989773, uncultured bacterium, subseafloor sediment at the KP−9EF061977, uncultured epsilon proteobacterium, mangrove sediment
JQ989775, uncultured bacterium, subseafloor sediment at the KP−9KF758699, uncultured Sulfurovum sp., ocean waterKF758616, uncultured Sulfurovum sp., ocean water
KF758740, uncultured Sulfurovum sp., ocean waterJQ989774, uncultured bacterium, subseafloor sediment at the KP−9KF758756, uncultured Sulfurovum sp., ocean water
KF758605, uncultured Sulfurovum sp., ocean waterJQ989767, uncultured bacterium, subseafloor sediment at the KP−9
KF758583, uncultured Sulfurovum sp., ocean waterJQ989770, uncultured bacterium, subseafloor sediment at the KP−9
AF420360, uncultured proteobacteriumJX403027, uncultured bacterium, underground waterEF467546, uncultured bacterium, Frasassi sulfidic cave stream biofilm
Jn662200, uncultured epsilon proteobacterium, Ridgeia piscesae tubewormAF420343, uncultured proteobacterium
120
uncultured
uncultured
8
JQ036280, uncultured bacterium, Hydrate Ridge sediment 2518
uncultured 11
JQ611092, uncultured bacterium, biofilm near white vent off Kueishan IslandAJ441206, uncultured epsilon proteobacterium, Paralvinella palmiformis mucus secretions
EU570833, uncultured bacterium, Nitinat Lake at a depth of 37.5 mKc545718, uncultured Desulfopila sp., oxycline region
GQ354918, uncultured Desulfobacterales bacterium, springGQ354989, uncultured delta proteobacterium, spring
Jn662041, uncultured proteobacterium, tubeworm Ridgeia piscesae Jn662234, uncultured delta proteobacterium, tubeworm Ridgeia piscesae
ARB_870C0E9A, denovo896 GII2.1_6517ARB_D61337BA, denovo3327 GII3.1_2152
GU120555, uncultured epsilon proteobacterium, inside erupting mud volcanoAB530185, uncultured bacterium, marine sediment
KF758719, uncultured Salimesophilobacter sp., ocean waterKF758696, uncultured Sulfurovum sp., ocean water
DQ394916, uncultured bacterium, harbor sedimentGQ354985, uncultured epsilon proteobacterium, spring
Fn554089, uncultured sediment bacterium, Logatchev hydrothermal vent fieldFJ615414, uncultured bacterium, high rate anaerobic methane−oxidizing submerged membrane bioreactor
HM445989, uncultured bacterium, wastewaterEU234154, uncultured bacterium, effluent of the WWTP for treating penicillin G production wastewater
AJ431220, proteobacterium Dex80−27FJ535262, uncultured bacterium, iron mat
GU220732, uncultured bacterium, low temperature hydrothermal precipitates of East Lau Spreading CenterFR852993, uncultured bacterium, active hydrothermal chimney collected from the Dudley site of Juan de Fuca RidgeFR853069, uncultured bacterium, active hydrothermal chimney collected from the Dudley site of Juan de Fuca Ridge
KF624533, uncultured bacterium, suboxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden SeaAB842287, uncultured bacterium, gut of S.crosnieri
KF545018, uncultured Sulfurovum sp., deep−sea sedimentJn662077, uncultured epsilon proteobacterium, tubeworm Ridgeia piscesae in high−flow environment
Ay280435, uncultured epsilon proteobacterium, exterior of a deep−sea hydrothermal vent sulfide chimney, Juan de Fuca RidgeJn662174, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae in high−flow environment
Jn874024, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific RiseJn874212, uncultured bacterium, TrapR2 located 115 m southwest of Ty/Io vents, East Pacific Rise
Jn662066, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae in high−flow environmentJn662253, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae in high−flow environmentJn662149, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae in high−flow environmentJQ712481, uncultured epsilon proteobacterium, hydrothermal vent fluids
Jn662098, uncultured epsilon proteobacterium, vestimentiferan tubeworm Ridgeia piscesae in high−flow environmentJQ712460, uncultured epsilon proteobacterium, hydrothermal vent fluids
JQ712484, uncultured epsilon proteobacterium, hydrothermal vent fluidsJQ712444, uncultured epsilon proteobacterium, hydrothermal vent fluidsAJ431224, proteobacterium Dex80−90
JN874140, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’NJN873965, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’N
JN874006, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’NAY672518, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean
JN873957, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’NJN874072, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’NJN874274, uncultured bacterium, TrapR2 located 115 m southwest of Ty/Io vents, East Pacific Rise, 9 degrees 50’N
JN873975, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’NAQWF01000016, Sulfurovum sp. SCGC AAA036−F05
JN873991, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’NAY672522, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific OceanJN873979, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’N
AY672531, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean
uncultured 25
AB842280, uncultured bacterium, gut of S.crosnieriAy280389, uncultured epsilon proteobacterium, exterior of a deep−sea hydrothermal vent sulfide chimney, Juan de Fuca Ridge
JX521118, uncultured bacterium, terrestrial sulfidic springJQ611148, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan Island
JQ611152, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan IslandJQ611146, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan IslandJQ611125, uncultured bacterium, core sediment at 21−24 cm depth in white vent off Kueishan Island
JQ611156, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan IslandJQ611139, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan Island
JQ611117, uncultured bacterium, core sediment at 21−24 cm depth in white vent off Kueishan IslandJQ611179, uncultured bacterium, porewater fluid near yellow vent off Kueishan Island
JQ611147, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan IslandJQ611151, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan Island
JQ611137, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan IslandAY672540, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean
Cam
pyl
obact
era
les_
Helic
obact
era
ceae_Sulfu
rovu
m
uncultured
Figure S6a: Bacterial 16S rRNA gene amplicon sequences assigned to the class of Epsilonproteobac-teria, order: Campylobacterales, family: Helicobacteraceae, genus: Sulfurovum (black bold: sequences retrieved in this study and closest relatives).
141
Supplementary Material
uncultured 16
JX570598, endosymbiont of Ridgeia piscesaeJQ712409, uncultured epsilon proteobacterium, hydrothermal vent fluids
AF449239, uncultured epsilon proteobacterium, Riftia pachyptila’s tubeARB_A468E98B, denovo1651 GII3.1_10383
JQ199082, uncultured bacterium, seawater; next to dolphin UGQ357014, uncultured bacterium, methane seep sediment
JX016315, uncultured bacterium, marine bulk waterHM057704, uncultured bacterium, ocean water from the Yellow SeaHQ203962, uncultured bacterium, seawater
ARB_BDD1DF7F, denovo1949 GI1.1_1153FR666865, uncultured bacterium, microbial matFR666868, uncultured bacterium, microbial mat
FR666860, uncultured bacterium, microbial matFR666861, uncultured bacterium, microbial mat
FR666863, uncultured bacterium, microbial matFR666862, uncultured bacterium, microbial mat
JQ712383, uncultured epsilon proteobacterium, hydrothermal vent fluidsARB_7969B766, denovo561 GI2.1_1182FR666864, uncultured bacterium, microbial matGq261829, uncultured epsilon proteobacterium, deep sea sediment whale falls
FR666869, uncultured bacterium, microbial matGu061298, uncultured epsilon proteobacterium, Yellow Sea intertidal beach
FR683719, uncultured marine bacterium, marine biome, fjord, coastal waterHe576783, uncultured epsilon proteobacterium, biorector inoculated microbial mat
KF799694, uncultured bacterium, gutKF799695, uncultured bacterium, gutKF799571, uncultured bacterium, gutARB_B31CB100, denovo3137 GII1.1_1105
AY548997, uncultured bacterium, marine environmentFn429802, uncultured epsilon proteobacterium, marine sediments (1.1 mbsf)
Jf268371, uncultured bacterium, Hikurangi margin, Wairarapa − TakahaeJQ712406, uncultured epsilon proteobacterium, hydrothermal vent fluidsAB189374, uncultured epsilon proteobacterium, cold seep sediment
JQ712417, uncultured epsilon proteobacterium, hydrothermal vent fluidsJQ712419, uncultured epsilon proteobacterium, hydrothermal vent fluids
JQ712382, uncultured epsilon proteobacterium, hydrothermal vent fluids
uncultured 6
JX521734, uncultured bacterium, terrestrial sulfidic spring
uncultured 4
uncultured
JX521782, uncultured bacterium, terrestrial sulfidic springAy922188, uncultured epsilon proteobacterium, grey whale bone
uncultured 22
uncultured 9
Gu061286, uncultured epsilon proteobacterium, Yellow Sea intertidal beach ARB_F642CBD4, denovo370 GI2.1_670Gu061291, uncultured epsilon proteobacterium, Yellow Sea intertidal beach seawater
EU050947, uncultured bacterium, sediment from the Kings Bay, Svalbard, ArcticKF799046, uncultured bacterium, gut
Eu573099, bacterium enrichment culture clone EB24.3, North Sea, Ekofisk oil field JQ862033, uncultured epsilon proteobacterium
JX391668, uncultured bacterium, marine sedimentJX391694, uncultured bacterium, marine sediment
EF999357, uncultured bacterium, Pearl River Estuary sediments at 6cm depthJN018454, uncultured bacterium, Gulf of Mexico stable isotope probing incubationsJn233497, uncultured marine bacterium, ocean water Cape Lookout, NC from 505m depth
KC682345, uncultured bacterium, substrate mineral chipsKC682364, uncultured bacterium, substrate mineral chips
AB015529, uncultured epsilon proteobacterium, deep−sea sediments from different depthsJn233480, uncultured marine bacterium, ocean water continental slope off Cape Lookout
ARB_87561165, denovo588 GI3.1_1443AJ810558, uncultured epsilon proteobacterium, superficial sediments
uncultured 4
Dq357825, epsilon proteobacterium Oy−M7, adult oyster mantleEF645952, uncultured bacterium, Namibian upwelling systemEF028937, uncultured bacterium, Zostera marina roots
GU584643, uncultured bacterium, marine hydrocarbon seep sedimentFj717168, uncultured bacterium, marine sediment from Cullercoats, NorthumberlandFj717163, uncultured bacterium, marine sediment from Cullercoats, Northumberland
JQ586324, uncultured bacterium, arctic marine sedimentARB_21BC0A68, denovo2795 GI2.1_5638EU142059, uncultured bacterium, methane seep sediment
EU236320, uncultured bacterium, 13 m depth in the Pacific Ocean
uncultured 50
uncultured 6
L42994, Arcobacter sp. Solar Lake, cyanobacterial mat from hypersaline lakeEF031096, uncultured bacterium, endorheic hypersaline atalasohaline lake
EF031092, uncultured bacterium, endorheic hypersaline atalasohaline lakeEU512920, Arcobacter marinus, seawater associated with starfish
JX403054, uncultured bacterium, bitumenFN356234, uncultured bacterium, oil production waterEu573100, bacterium enrichment culture clone EB27.1, North Sea, Ekofisk oil field
FR675876, Arcobacter molluscorumFR675875, Arcobacter molluscorumFR675874, Arcobacter molluscorum CECT 7696
AB893930, uncultured bacterium, digestive tractJN596130, bacterium A1(2011)JN596128, bacterium A2(2011b)
ARB_18DB62B1, denovo487 GI2.1_2840ARB_3F2E08E3, denovo592 GII2.1_8864
EU669904, Arcobacter mytili, musselsHG792246, uncultured bacterium, intestinal contents of Chinese Mitten Crab
AF513455, Arcobacter halophilusKF268902, uncultured bacterium, marine sedimentFJ202783, uncultured bacterium, Montastraea faveolata kept in aquarium for 23 days
uncultured 7
KC527432, uncultured bacterium, White Plague Disease infected coral
uncultured 25
uncultured 4
AJ271655, Arcobacter sp. A3b2EU142043, uncultured bacterium, methane seep sediment
AJ271654, Arcobacter sp. D1a1
uncultured 9
FR683715, uncultured marine bacterium, marine biome, fjord, coastal waterAJ810559, uncultured epsilon proteobacterium, superficial sediments
ARB_DD34D980, denovo2326 GII2.1_3882Fj717102, uncultured bacterium, marine sediment from Cullercoats, NorthumberlandFj717122, uncultured bacterium, marine sediment from Cullercoats, Northumberland
HQ203797, uncultured bacterium, seawaterEU052239, uncultured epsilon proteobacterium, anode from microbial fuel cell fed with marine plankton
GU584648, uncultured bacterium, marine hydrocarbon seep sediment
uncultured 15
uncultured 26
AB530236, uncultured bacterium, marine sedimentFR666867, uncultured bacterium, microbial mat
Jf344171, uncultured epsilon proteobacterium, petroleum spot over marine sediments EU245155, uncultured organism, hypersaline microbial mat
EF123613, uncultured epsilon proteobacterium, black band diseased (BBD) coral tissuesJX570599, endosymbiont of Ridgeia piscesae
DQ218324, uncultured Arcobacter sp., microbial mat
uncultured 15
FJ628351, uncultured bacterium, brackish water from anoxic fjord Nitinat Lake at depth 28FR666871, uncultured bacterium, microbial matARB_2017809, denovo3313 GII3.1_10544
HM057719, uncultured bacterium, ocean water from the Yellow SeaCP001999, Arcobacter nitrofigilis DSM 7299, rootsL14627, Arcobacter nitrofigilis
CP001999, Arcobacter nitrofigilis DSM 7299, rootsCP001999, Arcobacter nitrofigilis DSM 7299, rootsCP001999, Arcobacter nitrofigilis DSM 7299, rootsEu106661, Arcobacter nitrofigilis
JX403044, uncultured bacterium, bitumenJF904743, uncultured Arcobacter sp., mangrove soil
EF648116, uncultured Arcobacter sp., aerobic activated sludgeHQ203800, uncultured bacterium, seawater
JN118552, Arcobacter sp. sw028, a−surface water of South PacificHM057804, uncultured epsilon proteobacterium, ocean water from the Yellow Sea
HM057749, uncultured epsilon proteobacterium, ocean water from the Yellow SeaHM057779, uncultured epsilon proteobacterium, ocean water from the Yellow SeaHQ203831, uncultured bacterium, seawaterJQ712049, uncultured bacterium, surface seawater offshore QingdaoJQ712030, uncultured bacterium, surface seawater offshore Qingdao
JQ712046, uncultured bacterium, surface seawater offshore QingdaoHM057765, uncultured epsilon proteobacterium, ocean water from the Yellow SeaJQ712055, uncultured bacterium, surface seawater offshore Qingdao
AM084114, Arcobacter sp. R−28314JQ845784, uncultured Arcobacter sp., wash water from wash basin 2 of a spinach−processing plant
HE565359, Arcobacter venerupis, SeaARB_AD7A5D23, denovo709 GI1.1_4652
JQ845782, uncultured Arcobacter sp., wash water from wash basin 2 of a spinach−processing plantDQ234254, uncultured Arcobacter sp., mangroveHM057679, uncultured epsilon proteobacterium, ocean water from the Yellow SeaFJ946551, uncultured epsilon proteobacterium, arctic meltwaterJX403059, uncultured bacterium, bitumen
HQ860689, uncultured bacterium, stream waterFJ612319, uncultured bacterium, lake water
uncultured 44
JQ845771, uncultured Arcobacter sp., wash water from wash basin 2 of a spinach−processing plant
group
DQ234101, uncultured Arcobacter sp., mangroveFN428747, uncultured bacterium, Mahananda river waterFR691497, uncultured bacterium, Mahananda river sediment
HQ860691, uncultured bacterium, stream water
uncultured 21
mainly uncultured including Arcobacter butzleri 26
JX912503, Arcobacter butzleriAM084124, Arcobacter sp. R−28214JQ086899, uncultured Arcobacter sp., push core sediment sample from the vadose zone of a hydrocarbon contaminated aquifer
JF497852, uncultured bacterium, activated sludgeJN397809, uncultured bacterium, river bank
Z93999, uncultured bacterium
uncultured 44
JF915357, Arcobacter cryaerophilusHQ860539, uncultured bacterium, stream waterKF703990, Arcobacter sp. 69948, American crow feces
EU560811, uncultured bacterium, intestinal floraAF324539, uncultured epsilon proteobacterium BioIuz K34
AB355029, uncultured bacterium, surface water, Manzallah LakeCU925313, uncultured bacterium, mesophilic anaerobic digester which treats municipal wastewater sludge
CU926906, uncultured bacterium, mesophilic anaerobic digester which treats municipal wastewater sludgeCU924753, uncultured bacterium, mesophilic anaerobic digester which treats municipal wastewater sludge
uncultured 62
JQ213140, uncultured bacterium, bottlenose dolphin mouthFJ959725, uncultured bacterium, blowhole
uncultured 20
uncultured 19
uncultured 4
JQ611225, uncultured bacterium, venting fluid in yellow vent off Kueishan IslandKC527475, uncultured bacterium, White Plague Disease infected coralAY035822, Candidatus Arcobacter sulfidicus
uncultured 9
AF144693, oilfield bacterium ’FWKO B’
uncultured 7
JQ712410, uncultured epsilon proteobacterium, hydrothermal vent fluidsJQ712384, uncultured epsilon proteobacterium, hydrothermal vent fluids
AY542568, uncultured epsilon proteobacterium, Gulf of Mexico seafloor sedimentARB_34C3AB2A, denovo2381 GI2.1_228
AF458287, uncultured epsilon proteobacterium, Mono Lake, California
Cam
pylo
bacte
rale
s_C
am
pylo
bacte
raceae
_A
rcobacte
r
Figure S6b: Bacterial 16S rRNA gene amplicon sequences assigned to the class of Epsilonproteobacteria, order: Campylobacterales family: Campylobacteraceae, genus: Acrobacter (black bold: sequences retrieved in this study and closest relatives).
