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Microbial management of anaerobic digestion:exploiting the microbiome-functionality nexusMarta Carballa, Leticia Regueiro and Juan M Lema
Available online at www.sciencedirect.com
ScienceDirect
Anaerobic reactors are mostly operated based on the
monitoring of process parameters and empirical expert
knowledge due to the limitations of microbial-based
management. This review analyzes the requirements to
conduct microbial management in anaerobic digestion,
emphasizing the importance of understanding the anaerobic
microbiome and the need of establishing microbial indicators of
optimal performance. The strategies currently applied to shape
the reactor microbiome are explored and we assess critically
the different types of management (retrospective, prospective
and proactive). We conclude that future research should lead to
more useful data or insights to accomplish proactive
management, seen as stimulation and anticipation rather than
remediation.
Addresses
Department of Chemical Engineering, Institute of Technology, University
of Santiago de Compostela, E-15782 Santiago de Compostela, Spain
Corresponding author: Carballa, Marta ([email protected],
Current Opinion in Biotechnology 2015, 33:103–111
This review comes from a themed issue on Environmental
biotechnology
Edited by Spiros N Agathos and Nico Boon
For a complete overview see the Issue and the Editorial
Available online 13th February 2015
http://dx.doi.org/10.1016/j.copbio.2015.01.008
0958-1669/# 2015 Elsevier Ltd. All rights reserved.
IntroductionThe human society is claiming for a renewable energy
supply and anaerobic digestion (AD) can make a substan-
tial sustainable contribution since it simultaneously solves
the problem of organic waste management, reducing its
deposition in landfills. AD consists of liquefaction and
hydrolysis of insoluble organic compounds and gasification
of intermediates, accompanied by a partial or complete
mineralization and humification of the organic matter.
Although AD is a well-known and consolidated technolo-
gy, the key players of anaerobiosis and their associations
and functioning are not completely understood yet. The
* Microbiome is defined as a group of microorganisms cooperating and inter
organization [1, 2��].
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complexity of the anaerobic microbiome* and the high
number of uncharacterized microorganisms [3��], the high
specialized functioning due to thermodynamic constrains
[4], the limitations of the frequently used DNA-based
methods [2��] and the continuous entrance of microorgan-
isms with the feedstock in open systems [5] are some of the
reasons of this gap. Additionally, the higher phylogenetic
diversity, multiple microbial interactions and the redun-
dant microbial functions hampers the microbial-based
management of anaerobic reactors. Yet, some efforts have
been made in the past years for monitoring complex
microbial communities and to set the standard character-
istics of an anaerobic microbiome for an optimal perfor-
mance, that is, successful (high efficiency at high rate)
methane production and process stability. In this review,
the requirements to conduct microbial management in
anaerobic digestion are analyzed. The combination of
fundamental knowledge about the anaerobic microbiome
with microbial indicators of optimal performance should
enable the development of microbial-based management.
In addition, the strategies currently applied to shape the
reactor microbiome are described and a critical and com-
parative assessment of the different types of management
(retrospective, prospective and proactive) is performed.
Needs for microbial management in anaerobicdigestionTwo needs for microbial management of anaerobic reac-
tors were identified: to understand the anaerobic micro-
biome, that is, fundamental knowledge about microbial
communities, including how they behave against envi-
ronmental and process disturbances, and to set microbial
indicators of optimal performance, that is, benchmark
values for well-performing reactors as well as warning
indicators of process failure.
Understanding the anaerobic microbiome:hydrolytic versus methanogenic functionThe conversion of complex organic compounds to CH4 and
CO2 is possible due to the cooperation of different micro-
organisms, that are clustered in two main domains: Bacteria,
in charge of decomposing the organic matter into volatile
fatty acids (VFAs), CO2 and H2, and Archaea, responsible of
CH4 formation [6�]. Moreover, the syntrophic relationship
between microorganisms producing and consuming hydro-
gen is necessary to guarantee efficient and stable operation.
acting among them, showing a higher resilience level of functionality and
Current Opinion in Biotechnology 2015, 33:103–111
104 Environmental biotechnology
y PCA: principle component analysis; PCoA: principle coordinate
analysis; RDA: redundancy analysis, NMDS: nonmetric multidimen-
sional scaling.