Chapter 5
142
AFRZ01000001, Sulfurimonas gotlandica GD1, sulfidic area of central Baltic Sea
Fj717113, uncultured bacterium, marine sediment from Cullercoats, NorthumberlandFj717120, uncultured bacterium, marine sediment from Cullercoats, Northumberland
JQ712116, uncultured bacterium, oil−contaminated seawaterKF268813, uncultured bacterium, marine sedimentKF268857, uncultured bacterium, marine sediment
Ay922189, uncultured epsilon proteobacterium, grey whale bone, Pacific Ocean, Santa Cruz BasinGQ261771, uncultured epsilon proteobacterium, deep sea sediment associated with whale falls
uncultured 3
JQ287474, uncultured bacterium, East Pacific RiseJQ287473, uncultured bacterium, East Pacific Rise
JQ287433, uncultured bacterium, East Pacific RiseKC492834, uncultured Sulfurimonas sp., Baltic Sea redoxcline, 119 m depth
ARB_CC0227FD, denovo2021 GI2.1_1757FJ497608, uncultured epsilon proteobacterium, Vailulu’u SeamountFJ497591, uncultured bacterium, Vailulu’u SeamountFj717063, uncultured bacterium, marine sediment from Cullercoats, Northumberland
uncultured 8
Fj717036, uncultured bacterium, marine sediment from Cullercoats, NorthumberlandFj717079, uncultured bacterium, marine sediment from Cullercoats, Northumberland
Fj717049, uncultured bacterium, marine sediment from Cullercoats, NorthumberlandFj717093, uncultured bacterium, marine sediment from Cullercoats, NorthumberlandFj717084, uncultured bacterium, marine sediment from Cullercoats, NorthumberlandFJ717065, uncultured bacterium, marine sediment from Cullercoats, Northumberland
Fj717096, uncultured bacterium, marine sediment from Cullercoats, NorthumberlandFj717067, uncultured bacterium, marine sediment from Cullercoats, Northumberland
uncultured 11
DQ228650, uncultured bacterium, sulfide−microbial incubatorGQ261797, uncultured epsilon proteobacterium, deep sea sediment associated with whale falls
uncultured 4
AB176067, uncultured bacterium, PCR−derived sequence from vent area waterAB176111, uncultured bacterium, PCR−derived sequence from vent area waterAB176109, uncultured bacterium, PCR−derived sequence from vent area water
AY704397, uncultured bacterium, oceanic crustARB_4672D8F7, denovo1916 GI2.1_90EU487967, uncultured bacterium, siliciclastic sedment from Thalassia sea grass bed
FJ624448, uncultured bacterium, Lau Basin hydrothermal vent sedimentGQ848475, uncultured bacterium, deep sea hydrothermal vent sediment
GQ848408, uncultured bacterium, deep sea hydrothermal vent sedimentGU198381, bacterium enrichment culture clone 16S−9, marine sediment
JX120496, uncultured bacterium, subsurface aquifer sedimentARB_40E96DC5, denovo1140 GI2.1_3851
AB176113, uncultured bacterium, PCR−derived sequence from vent area waterGQ349272, uncultured epsilon proteobacterium, Saanich Inlet, 120 m depth
Fj717167, uncultured bacterium, marine sediment from Cullercoats, NorthumberlandJQ287448, uncultured bacterium, East Pacific Rise
Jn873929, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific RiseAb193899, uncultured bacterium, obtained from Mariana Trough hydrothermal vent waterJn874362, uncultured bacterium, TrapR2 located 115 m southwest of Ty/Io vents, East Pacific RiseJn873940, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise
AB015257, unidentified epsilon proteobacterium, deepest cold−seep area of the Japan TrenchARB_EC842CDC, denovo3733 GII1.1_1431
Jn874097, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific RiseARB_C5F1B8A5, denovo885 GI3.1_315AY211683, uncultured epsilon proteobacterium, Gulf of Mexico seafloor sediment
JQ712411, uncultured epsilon proteobacterium, hydrothermal vent fluids
uncultured 5
FJ497252, uncultured epsilon proteobacterium, Vailulu’u SeamountJN637808, uncultured marine microorganism, middle port
JN637788, uncultured marine microorganism, middle portFJ497618, uncultured gamma proteobacterium, Vailulu’u Seamount
HQ203919, uncultured bacterium, seawaterFJ497584, uncultured delta proteobacterium, Vailulu’u Seamount
FJ535288, uncultured bacterium, iron mat
mainly uncultured including Sulfurimonas autotrophica 25
FJ535336, uncultured bacterium, sedimentFJ535346, uncultured bacterium, sediment
DQ394918, uncultured epsilon proteobacterium, harbor sedimentARB_251565CE, denovo454 GII2.1_1533
JX391546, uncultured bacterium, marine sedimentAb697024, uncultured bacterium, Bacterial mat
Jq723654, uncultured Campylobacterales bacterium, biofilm AF068806, uncultured bacterium VC2.1 Bac32
EF644801, uncultured bacterium, MAR Logatchev hydrothermal vent system, 3000m water depth, sulfide sampleAF367490, uncultured epsilon proteobacterium
AF367496, uncultured epsilon proteobacteriumAY225613, uncultured epsilon proteobacterium, pumice fragments exposed to a Mid−Atlantic Ridge vent
EU574671, uncultured bacterium, hydrothermal vent mat; Champagne Vent on N.W. EifukuEU574674, uncultured bacterium, hydrothermal vent mat; Champagne Vent on N.W. Eifuku
uncultured 21
JX391632, uncultured bacterium, marine sedimentKF624431, uncultured bacterium, suboxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea
Fr853059, uncultured bacterium, active hydrothermal chimney Juan de Fuca RidgeJq072913, uncultured prokaryote, active sulfide structures Juan de Fuca RidgeFr852963, uncultured bacterium, active hydrothermal chimney Juan de Fuca Ridge
Fr853045, uncultured bacterium, active hydrothermal chimney Juan de Fuca RidgeARB_E46846F5, denovo2532 GII1.1_85
Fr852998, uncultured bacterium, active hydrothermal chimney Juan de Fuca RidgeARB_D69AC317, denovo4058 GII1.1_2141Fr852969, uncultured bacterium, active hydrothermal chimney Juan de Fuca RidgeFJ497579, uncultured bacterium, Vailulu’u Seamount
DQ145977, bacterium ML2−86JX391568, uncultured bacterium, marine sediment
GQ261791, uncultured epsilon proteobacterium, deep sea sediment associated with whale fallsEF999352, uncultured bacterium, Pearl River Estuary sediments at 6cm depth
AY218555, uncultured bacteriumEF219007, uncultured bacterium, Ridge Flank Abyssal Hill hydrothermal site on the east Pacific rise
EF219001, uncultured bacterium, Ridge Flank Abyssal Hill hydrothermal site on the east Pacific riseJQ287049, uncultured bacterium, East Pacific Rise
JQ036261, uncultured bacterium, Eel River Basin sediment 2688EF687416, uncultured bacterium, sulfide−oxidizing mat, Chefren mud volcano, Nile Deep Sea Fan, Eastern Mediterranean
AJ441199, uncultured epsilon proteobacterium, Paralvinella palmiformis mucus secretionsEU652648, uncultured bacterium, Yellow Sea sediment
EU662310, uncultured bacterium, microbial matAJ441200, uncultured epsilon proteobacterium, Paralvinella palmiformis mucus secretions
DQ676325, uncultured epsilon proteobacterium, suboxic freshwater−pond sedimentKF464419, uncultured Sulfurimonas sp., Alang−Sosiya ship breaking yard
JQ611140, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan IslandAF355050, uncultured epsilon proteobacterium
AY225615, uncultured epsilon proteobacterium, iron−rich substrate exposed to a Mid−Atlantic Ridge ventEF441903, uncultured epsilon proteobacterium, endolithic community in the acidic Rio Tinto basin
DQ071281, uncultured epsilon proteobacterium, deep−sea hydrothermal ventDQ071286, uncultured epsilon proteobacterium, deep−sea hydrothermal ventDQ228651, uncultured bacterium, sulfide−microbial incubator
KC682636, uncultured bacterium, inactive hydrothermal sulfide chimney, Tui Malila vent field, Lau BasinJQ611149, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan Island
mainly uncultured including Sulfurimonas denitrificans 49
AY532543, uncultured bacterium, uranium−contaminated aquiferFJ628245, uncultured bacterium, brackish water from anoxic fjord Nitinat Lake at depth 50
FJ628235, uncultured bacterium, brackish water from anoxic fjord Nitinat Lake at depth 37.5KC682581, uncultured bacterium, inactive hydrothermal sulfide chimney, Tui Malila vent field, Lau Basin
ARB_314DFE6B, denovo3359 GII3.1_4254AY672532, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific Ocean
JQ611150, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan IslandAJ441204, uncultured epsilon proteobacterium, Paralvinella palmiformis mucus secretions
AJ575997, uncultured epsilon proteobacterium, deep sea hydrothermal ventFJ628204, uncultured bacterium, brackish water from anoxic fjord Nitinat Lake at depth 37.5
Ay251063, uncultured proteobacterium, deep−sea hydrothermal vent biofilm from the Edmond vent field JQ586311, uncultured bacterium, arctic marine sediment
ARB_FBD03AE6, denovo1223 GI2.1_522FJ628251, uncultured bacterium, brackish water from anoxic fjord Nitinat Lake at depth 50
KF624356, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden SeaARB_7A60E850, denovo2375 GI2.1_220
ARB_97CD83C8, denovo1803 GII3.1_2388FJ535253, uncultured bacterium, iron mat
AJ575998, uncultured epsilon proteobacterium, deep sea hydrothermal ventARB_DFCFDB0A, denovo1215 GI1.1_2525
AJ441201, uncultured epsilon proteobacterium, Paralvinella palmiformis mucus secretionsJn662179, uncultured epsilon proteobacterium, tubeworm Ridgeia piscesae in high−flow environmentDQ890422, uncultured bacterium, empty intestine
AJ441198, uncultured epsilon proteobacterium, Paralvinella palmiformis mucus secretionsHM154512, uncultured bacterium, Yellowstone Lake hydrothermal vent biofilmHM154504, uncultured bacterium, Yellowstone Lake hydrothermal vent biofilm
GU291331, uncultured bacterium, acid mine drainage contaminated salt marsh sedimentsKc682699, uncultured bacterium, inner conduit of inactive hydrothermal sulfide chimneyJQ287031, uncultured bacterium, East Pacific Rise
GU291328, uncultured bacterium, acid mine drainage contaminated salt marsh sedimentsGU291330, uncultured bacterium, acid mine drainage contaminated salt marsh sediments
JX403024, uncultured bacterium, underground waterKf624439, uncultured bacterium, suboxic sulfur−particle colonization experiment, Janssand tidal flat
uncultured 9
uncultured 3
JX521790, uncultured bacterium, terrestrial sulfidic springHQ729106, uncultured epsilon proteobacterium, bacterial matJX521773, uncultured bacterium, terrestrial sulfidic springJX521779, uncultured bacterium, terrestrial sulfidic springHQ729098, uncultured epsilon proteobacterium, bacterial matJX521774, uncultured bacterium, terrestrial sulfidic springHQ729096, uncultured epsilon proteobacterium, bacterial mat
Gu120613, uncultured epsilon proteobacterium, active mining area ARB_FD05D18F, denovo2886 GI1.1_2548
AM982624, uncultured bacterium, pig saw dust spent beddingFj037619, uncultured bacterium, biofilms of iron−ixodizing bacteria
JN637800, uncultured marine microorganism, middle portJn662232, uncultured epsilon proteobacterium, tubeworm Ridgeia piscesae
ARB_E5EE2E71, denovo1628 GI2.1_503JN637811, uncultured marine microorganism, middle portGU583978, uncultured bacterium, mangrove soilHM057666, uncultured bacterium, ocean water from the Yellow Sea
EF444735, uncultured bacterium, Thermopiles hot springsJX403049, uncultured bacterium, bitumenJX403058, uncultured bacterium, bitumen
FJ535290, uncultured bacterium, iron matFJ535325, uncultured bacterium, sedimentAB189712, Alviniconcha sp. gill symbiont
DQ228648, uncultured bacterium, sulfide−microbial incubatorAy251059, uncultured proteobacterium, deep−sea hydrothermal vent biofilm from the Edmond vent field DQ925870, uncultured bacterium, hydrothermal vent chimneys of Guaymas Basin
AB252048, Sulfurimonas paralvinellae, Paralvinella sp. polychaetes’ nestJn873966, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific RiseJn874012, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise
Jn874124, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific RiseJn874136, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise
Jn874166, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific RiseAy280406, uncultured epsilon proteobacterium, exterior of a deep−sea hydrothermal vent sulfide chimney, Juan de Fuca RidgeAY672505, uncultured bacterium, hydrothermal vent, 9 degrees North, East Pacific Rise, Pacific OceanJn662183, uncultured epsilon proteobacterium, tubeworm Ridgeia piscesae in high−flow environment
JQ712432, uncultured epsilon proteobacterium, hydrothermal vent fluidsJQ712447, uncultured epsilon proteobacterium, hydrothermal vent fluids
AY225611, uncultured epsilon proteobacterium, organic−rich substrate exposed to a Mid−Atlantic Ridge vent
uncultured 23
EF036297, uncultured bacterium, Zostera marina rootsAJ515712, uncultured epsilon proteobacterium
AJ515713, uncultured epsilon proteobacteriumJQ712418, uncultured epsilon proteobacterium, hydrothermal vent fluids
Jn662192, uncultured epsilon proteobacterium, tubeworm Ridgeia piscesae AY216438, uncultured bacterium, temperate estuarine mud
KF465274, uncultured Sulfurimonas sp., Alang−Sosiya ship breaking yardEU574677, uncultured bacterium, hydrothermal vent mat; Champagne Vent on N.W. EifukuAY211663, uncultured epsilon proteobacterium, Gulf of Mexico seafloor sediment
GQ357037, uncultured bacterium, methane seep sedimentGQ357021, uncultured bacterium, methane seep sedimentAB013263, uncultured epsilon proteobacterium, Nankai Trough sediments at a depth of 3,843m
ARB_3F56C503, denovo1533 GI2.1_190AY225612, uncultured epsilon proteobacterium, organic−rich substrate exposed to a Mid−Atlantic Ridge ventHq153998, uncultured bacterium, white filamentous microbial mat in the photic zone of a shallow hydrothermal ventAB188787, uncultured Helicobacter sp., cold seep sediment
FN553987, uncultured sediment bacterium, Logatchev hydrothermal vent field,site F, watercolumn depth = 3000 mFn554146, uncultured sediment bacterium, Logatchev hydrothermal vent field,Anya’s GardenJn874121, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific RiseJQ712373, uncultured epsilon proteobacterium, hydrothermal vent fluids
FJ535303, uncultured bacterium, iron matJN874138, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’N
Jn874070, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific RiseKC682592, uncultured bacterium, inactive hydrothermal sulfide chimney, Tui Malila vent field, Lau Basin
JQ712437, uncultured epsilon proteobacterium, hydrothermal vent fluidsKF464524, uncultured bacterium, Alang−Sosiya ship breaking yardKF624354, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea
GQ848454, uncultured bacterium, deep sea hydrothermal vent sedimentGQ848449, uncultured bacterium, deep sea hydrothermal vent sediment
JN874382, uncultured bacterium, TrapR2 located 115 m southwest of Ty/Io vents, East Pacific Rise, 9 degrees 50’NJN874185, uncultured bacterium, TrapR2 located 115 m southwest of Ty/Io vents, East Pacific Rise, 9 degrees 50’N
JN874190, uncultured bacterium, TrapR2 located 115 m southwest of Ty/Io vents, East Pacific Rise, 9 degrees 50’NJN873941, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’N
EU491825, uncultured bacterium, seafloor lavas from the East Pacific RiseEU491791, uncultured bacterium, seafloor lavas from the East Pacific Rise
EU491826, uncultured bacterium, seafloor lavas from the East Pacific RiseDQ070790, uncultured epsilon proteobacterium, basalt glass from 9N latitude East Pacific RiseEU491816, uncultured bacterium, seafloor lavas from the East Pacific RiseEU491792, uncultured bacterium, seafloor lavas from the East Pacific Rise
GQ848457, uncultured bacterium, deep sea hydrothermal vent sedimentJN873959, uncultured bacterium, TrapR1 located 30 m southwest of Bio9 vent complex, East Pacific Rise, 9 degrees 50’NJQ287099, uncultured bacterium, East Pacific Rise
JQ586308, uncultured bacterium, arctic marine sedimentARB_8340C096, denovo2767 GII2.1_5839KF624353, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea
KF624411, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden SeaKF624438, uncultured bacterium, suboxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea
KF624409, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden SeaFj717137, uncultured bacterium, marine sediment from Cullercoats, NorthumberlandFj717173, uncultured bacterium, marine sediment from Cullercoats, Northumberland
uncultured 18
Fj717179, uncultured bacterium, marine sediment from Cullercoats, NorthumberlandFj717157, uncultured bacterium, marine sediment from Cullercoats, NorthumberlandFJ615170, uncultured epsilon proteobacterium, Saanich Inlet, depth of 10m in anoxic marine fjord
ARB_1401C19A, denovo2596 GI1.1_1762EU652653, uncultured bacterium, Yellow Sea sediment
FJ535347, uncultured bacterium, sedimentKF465277, uncultured Sulfurimonas sp., Alang−Sosiya ship breaking yardKF465242, uncultured Sulfurimonas sp., Alang−Sosiya ship breaking yard
KF464511, uncultured bacterium, Alang−Sosiya ship breaking yardGU369904, uncultured epsilon proteobacterium, white filamentous microbial mat in the photic region of a shallow hydrothermal vent
KF465252, uncultured Sulfurimonas sp., Alang−Sosiya ship breaking yardEF379628, uncultured bacterium, sea water from Victoria Harbor (Hong Kong) area
ARB_3223D2E0, denovo508 GI3.1_1312KF624336, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea
GQ261804, uncultured epsilon proteobacterium, deep sea sediment associated with whale fallsAY922185, uncultured epsilon proteobacterium, grey whale bone, Pacific Ocean, Santa Cruz Basin (N33.30 W119.22) depth 1674 meters
KF624343, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden SeaARB_C6318A, denovo1788 GI1.1_3689
DQ395005, uncultured epsilon proteobacterium, harbor sedimentEU652651, uncultured bacterium, Yellow Sea sediment
ARB_5EA6F342, denovo917 GI2.1_381ARB_53282A96, denovo2773 GII2.1_8103
ARB_1615A492, denovo2370 GI2.1_3681EU652650, uncultured bacterium, Yellow Sea sediment
GQ349003, uncultured epsilon proteobacterium, Saanich Inlet, 100 m depthGQ261792, uncultured epsilon proteobacterium, deep sea sediment associated with whale falls
FJ497261, uncultured bacterium, Vailulu’u SeamountKF545003, uncultured Sulfurimonas sp., deep−sea sediment
JN977221, uncultured bacterium, Jiaozhao Bay sedimentAB530237, uncultured bacterium, marine sediment
KF624267, uncultured bacterium, anoxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden SeaKF624342, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden SeaKF624358, uncultured bacterium, oxic sulfur−particle colonization experiment, Janssand tidal flat, Wadden Sea
JQ196547, uncultured bacterium, seawater; next to dolphin EARB_77205F9F, denovo889 GI2.1_254
JQ586310, uncultured bacterium, arctic marine sedimentFJ205271, uncultured epsilon proteobacterium, active hydrothermal field sediments, depth:1922m
EU652667, uncultured bacterium, Yellow Sea sedimentEU266014, uncultured bacterium, Nitinat Lake at a depth of 26 m
KF801506, uncultured epsilon proteobacterium
Cam
pylo
bacte
raceae
_S
ulfurim
onas
mainly uncultured related to Sulfuricurvum
256
uncultured 7
Figure S6c: Bacterial 16S rRNA gene amplicon sequences assigned to the class of Epsilonproteobac-teria, order: Campylobacterales family: Campylobacteraceae, genus: Sulfurimonas (black bold: sequences retrieved in this study and closest relatives).
143
X82931, Sulfurospirillum multivoransJQ713915, uncultured Sulfurospirillum sp., sediments from shallow hydrothermal vents
CP007201, Sulfurospirillum multivorans DSM 12446CP007201, Sulfurospirillum multivorans DSM 12446JX403043, uncultured bacterium, surface water
JX521007, uncultured bacterium, terrestrial sulfidic springEu864435, uncultured bacterium, Xiao River wastewater
Jq087039, uncultured Sulfurospirillum sp.,sedimenthydrocarbon contaminated aquiferAY570615, uncultured bacterium, low−temperature biodegraded Canadian oil reservoir
JX521473, uncultured bacterium, terrestrial sulfidic springJX521469, uncultured bacterium, terrestrial sulfidic spring
JN685481, uncultured bacterium, production water sample from oil wellJF304793, uncultured Sulfurospirillum sp., mining wastewater
Fq659417, uncultured soil bacterium, PAH−contaminated soil; retention systems HM481314, uncultured bacterium, TCE−contaminated field site
FJ612331, uncultured bacterium, lake waterCU922216, uncultured bacterium, mesophilic anaerobic digester
Dq295746, uncultured epsilon proteobacterium, microbial mat in sulfidic springDq295743, uncultured epsilon proteobacterium, microbial mat in sulfidic spring
AB355036, uncultured bacterium, surface water, Manzallah LakeJF747911, uncultured bacterium, Frasassi cave system sulfidic springAB355034, uncultured bacterium, surface water, Manzallah Lake
AB186804, uncultured bacterium, uncultured clone from polychlorinated dioxin dechlorinating microcosmAY756596, uncultured bacterium, Siwhaho sediment
Jx271945, uncultured bacterium, activated sludge in lab−scale reactor JX521449, uncultured bacterium, terrestrial sulfidic spring
Fq660045, uncultured soil bacterium, PAH−contaminated soilFq659173, uncultured soil bacterium, PAH−contaminated soilAf144694, Campylobacter sp. DSM 806
Fq659063, uncultured soil bacterium, PAH−contaminated soilL14632, Campylobacter sp.Jx462539, uncultured Campylobacter sp., methanogenic bioelectrochemical reactor
AY780560, uncultured Sulfurospirillum sp., chlorinated ethene−degrading cultureFJ612315, uncultured bacterium, lake waterAY189928, Sulfurospirillum sp. JPD−1FQ659988, uncultured soil bacterium, PAH−contaminated soil; retention systems which treat road runoffs
FQ659274, uncultured soil bacterium, PAH−contaminated soil; retention systems which treat road runoffsHM481322, uncultured bacterium, TCE−contaminated field site
JF789596, uncultured Sulfurospirillum sp., Athabasca oil sands formation waterFJ612310, uncultured bacterium, lake water
DQ234114, uncultured Sulfurospirillum sp., mangroveFJ612314, uncultured bacterium, lake water
FJ612328, uncultured bacterium, lake waterFJ612333, uncultured bacterium, lake water
FJ612317, uncultured bacterium, lake waterKF933844, Sulfurospirillum sp. b10KF933843, Sulfurospirillum sp. b1
DQ234236, uncultured Sulfurospirillum sp., mangroveAY756183, arsenate−reducing bacterium NP4, groundwater
JX521339, uncultured bacterium, terrestrial sulfidic springFQ659969, uncultured soil bacterium, PAH−contaminated soil; retention systems which treat road runoffs
AB368775, Sulfurospirillum deleyianumAB286550, uncultured bacterium, activated sludge
AB246781, Sulfurospirillum cavolei, underground crude−oil storage cavityJx000050, uncultured bacterium, anaerobic wastewater reactorJx271924, uncultured bacterium, activated sludge in lab−scale reactor with dissolved oxygen above 2.5 mg/lAJ488086, uncultured bacterium
Kc179071, uncultured bacterium, activated sludge taken from a microaerobic bioreactor KF836224, uncultured bacterium, springs and wells fed by a deep, fractured rock aquifer in the Mojave DesertAF038843, Sulfurospirillum barnesii
U41564, Sulfurospirillum barnesiiCP003333, Sulfurospirillum barnesii SES−3, selenate−contaminated freshwater marsh sedimentCp003333, Sulfurospirillum barnesii SES−3, selenate−contaminated freshwater marsh sediment
AJ535704, Sulfurospirillum sp. EK7, river sedimentY13671, Sulfurospirillum deleyianumCP001816, Sulfurospirillum deleyianum DSM 6946CP001816, Sulfurospirillum deleyianum DSM 6946CP001816, Sulfurospirillum deleyianum DSM 6946
AJ249226, bacterium DCE10GU120580, uncultured epsilon proteobacterium, active mining area of Pitch LakeEU662599, uncultured bacterium, floating microbial mat from sulfidic waterJX399885, Sulfuricurvum sp. L12, enrichment culture of coal−tar from a natural coal−tar source
Am157656, epsilon proteobacterium AN−BI3A, hypersaline brine and seawater in the Mediterranean.HM468037, uncultured bacterium, solid waste with green color in tanning process before Cr recovery
FN356324, uncultured bacterium, oil production waterFN356312, uncultured bacterium, oil production water
DQ228139, Sulfurospirillum sp. C6, bioreactor inoculated with oil field produced waterAY570614, uncultured bacterium, low−temperature biodegraded Canadian oil reservoirAY570602, uncultured bacterium, low−temperature biodegraded Canadian oil reservoirGQ863490, Sulfurospirillum alkalitolerans
AY570598, uncultured bacterium, low−temperature biodegraded Canadian oil reservoirAY570558, uncultured bacterium, low−temperature biodegraded Canadian oil reservoirJx898111, uncultured bacterium, series of continously fed aerated tank reactors system
Gq133407, uncultured bacterium, ASBR reactor treating swine wasteGQ415373, uncultured bacterium, Daqing oilfield production water
AB546014, uncultured bacterium, #AR39 oil wellheadJQ088439, uncultured bacterium, crude oil reservoir
JQ214236, uncultured bacterium, bottlenose dolphin mouthJQ214253, uncultured bacterium, bottlenose dolphin mouth
JQ215461, uncultured bacterium, bottlenose dolphin mouthAB546035, uncultured bacterium, #AR39 oil wellhead
AB546080, uncultured bacterium, #SR123 oil wellheadAB192073, uncultured epsilon proteobacterium, Microcerotermes sp. 2AB192072, uncultured epsilon proteobacterium, Microcerotermes sp. 1
AJ576349, uncultured bacterium, hindgut homogenate of Pachnoda ephippiata larvaAB231076, uncultured epsilon proteobacterium, Neotermes koshunensis
JN619494, uncultured bacterium, insect gutJN620073, uncultured bacterium, insect gut
AB234540, uncultured epsilon proteobacterium, Macrotermes gilvusFJ792313, uncultured bacterium, carbonate chimney in Lost City Hydrothermal Field
FJ792353, uncultured bacterium, carbonate chimney in Lost City Hydrothermal FieldFJ792370, uncultured bacterium, carbonate chimney in Lost City Hydrothermal FieldFJ791985, uncultured bacterium, carbonate chimney in Lost City Hydrothermal Field
FJ792434, uncultured bacterium, carbonate chimney in Lost City Hydrothermal FieldFJ792359, uncultured bacterium, carbonate chimney in Lost City Hydrothermal Field
ACQI01000338, hydrothermal vent metagenome, Lost City hydrothermal chimney biofilmFJ792218, uncultured bacterium, carbonate chimney in Lost City Hydrothermal Field
FJ792357, uncultured bacterium, carbonate chimney in Lost City Hydrothermal FieldFJ792283, uncultured bacterium, carbonate chimney in Lost City Hydrothermal FieldFJ792210, uncultured bacterium, carbonate chimney in Lost City Hydrothermal Field
KC682802, uncultured bacterium, surface of a basalt collected from Kilo Moana vent field, Lau BasinJN637820, uncultured marine microorganism, middle port
ARB_E5A35806, denovo3111 GII1.1_6079JX391284, uncultured bacterium, marine sedimentJX391327, uncultured bacterium, marine sedimentU85965, Sulfurospirillum sp. SM−5
AF367491, uncultured epsilon proteobacteriumFn773278, bacterium endosymbiont of Osedax mucofloris, Osedax mucofloris extacted from whale boneAY548994, uncultured bacterium, marine environment
FN658698, epsilon proteobacterium ectosymbiont of Rimicaris FJ717081, uncultured bacterium, marine sediment from Cullercoats, Northumberland
FJ497338, uncultured bacterium, Vailulu’u SeamountFJ814746, uncultured Campylobacterales bacterium, Carmel Canyon
ARB_E2983623, denovo180 GII3.1_8793FJ497463, uncultured epsilon proteobacterium, Vailulu’u Seamount
FJ535312, uncultured bacterium, iron matAY211681, uncultured epsilon proteobacterium, Gulf of Mexico seafloor sediment
Y11561, Sulfurospirillum arcachonenseGU220754, uncultured bacterium, low temperature hydrothermal precipitates of East Lau Spreading Center
ARB_9981C26F, denovo2147 GII3.1_1394AF357198, Sulfurospirillum sp. Am−NAF357199, Sulfurospirillum sp. 18.1
HM128339, uncultured bacterium, Xiaochaidan LakeAF513952, uncultured Sulfurospirillum sp., Hawaiian lake water
AB550501, uncultured Sulfurospirillum sp.FJ497442, uncultured epsilon proteobacterium, Vailulu’u Seamount
JQ287455, uncultured bacterium, East Pacific RiseJQ286985, uncultured bacterium, East Pacific Rise
JQ287296, uncultured bacterium, East Pacific RiseJQ287108, uncultured bacterium, East Pacific Rise
KC682703, uncultured bacterium, inner conduit of inactive hydrothermal sulfide chimney, ABE vent field, Lau BasinJQ611155, uncultured bacterium, core sediment at 18−21 cm depth in yellow vent off Kueishan Island
KC682704, uncultured bacterium, inner conduit of inactive hydrothermal sulfide chimney, ABE vent field, Lau BasinFJ497620, uncultured bacterium, Vailulu’u Seamount
Ay280408, uncultured epsilon proteobacterium, exterior of a deep−sea hydrothermal vent sulfide chimney, Juan de Fuca RidgeKC357921, uncultured bacterium, large−discharge carbonate springs
Jn662188, uncultured epsilon proteobacterium, tubeworm Ridgeia piscesae in high−flow environmentEf462744, uncultured bacterium, dorsal surface of the deep sea hydrothermal vent polychaete worm Alvinella pompejana
Sulfurospirillum
Thiofractor 6
0.10
Figure S6d: Bacterial 16S rRNA gene amplicon sequences assigned to the class of Epsilonproteobacte-ria, order: Campylobacterales family: Campylobacteraceae, genus: Sulfurospirillum (black bold: sequences retrieved in this study and closest relatives).