Most studies target Archaea [7,8], as methanogenesis is
usually the rate-limiting step and the low diversity of
archaeal population hinders the functional redundancy
[9]. However, the monitoring of bacterial populations
becomes essential in anaerobic reactors treating solid waste,
in which the hydrolytic phase is often the bottleneck.
As functioning and stability of an anaerobic reactor rely on
microbial community structure, understanding anaerobic
microbiome composition and interactions is crucial. The
biodiversity of the anaerobic microbiome is not only
influenced by the environment (especially temperature
[10] or the type of substrate (which also determines the
rate-limiting step), but also by the arrival and quantity of
new species [11]. Proteobacteria, Firmicutes, Bacteroidetesand Chloroflexi are the four major phyla in the bacterial
domain [12,13��], whose diversity is mainly driven by the
use of different substrates [5,14,15] and the operational
conditions, such as temperature [16,17] or organic loading
rate (OLR) [18]. For instance, lipid-rich substrates pro-
mote Thermosediminibacter litoperuensis presence [14],
higher OLRs favor the dominance of Firmicutes species
[18] and Bacteroidetes and Chloroflexi predominate at meso-
philic temperature [17]. On the contrary, the archaeal
population is steered by the reactor environment, mainly
the concentrations of volatile fatty acids (VFAs) [19,20],
ammonium [20] and temperature [16], as well as by
reactor configuration [19,21], with Methanosaeta and the
uncharacterized WSA2 group [12,22] as dominant species.
Recently, a clear relationship between operation and
microbiome was detected and three clusters based on
the operational conditions (easy, harsh and very harsh)
were proposed [23].
However, to design microbial-based strategies to manage
anaerobic reactors, not only the microbial community
structure during steady-state performance is required,
but also how they react to operational or environmental
disturbances. Some information is available about the
response of the archaeal domain, but these patterns are
poorly understood for bacterial populations. Overall,
stressful conditions, such as loading shock events, de-
creased hydraulic retention times (HRTs), temperature
variations, increased ammonium or long chain fatty acid
(LCFA) concentrations, promote the dominance of
Methanobacteriaceae, Methanomicrobiaceae and Methanosar-cina and a likely shift from aceticlastic methanogenesis to
syntrophic acetate oxidation followed by hydrogeno-
trophic methanogenesis [24–27,28��].
Certainly, the rapid development in culture-independent
techniques over the last decade has generated a lot of data
about the anaerobic microbiome, but the link between
microbial community structure with reactor functioning is
still unclear [3��]. Future research should focus not only on
the simultaneous identification of phylogeny, interrela-
tionships and function, but also on microbial population
Current Opinion in Biotechnology 2015, 33:103–111
dynamics during transitional periods caused by environ-
mental stresses or operational disturbances, particularly
the bacterial domain.
Microbial indicators for optimal performanceBenchmark values based on microbial community struc-
ture associated to optimal reactor performance (microbial
indicators) are needed for microbial management of an-
aerobic digestion. By contrast to process performance
indicators (VFA levels, Ripley index, hydrogen concen-
tration, among others), no much information is available
about microbial indicators. In this section, besides review-
ing the published data and speculating on the reasoning
behind each indicator, we will try to distinguish between
monitoring indicators (those associated to good steady-
state performance) and warning indicators (those pointing
out a process disturbance that might end in process
failure).
Firstly, phylogeny-based indicators, that is, presence or
variation on specific microorganism(s), are described. The
importance of Clostridia class, which contribute to degrad-
ing both protein and cellulose, and Bacilli class, responsi-
ble of decomposing fat and carbohydrate, of the phylum
Firmicutes and the phyla Bacteroidetes and Proteobacteriahave been stand out by many authors in solid-based
reactors [13��,16,29–31]. The main explanation lies in
the capacity of these fermentative Bacteria to process a
wide range of substrates [32,33]. The presence of Syn-trophomonas (propionate and butyrate degraders) and
Synergistetes (syntrophic acetate oxidizers) might be a sign
of well acetogenic [11,12] and acetotrophic performance
[34], respectively. The order Methanosarcinales and in a
lesser extent Methanomicrobiales are the dominant Archaea
in stable reactors [9,19], with the genus Methanosaeta as
the main acetate-degrader [19]. The combination of
phylogenetic data with operational/environmental vari-
ables by using computational ecology methods (PCA,
PCoA, RDA, NMDS)y has been widely used in the last
years in order to reinforce the link between microbiome
structure and function. Zingashin [9], for instance, found
a strong correlation between Methanoculleus and ammonia
concentration using NMDS, and Sundberg [13��] corre-
lated higher numbers of Thermotogae and Sphingobacteriawith thermophilic temperatures applying PCA. The lack
of studies assessing Bacteria response to disturbances and
the functional redundancy and resilience of bacterial
populations hampers the selection of a warning bacterial
indicator. On the contrary, Methanosaeta decrease can be
used as warning indicator in Methanosaeta-dominated
reactors [22], while a decrease in the active archaeal
community can be selected for those well-performing
reactors with no presence of this genus [10] (e.g. dry
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Microbial management of anaerobic digestion Carballa, Regueiro and Lema 105
anaerobic digesters or thermophilic digesters with rela-
tively high ammonium).