Chapter 5
144
Supplementary Material
Figure S7: Characteristic PLFA profiles of (a) the average relative concentration of PLFAs for March (0–0.5 cm and 2–4 cm) and August (0–1 cm), (b) the average Δδ 13C values and (c) relative 13C incorpora-tion of PLFAs for S2 and S1/S3 March (0–1 cm).
147
6. Potential recycling of thaumarchaeotal lipids by DPANN archaea in seasonally hypoxic surface marine sediments
Yvonne A. Lipsewers, Ellen C. Hopmans, Jaap S. Sinninghe Damsté, and Laura Villanueva
Thaumarchaeota are known to synthesize specific glycerol dibiphytanyl glycerol tetraethers (GDGTs), the distribution of which is affected by temperature which forms the base of the paleotemperature proxy TEX86. Lipids present in the marine surface sediments are believed to be mostly derived from pelagic Thaumarchaeota; however, some studies have evaluated the possibility that benthic archaea also contribute to the lipid fossil record. Here, we compared the archaeal abundance and composition by DNA-based methods and the archaeal intact polar lipid (IPL) diversity in surface sediments of a seasonally hypoxic marine lake to determine the potential biological sources of the archaeal IPLs detected in surface sediments under changing environmental conditions. The archaeal community changed from March (oxic conditions) to August (euxinic) from a Thaumarchaeota-dominated (up to 82%) to an archaeal community dominated by the DPANN superphylum (up to 95%). This marked change coincided with a one order of magnitude decrease in the total IPL-GDGT abundance. In addition, the polar head groups of the IPL-GDGTs changed from predominantly containing phospho- to glyco- polar head groups. This may indicate a transition to Thaumarchaeota growing in stationary phase or selective preservation of the GDGT pool. However, considering the apparent inability of the DPANN archaea to synthesize their own membrane lipids, we hypothesize that an alternative explanation might be that DPANN archaea use the lipids previously synthesized by the Thau-marchaeota to form their own cell membranes, which would indicate an active recycling of fossil IPLs in the marine surface sediment.
Submitted to Organic Geochemistry
Chapter 6
148
6.1. IntroductionArchaea occur ubiquitously, are abundant in aquatic and terrestrial habitats, and play an import-ant role in global biogeochemical cycles (Jarrell et al., 2011). Marine sediments have been shown to harbor a diverse archaeal community, of which ammonia-oxidizing Thaumarchaeota (marine group I.1a) are the most studied (Pester et al., 2011). Recent genomic studies have revealed the presence of other benthic archaeal groups, such as Miscellaneous Crenarchaeota Group (MCG), Marine Benthic Group-B and D, and archaea of the DPANN superphylum, in marine sediments, which are predicted to be involved in degradation of polymers and proteins under anoxic con-ditions (Castelle et al., 2015; Lloyd et al., 2013, Meng et al., 2014).
Archaeal lipids occur widespread in marine sediments and are commonly used as biomarkers of Archaea both in present-day systems and in past depositional environments. However, their biological sources are not well constrained, especially in the light of the expanding archaeal di-versity. Archaeal lipids in marine surface sediments are thought to be derived mainly from pelagic Thaumarchaeota, which due to grazing and packing in fecal pellets are efficiently transported to the sediment where they get preserved in the sedimentary record (Huguet et al., 2006b). Thaumarchaeota are known to synthesize isoprenoid glycerol dibiphytanyl glycerol tetraether (GDGT) containing 0–4 cyclopentane moieties (GDGT-0 to GDGT-4) as well as the GDGT crenarchaeol (Sinninghe Damsté et al., 2002), containing four cyclopentane moieties and a cy-clohexane moiety, which is considered to be characteristic of this phylum (Pearson et al., 2004; Zhang et al., 2006; Pester et al., 2011; Pitcher et al., 2011a; Sinninghe Damsté et al., 2012). The distribution of thaumarchaeotal GDGTs in the marine environment has been shown to be affected by temperature, i.e. with increasing temperature there is an increase in the relative abun-dance of cyclopentane-containing GDGTs (Schouten et al., 2002; Wuchter et al., 2004, 2005). Based on this relationship, the TEX86 paleotemperature proxy was developed and calibrated on sea surface temperature (e.g. Schouten et al., 2002; Kim et al., 2010) and it has been widely ap-plied for more than a decade (Schouten et al., 2013).
Although it is generally thought that GDGTs in marine sediments derive from surface-derived thaumarchaeotal biomass (e.g. Wakeham et al., 2003), some studies have addressed the possibility of a potential contribution of lipids from benthic archaea to the fossil record, which would be relevant for the reliability of TEX86 (Shah et al., 2008; Biddle et al., 2006; Lipp et al., 2008; Lipp and Hinrichs, 2009). Archaeal intact polar lipids (IPLs), where the core lipid (CL) GDGTs are attached to polar head groups from the building blocks of membranes of living cells with phos-pho head groups have been shown to degrade rapidly upon death of the source organism (White et al., 1979; Harvey et al., 1986), while IPLs with glyco polar head groups may be preserved over (much) longer timescales (Lipp et al., 2008; Lipp and Hinrichs, 2009; Bauersachs et al., 2010). IPLs of Archaea have been detected in surface marine sediments and used as biomarkers of the presence of living in situ benthic Archaea (Biddle et al., 2006; Lipp et al., 2008; Lipp and Hin-richs, 2009; Lengger et al., 2012). Evidence has been presented that the IPL-GDGTs produced in situ in the surface sediments are rapidly recycled upon burial (Lengger et al., 2012). Some studies have suggested that benthic marine archaea recycle fossil CL-GDGTs when producing IPL-GDGTs de novo to decrease energy requirements (Liu et al., 2011; Takano et al., 2010).
With the exception of Thaumarchaeota, the membrane lipid composition of other phyla of benthic archaea present in marine sediments has not been yet characterized and, therefore, their potential impact on the archaeal lipid pool preserved in the sedimentary record remains un-
149
Introduction/Material and Methods
known. In surface sediments where oxygen is still available, Thaumarchaeota are expected to be dominant due to their oxygenic metabolism as nitrifiers (Könneke et al., 2005, Wuchter et al., 2006). However in subsurface sediments, where oxygen is no longer present, archaeal groups such as MBG-D, MCG, Thermoplasmatales and methanogens have been reported to be pre-dominant (Lloyd et al., 2013; Kubo et al., 2012), and may contribute to the total archaeal lipid pool in marine sediments. Recent studies have also observed a high presence of archaea of the superphylum DPANN both in surface and subsurface coastal marine sediments (Choi et al., 2016), as well as in freshwater systems (Ortiz-Alvarez et al., 2016; Ma et al., 2016). However, their contribution to the sedimentary archaeal lipid pool is expected to be negligible as their small genomes (Castelle et al., 2015) lack the genes of the membrane lipid biosynthetic pathway, suggesting that they rely on host cells or cell debris for the synthesis of their lipids (Waters et al., 2003; Jahn et al., 2004).
Here, we determined the archaeal abundance and composition using DNA-based methods in surface sediments of a seasonally hypoxic marine lake with different oxygen and sulfide bottom water concentrations and compared this with the composition of the archaeal IPLs. We aim to identify the potential biological sources of the archaeal IPL lipids detected in surface sediments under changing environmental conditions which could impact the biology of the producer but also the preservation potential of the archaeal lipids.
6.2. Material and Methods
6.2.1. Study site, sediment sampling and physicochemical analysesLake Grevelingen is a former estuary located within the Rhine-Meuse-Scheldt delta area of the Netherlands. The delta became a closed saline reservoir (salinity ~30) by dam construction at both the land side and sea side in the early 1970s. As a result of the absence of tides and strong currents, Lake Grevelingen experiences a seasonal stratification of the water column, which in turn, leads to a depletion of oxygen in the bottom waters (Hagens et al., 2015). Bottom water oxygen concentration at the deepest stations starts to decline in April, reaches hypoxic condi-tions by end of May (O2 < 63 µM), and further decreases to reach the state of anoxia in August (O2 < 0.1 µM), while re-oxygenation of the bottom water takes place in September (Seitaj et al., 2015).
Two sampling campaigns were performed on March 13th, 2012 (before the start of the annual O2 depletion) and on August 20th, 2012 (at the peak of the annual O2 depletion). Detailed water column, pore water and solid sediment chemistry of Lake Grevelingen over the year 2012 have been previously reported (Seitaj et al., 2015; Sulu-Gambari et al., 2016, Hagens et al., 2015). In-tact sediment cores were recovered at three stations along a depth gradient within the Den Osse basin, one of the deeper basins in Marine Lake Grevelingen: Station 1 (S1) was located in the deepest point (34 m) of the basin (51.747°N, 3.890°E), Station 2 (S2) at 23 m depth (51.749°N, 3.897°E) and Station 3 (S3) at 17 m depth (51.747°N, 3.898°E) (Fig. S1). Sediment cores were retrieved with a single core gravity corer (UWITEC) using PVC core liners (6 cm inner diameter, 60 cm length). Further details of sediment sampling have been previously described in detail (Chapter 4). Four sediment cores were sliced with a 1 cm resolution (for the purposes of this study we only focused on the top centimeter) for lipid and DNA/RNA analysis and kept at –80ºC until further processing.
Chapter 6
150
The total organic carbon (TOC) content of the sediment was determined on sub-samples that were freeze-dried, ground to a fine powder and analyzed by an a Thermo Finnigan Delta plus isotope ratio monitoring mass spectrometer (irmMS) connected to a Flash 2000 elemental analyzer (Thermo Fisher Scientific, Milan). Before the analysis, samples were first acidified with 2N hydrogen chloride (HCl) to remove the inorganic carbon (Nieuwenhuize et al., 1994). Con-centrations of TOC are expressed as mass % of dry sediment. Oxygen, sulfide, bottom water and pore water ammonium, nitrite and nitrate were determined as previously described (Malkin et al., 2014; Seitaj et al., 2015) and reported in Chapter 5.
6.2.2. DNA/RNA extractionSediment was centrifuged and the excess of water was removed by pipetting before proceeding with the extraction of nucleic acids from the sediment. DNA/RNA of surface (0–1 cm) sedi-ments was extracted with the RNA PowerSoil® Total Isolation Kit plus the DNA elution acces-sory (Mo Bio Laboratories, Carlsbad, CA). Concentration of DNA was quantified by Nanodrop (Thermo Scientific, Waltham, MA) and Fluorometric with Quant-iTTM PicoGreen® dsDNA Assay Kit (Life technologies, Netherlands).
6.2.3. 16S rRNA gene amplicon sequencing and sequencing analysesPCR reactions were performed with the universal, Bacteria and Archaea, primers S-D-Arch-0159-a-S-15 and S-D-Bact-785-a-A-21 (Klindworth et al., 2013) as previously described in Moore et al. (2015). The archaeal 16S rRNA gene amplicon sequences were analyzed by QIIME v1.9 (Caporaso et al., 2010). Raw sequences were demultiplexed and then quality-filtered with a minimum quality score of 25, length between 250–350, and allowing maximum two errors in the barcode sequence. Taxonomy was assigned based on blast and the SILVA database version 123 (Altschul et al., 1990; Quast et al., 2013). The 16S rRNA gene amplicon reads (raw data) have been deposited in the NCBI Sequence Read Archive (SRA) under BioProject no. PRJNA293286.
6.2.4. PCR amplification, cloning and archaeal 16S rRNA gene quantificationAmplification of the archaeal amoA gene was performed as described by Yakimov et al. (2011). PCR reaction mixture was the following (final concentration): Q-solution 1 × (PCR additive, Qiagen); PCR buffer 1 ×; BSA (200 µg ml–1); dNTPs (20 µM); primers (0.2 pmol µl–1); MgCl2 (1.5 mM); 1.25 U Taq polymerase (Qiagen, Valencia, CA, USA). PCR conditions for these ampli-fications were the following: 95°C, 5 min; 35 × 95°C, 1 min; 55°C, 1 min; 72°C, 1 min]; final ex-tension 72°C, 5 min. PCR products were gel purified (QIAquick gel purification kit, Qiagen) and cloned in the TOPO-TA cloning® kit from Invitrogen (Carlsbad, CA, USA) and transformed in E. coli TOP10 cells following the manufacturer’s recommendations. Recombinant clones plasmid DNAs were purified by Qiagen Miniprep kit and screening by sequencing (n ≥ 30) using M13R primer by BaseClear (Leiden, The Netherlands). Obtained archaeal amoA protein sequences were aligned with already annotated amoA sequences by using the Muscle application (Edgar, 2004). Phylogenetic trees were constructed with the Neighbor-Joining method (Saitou and Nei, 1987) and evolutionary distances computed using the Poisson correction method with a boot-strap test of 1,000 replicates. Quantification of archaeal 16S rRNA gene copies was performed by quantitative PCR (qPCR) by using the primers Parch519F and ARC915R as previously de-scribed (Pitcher et al., 2011b).
151
Material and Methods/Results
6.2.5. Lipid extraction and analysisTotal lipids were extracted from surface (upper 0–1 cm) sediments after freeze-drying using a modified Bligh and Dyer method (Bligh and Dyer, 1959) following an experimental protocol previously described by Lengger et al. (2014). The extracts were then dissolved by adding solvent (hexane:isopropanol:H2O 718:271:10 [v/v/v/v]) and filtered through a 0.45 µm, 4 mm-diameter True Regenerated Cellulose syringe filter (Grace Davison, Columbia, MD, USA).
IPLs were analyzed with Ultra High Pressure Liquid Chromatography- High Resolution Mass spectrometry (UHPLC-HR MS). An Ultimate 3000 RS UHPLC, equipped with thermostated auto-injector and column oven, coupled to a Q Exactive Orbitrap MS with Ion Max source with heated electrospray ionization (HESI) probe (Thermo Fisher Scientific, Waltham, MA), was used. Separation was achieved on a YMC-Triart Diol-HILIC column (250 x 2.0 mm, 1.9 µm particles, pore size 12 nm; YMC Co., Ltd, Kyoto, Japan) maintained at 30°C. The following elution program was used with a flow rate of 0.2 mL min–1: 100% A for 5 min, followed by a linear gradient to 66% A: 34% B in 20 min, maintained for 15 min, followed by a linear gradient to 40% A: 60% B in 15 min, followed by a linear gradient to 30% A: 70% B in 10 min, where A = hexane/2-propanol/formic acid/14.8 M NH3aq (79:20:0.12:0.04 [v/v/v/v]) and B = 2-propa-nol/water/formic acid/ 14.8 M NH3aq (88:10:0.12:0.04 [v/v/v/v]). Total run time was 70 min with a re-equilibration period of 20 min in between runs. HESI settings were as follows: sheath gas (N2) pressure 35 (arbitrary units), auxiliary gas (N2) pressure 10 (arbitrary units), auxiliary gas (N2) T 50 ˚C, sweep gas (N2) pressure 10 (arbitrary units), spray voltage 4.0 kV (positive ion ESI), capillary temperature 275 °C, S-Lens 70 V. IPLs were analyzed with a mass range of m/z 375 to 2000 (resolution 70,000), followed by data-dependent MS2 (resolution 17,500), in which the ten most abundant masses in the mass spectrum (with the exclusion of isotope peaks) were fragmented successively (stepped normalized collision energy 15, 22.5, 30; isolation window 1.0 m/z). An inclusion list was used with a mass tolerance of 3 ppm to target specific compounds (supplementary File S1). The Q Exactive Orbitrap MS was calibrated within a mass accuracy range of 1 ppm using the Thermo Scientific Pierce LTQ Velos ESI Positive Ion Calibration Solution (containing a mixture of caffeine, MRFA, Ultramark 1621, and N-butylamine in an acetonitrile-methanol-acetic solution). IPLs were quantified by integrating the summed mass chromatograms (within 3 ppm mass accuracy) of the dominant adduct formed (in case of MH-, DH- and HPH-IPLs the ammoniated adduct) and the first isotopomer and reported as peak area response per gram of dry sediment extracted, due to the lack of quantitative standards (for details see Pitcher et al., 2011b).
The total lipid extracts from the surface sediments were further analyzed by acid hydrolysis to determine the composition and relative abundance of IPL-derived CL (resulting from the acid hydrolysis of IPLs) and CL-GDGTs using the method described by Lengger et al. (2012) and analyzed by via high-performance liquid chromatography-atmospheric pressure chemical ioniza-tion/mass spectrometry (HPLC-APCI/MS) (Schouten et al., 2007) using an internal C46 GTGT standard as described previously (Huguet al. 2006a).
6.3. Results
6.3.1. Physicochemical conditionsThe seasonal variation of the bottom water oxygen concentration in Lake Grevelingen strongly
Chapter 6
152
influenced the bottom and pore water concentrations of O2 and sulfide (Table 1). In March, bot-tom waters were fully oxygenated in all stations (299–307 μM), oxygen penetrated 1.8–2.6 mm deep in the sediment, and no free sulfide was recorded in the first few centimeters (Hagens et al., 2015). The width of the suboxic zone, operationally defined as the sediment layer located between the oxygen penetration depth (OPD) and the sulfide appearance (SAD), varied between 16–39 mm across the three stations in March 2012. In contrast, in August, oxygen was strongly depleted in the bottom waters at S1 (<0.1 μM) and S2 (11 μM), and no O2 was detected by mi-crosensor profiling in the surface sediment at these two stations. At station S3, the bottom water concentration of O2 remained higher (88 μM), and oxygen still penetrated into the surface sed-iment down to 1.1 mm. In August, free sulfide was present near the sediment-water interface at all three stations, and the concentration of sulfide in the pore water increased with water depth.
Bottom water ammonium (NH4+) concentrations in station S1 ranged from 3 µM in March to
11.5 µM in August; nitrite (NO2–) concentrations were relatively constant (0.7–1 µM) in March
and August. Nitrate concentrations ranged from 28 µM in March to <2 µM in August in station S1, whereas in stations S2 and S3 values varied between 28 µM in March to ~10 µM in August (Table 1; for detailed bottom water biogeochemistry see Seitaj et al., 2015; Sulu-Gambari et al., 2016; Hagens et al., 2015; Chapter 4).The TOC content of the sediments varied slightly between stations and seasons, ranging between 1.8 and 4.4% as described previously (Table 1; Chapter 4).
6.3.2. Archaeal lipid diversity and distributionThe archaeal IPL GDGT concentration (quantified as IPL-derived CLs) was almost an order of magnitude higher in March in all stations in comparison with the values in August, although this drop was less for station 3, where slightly lower concentrations of GDGT-0 and crenarchaeol were detected in March in comparison with the other stations (Table 2). In March, total IPL-GDGTs were mostly distributed between IPL-GDGT-0 (approximately 5 μg g–1 dry weight of sediment) and IPL-crenarchaeol (average 2.6 μg g–1). In August, the total IPL-GDGT abundance was lower in comparison with March (approximately an order of magnitude less), while the dis-tribution did not change (Table 2). CL-GDGT abundance was also higher in March (26 to 79 μg g–1 dry weight of sediment) than in August (5 to 15 μg g–1 dry weight of sediment) (Table 2). CL-GDGT abundances were also higher than those of IPL-GDGTs at all stations and seasons (Table 2). In station 1 it was on average three times higher both in March and in August. On the other hand in station 2, CL-GDGTs were in average 8 times higher than IPL-GDGTs in March, and 30 times higher in August, with CL-crenarchaeol as the most abundant CL-GDGT in August (8 μg g–1 dry weight of sediment; Table 2), 40 times more of that detected for IPL-cre-narchaeol (0.2 μg g–1; Table 2). In station 3, CL-GDGTs were on average 4 times higher in con-centration than IPL-GDGTs (Table 2).
The IPL composition was assessed by UHPLC-HRMS analysis and various GDGT-IPLs and archaeol-IPLS were specifically targeted by using an inclusion list as part of the analytical rou-tine (see supplementary File S1). Within the various IPL types detected, the distribution of observed cores was comparable to the distribution obtained after analysis of the IPL-derived CLs. IPLs with GDGT-0 and crenarchaeol as CL are the most abundant IPLs, with the highest concentrations in March (approximately 1010 response units g–1), while IPLs with GDGT-1 and -2 as CLs were two orders of magnitude less abundant (Table 3). In August, total IPL-GDGT concentrations decreased by two orders of magnitude as compared with the concentrations in
153
ResultsTa
ble
1: P
hysic
oche
mic
al p
aram
eter
s of
the
botto
m w
ater
and
surf
ace
sedi
men
t (0–
1 cm
) in
the
thre
e st
atio
ns in
Lak
e G
reve
linge
n in
sprin
g (M
arch
) an
d in
sum
mer
(Aug
ust).
Dat
a in
clud
ed in
Sei
taj e
t al.,
201
5; S
ulu-
Gam
bari
et a
l., 2
016;
Hag
ens e
t al.,
201
5; C
hapt
er 4
and
5.
Bot
tom
wat
erSt
atio
n 1
Stat
ion
2St
atio
n 3
Aug
ust
Mar
chA
ugus
tM
arch
Aug
ust
Mar
ch
Tem
pera
ture
[°C
]5
175
175
19
O2 [
μM]
299
030
112
307
88
(oxi
c)(a
noxi
c)(o
xic)
(hyp
oxic
)(o
xic)
(hyp
oxic
)
NH
4+ [μ
M]
3.2
11.5
3.0
4.3
2.8
2.5
NO
2− [μ
M]
0.7
1.0
0.7
0.7
0.7
0.1
NO
3− [μ
M]
28.2
1.7
27.9
11.6
27.7
10.6
Surf
ace
sedi
men
t
HS−
[μM
]0
810
011
570
211
NH
4+ [μ
M]
279
656
165
550
7353
7
TOC
[%]
2.86
1.81
3.11
2.38
2.87
3.04
OPD
[mm
]1.
8±0.
040
2.6±
0.65
02.
4±0.
41.
1±0.
1
SAD
[mm
]17
.5±
0.7
0.9±
1.1
21.3
±2.
50.
6±0
41.8
±8.
64.
2±2.
7Bo
ttom
wat
er is
cla
ssifi
ed a
s ano
xic
with
O2 c
once
ntra
tion
belo
w 1
μM
and
hyp
oxic
bel
ow 6
3 μM
; OPD
: O2 p
enet
ratio
n de
pth;
SA
D: ∑
H2S
app
eara
nce
dept
h.
Chapter 6
154
Tabl
e 2:
Abu
ndan
ce a
nd d
istrib
utio
na o
f IP
L-de
rived
(rel
ease
d by
aci
d hy
drol
ysis)
and
CL
GD
GTs
(µg
g-1 o
f dr
y w
eigh
t) in
the
surf
ace
sedi
men
t (0–
1 cm
) of
the
thre
e st
atio
ns in
Lak
e G
reve
linge
n in
sprin
g (M
arch
) and
in su
mm
er (A
ugus
t).
Stat
ion
1St
atio
n 2
Stat
ion
3M
arch
Aug
ust
Mar
chA
ugus
tM
arch
Aug
ust
IPL-
deriv
ed
GD
GTs
GD
GT-
05.
1 (5
6.9)
0.8
(48.
2)5.
9 (6
0.5)
0.2
(45.
5)3.
0 (5
8.6)
1.7
(54.
6)
GD
GT-
10.
4 (4
.6)
0.1
(5.5
)0.
4 (4
.4)
0.02
(4.9
)0.
3 (5
)0.
1 (4
.6)
GD
GT-
20.
2 (2
.2)
0.1
(3.7
)0.
2 (2
.2)
0.01
(2.6
)0.
1 (2
.7)
0.1
(2.3
)
GD
GT-
30.
1 (0
.9)
0.02
(1.3
)0.
1 (0
.8)
0.01
(1.1
)0.
05 (1
)0.
03 (0
.9)
Cre
nb3.
1 (3
4.8)
0.6
(40.
8)3.
1 (3
1.6)
0.2
(44.
8)1.
7 (3
2.5)
1.1
(37.
2)
Cre
n’b
0.04
(0.5
)0.
01 (0
.5)
0.04
(0.4
)0.
01 (1
.1)
0.02
(0.3
)0.
01 (0
.4)
Tota
l9.
01.
69.
70.
55.
13.
0
CL-
GD
GTs
GD
GT-
012
.9 (4
4)2.
1 (4
3)36
.2 (4
6)5.
8 (3
9.3)
11.8
(45.
3)2.
9 (4
0.8)
GD
GT-
11.
1 (3
.7)
0.2
(3.6
)2.
9 (3
.7)
0.5
(3.5
)0.
9 (3
.5)
0.2
(3.5
)
GD
GT-
20.
5 (1
.6)
0.1
(1.6
)1.
3 (1
.6)
0.2
(1.4
)0.
4 (1
.5)
0.1
(1.5
)
GD
GT-
30.
2 (0
.8)
0.04
(0.7
)0.
6 (0
.8)
0.1
(0.7
)0.
2 (0
.7)
0.05
(0.7
)
Cre
n14
.5 (4
9.5)
2.5
(50.
5)37
.5 (4
7.6)
8.1
(54.
8)12
.7 (4
8.8)
3.7
(53)
Cre
n’0.
1 (0
.4)
0.03
(0.5
)0.
3 (0
.4)
0.04
(0.3
)0.
1 (0
.2)
0.04
(0.6
)To
tal
29.2
4.9
78.8
14.8
26.0
7.1
a Val
ues b
etw
een
pare
nthe
ses c
orre
spon
d to
the
frac
tiona
l (re
lativ
e) a
bund
ance
of
each
indi
vidu
al G
DG
T as
the
conc
entra
tion
of th
e in
divi
dual
GD
GT
divi
ded
by th
e su
m o
f th
e co
ncen
tratio
n of
all
GD
GTs
in th
at fr
actio
n. b
Cre
n =
Cre
narc
haeo
l, C
ren’
= c
rena
rcha
eol r
egio
isom
er.
155
Results Ta
ble
3: A
bsol
ute
abun
danc
e as
resp
onse
uni
ts p
er g
ram
of
dry
wei
ght o
f de
tect
ed a
rcha
eal G
DG
T IP
Ls in
surf
ace
sedi
men
ts (0
–1cm
).
GD
GT
IPL
Stat
ion
1St
atio
n 2
Stat
ion
3
Mar
chA
ugus
tM
arch
Aug
ust
Mar
chA
ugus
t
GD
GT-
0-M
H9.
4×10
7 1.
3×10
7 3.
1×10
8 4.
4×10
7 1×
108
4.9×
107
GD
GT-
0-D
H6.
3×10
7 n.
d.7.
3×10
7 n.
d.6.
7×10
7 n.
d.
GD
GT-
0-D
H’
2×10
8 n.
d.2.
1×10
8 n.
d.1.
4×10
8 2.
6×10
7
GD
GT-
0-H
PH1.
7×10
10
3.3×
108
1.9×
1010
8.
5×10
8 1.
4×10
101.
8×10
9
GD
GT-
1-M
H9.
4×10
7 n.
d.8.
9×10
6 n.
d.1.
2×10
6 n.
d.
GD
GT-
1-D
H1.
9×10
8 n.
d.2.
1×10
8 n.
d.6.
2×10
7 n.
d.
GD
GT-
1-D
H’
n.d.
n.d.
n.d.
n.d.
8.2×
107
n.d.
GD
GT-
1-H
PH4.
6×10
8 n.
d.3.
4×10
8 n.
d.5.
2×10
8 n.
d.
GD
GT-
2-D
H1.
4×10
8 n.
d.2.
7×10
8 n.
d.1.
1×10
8 n.
d.
GD
GT-
3-D
H8×
106
n.d.
2.7×
107
n.d.
1×10
7 n.
d.
GD
GT-
3-D
H’
n.d.
n.d.
1.2×
107
n.d.
n.d.
n.d.
GD
GT-
4-D
H7.
8×10
7 n.
d.1.
5×10
8 n.
d.5×
107
n.d.
GD
GT-
4-D
H’
n.d.
n.d.
n.d.
n.d.
1.3×
107
n.d.
Cre
narc
haeo
l-MH
1.5×
108
5.3×
107
3.1×
108
5.7×
107
9.5×
107
7×10
7
Cre
narc
haeo
l-HPH
1.1×
1010
2.4×
108
8.5×
109
6.1×
108
6.6×
109
1.5×
109
Arc
haeo
l-DH
3.8×
108
n.d.
n.d.
n.d.
n.d.
n.d.
Tota
l ru
g–13.
0×10
108.
7×10
83.
0×10
101.
6×10
92.
2×10
103.
4×10
9
’isom
ers o
f sp
ecifi
c G
DG
Ts; n
.d.:
not d
etec
ted.
MH
: mon
ohex
ose,
DH
: Dih
exos
e, H
PH, h
exos
e ph
osph
ohex
ose.
Chapter 6
156
Tabl
e 4:
Arc
haea
l cla
sses
abu
ndan
ces (
cells
g–1
of
sedi
men
t) ca
lcul
ated
by
mul
tiply
ing
the
perc
enta
ges o
f to
tal a
rcha
eal 1
6S rR
NA
gen
e re
ads b
y th
e ar
chae
al 1
6S rR
NA
gen
e ab
unda
nce
(cop
y nu
mbe
r g–1
of
sedi
men
t) de
tect
ed in
the
surf
ace
sedi
men
t (0–
1cm
) of
the
thre
e st
atio
ns in
Mar
ch a
nd in
A
ugus
t, as
sum
ing
one
16S
rRN
A g
ene
copy
num
ber p
er g
enom
e.
orga
nism
Stat
ion
1St
atio
n 2
Stat
ion
3
Mar
chA
ugus
tM
arch
Aug
ust
Mar
chA
ugus
t
The
rmop
lasm
ata,
20a-
9n.
dn.
dn.
d7.
8 ×
108
n.d
2.0
×10
8
The
rmop
lasm
atal
es, A
MO
S1A
-411
3-D
04n.
dn.
d5.
5 ×
107
6.0
×10
74.
1 ×
108
6.0
×10
8
The
rmop
lasm
atal
es, C
CA
47n.
dn.
d1.
7 ×
108
2.4
×10
82.
3 ×
108
1.7
×10
7
The
rmop
lasm
atal
es, M
BG-D
& D
HV
EG
-1n.
d1.
1 ×
108
6.1
×10
87.
8 ×
108
1.2
×10
82.
0 ×
108
The
rmop
lasm
atal
es, V
C2.
1 A
rc6
n.d
n.d
1.1
×10
83.
0 ×
108
5.8
×10
71.
2 ×
109
Sum
of
read
s The
rmop
lasm
atal
esn.
d1.
1 ×
108
9.4
×10
81.
4 ×
109
8.2
×10
83.
7 ×
109
Misc
ella
neou
s Cre
narc
haeo
ta G
roup
, C3
9.9
×10
71.
1 ×
108
1.7
×10
82.
1 ×
109
n.d
9.0
×10
8
Tha
umar
chae
ota,
Mar
ine
Gro
up I,
Nitr
osop
umilu
s5.
8 ×
109
n.d
3.1
×10
92.
9 ×
109
2.2
×10
101.
2 ×
109
Misc
ella
neou
s Eur
yarc
haeo
tic G
roup
(ME
G)
n.d
n.d
n.d
1.4
×10
9n.
dn.
d
DPA
NN
, Woe
sear
chae
ota
DH
VE
G-6
1.1
×10
94.
2 ×
109
2.0
×10
91.
9 ×
1010
6.4
×10
91.
2 ×
1010
MBG
-Bn.
dn.
dn.
d9.
0 ×
108
n.d
1.0
×10
9
Oth
ers
4.9
×10
7n.
d2.
2 ×
108
6.0
×10
71.
5 ×
109
2.3
×10
9
Tota
l arc
haea
l abu
ndan
ce [c
ell g
–1]
7.1×
109
4.4×
109
6.5×
109
2.8×
1010
3.1×
1010
2.1×
1010
Tota
l CL-
GD
GTs
and
IPL-
deriv
ed G
DG
T m
g g–1
38.2
6.5
88.5
15.3
31.1
10.1
Cal
cula
ted
fem
togr
ams o
f G
DG
T pe
r cel
l1.
37.
53.
09.
81.
42.
9n.
d =
not
det
ecte
d. M
BG-D
, Mar
ine
Bent
hic
Gro
up D
; MBG
-B, M
arin
e Be
nthi
c G
roup
B.
157
Results
Figu
re 1:
(A) P
erce
ntag
es o
f to
tal a
rcha
eal 1
6S rR
NA
gen
e rea
ds [%
] and
(B) a
rcha
eal 1
6S rR
NA
gen
e abu
ndan
ce [c
opy n
umbe
r g–1
of
sedi
men
t] de
tect
ed
in th
e su
rfac
e se
dim
ent (
0–1c
m) o
f th
e th
ree
stat
ions
in M
arch
and
in A
ugus
t. O
nly
arch
aeal
gro
ups w
ith p
erce
ntag
es >
3% ar
e re
port
ed. q
PCR
cond
ition
s, ef
ficie
ncy
= 9
0%; R
2=0.
991.
Chapter 6
158
March. In March both IPLs with GDGT-0 and crenarchaeol cores were mostly found with hexose phosphohexose (HPH) as IPL type, while in August the IPL type MH increased at the expense of HPH (Table 3).
6.3.3. Archaeal 16S rRNA gene diversity and abundanceArchaeal diversity was estimated by 16S rRNA gene amplicon sequencing using universal prim-ers. The archaeal community was dominated by Thaumarchaeota marine group I (MGI) in March both in station 1 and 3 with 72–82% of the total archaeal reads (Fig. 1A, Table S1). In station 2 these archaea were slightly less dominant but still comprised almost half of the total archaeal reads. Other archaeal groups were also present in the surface sediment in March in addition to MGI such as members of the DPANN Woesearchaeota (DHVE-6) (16–31%), Thermoplasmatales (3–14%), and MCG (1.4–2.5%). In August, the percentage of reads attribut-ed to the DPANN Woesearchaeota increased notably from 16 to 95% in station 1, from 31 to 66% in station 2, and from 21 to 57% in station 3 at the expense of the reads assigned to the Thaumarchaeota MGI (Fig. 1A, Table S1). In addition, a slight increase of percentage of reads was observed from March to August for archaea affiliated to the MCG and Thermoplasmatales groups. Total archaeal abundance estimated by qPCR with general archaea 16S rRNA gene prim-ers was comparable between March and August in all stations with slightly lower values in station 1 (average 6 × 109 gene copies g–1) and 1–2 × 1010 gene copies g–1 for station 2 and 3 (Fig. 1B).
The diversity of Thaumarchaeota was further analyzed by amplification, cloning and sequenc-ing of the amoA gene in the surface sediments of the three stations. All amoA sequences were closely related to sequences previously detected in marine surface sediments. Although certain variability was detected between the sequences recovered in different stations and seasons, no clear clustering was observed (Figs. S2A, B).
6.4. DiscussionThe seasonal changes in the oxygen and sulfide concentration in the bottom water of the ma-rine Lake Grevelingen trigger an important switch in the archaeal community composition in the surface sediment. The archaeal community changed considerably from a Thaumarchaeota MGI-dominated community in March, when oxygen was still present and sulfide was not (Table 1) to an archaeal community dominated by archaea of the DPANN superphylum. Besides, the seasonal change did not induce a diversity change within the Thaumarchaeota as indicated by the amoA gene phylogeny (Figs. S2A, B).
By multiplying the percentage of 16S rRNA gene reads of the Thaumarchaeota and the DPANN Woesearchaeota by the total archaea 16S rRNA gene copies per gram of sediments, we can estimate the abundances of these groups (assuming one 16S rRNA gene copy number per genome) (Table 4). For Thaumarchaeota, the abundance decreased dramatically in station 1 (from 6 × 109 cells g–1 to undetected) and in station 3 (2 × 1010 to 1.2 × 109 cells g–1), while in station 2 the abundance remained fairly constant (Table 4). On the other hand, members of the DPANN Woesearchaeota were the major component of the archaeal population in August in all stations with absolute numbers increasing in all stations (1 × 109 to 4.2 × 109 cells g–1 of sediment in station 1; 2 × 109 to 2 × 1010 cells g–1 in station 2, 6.4 × 109 to 1.2 × 1010 cells g–1 in station 3; Table 4). This change in the archaeal community is entirely compatible with the metabolism of both Thaumarchaeota and the DPANN archaea, which is aerobic (Könneke
159
Results/Discussion
et al., 2005) and anaerobic (Castelle et al., 2015), respectively. Also, nitrification conducted by Thaumarchaeota has been shown to be inhibited by sulfide (Berg et al., 2015), which additionally explains the decrease in the MGI population upon increase of the sulfide concentration in the summer. In the same way, the abundance of the other archaeal benthic groups, which increased in the surface sediments in August, such as the Thermoplasmatales and the MCG, are predicted to have an anaerobic metabolism based on their genome. The environmental control of the change in the archaeal community diversity is also supported by the fact that this change is less evident in the surface sediment of station 3, where oxygen was still present and the sulfide con-centration in summer was substantially lower than at stations 1 and 2 (Table 1). Although the seasonality changes in the physicochemical conditions in the bottom and pore water induced a large change in the archaeal community diversity, the total archaeal abundance remained fairly constant between seasons and in the different stations (Fig. 1B). The archaeal community analy-sis was conducted by primer-based 16S rRNA gene amplicon sequencing. Therefore, we cannot completely rule out a possible primer bias (Sipos et al., 2010; Schloss et al., 2011), although the underrepresentation of DPANN sequences in the databases would imply that if any those prim-er biases would negatively detect DPANN in our samples, which in that case would induce to a underestimation of this group.
The large change in the archaeal community composition in the surface sediments upon the decrease of oxygen concentration in the summer coincided with an order of magnitude decrease of the total IPL-GDGTs detected. The IPL-GDGT profiles in March were compatible with a Thaumarchaeota-dominated population, due to the relatively high abundance of crenarchaeol, the specific CL of Thaumarchaeota (Sinninghe Damsté et al., 2002). In addition, the IPL type of crenarchaeol (and all other main GDGTs) switched from mostly HPH to MH from March to August (Table 3). The predominance of HPH IPL-crenarchaeol has been previously interpreted as an indication of the presence of an active Thaumarchaeotal population synthesizing mem-brane lipids in situ (Lengger et al., 2012, 2014), due to the labile nature of HPH IPLs (Harvey et al., 1986; Schouten et al., 2010). On the other hand, glycolipid-type IPLs (here mostly MH) have been considered as fossil signal (Lengger et al., 2012, 2014) or, alternatively, as the preferred IPL type in conditions where the Thaumarchaeota are in a stationary phase of growth (Elling et al., 2014). This latter explanation is not likely in the case where the surface sediment became fully sulfidic.
Recent studies suggest that members of the DPANN have a reduced genome with limited metabolic capabilities (Rinke et al., 2013; Castelle et al., 2015), suggesting that these archaea may have a symbiotic or parasitic lifestyle. In addition, they also lack most if not all the genes coding for the enzymes of the archaeal lipid biosynthetic pathway (Jahn et al., 2004; Villanueva et al., 2017). They are, therefore, not expected to contribute to the total IPL-GDGT pool by actively synthesizing lipids but may recycle the membrane lipid of other archaea. The decline of the total archaeal IPL-GDGTs in August coinciding with the switch to a DPANN-dominant population with similar or even higher cell abundances to that reported in March would therefore imply that the DPANN Woesearchaeota make use of the preserved (‘fossil’) pool of IPL-GDGTs to make their membranes. A question with respect to this membrane lipid acquisition mechanism is whether the pool of ‘fossil’ IPL-GDGTs is able to fulfill the membrane requirements of the large archaeal DPANN population detected in the surface sediments sampled in August in view of the much reduced concentration of IPL-GDGTs, which is an order of magnitude lower. This
Chapter 6
160
can only work when the DPANN archaea have a much smaller cell size than the Thaumarchae-ota that thrive in spring. The size of the DPANN Woesearchaeota present in Lake Grevelingen surface sediment is unknown. The only characterized archaeon from the DPANN superphylum is Nanoarchaeum equitans, which is considered to be a symbiont of the archaeon Ignicoccus sp. by growing on its surface. The lipids of N. equitans have been shown to be derived from Ignicoccus sp. (Jahn et al., 2004), but the uptake mechanisms remain unknown. N. equitans is 5 times smaller than its host, the archaeon Ignicoccus sp.. Assuming a similar size difference between the DPANN Woesearchaeota found in the Lake Grevelingen surface sediments and its potential host, suffi-cient IPLs would be available to sustain the DPANN population detected in the sediments in August.
Alternatively, the DPANN archaea could recycle the CL-GDGTs present in the sediment as previously suggested (Liu et al., 2011; Takano et al., 2010), which is presumed to involve hydro-lysis and reformation of the ether bond to the glycerol backbone as suggested by the 13C-glucose labeling studies of Takano et al. (2010). However, since the members of the DPANN generally lack the genes coding for the enzymes involved in producing the ether bonds to the glycerol backbone (Villanueva et al., 2017), this is unlikely. Alternatively, they could also use the CL-GDGTs and add the polar head groups de novo. Waters et al. (2003) observed the presence of genes for lipid modification, such as glycosylation, in the genome of N. equitans. We performed a search for the gene encoding cytidine diphosphate (CDP)-archaeol synthase (CarS, E.C. 2.7.7.67) that catalyzes the activation of 2,3-bis-O-geranylgeranylglyceryl diphosphate (DGGGP) by cyti-dine triphosphate (CTP) to form the intermediate for polar head group attachment (i.e. CDP-ar-chaeol), and we found homologs in most of the DPANN Micrarchaeota genomes and in some of the DPANN Parvarchaeota and Diapherotrites (perfomed by find function in JGI Integrated Microbial Genomes, IMG with genomes available in July 2017). However, the genes coding for the enzymes that catalyze the subsequent replacement of cytidine monophosphate of the cyt-idine diphosphate (CDP)-archaeol of CDP-diacylglycerol with a polar head group in DPANN genomes were not detected, in contrast to N. equitans (Waters et al., 2003). This may indicate that the members of the DPANN either do not have the capacity of adding the polar head groups to the CL-GDGT or that the polar head groups of their IPLs are different and added by enzymes different to those already characterized.
6.5. ConclusionWe observed a dramatic change in the archaeal community composition and lipid abundance in surface sediments of a seasonally hypoxic marine lake which corresponded to a switch from a Thaumarchaeota-dominated to a DPANN-dominated archaeal community, while the total IPLs detected were significantly reduced. Considering the reduced genome of the members of the superphylum DPANN and their apparent inability to synthesize their own membrane lipids, we hypothesize that they use the CLs previously synthesized by the Thaumarchaeota to form their membrane.
Acknowledgements
We acknowledge the crew of the R/V Luctor and Pieter van Rijswijk for their help in the field during sediment collection, Marcel van der Meer and Sandra Heinzelmann for support onboard
161
Discussion/Conclusion/Supplementary Material
and assistance with incubations, Elda Panoto for technical support, and Eric Boschker and Filip Meysman for helpful discussions. This work was financially supported by the Darwin Centre for Biogeosciences to LV (grant no: 3062). LV and JSSD receive funding from the Soehngen Institute for Anaerobic Microbiology (SIAM) through a Gravitation Grant (024.002.002) from the Dutch Ministry of Education, Culture and Science (OCW).
Figure S1: Scheme of the sampling locations in Lake Grevelingen
Chapter 6
162
Tabl
e S1
: Per
cent
ages
of
tota
l arc
haea
l 16S
rRN
A g
ene
read
s [%
] det
ecte
d in
the
surf
ace
sedi
men
t (0–
1cm
) of
the
thre
e st
atio
ns in
Mar
ch a
nd in
Aug
ust.
Onl
y ar
chae
al g
roup
s with
per
cent
ages
>3%
are
repo
rted
.
orga
nism
Stat
ion
1St
atio
n 2
Stat
ion
3
Mar
chA
ugus
tM
arch
Aug
ust
Mar
chA
ugus
t
The
rmop
lasm
ata,
20a-
9n.
d.n.
d.n.
d.2.