The huge amount of data derived from the molecular
techniques, particularly the high-throughput methods, calls
for a universal platform to interpret and compare them.
Consequently, a set of tools (here called numerical indica-
tors) have been proposed [1,35], which also incorporates
information about microbiological interactions. To main-
tain functional stability and robustness, three ecological
parameters play an important role: microbial community
diversity, evenness of microbial community structure and
microbial community dynamics over time [1,35–37,38�].
Although there are reactors with low diversity indexes
operating in stable conditions (e.g. those treating simple
substrates [5] or working at high temperature [39]), a
functional diverse microbial community provides a suite
of parallel pathways for each trophic step [37], and thus, a
higher diversity is often correlated with good-performing
anaerobic reactors [5,27,36,40�]. The explanation lies
behind the resistance, resilience and functional redun-
dancy of the anaerobic microbiome (Box 1). The combi-
nation of these three types of populations ensures the
overall functional stability and qualifies the microbial
community to face environmental stresses or process
perturbations [37,41], as shown in Figure 1. However,
the use of diversity as warning indicator is not clear yet.
The technique-dependence of most diversity indexes
and the calculation methods used are the likely argu-
ments for the discrepancy among studies [28��,36].
Evenness in the structure of the microbial diversity
ensures an adequate distribution of dominant microor-
ganisms and resilient ones [35], thereby the community
Box 1 Resistance, resilience and functional redundancy of
anaerobic microbiome
There are three basic mechanisms to maintain microbial community
function over time, regardless a disturbance [37,41]: resistance
(populations able to withstand changes without variations in
composition), resilience (populations with the ability to rebound
following a disturbance) and redundancy (a disturbed population is
replaced by a new population whose function is redundant with the
original, thus not affecting system performance). Applying these
concepts to anaerobic microbiome, the ‘core microbiome’ contains
the resistant populations, but as their contribution to the overall
system functioning is poorly understood, they can only be used as
fingerprint of specific reactor environments. Hydrolytic-fermentative
bacteria are functionally redundant, whereas syntrophic commu-
nities tend to be more resilient [3��]. The latter are usually minority
community members, but extremely function-specialized (only they
can perform the task). Therefore, their upturn following a disturbance
is crucial to preserve or recover the overall system performance.
Archaea are less diverse, metabolically slower and less resilient to
stress than Bacteria [6�]. Therefore, methanogenesis is more
susceptible to stress and instability. We speculate Methanobacter-
iales as resistant, Methanosaeta as redundant and Methanosarci-
na and Methanomicrobiales as resilient and redundant.
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has more capacity to use its varied array of metabolic
pathways [37]. Consequently, microbial communities
with intermediate evenness have a more robust function
[28��,35,37,40�,42]. More important, a decrease in bacte-
rial evenness can be used as warning indicator, as dem-
onstrated by different perturbations (loading shock,
temperature, ammonia) [28��,36]. This is explained by
the fact that anaerobic process requires both key (impor-
tant as they are responsible of a big fraction of the
functioning) and team players (equilibrium approach to
fully exploit all metabolic pathways) in the microbial
community to guarantee well-performance.
The dynamics of populations over time allows the com-
munity to adjust following disturbances, providing the
system with access to the total functional diversity and
environmental specificity available in the community [37].