7n.
d.0.
9
The
rmop
lasm
atal
es, A
MO
S1A
-411
3-D
04n.
d.n.
d.0.
80.
21.
32.
8
The
rmop
lasm
atal
es, C
CA
47n.
d.n.
d.2.
50.
80.
77.
9
The
rmop
lasm
atal
es, M
BG-D
& D
HV
EG
-1n.
d.2.
69.
32.
70.
40.
9
The
rmop
lasm
atal
es, V
C2.
1 A
rc6
n.d.
n.d.
1.7
1.1
0.2
5.6
Sum
of
read
s The
rmop
lasm
atal
esn.
d.2.
614
.44.
92.
617
.1
Misc
ella
neou
s Cre
narc
haeo
ta G
roup
, C3
1.4
2.6
2.5
7.4
n.d.
4.2
Tha
umar
chae
ota,
Mar
ine
Gro
up I,
Nitr
osop
umilu
s81
.9n.
d.48
.310
.172
.15.
6
Misc
ella
neou
s Eur
yarc
haeo
tic G
roup
(ME
G)
n.d.
n.d.
n.d.
5.1
n.d.
n.d.
DPA
NN
, Woe
sear
chae
ota
DH
VE
G-6
16.0
94.9
31.4
66.5
20.6
56.9
MBG
-Bn.
d.n.
d.n.
d.3.
2n.
d.4.
6
Oth
ers
0.7
n.d.
3.4
0.2
4.7
10.6
n.d
= n
ot d
etec
ted.
MBG
-D, M
arin
e Be
nthi
c G
roup
D; M
BG-B
, Mar
ine
Bent
hic
Gro
up B
.
163
Supplementary Material
Lake Grevelingen sediment; 0-1 cm depth; 2 seq March: 1 x S2, 1 x S3; 6 seq August: 2 x S1, 2 x S2, 2 x S3
Lake Grevelingen sediment; 0-1 cm depth; March S2 uncultured crenarchaeote, Elkhorn Slough sediment (DQ148892)
Lake Grevelingen sediment; 0-1 cm depth; August S1 Lake Grevelingen sediment; 0-1 cm depth; August S2
Lake Grevelingen sediment; 0-1 cm depth; March S2 Lake Grevelingen sediment; 0-1 cm depth; August S3
Lake Grevelingen sediment; 0-1 cm depth; 5 seq March: 2 x S1, 2 x S2, 1 x S3 Lake Grevelingen sediment; 0-1 cm depth; March S3
Lake Grevelingen sediment; 0-1 cm depth; August S2 Lake Grevelingen sediment; 0-1 cm depth; 4 seq March: 1 x S1, 3 x S2; 5 seq August: 1 x S1, 2 x S2, 2 x S3 Lake Grevelingen sediment; 0-1 cm depth; 2 seq March: 1 x S1, 1 x S3; 2 seq August: 1 x S1, 1 x S3
Lake Grevelingen sediment; 0-1 cm depth; March S3 Lake Grevelingen sediment; 0-1 cm depth; August S2
uncultured crenarchaeote clone, Elkhorn Slough sediment (DQ148771) uncultured archaeon clone, aquarium biofilter (AB373356) Lake Grevelingen sediment; 0-1 cm depth; March S1
Lake Grevelingen sediment; 0-1 cm depth; March S3 uncultured archaeon, marine aquaculture (AM295172)
uncultured crenarchaeote clone, marine sediment (FJ656584) Nitrosopumilus maritimus (SCM1) (CP000866) Lake Grevelingen sediment; 0-1 cm depth; 4 seq March: 2 x S1, 2 x S3
Lake Grevelingen sediment; 0-1 cm depth; March S3 Lake Grevelingen sediment; 0-1 cm depth; March S1
Lake Grevelingen sediment; 0-1 cm depth; August S3 Lake Grevelingen sediment; 0-1 cm depth; August S1
Lake Grevelingen sediment; 0-1 cm depth; 4 seq March: 1 x S1, 2 x S2, 1 x S3; 4 seq August: 1 x S2, 3 x S3 Lake Grevelingen sediment; 0-1 cm depth; March; S1
Lake Grevelingen sediment; 0-1 cm depth; March; S1 Lake Grevelingen sediment; 0-1 cm depth; August S1
uncultured archaeon clone, deep sea sediments (AB289355) uncultured crenarchaeote clone, Black Sea water 100 m (EF414231) Lake Grevelingen sediment; 0-1 cm depth; August S3
Lake Grevelingen sediment; 0-1 cm depth; March: 1 x S1; 6 seq August: 3 x S1, 2 x S2, 1 x S3
Lake Grevelingen sediment; 0-1 cm depth; 20 seq March: 5 x S1, 8 x S2, 7 x S3; 24 seq August: 5 x S1, 12 x S2, 7 x S3
Lake Grevelingen sediment; 0-1 cm depth; March; S2 Lake Grevelingen sediment; 0-1 cm depth; March; S1
Lake Grevelingen sediment; 0-1 cm depth; August S1 Lake Grevelingen sediment; 0-1 cm depth; March S2
Lake Grevelingen sediment; 0-1 cm depth; March S3 Lake Grevelingen sediment; 0-1 cm depth; 3 seq March: 1 x S1, 1 x 2, 1 x S3; 3 seq August: 2 x S1, 1 x S3
Lake Grevelingen sediment; 0-1 cm depth; August S2 Lake Grevelingen sediment; 0-1 cm depth; August S3
uncultured archaeon clone, deep sea sediments (AB289348)uncultured thaumarchaeota clone, Arabian Sea surface sediment (KJ509763)
uncultured archaeon clone (deep sea water column) (AB289377) Lake Grevelingen sediment; 0-1 cm depth; August S3
Lake Grevelingen sediment; 0-1 cm depth; 3 seq March: 1 x S1, 1 x S2, 1 x S3; 3 seq August: 2 x S1, 1 x S3
Lake Grevelingen sediment; 0-1 cm depth; 8 seq March: 2 x S1, 2 x S2, 4 x S3; 8 seq August: 2 x S1, 4 x S2, 2 x S3
Lake Grevelingen sediment; 0-1 cm depth; March S2 uncultured crenarchaeote clone, San Francisco Bay sediment (DQ148664)
Lake Grevelingen sediment; 0-1 cm depth; 2 seq August S3 Lake Grevelingen sediment; 0-1 cm depth; 3 seq March: 1 x S1, 1 x S2, 1 x S3
uncultured crenarchaeote clone, wastewater (HM589775) uncultured crenarchaeote clone, wastewater (HM191510) uncultured archaeon clone, freshwater aquaria (JN183601)53
96
73
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Figure S2A: Phylogenetic tree of amoA protein sequences recovered from the surface sediment (0–1 cm) of Stations 1, 2 and 3 in Lake Grevelingen during March and August (black bold: sequences retrieved in this study and closest relatives) constructed with the Neighbor-Joining method (Saitou and Nei, 1987). Scale bar indicates 2% sequence dissimilarity. The evolutionary distances were computed using the Poisson correc-tion method with a bootstrap test of 1,000 replicates (values higher than 50% are shown on the branches).
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uncultured crenarchaeote clone, Gulf of California (EU340510) uncultured crenarchaeote clone, Black Sea water 70 m (DQ148740) uncultured archaeon clone, Peruvian OMZ (FJ799200)
uncultured crenarchaeote clone, South China Sea 100m (EU885994) uncultured crenarchaeote clone, North Pacific subtropical gyre 130 m (EF106932)
uncultured crenarchaeote clone, tropical marine estuarine sediment (FJ601621) uncultured crenarchaeote clone, Elkhorn Slough sediments (DQ148805) uncultured crenarchaeote clone, ETNP OMZ 200 m (DQ148759)
uncultured crenarchaeote clone, intertidal sandy flat (EU099940) uncultured ammonia-oxidizing archaeon clone, salt marsh sediment (EU925267)
Candidatus Nitrosoarchaeum limnia (SFB1) (CM001158) uncultured crenarchaeote clone (Monterey Bay 30 m) (DQ148820)
uncultured crenarchaeote clone, Changjiang Estuary sediment (EU025183) uncultured Thaumarchaeota clone, Arabian Sea 170 m (KF512326)
uncultured archaeon clone, Peruvian OMZ (FJ799198) uncultured crenarchaeote clone, Pacific Ocean 150 m (GU364066)
Lake Grevelingen sediment; 0-1 cm depth; March S1 Lake Grevelingen sediment; 0-1 cm depth; August S2
uncultured crenarchaeote clone, San Francisco Bay sediment (DQ148670.1) Lake Grevelingen sediment; 0-1 cm depth; March S1 Lake Grevelingen sediment; 0-1 cm depth; March S2
uncultured crenarchaeote clone, Elkhorn Slough South Marsh (FJ227870) uncultured archaeon clone, aquarium biofilter (AB373264)
Cenarchaeum symbiosum (A) (DQ397569) uncultured crenarchaeote clone, San Francisco Bay sediment (DQ148654)
Candidatus Nitrosoarchaeum koreensis (My1) (HQ331117) uncultured crenarchaeote clon, Gulf of California (DQ148574)
uncultured crenarchaeote clone, Elkhorn Slough sediment (DQ148796) uncultured crenarchaeote clone, San Francisco Bay sediment (DQ148671) uncultured archaeon clone, hydrothermal vents (AB451499)
uncultured crenarchaeote clone, Gulf of California (EU340541) uncultured crenarchaeote clone, North pacific subtropical gyre 4000 m (EF106928) uncultured crenarchaeote clone, Black Sea 70 m (DQ148697) uncultured archaeon, sponge tissue (DQ333425)
uncultured crenarchaeote clone, ETNP OMZ 200 m (DQ148764) uncultured crenarchaeote, ETNP OMZ 200 m (DQ148750)
uncultured crenarchaeote clone, North East Atlantic 2502 m (EU810223) uncultured crenarchaeote clone, North East Atlantic 2502 m (EU810225)
uncultured crenarchaeote clone, ETNP OMZ 200 m (DQ148769) uncultured archaeon, sponge tissue (DQ333419) uncultured thaumarchaeota clone, Arabian Sea 1050 m (KF512379)
uncultured crenarchaeote clone, Gulf of California (EU340549) uncultured crenarchaeote clone, ETNP OMZ 200 m (DQ148746)
uncultured crenarchaeote clone, Gulf of Mexico (GQ250723) uncultured crenarchaeote clone, Juan de Fuca Ridge 2267 m (EU864296)
uncultured crenarchaeote clone, North Pacific subtropical gyre 700 m (EF106899) uncultured crenarchaeote clone, ETNP OMZ 200 m (DQ148762)
uncultured archaeon clone, Lake water (FN773449) uncultured archaeon clone, Lake water (FN773418)
uncultured archaeon clone, Lake water (FN773404) uncultured crenarchaeote clone, rhizosphere (EU667867)
Candidatus Nitrosotalea devanaterra (JN227489) uncultured crenarchaeote clone, forest soil (EF530119)
Candidatus Nitrosocaldus yellowstonii (EU239961) Candidatus Nitrososphaera vienensis (FR773159)
Candidatus Nitrososphaera gargensis (EU281321) uncultured crenarchaeote clone, vapour cave (DQ672686)99
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Figure S2B: Phylogenetic tree of amoA protein sequences recovered from the surface sediment (0–1 cm) of Stations 1, 2 and 3 in Lake Grevelingen during March and August (black bold: sequences retrieved in this study and closest relatives) constructed with the Neighbor-Joining method (Saitou and Nei, 1987). Scale bar indicates 2% sequence dissimilarity. The evolutionary distances were computed using the Poisson correc-tion method with a bootstrap test of 1,000 replicates (values higher than 50% are shown on the branches).
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The role of chemolithoautotrophic microorganisms has been considered to be of minor impor-tance in coastal marine sediments although it has not been investigated in depth. Additionally, the impact of seasonal hypoxic/anoxic conditions on microbial chemolithoautotrophy in coastal marine sediments has not been examined. Therefore, in this thesis the diversity, abundance and activity of specific groups of chemolithoautotrophic microorganisms involved in the nitrogen and sulfur cycling, such as ammonia oxidizing archaea and bacteria, denitrifying and anammox bacteria, sulfate reducing and sulfur oxidizing bacteria, as well as the total microbial communi-ty, has been determined in coastal sediments by using DNA/RNA- and lipid-based biomarker approaches. Results show the presence and potential importance of chemolithoautotrophs in the biogeochemical cycling of carbon, nitrogen and sulfur. Additionally, temporal changes of the diversity, abundance and activity of chemolithoautotrophic microorganisms coinciding with seasonal hypoxia in coastal sediments have been determined.
7.1. Physicochemical factors of the sediments harboring chemolithoautotrophs studied in the framework of this thesisIn this thesis, coastal sediments with different sediment properties and oxygen conditions were examined. In this section, I focus on the most important environmental factors affecting chem-olithoautotrophic microorganisms targeted in this thesis, i.e. aerobic (ammonia oxidizing archaea and bacteria, AOA and AOB) and anaerobic ammonia oxidizing (anammox) bacteria, denitrify-ing bacteria, as well as sulfate reducing and sulfur oxidizing bacteria including sulfide-dependent denitrifiers. Effects on the seasonal and spatial distribution of the diversity, abundance and ac-tivity of the target organisms, as well as applied methods are discussed in detail in the following sections.
Sediments of the Oyster Grounds (Chapter 2), a deep depression in the central North Sea and a temporary deposition center for sediment, play an important role in the carbon and nitrogen cycle in the region (van Raaphorst et al., 1998; Weston et al., 2008). High levels of benthic fauna has been reported for this area (Duineveld et al., 1991; van Raaphorst et al., 1992) even during summer stratification. Oxygen concentrations in the water column commonly decrease from winter to summer (as seen in our case between the sampling performed in February and August), as well as the oxygen penetration depth (OPD) into the sediment. In this thesis, sediments sam-pled in February, May and August were investigated.
Also Lake Grevelingen sediments (Chapters 4, 5, and 6) were exposed to varying oxygen concntrations, i.e. bottom water hypoxia due to summer stratification of the water column, and sulfide accumulation in the sediment pore water due to intense sulfate reduction. Sediments, lo-cated at different water depths of a deep basin within Lake Grevelingen were investigated (S1 at 34 m, S2 at 23 m, and S3 at 17m). Bottom waters were fully oxygenated in March (S1-S3), where-as in August oxygen was strongly depleted in the bottom waters and no oxygen has been detect-ed in the surface sediments (S1, S2). Bottom water oxygen concentration at S3 remained higher in August (~88 μM), and oxygen penetrated down to 1.1 mm into the sediment. In August, free sulfide was present near the sediment-water interface at all three stations, and the accumulation of sulfide in the sediment pore water increased with water depth (S3 to S1).
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In general, my results support that the oxygen concentration of the bottom water and the OPD into the sediment is one of the major factors shaping the temporal and spatial distribution of the diversity, abundance and activity of chemolithoautotrophic microorganisms, due to dif-ferent oxygen requirements of their respective metabolism. Next to the availability of electron donors and acceptors, I have concluded that other factors such as bioturbation (Kristensen, 2000; Meyer et al., 2005; Beman et al., 2012) and the interactions between different microbial groups are important factors allowing for the activity of aerobic and anaerobic microorgan-isms together in the same niche. The abundance and activity of Thaumarchaeota and anammox bacteria was detected in Oyster Grounds sediments (Fig. 1) independent of the season and decreasing oxygen concentrations in the bottom water, whereas in Lake Grevelingen sediments, the abundance and activity of Thaumarchaeota was restricted to March, when the bottom water was still oxygenated (Fig. 2). These results suggest that the presence of bioturbation, oxygen-ating deeper layers in Oyster Grounds sediments, favors the presence and activity of aerobic ammonia oxidizing microorganisms, which could in turn fuel the activity of anammox bacteria by consuming oxygen and providing nitrite (Meyer et al., 2005; Laverock et al., 2013), compared to Lake Grevelingen sediments, where bioturbation was absent and sulfide accumulates in the sediment pore water during summer hypoxia.
In comparison to Oyster Grounds sediments, temporal and spatial differences of the com-munity structure, as well as of the abundance and activity of studied microorganisms were more pronounced in Lake Grevelingen sediments (Fig. 2), most likely due to the full development of hypoxia and rising sulfide concentrations as it has been shown recently for Black Sea sediments (Jessen et al., 2017). High sulfide concentrations are not only toxic for benthic bioturbating an-imals as sulfide has also been shown to inhibit ammonia oxidation (Joye and Hollibaugh, 1995; Berg et al., 2015) and the last steps of denitrification (Sørensen, 1980; Porubsky et al., 2009). My results showed that decreasing oxygen and rising sulfide concentrations induce drastic changes in the archaeal and bacterial community structure, and limit the abundance and/or the activity as well of specific groups involved in the sedimentary nitrogen and sulfur cycle, i.e. Thaumarchae-ota (AOA), AOB, anammox (Chapters 2, 3, 4) and denitrifying bacteria, sulfate and sulfur oxi-dizing bacteria including sulfide-dependent denitrifiers in Lake Grevelingen sediments (Chapters 4 and 6), as well as of chemolithoautotrophic bacteria (Chapter 5). Additionally, the potential activity of anammox bacteria was relatively low in Lake Grevelingen sediments compared to Oyster Grounds sediments, suggesting that this group is strongly affected by increasing sulfide concentrations. The activity of other groups, i.e. denitrifying bacteria, sulfate reducing and sul-fur oxidizing bacteria including sulfide-dependent denitrifiers, was relatively low in seasonally hypoxic Lake Grevelingen sediments independent of the season, suggesting that the activity of these groups is as well affected by decreasing oxygen and rising sulfide concentrations between spring and summer.
Both anammox and denitrification pathways have been suggested to be more important in sediments with low sulfide concentrations, but also with low carbon input (Burgin and Ham-ilton, 2007). The TOC content in Lake Grevelingen sediments is high (2.5−4.5%) and fresh organic rich sediment rapidly accumulates (> 2 cm y−1), which might additionally inhibit the activity of anammox and denitrifying bacteria. The TOC content in Oyster Grounds sediments was low (0.15−0.38%), which might explain the higher activity of anammox activity compared to Lake Grevelingen sediments. However, sediment incubation experiments (using labeled ni-
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trite) have previously shown that the ratio of anammox to denitrification depends on the carbon to nitrogen (C/N) ratio, i.e. the activity of anammox bacteria increased with higher nitrogen relative to carbon content (lower C/N) ratio of the source substrate (Babbin et al., 2014). How-ever, in my studies, I have observed a difference in the potential activity of anammox bacteria with higher expression levels in Oyster Ground compared to Lake Grevelingen sediments. The C/N ratio is relatively high in sediments of the Oyster Ground (7−8) and Lake Grevelingen (9.2 ± 0.2; Rao et al., 2016), indicating that this does potentially not explain the differences in the potential activity of anammox bacteria in the sediments studied here. Generally, the activity of chemolithoautotrophic bacteria in Lake Grevelingen sediments was restricted to March un-der oxygenated bottom water concentrations, indicating that chemolithoautotrophic bacteria in general are affected by bottom water hypoxia/anoxia, the lack of bioturbation and rising sulfide concentrations (Chapter 5).
Additionally, the abundance and metabolic capacities of the chemolithoautotrophic aerobic ammonia oxidizing archaea (AOA), i.e. Thaumarchaeota, were also evaluated in other marine sediment systems, i.e. in sandy to muddy sediments of the Iceland shelf. Thaumarchaeota were detected at all stations but their metabolic activity was low based on lack of incorporation of 13C-labeled substrate in archaeal GDGT lipids. The low activity of Thaumarchaeota is in agree-ment with the low oxygen penetration into the sediment, supporting that the absence of oxy-gen is limiting the activity of Thaumarchaeota. Ammonia and nitrite concentrations showed no changes during incubations, indicating that other factors than the availability of ammonia might inhibit the activity of Thaumarchaeota.
7.2. Diversity of chemolithoautotrophic microorganisms in coastal sedimentsThe general diversity of the microbial community was studied in Lake Grevelingen surface sed-iments by applying 16S rRNA amplicon sequencing analysis (Chapters 5, 6), before and during summer hypoxia. In general, these sediments harbor a distinct bacterial community comparable to other surface sediments, such as coastal marine (North Sea), estuarine and Black Sea sedi-ments (Jessen, et al., 2016; Ye et al., 2016; Dyksma et al., 2016). Approximately, 50% of the bac-terial reads were assigned to the clades of Gammaproteobacteria, Deltaproteobacteria and Ep-silonbacteria, whereas the remaining reads were distributed among the orders of Bacteroidetes (14%), Planctomycetes (6%), Alphaproteobacteria (2%) and other orders (22%). The majority of reads assigned to the Gammaproteobacteria were closely related to the orders Alteromo-modales, Chromatiales and Thiotrichales, whereas most of the reads of Epsilonproteobacteria were assigned to the order of Campylobacterales. Within the Deltaproteobacteria, most reads were assigned to the orders of Desulfarculales and Desulfobacterales.
In March, under oxygenated bottom water conditions, the surface sediment was characterized by high relative abundances (percentage of 16S rRNA gene reads) of Gammaproteobacteria and Epsilonproteobacteria, which are known chemolithoautotrophic sulfur oxidizers, e.g. ca-pable of oxidizing sulfide, thiosulfate, elemental sulfur and polythionates, using oxygen and nitrate as electron acceptor. In August, the lack of electron acceptors in the bottom water, i.e. oxygen and nitrate, coincided with a decrease in the relative abundance of Gammaproteobac-teria and Epsilonproteobacteria. At the same time, the number of reads assigned to the order of Desulfobacterales increased in the top centimeter of the sediment and a shift in the bacterial
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community toward chemoorganoheterotrophic sulfate-reducing bacteria related to the genera Desulfococcus and Desulfosarcina was evident. In coastal sediments, these genera are characteristic in deeper sediment layers experiencing anaerobic mineralization (Llobet-Brossa et al., 2002; Mi-yatake, 2011; Muyzer and Stams, 2008). The DNA-based 16S rRNA gene amplicon sequencing was complemented with the analysis of bacterial phospholipid derived fatty acids (PLFA) anal-ysis in Lake Grevelingen sediments down to 6 cm sediment depth in all seasons and stations. In March, surface sediments were characterized by relative high concentrations of C16 and C18 monosaturated PLFAs found in Gammaproteobacteria and Epsilonproteobacteria (Vestal and White 1989), whereas in deeper sediment layers, ai15:0, i17:1ω7c, and Me16:0, indicating that sulfate-reducing Deltaproteobacteria were more abundant (Boschker et al., 2002; Taylor and Parks, 1983; Edlund et al., 1985). In August, surface sediment showed an increased contribution of iso, anteiso, and branched PLFAs, more similar to the deeper sediments from March, but showed higher abundances of 16:0, 14:0, and 18:1ω9c compared to March. These shifts in the PLFA patterns are in agreement with the temporal difference in the bacterial community shown by 16S rRNA gene amplicon sequencing. However, the results of the PLFA analysis have to be interpreted with caution because there is now evidence that the method used here (Guckert et al., 1985), i.e. the separation of phospholipids from glycolipids and neutral lipids using silica col-umn chromatography, does not result in a fraction only containing phospholipids but also other lipid classes (Heinzelmann et al., 2014). Thus, commonly reported PLFA composition might be not derived purely from phospholipids but from of other lipid classes.
Additionally, the archaeal diversity was estimated by 16S rRNA gene amplicon sequencing in surface sediments of Lake Grevelingen (Chapter 6). The archaeal community was dominated by chemolithoautotrophic Thaumarchaeota marine group I (MGI) in March (50−82%), when oxygen was still present and sulfide was absent, next to the presence of other archaeal groups, such as members of the DPANN Woesearchaeota, Thermoplasmatales and members of the Miscellaneous Crenarchaeotic group (MCG). In August, the percentage of reads, attributed to the DPANN Woesearchaeota increased notably (57−95%) at the expense of reads assigned to the Thaumarchaeota. This change in the archaeal community is compatible with the aerobic me-tabolism of Thaumarchaeota (Könneke et al., 2005) and the anaerobic metabolism of DPANN archaea (Castelle et al., 2015). Thaumarchaeota have been shown to be inhibited by sulfide (Berg et al., 2015), potentially explaining the decrease in the MGI population upon the increase of sulfide concentrations in the summer.
In summary, results of the community analysis revealed a diverse microbial community in Lake Grevelingen surface sediments consisting of chemolithoautotrophic and chemoorgano-hetero-trophic microorganisms, responding to changes in the availability of reduced nitrogen and sulfur compounds and electron acceptors (oxygen and nitrogen) induced by hypoxia. Nevertheless, the bacterial and archaeal community analysis was performed by 16S rRNA gene amplicon sequenc-ing, therefore I cannot completely exclude a possible primer bias (Sipos et al., 2010; Schloss et al., 2011). Additionally, the diversity analysis of the 16S rRNA gene does not give information about absolute abundances, the metabolism and more importantly, about the activity of sedimentary microorganisms and their role in biogeochemical cycling of carbon, nitrogen and sulfur.
To further estimate the diversity of microorganisms fixing CO2 via the Calvin-Benson-Bassh-am (CBB) and the reductive tricarboxylic acid (rTCA) pathways, surface sediments of Lake Grevelingen sediments (Chapter 5) were investigated by cloning and sequencing the cbbL and
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aclB gene, encoding for the key enzymes ribulose 1,5-bisphosphate carboxylase/oxygenase (Ru-bisCO) and ATP citrate lyase, respectively. All detected cbbL sequences clustered with uncultered gammaproteobacterial clones, assigned to the orders Chromatiales and Thiotrichales, reported in intertidal sediment from Lowes Cove, ME (Nigro and King, 2007). The aclB gene sequences in surface sediments were predominantly related to aclB sequences of Epsilonproteobacteria of the order Campylobacterales, macrofaunal symbionts and to sequences of Euryarchaeota. No clustering of cbbL and aclB gene sequences according to one of the stations or one of the seasons was observed. Results revealed a stable community of bacteria using the CBB cycle, as well as bacteria and archaea using the rTCA pathway in Lake Grevelingen surface sediments. Until today, there is no PCR-based approach available to identify microorganisms using other CO2 fixation pathways, such as the reductive acetyl-CoA, or Wood-Ljungdahl (WL) pathway utilized by Firmicutes, Planctomycetes, Deltaproteobacteria, Spirochaeta and Euryarchaeota, or the 3-hydroxypropionate/4-hydroxybutyrate (3-HP/4-HB) cycle and the dicarboxylate/4- hy-droxybutyrate (DC/4-HB) cycle operating in Crenarchaeota (Hügler and Sievert, 2011), mainly due to the diversity of key genes of these pathways which impairs the development of a PCR-based detection method. Thus, an underestimation of the diversity of chemolithoautotrophic microorganisms in the coastal marine sediments under study in this thesis is possible.
Another goal of this thesis was to further estimate the diversity of chemolithoautotrophic microorganisms involved in the sedimentary nitrogen and sulfur cycle by using group specific 16S rRNA genes and functional genes involved in reoxidation pathways. This approach was applied in sediments of the Oyster Grounds (North Sea) and Lake Grevelingen surface sedi-ments. In Oyster Grounds surface (0–1 cm) and deeper (9–10 cm) sediments, the diversity of ammonia oxidizing archaea (Thaumarchaeota, AOA) and ammonia oxidizing bacteria (AOB), was determined by targeting the functional amoA gene of AOA and AOB. Results showed that amoA gene sequences of AOA amplified from Oyster Grounds surface sediments fell into dis-tinct subclusters of Nitrosopumilus sp., whereas most of the archaeal amoA sequences obtained from Lake Grevelingen sediments were closely related to Nitrosopumilus maritimus (SCM1) and in minor proportion to “Candidatus Nitrosoarchaeum limnia” found in low-salinity habitats (Mosier et al., 2012), showing a different community composition of AOA in Lake Grevelingen surface sediments, which is most likely explained by the lower salinity (~30 psu) compared to Oyster Grounds sediments (~34.5 psu). AOB amoA gene sequences retrieved from Oyster Grounds sediments were closely related to Nitrospira sp. and Nitrosolobus multiformis.
Another important chemolithoautotrophic microbial group present in anoxic sediment and involved in the nitrogen cycle is anammox bacteria. One issue much in debate is the relevance of anammox bacteria vs. heterotrophic denitrifiers in the N2 removal process in the environment. In this thesis I tackled this issue by determining the diversity and role of anammox bacteria, heterotrophic denitrifiers and other microbial groups involved in nitrogen removal (e.g. sulfur oxidizers coupled to nitrate reduction) in Lake Grevelingen sediments (Chapter 4). The diversity of the anammox 16S rRNA gene, whereas the nirS gene of denitrifying and anammox bacteria, as well as the aprA gene of sulfur oxidizing and sulfate reducing bacteria, were determined in Lake Grevelingen surface sediments (chapter 4). The diversity of nirS-type denitrifiers in surface sediments (0−1 cm) revealed a temporally stable community of denitrifying bacteria involved in autotrophic denitrification coupled to sulfide or iron oxidation (e.g. Thiobacillus denitrificans, Sid-eroxidans lithotrophicus), and of diverse heterotrophic denitrifiers. Most of the anammox bacterial
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nirS gene sequences obtained from Lake Grevelingen surface sediments were closely related to “Candidatus Scalindua profunda”, whereas anammox bacterial 16S rRNA gene sequences were closely related to “Candidatus Scalindua marina” and “Candidatus Scalindua brodae” as found in Oyster Grounds sediments (0–1 cm and 9–10 cm sediment depth).
The analysis of the aprA gene also revealed a diverse sulfur oxidizing community; including affiliations to autotrophic sulfur-dependent denitrifying Beta- and Gammaproteobacteria (Thio-bacillus denitrificans and Sulfuricella denitrificans), chemolithoautotrophic sulfur-dependent nitrate reducing Betaproteobacteria (Thiobacillus thioparus), heterotrophic sulfate reducing Deltaproteo-bacteria (e.g. Desulfosarcina sp., Desulfobulbus propionicus) or phototrophic sulfur oxidizing bacteria (Lamprocystis purpurea). In addition, the diversity of genes involved in carbon fixation and reoxi-dation pathways were also estimated showing no clustering of sequences according to the depth, station or season. These results were interpreted as an indication of the presence of a stable population of ammonia oxidizing archaea and bacteria, anammox (Chapter 2) and denitrifying bacteria, as well as sulfate reducing and sulfur oxidizing bacteria including sulfide-dependent denitrifiers (Chapter 4) in coastal sediments experiencing decreasing bottom water oxygen con-centrations due to summer stratification.
In general, the microbial community in Lake Grevelingen surface sediments consisted of phototrophic, heterotrophic and autotrophic microorganisms involved in carbon-, nitrogen and sulfur cycling. Thaumarchaeota have been detected in Oyster Ground sediments and Lake Grev-elingen sediments, where they seem to play an important role in the reoxidation of reduced inorganic compounds in order to sustain biogeochemical cycling of carbon and nitrogen com-pounds especially under oxygenated bottom water conditions and/or in bioturbated sediments (Fig. 1). The diversity of anammox bacteria in Oyster Grounds sediment is comparable to the anammox bacterial diversity in Lake Grevelingen sediments by the 16S rRNA gene diversity, indicating that the diversity of anammox bacteria is less affected by seasonal hypoxia and rising sulfide concentrations compared to the archaeal population as shown in chapter 2 and 4.
7.3. Abundance and distribution of chemolithoautotrophic microorganisms in coastal sedimentsMicrobial processes such as nitrification, denitrification and anammox are important for ni-trogen and carbon cycling, and are tightly coupled in marine sediments (Zhang et al., 2013). The abundance and seasonal variations of archaeal and bacterial ammonia oxidizers, anammox and denitrifying, and sulfide dependent denitrifiers, as well as environmental factors affecting these groups, are not well studied in coastal marine sediments. In this thesis, the seasonal and depth distribution of the abundance of these groups was estimated in marine sediments of the Oyster Grounds (North Sea), in sediments of the Iceland shelf, as well as in Lake Grevelingen sediments to get insights of the importance of these groups and their impact in the carbon and nitrogen cycles in selected marine sediments.
In Oyster Grounds sediments (Chapter 2) this was achieved by quantifying specific intact po-lar lipids attributed to ammonia oxidizing Thaumarchaeota (AOA) (i.e. hexose phosphohexose (HPH) crenarchaeol) and anammox bacteria (i.e. phosphatidylcholine (PC)-monoether ladder-ane), as well as the abundance of the 16S rRNA genes, the ammonia monooxygenase subunit A (amoA) gene of AOA and AOB, and the hydrazine synthase (hzsA) of anammox bacteria, in February, May, and in August during decreasing bottom water oxygen concentrations. One of
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the highlights of the study in the Oyster Grounds sediments is the detection of aerobic am-monia oxidizing microorganisms at depths where the oxygen concentration was expected to be undetectable, which is counterintuitive with their aerobic metabolism. This was attributed to the intense bioturbation reported in these sediments which could provide enough oxygen to support the presence and activity of these microbial groups. This is further supported by other studies like the one of Beman et al. (2012), where AOA and AOB amoA genes were detected up to 10 cm sediment depth in bioturbated sediments of Catalina Island (CA, USA). My results, and those of Beman et al. (2012), suggest that aerobic ammonia oxidizers are indeed living and actively involved in the marine sedimentary nitrogen cycle in deeper layers of coastal marine sediments than previously thought, which is relevant as it extends the area of active dark carbon fixation and nitrification in marine sediments.
Another conclusion of the study performed in the Oyster Grounds sediments is that seasonal variation in the abundance of Thaumarchaeota (AOA) within the sediment given by quantifi-cation of 16S rRNA and amoA gene were not reflected in the specific Thaumarchaeota lipid biomarker HPH-crenarchaeol quantification, which was stable with depth in the first 12 cm. HPH-crenarchaeol has been shown to be more labile compared to crenarchaeol with a glycosidic head group, and its concentration corresponds well to the DNA-based abundance of Thaumar-chaeota (Pitcher et al., 2011a; Schouten et al., 2012; Lengger et al., 2012a). These results might suggest a possible preservation of this biomarker within the sediment vertical profile which would invalidate the use of it as indicator of abundance of living Thaumarchaeota in deep sed-iments.
The presence and potential activity of Thaumarchaeota were also assessed in Iceland shelf sediment incubations with 13C-labeled substrates (chapter 3). This study also included a direct analysis of IPL-crenarchaeol as specific lipid of Thaumarchaeota. The IPL-crenarchaeol with (HPH)- head group was between 80−90% in surface sediments of all stations and it decreased up to 10−25% in the deepest sediment layer. However, the presence of HPH-crenarchaeol in anoxic parts of the sediment, as seen in the Oyster Grounds sediments (Chapter 2), can again be due to preservation of this compound and cannot be then taken as a biomarker of a living Thaumarchaeota population.
In order to rule out a possible preservation effect of lipid biomarkers in deep sediments, the analysis or archaeal lipids was later restricted to surface sediments in Lake Grevelingen in or-der to determine the abundance and distribution of chemolithoautotrophic ammonia oxidizing Thaumarchaeota as well as other archaeal groups present. The methodological improvement of this study with respect to the one included in Chapter 2 and chapter 3 is that a new method was applied for the detection of the polar head groups of different IPL-GDGTs and was not only restricted to the specific GDGT crenarchaeol of Thaumarchaeota. With this, it was possible to extend the analysis of IPL-GDGT to the entire archaeal population present in the sediments. The detection of HPH-GDGTs in March in Lake Grevelingen sediment, coinciding with a higher presence of Thaumarchaeota detected by 16S rRNA gene amplicon sequence, indicated that the Thaumarchaeota population was actively living in those sediments. On the other hand, the switch to an archaea DPANN-dominated population in August with a similar IPL-GDGT profile, and the fact that DPANN archaea are not genetically capable of synthesizing their own lipids, suggest that this archaea group might be recycling the IPL-GDGTs already present in the sediment. This factor complicates the interpretations of the lipid sources in sedimentary settings
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and highlight the need of combining different methodological approaches (i.e. lipid biomarkers, gene-based detection, activity measurements) to determine the chemolithoautotrophic potential and biological sources. Also, this study highlights the dramatic change in the archaea population in Lake Grevelingen surface sediments upon summer hypoxia and increase of sulfide concentra-tion in the pore water. This can be explained by a toxic effect of sulfide on the Thaumarchaeota population, together with decrease in oxygen available for their aerobic metabolism. In fact, a similar toxic effect of sulfide has been observed in Thaumarchaeota enrichment cultures from Baltic Sea water (Berg et al., 2015).
In this thesis, I have also determined the abundance and distribution of anammox bacteria in different marine sediment systems both by using specific lipid biomarkers and quantification of specific 16S rRNA and metabolic genes. For example, anammox bacteria 16S rRNA and the hydrazine synthase (hzsA) gene abundance were detected throughout the Oyster Grounds sediment with more pronounced depth and seasonal differences than those observed for AOA and AOB. Both, anammox bacteria 16S rRNA and hzsA gene abundances were higher in August compared to February and May, which was not reflected in the abundance of the anammox spe-cific lipid biomarker PC-monoether ladderane. This can be explained by partial preservation of this biomarker lipid in the sediment due to a relatively low turnover rate (Brandsma et al., 2011; Bale et al., 2014). I also observed a ten-fold difference between abundances of the anammox 16S rRNA gene and the hzsA gene. This difference between the 16S rRNA gene and functional genes of anammox bacteria has been previously observed and is possibly explained by primer biases of the 16S rRNA gene primers, suggesting the amplification of 16S rRNA gene fragments of bacteria other than anammox bacteria (Harhangi et al., 2012; Bale et al., 2014).
The presence of anammox bacteria biomarkers in the upper layers of Oyster Grounds sed-iments (0−4 cm) is still remarkable as the metabolism of anammox bacteria is expected to be incompatible with the presence of oxygen. Some studies have reported that anammox bacteria can be present at high oxygen levels, by being dormant or using anaerobic niches (Kuypers et al., 2005; Woebken et al., 2007). It is also possible that the metabolic activity of AOA/AOB and heterotrophic bacteria support the presence of anammox bacteria by oxygen consumption al-lowing the presence of anammox bacteria even in the oxygenated sediments. My results suggest that anammox bacteria can tolerate the presence of oxygen (Kalvelage et al., 2011; Yan et al., 2012) and co-exist with aerobic ammonia oxidizers and potentially have an important role in the nitrogen cycle in marine sediments.
Similarly, anammox bacteria detected in Lake Grevelingen sediments showed a clear seasonal contrast in their nitrite reductase (nirS) gene abundance with higher copy numbers in August during summer hypoxia compared to March, similar to the 16S rRNA and hzsA gene abundance of anammox bacteria detected in Oyster Ground sediments (Chapter 2). The seasonal trend was as well not reflected in the abundance of the anammox bacteria lipid biomarker PC-monoether ladderane lipid, as it has been reported for Oyster Grounds sediments (Brandsma et al., 2011; Bale et al., 2014). In contrast, the concentration of ladderane lipid fatty acids correlated with the abundance of anammox bacteria determined by the 16S rRNA gene abundance, suggesting that the abundance of ladderane lipid fatty acids could be interpreted as a proxy for the abundance of anammox bacteria, together with specific gene quantification. A difference of three to four orders of magnitude between abundances of the anammox 16S rRNA gene and the “Candidatus Scalindua” specific nirS gene was detected. This discordance between the 16S rRNA gene and
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functional genes of anammox bacteria has been previously observed and has been discussed above in detail, thus the possibility of amplifying other bacteria has been ruled out by cloning and sequencing of the product generated during the quantitative PCR reaction for Lake Grev-elingen sediments.
Overall, the nirS gene abundance of denitrifiers was three to four orders higher compared to the anammox nirS gene abundance, suggesting that nirS-type denitrifiers have a more prominent role in the nitrogen removal in Lake Grevelingen sediments compared to anammox bacteria. The abundance of denitrifying bacteria did not vary substantially despite of differences in the oxygen and sulfide availability, whereas anammox bacteria were more abundant in the summer hypoxia, but in those sediments with lower sulfide concentrations, indicating that the abundance of anammox bacteria is impaired by high sulfide concentrations as previously suggested by oth-ers (Dalsgaard et al., 2003; Jensen et al., 2008). Anammox abundance was also highest in Oyster Grounds sediments (0.5 cm) in August under low bottom water oxygen conditions and decreas-ing oxygen penetration. These results are most likely explained by of the fact that anammox bacteria are favored by hypoxic conditions (i.e. Neubacher et al., 2013). Besides, the optimum temperature of anammox bacteria of 15°C has been reported in temperate shelf sediments (Dalsgaard et al., 2005) which is close to the summer temperature in Oyster Grounds and Lake Grevelingen sediments (~17°C). Additionally, bioturbation has been shown to extend the area of aerobic processes such as nitrate reduction and thus the availability of reduced compounds such as nitrite, which would fuel the anammox process (Meyer et al., 2005). In Lake Grevelingen sediments, anammox abundance was highest in bioturbated compared to non bioturbated sed-iments (S3), indicating that bioturbation might additionally favor the abundance of anammox bacteria. Bioturbation has also been reported in Oyster Grounds (Duineveld et al., 1991), which together with the reported high activity of AOA, AOB and/or other aerobic heterotrophs re-moving the available oxygen, could contribute to the proliferation of anammox bacteria.
In order to determine the abundance of other microorganisms involved in nitrogen removal in Lake Grevelingen sediments (Chapter 4), I also quantified the nitrite reductase (nirS) gene of chemoorganoheterotrophic denitrifying bacteria and archaea, performing the stepwise conver-sion of nitrate/nitrite to dinitrogen gas (Zumft, 1997), as well as the aprA gene of sulfate reduc-ing and sulfur oxidizing bacteria including autotrophic sulfide-dependent denitrifying members of the Alpha-, Beta-, Gamma-, and Epsilonproteobacteria (Shao et al., 2010).The nirS gene abundance has previously been show to correlate positively with potential denitrification rates (Mosier and Francis, 2010). Here, the nirS gene abundance of denitrifying bacteria was relatively constant with sediment depth, suggesting a stable community of heterotrophic and autotro-phic denitrifying bacteria actively involved in the denitrification process in Lake Grevelingen sediments. However, assumptions have to be made with caution, because foraminiferal denitri-fication might be as important as heterotrophic denitrification in marine sediments, as well as metal-dependent denitrification (Devol, 2015). Besides, and some denitrifying microorganisms use the copper-containing nitrite reductase encoded by the nirK gene which could have led to the underestimation of the diversity and abundance of total denitrifiers by exclusively targeting the nirS gene. However, nirS denitrifiers are more likely to have a complete denitrification pathway (including nor and nos genes), suggesting that nirS-containing denitrifiers may be more likely to reduce nitrite to N2 (Graf et al. 2014). In addition, the nirS gene has been shown to be more abundant and more diverse than nirK in estuarine sediments, although this pattern sometimes
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shifts in different estuarine regions (Nogales et al. 2002; Abell et al. 2010; Mosier and Francis 2010; Beman, 2014; Smith et al. 2015b; Lee and Francis, 2017). In general, the nirS gene abun-dance was slightly higher in March in all three stations in Lake Grevelingen sediments (Chapter 4), but the difference was more pronounced in station 1, which can be most likely explained by lower sulfide concentrations in March compared to August. The lower sulfide concentrations in March could favor the proliferation of heterotrophic denitrifiers, as sulfide has been shown to impair denitrification by inhibition of NO and N2O reductases (Sørensen et al., 1980).
The abundance of chemolithoautotrophic microorganisms utilizing the CBB and rTCA path-ways for carbon fixation was also estimated in Lake Grevelingen sediments (Chapter 5) by quan-tifying the cbbL and aclB gene, encoding for the key-enzymes ribulose 1,5 bisphosphate carbox-ylase/oxygenase (CBB) and ATP citrate lyase (rTCA). Significant differences were determined in the abundance of cbbL and aclB genes between the seasons but not between the stations, suggesting a stable community of community of autotrophic microorganisms using the CBB and rTCA pathway. The abundance of the cbbL gene was at least 2-fold higher than aclB gene abundance independent of the season or station, indicating a more prominent role of microor-ganisms using the CBB cycle compared to those using the rTCA pathway. The results indicated a more important role of autotrophic aerobic or facultative aerobic Gammaproteobacteria of the orders Chromatiales and Thiotrichales compared to Epsilonproteobacteria of the order Cam-pylobacterales and Euryarchaeota in Lake Grevelingen sediments. However, these assumptions have to be made with caution, as the primers used to amplify aclB genes are mainly based on sequences of Epsilonproteobacteria (Campbell et al., 2006), suggesting that potentially there is an underestimation of the abundance of microorganisms using the rTCA pathway in these sed-iments, as well as the abundance of microorganisms using other carbon fixation pathways than the CBB or rTCA pathway (Hügler and Sievert, 2011; Berg et al., 2010, 2011).
Taking all the considerations mentioned above, the determination of the abundance of mi-croorganisms based on DNA sequences and lipid biomarker molecules in marine coastal and estuarine sediments has to be interpreted with caution. DNA-based methods employed in this thesis depend on PCR amplification with primers, designed based on the sequences available in the databases, potentially causing an underestimation of the diversity as well as of the abundance of target organisms. As the abundance of functional and 16S rRNA genes was estimated by qPCR and 16S rRNA gene amplicon sequencing, I cannot completely rule out primer induced PCR biases (Schloss et al., 2011; Sipos et al., 2010). Additionally, DNA and lipid biomarkers can be partly preserved in anoxic sediments, which possibly leads to an overestimation of the abun-dance of the studied microorganisms (Torti et al., 2015; Lengger et al., 2012; Rush et al., 2012).