The population dynamics in anaerobic reactors are quite
unclear, since some researchers observed community shifts
in functionally stable [43,44] and unstable reactors [31,37],
while others observed stable communities in functionally
stable systems [5]. Moreover, some authors suggest a high
population dynamics, mainly bacterial, as a well-function-
ing symptom [36,40�], while others described a stable
community in well-performing reactors [5]. These contro-
versial results are likely due to the functional redundancy
and resilience of the anaerobic microbiome, but hinder the
use of dynamics as microbial indicator.
From the abovementioned results, we propose interme-
diate bacterial evenness and a minimum active archaeal
population as monitoring indicators and a decrease in
bacterial evenness, in Methanosaeta or in the active ar-
chaeal population as warning indicators (Table 1). Yet,
further research is required to establish the optimal values
of these parameters, ideally independent of the molecular
technique used.
Management strategies in anaerobicdigestionDespite the hurdles for microbial-based management,
several strategies are applied to shape the reactor micro-
biome with the ultimate goal to increase methane pro-
ductivity. Current management strategies can be divided
into two groups: microbial-based strategies, those target-
ing directly the microbial community, and operational-
based strategies, those relying on a process parameter
variation, which indirectly affects the microbial commu-
nity. Moreover, a differentiation between boosting (aim-
ing at enhancing reactor performance) and remediation
(aiming at recovering a deteriorated performance) strate-
gies was done (Figure 2).
Microbial-based strategiesAn inoculum with high activity levels and balanced
anaerobic microbial communities plays an important role
in anaerobic reactor start up [6�,45]. Furthermore, the use
Current Opinion in Biotechnology 2015, 33:103–111
106 Environmental biotechnology
Figure 1
REACTOR PERFORMANCE
CH4 PRODUCTION
% VS DESTRUCTION
ACETIC ACID
MICROBIAL COMMUNITY STRUCTURE
Time
REDUNDANT
REDUNDANT
RESISTANT
RESISTANT
RESISTANT
RESILIENT
RESILIENT
DISTURBANCEMICROBIOME LEGEND
COLOUR: mechanisms tomaintain microbial community
function over time.
SHAPE: Microorganism type
RED -> RESISTANTGREEN -> RESILIENT
MULT IPL ECOLOURS -> REDUND ANT
Hydrolytic-fermentative
Acetogenic-Syntrophic
Methanosaeta
Methanobacteriales
Methanomicrobiales
Methanosarcina
Current Opinion in Biotechnology
Understanding the response of anaerobic microbiome to disturbances based on resistance, resilience and redundancy. Left: the legend (shape:
type of microorganism; color: behavior (resistant, resilient or redundant)). Right: the response of the different microbial communities (bottom)
against a process disturbance (up). Hydrolysis-fermentation is not affected (VS destruction is constant) due to functional redundancy.
Acetogenesis-syntrophy is affected (acetate accumulation), but recovered, due to resilience. Methanogenesis is affected (methane yield
decreased), but recovered, due to resilience and functional redundancy. Resistant microorganisms are assumed to be present in all stages.
of an acclimated microbial consortium is a promising
boosting strategy to accelerate the start-up of the diges-
tion process [46,47]. For example, around 5-fold faster
start-up was attained in a reactor treating olive mill
wastewater using an adapted consortium to lipids degra-
dation (Figure 2a, [46]).
Stimulation of microbial growth by trace elements addition
improved the performance of the anaerobic process (higher
methane yields and low levels of VFA) not only during
start-up [48,49], but also during steady-state operation
(Figure 2b, [48]). Furthermore, supplementation of trace
elements resulted to be a successful remediation strategy
to overcome a propionic acid accumulation event ([50],
Figure 2c, [51�]). Different combinations of trace metal
supplementations can have synergistic or antagonistic
Current Opinion in Biotechnology 2015, 33:103–111
effects [52,53], thereby the elements to be supplied and
the dosages are not clear yet. As a consequence, this
strategy is still quite empirical and more research on the
relationship between microbial populations and trace
metals is needed.