7.4. Activity of chemolithoautotrophic microorganisms in coastal sediments In my thesis, I have estimated activity by determining incorporation of 13C-labeled substrates in membrane lipids as well as the gene expression of 16S rRNA and functional genes as proxy of transcriptional activity. The abundance and gene expression of functional genes has been frequently interpreted as an indication of the process rate in which the protein-coding gene is involved (Nogales et al., 2002; Smith et al., 2007; Abell et al., 2010, 2011; Bowen et al., 2014). However, this is not always the case and it is in general dependent on the regulation of the specif-ic gene under study. As an example, the transcript levels of the coding gene for the dissimilatory sulfite reductase (dsrA), catalyzing the final step in sulfate reduction, has been seen to positively
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correlate with sulfate reduction rate (SRR) when growing under limited electron acceptor (sul-fate) while no correlation between SRR and dsrA gene expression was observed when grown under electron donor limitation (Villanueva et al., 2008). Similarly, a recent study by Carini et al. (2017) observed that ammonia limitation in the thaumarchaeon “Candidatus Nitrosopelagicus brevis” induced a decrease in the expression of the ammonia oxidation core proteins, which could be interpreted as a confirmation that lower ammonia oxidation activity is correlated to lower amoA gene expression levels. However, this study also concluded that the genes involved in ammonia oxidation constitute a large part of the total transcript pool irrespective of growth and environmental conditions, which makes it difficult to connect changes in gene expression to differences in the metabolic process.
Examples like this illustrate the need of studying, in pure cultures and under controlled con-ditions, the regulation of the expression of metabolic genes and its potential correlation to the process rates before making definite conclusions based on environmental samples. In this thesis, several metabolic genes involved in key re-oxidation pathways were analyzed for their gene ex-pression patterns in environmental samples. For some of these genes, previous information on the regulation of their gene expression was available (e.g. AOA amoA gene; Abell et al., 2011), which allowed us to interpret the results more confidently. For some other genes, e.g. anammox bacterial hzsA gene (Harhangi et al., 2011), the determination of their gene expression and comparison with their gene abundance and process rate in environmental samples in this thesis (Chapters 2, 4), has allowed to get a better understanding of the environmental conditions that can affect the activity of the metabolic process.
To estimate the activity of aerobic and anaerobic ammonia oxidizers and anammox bacteria in coastal sediments, the gene expression of their 16S rRNA gene, the amoA gene of AOA and AOB, and the expression of the anammox bacterial hzsA gene, were analyzed here by quantify-ing the transcript abundance by reverse transcription and subsequent qPCR, in sediments of the Oyster Grounds (North Sea) (Chapter 2) and in Lake Grevelingen (chapter 4). The detection of the transcriptional activity of the AOA 16S rRNA gene up to 12 cm depth in Oyster Grounds sediment supports that AOA are indeed active in subsurface sediments. The potential transcrip-tional activity, by the 16S rRNA gene RNA:DNA ratio, was higher during winter, whereas the abundance was slightly higher during the summer months. The AOA amoA gene RNA:DNA ratio has been detected in August throughout the core but only in the upper 3 cm in February, because the quantity of transcripts in other seasons and depths was under the detection limit of the qPCR assay. However, the relationship of amoA gene expression and in situ ammonia oxi-dation is still unclear (Lam et al., 2007; Nicol et al., 2008; Abell et al., 2011; Vissers et al., 2013). Recent studies have observed a good correlation between nitrification rates and the abundance of amoA genes and transcripts in coastal waters (Smith et al., 2014; Urakawa et al., 2014), indi-cating that the detection of AOA amoA transcripts suggest AOA were active in Oyster Grounds sediments in the summer throughout the sediment in comparison with the winter in which AOA would be only active in the upper part of the sediment (upper 2 cm).
The abundance of AOB amoA transcripts was higher than for AOA, and was detected up to 12 cm sediment depth in all seasons, which would suggest a higher AOB activity compared to AOA. However, a study by Urakawa et al. (2014) in estuarine waters did not observe a correlation between nitrification rates and AOB amoA transcripts. Additionally, previous studies have de-tected the presence of AOB amoA transcripts in non-active starved cells (Bollmann et al., 2005;
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Geets et al., 2006; Sayaveda-Soto and Arp, 2011) indicating that the AOB amoA transcriptional activity is not a good indicator of AOB nitrification activity due to a longer half-life of AOB amoA transcripts than expected for AOA amoA transcripts.
The metabolic capacities of sedimentary Thaumarchaeota are still under debate. To shed fur-ther light on this important chemolithoautotrophic metabolism in marine sediments, we also performed labeling experiments using 13C-labeled substrates, such as bicarbonate, pyruvate, ami-no acids and glucose in sediment cores of the Iceland Shelf (Chapter 3) and determined the de-gree of 13C-incorporation into the most abundant GDGT lipids, i.e. crenarchaeol and GDGT-0. These compounds have been suggested to be taken up by Thaumarchaeota in the environment (Ouverney and Fuhrman, 2000; Wuchter et al., 2003; Herndl et al., 2005; Takano et al., 2010; Pitcher et al., 2011c), or in enrichment cultures (Park et al., 2010; Jung et al., 2011; Tourna et al., 2011; Kim et al., 2012), and are possibly the most suitable substrates resulting in uptake by sedimentary Archaea. However, the incubation with labeled 13C substrates did not result in any substantial incorporation of the 13C into the biphytanyl chains of these lipids. No incorpora-tion of 13C in IPL-GDGT was detected in clay rich and organic rich sediments, whereas some enrichment in δ13C (1−4‰) of IPL-GDGTs recovered from sandy sediment was detected after incubation with bicarbonate and pyruvate. This apparent lack of uptake could be due to several reasons. It is possible that the Thaumarchaeota were active, but the substrates were not taken up. Secondly, it is possible that most of the IPLs measured are fossil, and thus only a small amount of these IPLs are part of living and active sedimentary Thaumarchaeota, as also discussed above. Another possibility is that the metabolism and growth rates are so slow that no incorporation could be detected over the timescales investigated. Thus, the incubation period of 96−144 h, may have been too short. These results suggested that sedimentary Thaumarchaeota grow slowly in contrast to other sedimentary organisms, and/or a slow turn-over of IPL-GDGTs compared to bacterial/eukaryotic PLFAs. Interestingly, enrichment culture experiments with a thaumarchaeal strain closely related (99%) to Nitrosopumilus maritimus (SCM1), discovered that α-keto acids, such as pyruvate and oxaloacetate, were not directly incorporated into AOA cells, but functioned as chemical scavengers that detoxified intracellularly produced H2O2 during ammonia oxidation (Kim et al., 2016), indicating that previous findings of pyruvate incorporation could have been misinterpreted as evidence for mixotrophic growth of AOA.
In order to determine the potential activity of anammox bacteria in Oyster Grounds and Lake Grevelingen sediments, the potential transcriptional activity of the 16S rRNA gene, as well as of the functional genes hzsA and nirS encoding for the key-enzymes of the anammox reaction, hydrazine synthase and nitrite reductase (Chapter 2 and 4, respectively). A previous study by Bale et al. (2014) observed a good correlation between anammox rate activity and anammox bacterial 16S rRNA transcript abundance in North Sea sediments, suggesting that the tran-scriptional activity of anammox bacteria 16S rRNA gene is a good proxy for anammox bacteria activity. In Oyster Grounds sediments, the transcriptional activity of anammox bacteria 16S rRNA and hzsA gene was detected throughout the sediment in all seasons, and the 16S rRNA RNA:DNA ratio was higher during summer as observed for the anammox bacteria abundance. In Lake Grevelingen sediments the anammox 16S rRNA gene transcript abundance was detect-ed throughout the sediment. However, the anammox bacteria 16S rRNA RNA:DNA ratio was low (0.01−1) compared to the values reported in sediments of the Oyster Grounds (1.6−34.5), further supporting a low anammox activity in Lake Grevelingen sediments.
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Nevertheless, quantification results of anammox bacteria 16S rRNA gene have to be inter-preted with caution because there is evidence that the ribosome content does not decrease during the period of starvation (Schmid et al., 2005; Li and Gu, 2011). Besides, the increase of anammox bacteria 16S rRNA gene transcriptional activity during summer in Oyster Grounds sediments was not observed for the hzsA gene, which remained stable with sediment depth and also for the different seasons. The low and constitutive transcriptional activity of the hzsA gene indicates that the hzsA gene transcript abundance does not reflect variations of anammox bac-teria activity in environmental sediment samples, thus the hzsA transcript abundance does not seem to be an adequate biomarker for the estimation of the activity of anammox bacteria. Fur-ther experiments, preferably with pure cultures and under controlled physiological conditions, should be performed to clarify the regulation of the hzsA gene expression.
Environmental conditions favoring the abundance and activity of anammox bacteria have been discussed above in detail. Bioturbation activity could explain the differences in the activity of anammox bacteria in sediments of the Oyster Grounds compared to the Lake Grevelingen sediments, where only in station S3 bioturbators have been recognized in March, coinciding with the highest anammox abundance compared to the other stations. Additionally, the activity of anammox bacteria might be inhibited by high carbon and sulfide concentrations, as discussed above, probably explaining the higher activity of anammox bacteria in Oyster Grounds (low TOC), compared to Lake Grevelingen sediments (high TOC).
To further estimate the potential activity of microbial groups involved in denitrification oth-er than anammox bacteria, i.e. denitrifying bacteria, sulfate reducing/sulfur oxidizing bacteria including sulfide-dependent denitrifying microorganisms, in seasonal hypoxic and sulfidic sedi-ments of Lake Grevelingen (Chapter 4), I also analyzed the potential transcriptional activity of these groups. This was achieved by quantifying the nirS transcript abundance of denitrifying bacteria, as well as the aprA transcript abundance of sulfate reducing and sulfur oxidizing mi-croorganisms. Unfortunately, there is a lack of studies correlating the nirS gene expression of denitrifying bacteria with denitrification rates, and some studies have shown a lack of direct relationship between nirS gene expression and modeled rates of denitrification in marine surface sediments (Bowen et al., 2014), whereas other studies have observed a correlation between a decrease of nirS transcript abundance and the reduction of denitrification rates coinciding with declining concentrations of nitrate in estuarine sediments (Dong et al., 2000, 2002; Smith et al., 2007). These studies would justify the use of nirS gene transcript abundance as a proxy for denitrification performed by nirS-type denitrifiers. In my study, the nirS transcript abundance of nirS-type denitrifiers was two or three orders lower compared to values previously reported for estuarine sediments, suggesting a low denitrification rate in surface sediments of all stations in March and in deeper sediment layers in August. Gene expression of the nirS gene was detected in surface sediments in March (all stations) and in deeper layers in August (stations S1 and S3), which is most likely explained by the availability of nitrate/nitrite in the bottom water. The potential transcriptional activity of sulfate reducing and sulfur oxidizing including chemolitho-autotrophic sulfide-dependent denitrifiers, determined by the aprA gene RNA:DNA ratio was relatively low (≤ 0.00088), which also indicated a low denitrification potential of these groups.
Although denitrification was more relevant than the anammox process as suggested by the gene abundance and potential transcriptional activity, and measured denitrification rates (be-tween 36 and 96 μM m−2 d−1; Seitaj, D. personal communication) in Lake Grevelingen sediments
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which were low compared to other marine sediments. Denitrification rates vary between 30 and 270 μM m−2 d−1 in marine arctic sediments (Rysgaard et al., 2004), whereas in estuarine sediments of the lower St. Lawrence estuary, denitrification rates of 270 ± 30 μM m−2 d−1 were measured (Crowe et al., 2012). The lower denitrification and anammox potential in Lake Grev-elingen sediments could be explained by the effect of high concentrations of sulfide, potentially inhibiting both heterotrophic denitrification and anammox. Another explanation of the low denitrification and anammox potential of Lake Grevelingen sediments can be found in the in-teractions of anammox and heterotrophic denitrifiers with sulfur-oxidizers also involved in the nitrogen cycle. Large filamentous sulfur oxidizing bacteria have been detected in Lake Grevelin-gen sediments, i.e. cable bacteria and Beggiatoaceae including the genera Beggiatoa, Thiomargarita and Thioploca (Salman et al., 2011, 2013). Cable bacteria perform electrogenic sulfur oxidation (e-SOx), in which the oxidation of the electron donor and the reduction of the electron accep-tor are separated over cm-scale distances and the redox coupling is ensured by long distance electron transport (Nielsen et al., 2010; Pfeffer et al., 2012). Cable bacteria can play a role in bioavailable nitrogen removal, as they have been shown to use oxygen but might as well use nitrite and nitrate (Meysman et al., 2015; Marzocchi et al., 2014; Risgaard-Petersen et al., 2014). Additionally, Beggiatoaceae couple the oxidation of sulfide to nitrate reduction resulting in N2 and/or NH4
+ (Mußmann et al., 2003). Previous studies have observed that in anoxic sediments both denitrification and anammox can be supported by intracellular nitrate transport, performed by sulfide-oxidizing Thioploca and Beggiatoa (Mußmann et al., 2007; Jorgensen, 2010; Prokopenko et al., 2013) down to deeper sediment layers and possibly supplying anammox and denitrifying bacteria with nitrite and/or ammonia produced by DNRA (Teske and Nelson, 2006; Proko-penko et al., 2011). Cable bacteria have been detected in S1 and S3 in March, whereas station S2 was dominated by Beggiatoaceae down to ~3 cm, but both groups were hardly detected in subsurface sediments (0.5 cm downwards) during summer hypoxia. The presence of sulfide-de-pendent denitrifiers, as shown by the aprA gene abundance and diversity, as well as the presence of cable bacteria and Beggiatoa-like bacteria could potentially support the denitrification and anammox processes in March. However, the nitrate and nitrite concentrations in the bottom water in March were reported to be relatively low (28 and 0.7 μM on average, respectively). This limitation could induce a strong competition for nitrate, nitrite and sulfide with Beggiatoaceae, cable bacteria and other nitrate-reducing bacteria, which may explain the limited denitrification potential observed in March. During summer hypoxia (August), sulfide inhibition and low nitrate and nitrite concentrations seem to limit the activity of heterotrophic and autotrophic denitrifiers and anammox bacteria. Further studies, involving denitrification rate measurements will be re-quired to further assess the effects of hypoxia and high sulfide concentrations in the sediments of Lake Grevelingen.
The chemolithoautotrophic activity of the bacterial community has also been determined by PLFA analysis combined with 13C-stable isotope probing in Grevelingen sediments (Chapter 5). In March, under oxygenated bottom water conditions, the chemolithoautotrophic rates were substantially higher than those in August, when oxygen in the bottom water was depleted to low levels. Moreover, in August, the chemolithoautotrophic rates showed a clear decrease in with water depth (S3 to S1), which is in line with the bottom water oxygen concentration over water depth. At the same time, the 16S rRNA gene amplicon sequencing revealed that the re-sponse of the chemolithoautotrophic bacterial community in surface sediments is associated
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with the seasonal changes in the bottom water oxygen concentrations. As described above, in March the microbial community in surface sediments of all stations was characterized by high relative abundances of chemolithoautotrophic sulfur oxidizing Gammaproteobacteria and Ep-silonproteobacteria using oxygen or nitrate as electron acceptor. In August, the lack of oxygen and nitrate in the bottom water was accompanied by a decrease in the relative abundances of Gamma- proteobacteria and Epsilonproteobacteria, and an increase of the relative abundance of heterotrophic sulfate-reducing Deltaproteobacteria using sulfate as electron acceptor. These results support the chemolithoautotrophic rates measured in March and August, indicating that the lack of electron acceptors such as oxygen and nitrate induced by hypoxia limiting the activity of chemolithoautotrophic bacteria in August. Recently, a study by Jessen et al. (2017) addressed the effects of hypoxia on the microbial community composition in Black Sea sediments, and showed that variations in oxygen supply to the seafloor influenced the composition of the bac-terial community in surface sediments. Similar to my results, they reported an increase of Del-taproteobacteria under variable to anoxic conditions, whereas Gammaproteobacteria reached highest abundances under variable hypoxic conditions while decreasing toward stable oxic and anoxic conditions (Jessen et al., 2017). Together, these results show the important impact of bottom water hypoxia on the microbial community composition and especially on chemolitho-autotrophs in sediments.
7.5. OutlookIn the last five years, new and improved methods have been developed and their cost reduced, which would now make them compatible with studies with a massive amount of samples. In the last two chapters of this thesis, I have already applied both 16S rRNA gene amplicon sequencing and lipid analysis with high resolution accurate mass/mass spectrometry that showed a quanti-tative and qualitative increase in the amount of data and the estimation of the diversity of not only chemolithoautotrophic microorganisms.
The studies included in this thesis regarding the gene expression and abundance of key met-abolic genes of chemolithoautotrophs under different environmental and physiological condi-tions have shed further light on the role of this group in the carbon and nitrogen cycle in coastal sediments. In this thesis, the diversity of chemolithoautotrophic microorganisms was mostly determined with gene-targeted approaches, either by amplifying and sequencing specific 16S rRNA gene or functional genes involved in the carbon fixation of re-oxidation pathways. In this synthesis, I have listed the disadvantages of this approach mainly due to the biases introduced by the primer design, lack of sequences in databases, and inherent PCR amplification biases. Currently, these limitations could have been overcome by metagenomic and metatranscriptomic approaches, which are now much more affordable, the data analysis is more feasible, and most importantly they are not PCR-biased. With this approaches, I could have determined both di-versity and the gene expression of chemolithoautotrophic key genes. However, the connection between gene expression and the activity of the actual process is still problematic. This infor-mation can only be validated by laboratory experiments in which the regulation of the gene of interest is thoroughly studied under different physiological and environmental conditions. Another recommendation is the combination of activity proxy measurements included in this thesis with direct rate measurements when possible to directly assess if the gene expression can be correlated to the activity measurement. Apart from using metatranscriptomics, the activity
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of specific microorganisms could now also detected by using more sensitive approaches than the lipid-SIP approaches used in this thesis. For example, nano-scale secondary ion mass spec-trometry (NanoSIMS) in combination with catalyzed reporter deposition (CARD)- fluorescence in situ hybridization (FISH) has proven to be very effective for the determination of metabolic capacity linked to phylogenetic identity at the single cell level (Behrens et al., 2008; Musat et al., 2008; Morono et al., 2011). However, a problem that remains is that this method still relies on incubation with labeled substrates with the inherent limitations of labeling-based incubations including labeling incubation time and cross-feeding of 13C metabolites produced by the primary consumers of the 13C substrate.
Finally, in this thesis both specific lipid biomarkers for targeted groups (i.e. crenarchaeol for Thaumarchaeota, ladderane lipids for anammox) and bacterial and archaeal lipid characterization were performed in sediment samples with the aim of determining the abundance and activity (i.e. Lipid-SIP) of chemolithoautotrophs. However, I have seen that some of this biomarkers (i.e. HPH-crenarchaeol, PC-ladderane) are potentially preserved in deeper sediments invalidating their use as proxies of living biomass. In this regard, a recommendation would be to continue in the search of lipid biomarkers that can be more representative of living biomass and less prone to preservation. Laboratory cultures together with characterization of the microbial lipidome with methods similar to the ones applied in Chapter 6 (i.e. high resolution accurate mass spec-trometry) to detect intact polar lipids would be key in improving this issue. Also in chapter 6, I have seen the potential recycling of IPLs by archaeal groups like the DPANN. Further studies need to carefully assess the effect of such lipid recycling in sediment and the interpretations derived from those results.
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Summary
The role of chemolithoautotrophic microorganisms has been considered to be of minor impor-tance in coastal marine sediments although it has not been investigated in depth. Additionally, the impact of seasonal hypoxic/anoxic conditions on microbial chemolithoautotrophy in coastal marine sediments has not been examined. Therefore, in this thesis the diversity, abundance and activity of specific groups of chemolithoautotrophic microorganisms involved in the nitrogen and sulfur cycling, as well as the total microbial community, has been determined in coastal sed-iments by using DNA/RNA- and lipid-based biomarker approaches. Results show the presence and potential importance of chemolithoautotrophs in the biogeochemical cycling of carbon, nitrogen and sulfur. Temporal changes of the diversity, abundance and activity of chemolith-oautotrophic microorganisms coinciding with seasonal hypoxia in coastal sediments have been determined.
The diversity, abundance and activity of chemolithoautotrophic microorganisms, such as am-monia oxidizing archaea (AOA) and bacteria (AOB), anammox and denitrifying bacteria, as well as sulfate reducing and sulfur oxidizing microorganisms, including sulfide dependent denitrifiers, have been determined. Additionally, the diversity and activity of chemolithoautotrophic micro-organisms involved in the CBB and rTCA cycle as well as the metabolism of Thaumarchaeota and the abundance of Archaea have been addressed. In the following studies, we focused on coastal marine sediments, exposed to summer hypoxia, i.e. (1) the Oyster Grounds in the central North Sea, exposed to decreasing bottom water oxygen concentrations, (2) different sediment types (sand, clay, and mud) of the Iceland Shelf, and (3) seasonally hypoxic and sulfidic sedi-ments of saline Lake Grevelingen (The Netherlands).
In Oyster Grounds sediments (chapter 2), seasonal variations of archaeal and bacterial am-monia oxidizers (AOA and AOB) and anammox bacteria, as well as the environmental factors affecting these groups, were addressed. We examined the seasonal and depth distribution of the abundance and potential activity of these microbial groups in coastal marine sediments of the southern North Sea. We quantified specific intact polar lipids (IPLs) as well as the abundance and gene expression of their 16S rRNA gene, the ammonia monooxygenase subunit A (amoA) gene of AOA and AOB, and the hydrazine synthase (hzsA) gene of anammox bacteria. AOA, AOB and anammox bacteria were detected and transcriptionally active down to 12 cm sediment depth. This study unraveled the coexistence and metabolic activity of AOA, AOB, and anammox bacteria in bioturbated marine sediments of the North Sea, leading to the conclusion that the metabolism of these microbial groups is spatially coupled based on the rapid consumption of oxygen that allows the coexistence of aerobic and anaerobic ammonia oxidizers. AOA outnum-bered AOB throughout the year which may be caused by the higher oxygen affinity of AOA compared to AOB. Anammox bacterial abundance and activity were higher during summer, indicating that their growth and activity are favored by higher temperatures and lower oxygen available in the sediments due to summer stratifying conditions in the water column. During the summer, anammox bacteria are probably not in competition with AOA and AOB for ammonia as the concentrations were relatively high in the sediment pore water most likely as a result of ammonification processes and the activity of denitrifiers and DNRA.
In Iceland Shelf sediments (chapter 3), we investigated the activity of Thaumarchaeota in sediments by supplying different 13C-labeled substrates which have previously been shown to be
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incorporated into archaeal cells in water incubations and/or enrichment cultures. We determined the incorporation of 13C-label from bicarbonate, pyruvate, glucose and amino acids into thau-marchaeal intact polar lipid-glycerol dibiphytanyl glycerol tetraethers (IPL-GDGTs) during 4–6 day incubations of marine sediment cores from three sites on the Iceland Shelf. Thaumarchaeal IPLs were present in sediment cores recovered from the Iceland Shelf and the presence of labile IPL-biomarkers for Thaumarchaeota, such as hexose phosphohexose (HPH)-crenarchaeol, sug-gested the presence of living Thaumarchaeota. However, incubations with 13C-labeled substrates bicarbonate, pyruvate, glucose and amino acids did not result in any substantial incorporation of the 13C into the biphytanyl chains of these lipids. Turnover times and generation times of thau-marchaeal lipids were estimated to be at least several years, suggesting slow growth of sedimen-tary Thaumarchaeota in contrast to other sedimentary organisms, and/or a slow degradation of IPL-GDGTs, in contrast to bacterial or eukaryotic PLFAs.