Bioaugmentation has been applied to enhance the deg-
radation of problematic substrates, such as lipid-rich feed-
stocks [54,55], or to recover digester performance after
perturbation [56,57]. Increased methane yield (10–24%,
Figure 2d, [54]) and shorter recovery period (70–80 days
earlier, Figure 2e, [56]) were observed after bioaugmen-
tation. Bacterial-based bioaugmentation is mostly used to
enhance solids anaerobic digestion, with the typical used
strains belonging to Pseudomonas, Bacillus and Actinomyces[58]. Archaeal-based bioaugmentation is not often
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Microbial management of anaerobic digestion Carballa, Regueiro and Lema 107
Table 1
Proposed microbial indicators. Phylogeny-based indicators are proposed for Archaea due to its low diversity: a minimum active Archaea
population and a decrease in Methanosaeta or in the active archaeal community as monitoring and warning indicator, respectively. The
high diversity and functional redundancy of bacterial communities hinder the definition of phylogeny-based indicators for Bacteria;
thereby numerical indicators are more appropriate. Among them, evenness is suggested as both monitoring and warning indicator,
supported by several studies. Diversity might also become a monitoring indicator once overcome its technique-dependence.
Monitoring Warning
Phylogenetic
Numerical
Indicator typeBacteria Archaea ArchaeaBacteria
Diversity
Evenness
Dynamics
High
Intermediate Decrease
Stable activearchaeal
population
Mathanosaetaand/or
active archaealpopulation decrease
X X
X
X X
X
XX
X
XX
employed, but recently bioaugmentation of ammonia
tolerant methanogenic consortia has been successfully
applied [59�]. However, bioaugmentation failure cases
have been also reported [60], pointing out that bioaug-
mentation potential is still lacking.
Operational-based strategiesA regular step-wise adaptation of the community to stress-
ful conditions has been used to strengthen the microbiome
against future disturbances (named here as endurance
development). In this way, a higher degree of functional
stability in the anaerobic digester is fostered [28��,38�,61].
For example, a regular application of organic material pulse
rather than continuous feeding allowed the microbial
community to be more tolerant to ammonium levels
(Figure 2f, [38�]). However, the most typical strategy
applied to manage the microbiome is the manipulation
of a process variable. Ho [16] improved the methane yield
by varying temperature and HRT (Figure 2g) and Schmidt
[62] dropped the OLR for few days to surpass a VFA
accumulation event (Figure 2h).
Retrospective versus prospective versusproactive managementThere is a high potential for microbial-based management
in anaerobic digestion with the final goal of initiate a
change in the microbial community to improve methane
production and process stability. But, this is not enough,
because the type of management conducted is also impor-
tant. If we simply evaluate reactor (well or deteriorated)
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functioning and then look backwards to assess microbial
community shifts explaining such performance (here
called retrospective management), the results would be
highly biased because of the several changes taken place
simultaneously and the lack of a comprehensive monitor-
ing. Accordingly learning from such experiments is ex-
tremely difficult. Most of the studies available in literature
performed retrospective management.
On the contrary, if we plan carefully a controlled pertur-
bation experiment with a detailed monitoring scheme
(here called prospective management), we will be able to
gather data to establish trustworthy patterns of microbial
community structure versus functionality. This informa-
tion is scarce in literature, although recently it has been
demonstrated that structural and functional changes can
be reliably predicted under controlled conditions [31] as
deterministic rather than stochastic processes guide mi-
crobial community dynamics.
More interestingly and desirable is the proactive man-
agement, seen as the trend to initiate a change rather than
react to changes. In other words, proactive management
implies stimulating and anticipating rather than remediat-
ing. To be predictive and avoid process failure, an addi-
tional condition is needed: the change at microbial
community level should occur before the change at
macroscopic level (here called as early microbial indica-
tor). Therefore, to accomplish proactive management: (i)
routine analysis of reactor microbiomes should become