In Lake Grevelingen sediments (chapter 4), we evaluated the abundance, diversity and poten-tial activity of denitrifying, anammox, and sulfide-dependent denitrifying bacteria in the sedi-ments of the seasonally hypoxic saline Lake Grevelingen, known to harbor an active microbial community involved in sulfur oxidation pathways. Depth distributions of 16S rRNA gene, nirS gene of denitrifying and anammox bacteria, aprA gene of sulfur-oxidizing and sulfate-reducing bacteria, and ladderane lipids of anammox bacteria were studied in sediments impacted by sea-sonally hypoxic bottom waters. This study unraveled the coexistence and potential activity of heterotrophic and autotrophic denitrifiers, anammox bacteria as well as SOB/SRB in seasonally hypoxic and sulfidic sediments of Lake Grevelingen. The nirS-type heterotrophic denitrifiers were a stable community regardless of changes in oxygen and sulfide concentrations in different seasons and with a similar abundance to that detected in other sediments not exposed to high sulfide concentrations. Besides, nirS-type denitrifiers outnumbered anammox bacteria leading to the conclusion that anammox does not contribute significantly to the N2 removal process in Lake Grevelingen sediments. The anammox bacteria population seemed to be affected by the physicochemical conditions between seasons and their abundance and activity was higher in lower sulfide concentrations and low carbon input, also supporting a possible inhibition of anammox bacteria by sulfide. The sulfide-dependent denitrifiers in Lake Grevelingen sediments have proven to be abundant, but their expected sulfide-detoxification potential did not seem to alleviate the predicted inhibition of organoheterotrophic denitrifiers and anammox by sulfide. Both denitrifiers and anammox bacteria activity could be inhibited by the competition with cable bacteria and Beggiatoaceae for electron donors and acceptors (such as sulfide, nitrate and nitrite) before summer hypoxia but might be still supported by the potential sulfide detoxification of the sediment through sulfide oxidation, supporting at least a low activity. During summer hypoxia, sulfide inhibition and low nitrate and nitrite concentrations seem to limit the activity of hetero-trophic and autotrophic (sulfide-dependent) denitrifiers and anammox bacteria.
Additionally, we examined the changes in activity and structure of the sedimentary chem-olithoautotrophic bacterial community in Lake Grevelingen under oxic (spring) and hypoxic (summer) conditions (Chapter 5). Combined 16S rRNA gene amplicon sequencing and analysis of phospholipid derived fatty acids indicated a major temporal shift in community structure. Chemolithoautotrophy rates in the surface sediment were three times higher in spring compared to summer. Besides, the depth distribution of chemolithoautotrophy was linked to the distinct sulfur oxidation mechanisms identified through microsensor profiling, i.e., canonical sulfur ox-
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idation, electrogenic sulfur oxidation by cable bacteria, and sulfide oxidation coupled to nitrate reduction by Beggiatoaceae. The metabolic diversity of the sulfur-oxidizing bacterial community suggests a complex niche partitioning within the sediment probably driven by the availability of reduced sulfur compounds and electron acceptors regulated by seasonal hypoxia.
In Lake Grevelingen sediments, we also compared the archaeal abundance and composition by DNA-based methods and the archaeal intact polar lipid (IPL) diversity in surface sediments to determine the potential biological sources of the archaeal IPLs detected in surface sedi-ments under changing environmental conditions (Chapter 6). We observed a dramatic change in the archaeal community composition and lipid abundance in surface sediments of a season-ally hypoxic marine lake which corresponded to a switch from a Thaumarchaeota-dominated to a DPANN-dominated archaeal community, while the total IPLs detected were significantly reduced. Considering the reduced genome of the members of the superphylum DPANN and their apparent inability to synthesize their own membrane lipids, we hypothesize that they use the CLs previously synthesized by the Thaumarchaeota to form their membrane. Results indi-cate an active recycling of fossil IPLs in the marine surface sediment.
Overall, the research presented in this thesis has provided new insights on the diversity, abun-dance and activity of chemolithoautotrophic microorganisms, such as AOA, AOB, anammox and denitrifying bacteria, as well as sulfate reducing and sulfur oxidizing microorganisms, includ-ing sulfide-dependent denitrifiers in coastal marine sediments. Hypoxia and increasing sulfide concentration have proven to be key factors restricting the presence and activity of the above mentioned groups. In addition, the interactions with other microbial groups and bioturbation seem to favor the presence of specific chemolithoautotrophs in unexpected sediment depths, such as the presence of AOA in depths where the oxygen concentration was expected to be undetectable, or the presence of anammox bacteria in bioturbated sediments where nitrate re-ducers could thrive and provide nitrite to fuel the anammox process. In general, the methods employed in these studies regarding the gene expression and abundance of key metabolic genes of chemolithoautotrophs under different environmental and physiological conditions have shed further light on the role of this group in the carbon and nitrogen cycle in coastal sediments. However, the connection between gene expression and the activity of the actual process is still be problematic and future studies should address the regulation of specific metabolic genes un-der different physiological and environmental conditions. Finally, the application of specific lipid biomarkers to detect the presence and abundance of specific chemolithoautotrophs in coastal sediments (i.e. crenarchaeol for Thaumarchaeota, ladderane lipids for anammox) has revealed a potential preservation effect of these biomarkers in deeper sediments potentially invalidating their use as proxies of living biomass. Further studies are needed to fully assess this effect as well as the recycling of intact polar lipids by specific archaeal groups.
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Samenvatting
De rol die chemolithoautotrofe micro-organismen spelen in sedimenten van kustzeeën is nog steeds onduidelijk. Met name is het effect van het optreden van seizoensgebonden hypoxische/anoxische condities op de microbiële chemolithoautotrofe gemeenschappen niet onderzocht. In dit proefschrift is de diversiteit, celaantallen en activiteit van specifieke groepen chemolithoau-totrofe micro-organismen die actief zijn in de stikstof- en zwavelcyclus, in relatie tot de totale microbiële gemeenschap, in kustsedimenten onderzocht door gebruik te maken van op DNA/RNA en lipiden gebaseerde biomarker benaderingen. Specifiek gaat het om ammonia-oxideren-de archaea (AOA) en bacteriën (AOB), anammox en denitrificerende bacteriën, sulfaat-reducer-ende en zwavel-oxiderende micro-organismen (waaronder sulfide-afhankelijke denitrificerende bacteriën). Ook werden de diversiteit en activiteit van chemolithoautotrofe micro-organismen betrokken bij de CBB- en rTCA-cycli bestudeerd. De studie richtte zich op sedimenten van kustzeeën, d.w.z. (1) de Oestergronden in de centrale Noordzee, die gedurende de zomer bloot-gesteld zijn aan verlaagde zuurstofconcentraties, (2) verschillende soorten sedimenten (zand, klei en modder) van de IJslandse kustzeeën, en (3) hypoxische en sulfidische sedimenten van het zoute Grevelingenmeer (Nederland), blootgesteld aan seizoensgebonden hypoxia. De resul-taten laten het belang van chemolithoautotrofe micro-organismen in de biogeochemische cycli van koolstof, stikstof en zwavel zien. Seizoensgebonden veranderingen in zuurstofconcentratie leiden tot grote tijdelijke veranderingen in het aantal, de diversiteit, en activiteit van chemolitho-autotrofe micro-organismen.
In de gebioturbeerde sedimenten van de Oestergronden in de zuidelijke Noordzee zijn de seizoensvariaties en diepteverdeling in concentratie van AOA en AOB en anammox-bacteriën in relatie tot omgevingsfactoren bestudeerd (hoofdstuk 2). Specifieke intacte polaire lipiden (IPL) zijn gekwantificeerd. Daarnaast werden specifieke 16S rRNA-genen, het ammoniakmonoox-ygenase subeenheid A (amoA) gen van AOA en AOB, en het hydrazine synthase (hzsA) gen van anammox bacteriën en hun expressie gekwantificeerd. AOA, AOB en anammox bacteriën werden gedetecteerd en waren actief tot 12 cm diepte in het sediment. Het metabolisme van deze microbiële groepen is ruimtelijk gekoppeld op basis van zuurstofverbruik, hetgeen de coëx-istentie van aërobe en anaërobe ammonia-oxiderende bacteriën mogelijk maakt. AOA waren gedurende het hele jaar meer dominant aanwezig dan AOB, hetgeen waarschijnlijk veroorzaakt wordt door de hogere zuurstofaffiniteit van AOA in vergelijking met AOB. De celaantallen en activiteit van anammox bacteriën waren hoger in de zomer. Dit wordt waarschijnlijk veroorzaakt door hogere temperaturen en lagere zuurstofbeschikbaarheid in de sedimenten gedurende de periode van zomerstratificatie. Gedurende de zomer zijn de anammox bacteriën waarschijnlijk niet in concurrentie met AOA en AOB voor ammonia omdat de concentraties betrekkelijk hoog waren in het poriewater van het sediment, waarschijnlijk als gevolg van ammonificatie processen.
In sedimenten van IJslandse kustzeeën werden de activiteit van ammonia-oxiderende Thau-marchaeota onderzocht met behulp van verschillende 13C-gelabelde substraten, die in eerdere studies met incubatie met verrijkingsculturen en zeewater succesvol bleken (hoofdstuk 3). Sedi-mentkernen werden gedurende 4-6 dagen geïncubeerd met 13C-gelabeled bicarbonaat, pyruvaat, glucose en aminozuren en opname van het label in Thaumarchaeale in de membraanlipiden (intacte polaire glyceroldibiphytanylglyceroltetraethers; IPL-GDGTs) werd bepaald. De aan-wezigheid van labiele IPL-GDGT membraanlipiden karakteristiek voor Thaumarchaeota, zoals
192
hexosefosfoshexose (HPH) -crenarchaeol, duidde op de aanwezigheid van levende Thaumar-chaeota. Incubatie met de 13C-gemerkte substraten leidde echter niet tot een substantiële inbouw van het 13C label in de bifytanylketens van deze membraanlipiden. Omzettijden en generatieti-jden van thaumarchaeale lipiden werden geschat op ten minste enkele jaren, hetgeen duidt op een trage groei van sedimentaire Thaumarchaeota of een langzame afbraak van IPL-GDGTs. Dit contrasteert met de bacteriële of eukaryotische membraanlipiden (vetzuren afkomstig van polaire lipiden) waar het label wel in terecht kwam.
In het sediment van het Grevelingenmeer werden de diversiteit, celaantallen en potentiële activiteit van denitrificerende, anammox en sulfide-afhankelijke denitrificerende bacteriën be-studeerd (hoofdstuk 4). De concentratie van 16S rRNA-genen, het nirS-gen van denitrificeren-de en anammox bacteriën, het aprA-gen van zwavel-oxiderende (SOB) en sulfaat-reducerende (SRB) bacteriën en ladderaanlipiden van anammox bacteriën werd bepaald in sedimenten tot 5 cm diepte op drie verschillende plaatsen en op twee verschillende momenten in het jaar. De condities in de sedimenten van het Grevelingenmeer worden sterk beïnvloed door het seizoens-gebonden optreden van hypoxia in het bodemwater. Deze studie toont de coëxistentie en po-tentiële activiteit van heterotrofe en autotrofe denitrificerende bacteriën, anammox bacteriën en SOB/SRB aan. De heterotrofe denitrificerende bacteriën van het nirS-type vormen een sta-biele gemeenschap, die onafhankelijk is van de veranderingen in zuurstof- en sulfideconcentratie gedurende de verschillende seizoenen. Hun celaantallen zijn even hoog als in sedimenten die niet gekenmerkt werden door hoge sulfideconcentraties. NirS-type denitrificerende bacteriën overtroffen in aantal de anammox bacteriën, hetgeen suggereert dat anammox niet significant bijdraagt aan stikstofverwijdering in sedimenten van het Grevelingenmeer. De gentranscriptie activiteit van denitrificerende en anammox bacteriën evenals van zwaveloxiderende, waaronder sulfide-afhankelijke denitrificerende en sulfaat-reducerende bacteriën, werden mogelijk door de accumulatie van sulfide in de zomer geïnhibeerd. Zowel de denitrificerende en anammox bac-teriën kunnen worden belemmerd door de concurrentie voor NO3
- en NO2- met kabel- en Beg-
giatoa-achtige bacteriën voor zomerhypoxia. Resultaten suggereren dat sulfide verwijdering door zwavel-oxiderende bacteriën onvoldoende is om de activiteit van denitrificerende en anammox bacteriën in de sedimenten van het Grevelingenmeer te ondersteunen.
In hoofdstuk 5 is het effect van seizoensgebonden hypoxia op de activiteit en de gemeen-schapsstructuur van chemolithoautotrofe bacteriën onderzocht in sedimenten van het Grevelin-genmeer voor (Maart) en tijdens (Augustus) het optreden van zomerhypoxia. Gecombineerde 16S rRNA gen amplicon sequencing en PLFA analyse onthulde een belangrijke temporale ver-schuiving in de gemeenschapsstructuur. Aërobe zwavel-oxiderende Gamma- en Epsilonproteo-bacteriën overheersten de chemolithoautotrofe gemeenschap in het voorjaar, terwijl Deltapro-teobacteriën veel meer voorkwamen tijdens de zomer. De bijdrage van chemolithoautotrofe bacteriën, bepaald m.b.v. PLFA-SIP, was drie maal hoger in de lente dan tijdens de zomer, vooral in oppervlaktesedimenten. De dominantie van cbbL (RuBisCO) en aclB (ATP-citraat lyase) genen liet een overheersing, onafhankelijk van het seizoen en plaats, van micro-organismen die de CBB cyclus gebruiken in vergelijking met de rTCA cyclus zien. De diepteverdeling in het sediment van chemolithoautotrofie was gekoppeld aan de verschillende zwavel-oxidatiemechanismen, die werden geïdentificeerd door middel van microsensorprofielen, d.w.z. kanonische zwavel-oxi-datie, elektrogenische zwavel-oxidatie door kabelbacteriën en sulfide-oxidatie gekoppeld aan nitraatreductie door Beggiatoaceae. De metabolische diversiteit van de zwavel-oxiderende bacte-
193
riële gemeenschap suggereert een complexe verdeling van niches in het sediment, waarschijnlijk veroorzaakt door de beschikbaarheid van gereduceerde zwavelverbindingen (H2S, S0 en S2O3
2-) en elektronacceptoren (O2 en NO3
-), gereguleerd door het optreden van seizoensgebonden hy-poxia.
In de oppervlakte sedimenten van het Grevelingenmeer is de op DNA-gebaseerde archaeale diversiteit en distributie vergeleken met die op basis van archaeale intacte membraanlipiden om de potentiële biologische bronnen van de archaeale IPLs te detecteren (hoofdstuk 6). De ar-chaeale levensgemeenschap veranderde ten gevolge van de hypoxia van het bodemwater van een door Thaumarchaeota-gedomineerde in een door DPANN-gedomineerde archaeale levens-gemeenschap. Tegelijkertijd nam de concentratie IPL-GDGTs met een orde van grootte af. Archaea in het superphylum DPANN worden gekenmerkt door een klein genoom en bezitten geen genen die coderen voor eiwitten die de synthese van membraanlipiden katalyseren. Op ba-sis hiervan is de hypothese geponeerd dat zij zogenaamde core lipiden gebruiken die eerder door de Thaumarchaeota zijn gesynthetiseerd om hun membraan te vormen. Dit zou duiden op een actieve recycling van fossiele IPL-GDGTs in oppervlaktesedimenten.
Samenvattend heeft het onderzoek in dit proefschrift nieuwe inzichten verschaft met betrek-king tot de diversiteit, celaantallen en activiteit van chemolithoautotrofe micro-organismen. Hy-poxia en sulfideconcentratie zijn belangrijke factoren die hun aanwezigheid en activiteit beperken. Bovendien lijken de interacties met andere microbiële groepen en bioturbatie de aanwezigheid van specifieke chemolithoautotrofe microben op onverwachte sedimentdiepten te bevorderen, zoals de aanwezigheid van AOA in sedimentlagen waar zuurstof niet detecteerbaar was. In het algemeen hebben de methoden die in deze studies worden toegepast met betrekking tot de gen-expressie en de overvloed aan belangrijke metabolische genen van chemolithoautotrophs onder verschillende milieu- en fysiologische omstandigheden, de rol van deze groep in de koolstof- en stikstofcyclus in kustsedimenten verder benadrukt. De directe koppeling tussen genexpressie en activiteit is echter nog steeds niet eenduidig en toekomstige studies zullen de regulering van spec-ifieke metabolische genen onder verschillende fysiologische en milieuomstandigheden verder moeten bestuderen. Tenslotte heeft het onderzoek aangetoond dat specifieke lipide biomarkers de potentie hebben om specifieke chemolithoautotrofe microben in sedimenten van kustzeeën te detecteren (bijv. crenarchaeol voor Thaumarchaeota, ladderaan lipiden voor anammox bacte-riën). Omdat deze lipiden bewaard kunnen blijven in sedimenten hebben zij potentie om gebrui-kt te worden in de reconstructie van vroegere microbiële activiteit. De mogelijke recycling van intacte polaire lipiden door specifieke archaea is een proces dat dit gebruik mogelijk zou kunnen compliceren.
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Acknowledgements
During the past years, I have made experiences that I would have missed, if I would not have worked at the NIOZ on Texel. There are many people I’d like to thank for making it a good experience.
First of all, to my supervisors, Laura, thank you so much for everything and especially for your outstanding support and patience over the past years. It has been a rocky road and I have learnt a lot from you scientifically but also about living far away of your family on a small island in the North Sea. Thank you very much for your open ears whenever I needed you for assistance or just to motivate myself again. You have been the best supervisor that I can imagine! This is not self-evident in this rushing times! Jaap, thanks a lot for your time and effort, reviewing the publications and the thesis, especially in the last phase of the process. It was a great pleasure to work with you. Stefan, thank you very much for your constructive comments and discussions especially during my first phase, I have learnt a lot from you, especially how to deal with scientific articles during our literature discussions. Thank you all for always leaving your door open!
Elda, Harry, Judith and Anneke, thanks a lot for hosting and teaching me in the molecular lab. It was a great pleasure to work with you and as well to chat and sing along during long hours in the lab. You made me feel very welcome in the old and brown part of the building. Elda, thank you for offering your desk to me. It was my favorite spot!
Ellen and Nicole, thanks a lot for sharing your expertise and teaching me in the lipid lab, where I was completely unexperienced before I came to the NIOZ. Jort, Monique, Denise, Anchelique and Irene, thanks for your help with extraction methods, machines and data analysis as well for cheering me up a lot! Marianne, thank you very much for your support in the lab, but especially for your help and nice chats during our cruise to and around Iceland. I will always remember that trip! Sebastiaan, thank you very much for technical and human support on the cruise and during my time at NIOZ, I’ve never met a gentler person with such a dry and clever sense of humor!
Sabine, thanks a lot for the nice collaboration during the Iceland cruise. I have learnt a lot from you scientifically, but also about life! It was my pleasure to meet you and get to know you a bit closer. You are an amazing person! Don’t ever change for others!
Marcel and Sandra, I would like to thank you for the nice collaboration during the Grevelingen campaign. It was funny and exciting! Additionally, a big thanks goes to the people from NIOZ Yerseke. Eric and Filip, thanks for inviting us to join the Grevelingen campaign. Diana, a special thanks to you for the excellent collaboration and your support. Dorina, Fatimah and Mathilde, thank you very much for the good collaboration and your support with data. Alexandra Vasquez Cardenas, thanks a lot for providing Figure 2 of the introduction.
The crazy thing about this small island in the North Sea and the NIOZ is, that I got to know the nicest people from all over the world. Some of them stay friends forever! Jenni, Martina, Marta, Catia, Claudia, Santi and Mireia, you will be always on my mind! Alex, Tristan, Maram, Johann, Santi and Sergio, thank you very much for being the nicest neighbors and friends in the special Potvis situation, which welds together! Thank you for sharing so many things with me, good and bad times! I am looking forward to see you again!
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A big thanks to all the people in the MMB department (and others) making work and life more enjoyable; Marc, Daniela, Yuki, Andreas, Darci, Sabine, Petra, Raquel, Elisabeth, Lisa, Eli, Sandra, Dave, John, Marcel, Sebastian, Cindy, Rob, Luke, Frederike, Rodrigo, and Kevin thanks for your company!
My office mates over the past years had to stand me and my moody phases, but they did well and cheered me up a lot! Lisa, Cecile, Sandra, Mireia, Eva and Michel, thanks for the nice time!
Down at NIOZ tropical, I have met some amazing people; Christine, Francesc, Francesco and Michele, it was very nice to talk about other things than science and enjoy your culinary skills.
Ashes over my head, but I have spent some time in the smoking room, and as usual, smokers make friends quite quickly. Kees, Ronald, Geert-Jan, Anneke and Edward, thanks a lot for nice chats and a bit of distraction.
For the “new” PhD students, Julie, Marijke, Gabriella, Saara, Laura, Caitlyn and Sophie; Success for your future and good luck with your thesis!
Michael Hagemann, Danke für Deine Hilfe in den letzten Zügen! Ohne Deinen scharfen Verstand und die Bereitschaft zu helfen, hätte ich es nicht gepackt!
Dieser Dank gilt allen meinen Freundinnen, die mich auf dem Weg ermutigt und unterstützt haben (wenn auch manchmal nur am Telefon); Miri, Helena, Moni, Svenja, Anni und Marén, ihr seid großartige Wegbegleiter!
Miri, Du bist die einzige, die wirklich versteht, was es heißt, auf Texel zu wohnen! Schön, daß wir die Erfahrung teilen!
Jetzt aber das Wichtigste, die Familie! Mama, Reimund und Papa, euch verdanke ich wer und wo ich bin! Ohne Eure langjährige Unterstützung und eure Geduld, hätte ich es nicht geschafft! Danke für Alles! Tobias, mein Bruderherz, Du bist der beste Bruder der Welt! Danke für Deine Unterstützung und Treue! Klausi, mein Herz, Danke, daß Du immer für mich da warst! Es war eine lange Reise, ich bin gespannt wo es als nächstes hingeht!
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About the Author
Yvonne Antonia Lipsewers was born on the 18th of July 1977 in Salzkotten, Germany. During her Abitur she gained interest in aquatic biology and was motivated by her biology teacher with a seminar about hydrology. After leaving secondary school, she first started studying food technol-ogy before finally, studying Biology at the University of Bielefeld from 2003 until 2007. After-wards, she was specializing in Marine Microbiology during her Master’s at the Institute of Chem-istry and Biology of the Marine Environment associated to the Carl-von-Ossietzky Universität in Oldenburg from 2008 until 2010. She completed a Master’s research project investigating the shift of the heterotrophic bacterial community composition during the aggregation of a diatom bloom in the North Sea. After graduating in 2010, Yvonne started a PhD project at NIOZ in 2011, focused on tracing chemolithoautotrophic microorganisms in coastal sediments, under the supervision of Dr. Laura Villanueva, which finally led to the composition of this thesis.