Current Opinion in Biotechnology 2015, 33:103–111
108 Environmental biotechnology
Figure 2
Strategy
Ino
culu
mT
race
ele
men
tsB
ioau
gm
enta
tio
nE
nd
ura
nce
dev
elo
pm
ent
Pro
cess
var
iab
lem
anip
ula
tio
n
Boosting Remediation
NOT APPLY
NOT APPLY
50 (a)
(b)
40
30
20
10
0
30
20
10
0
504540353025201510
50
140
120
100
80
60
40
20
200
160
120
80
40
0
0 1 2 3 4
55 °C 60 °C 65 °C
5
12
10
8
6
2
4
00 100 200 300 400 500 600 700 800
0 10 20 30 40 50
50 60 70 80
5 10 15Time (days)
mg
CO
D_C
H4
Time (days) Time (days)
Time (days) SCOD<2 g L–1
Rec
ove
ry p
erio
d (
day
s)
Propionic<200 mg L–1
Time (days)
Time (d)
OL
R (
g L
–1 d
–1)
AC
(g
L–1
)
Pro
pio
nat
e (m
M)
Met
han
e yi
eld
(m
L g
SV
–1)
Rel
ativ
e m
eth
ane
pro
du
ctio
n(%
of
con
tro
l)
Non-acclimatedbiomass
Acclimatedbiomass
Bioaugmentation
Endured reactor
No-endured reactor
Trace elements added
No trace elements
5-fold faster start-up
Improved stability
IncreaseCH4 yield
Endured biomassmore resistant toammonia levels
Immediatepropionatedegradation
Shorter recovery period
Methane yield can be improvedby varying temperature & HRT
OLR drop surpassed acidaccumulation
20
4d_HRT 3d_HRT 2d_HRT
Met
han
e (L
kg
VS
add
ed–1
)
2500
2000
1500
1000
Pro
pio
nic
aci
d (
mg
L–1
)
500
0
0
200
150
100
50
0
100 200 300 400
Bioaugmented
Control
500 600
Trace elementsand lime addition
OLR AC
(d)
(f)
(g) (h)
(e)
(c)
Current Opinion in Biotechnology
(a) Cumulative methane production in batch assays using olive mil wastewater and acetate as substrates with acclimated and non-acclimated
biomass [46]. (b) Propionate levels in reactors with and without trace elements addition [48]. (c) Effect of trace elements supplementation on
propionic acid degradation [51�]. (d) Methane yield in a reactor bioaugmented with Caldicellulosiruptor lactoaceticus at day 28 [54]. (e) Recovery
periods to reach soluble COD and propionic acid concentrations below 1 g/L and 200 mg/L, respectively [56]. (f) Response of endured and non-
endured biomass to high ammonia concentrations [38�]. (g) Variation of methane yield with temperature and HRT [16]. (h) Organic loading rate
(OLR) and acid capacity (AC), calculated as the sum of organic acid concentrations, during the digestion of grain stillage in a CSTR reactor [62].
Current Opinion in Biotechnology 2015, 33:103–111 www.sciencedirect.com
Microbial management of anaerobic digestion Carballa, Regueiro and Lema 109
more feasible (the requirements to fulfill this have already
been reviewed, [2��]), (ii) the large amount of data result-
ing from high-throughput sequencing should be con-
verted into meaningful microbial patterns by using, for
example, data mining, and (iii) robust microbial indicators
and early microbial indicators should be set down. We are
still on the road.
Acknowledgements
This research was supported by the Ministry of Economy andCompetitiveness through (CTM2010-17196) project and the Ramon y Cajalcontract (RYC-2012-10397) and by the Xunta de Galicia throughMicroDAN (EM2012/087) project. The authors belong to the GalicianCompetitive Research Group GRC 2013-032, programme co-funded byFEDER.
References and recommended readingPapers of particular interest, published within the period of review,have been highlighted as:
� of special interest�� of outstanding interest
1. Read S, Marzorati M, Guimaraes BCM, Boon N: Microbialresource management revisited: successful parameters andnew concepts. Appl Microbiol Biotechnol 2011, 90:861-871.
2.��
Koch C, Muller S, Harms H, Harnisch F: Microbiomes inbioenergy production: from analysis to management. CurrOpin Biotechnol 2014, 27:65-72.
This paper highlights the current constraints for routine microbiomeanalysis and lists the desired properties of the analysis methods to beapplied for microbiome-based reactor management. In addition, it illus-trates in two case-studies the potential of a molecular and a cell basedmethod for routine monitoring in bioenergy production.
3.��
Vanwonterghem I, Jensen PD, Ho DP, Batstone DJ, Tyson GW:Linking microbial community structure, interactions andfunction in anaerobic digesters using new moleculartechniques. Curr Opin Biotechnol 2014, 27:55-64.
This review focuses on the suitability of new molecular methods to linkmicrobial community structure to function in anaerobic digesters. Theyconcluded that, in order to fully understand anaerobic microbial com-munities, time resolved meta-omic datasets need to be combined withvisualization methods and chemical analyses.
4. Batstone D, Virdis B: The role of anaerobic digestion in theemerging energy economy. Curr Opin Biotechnol 2014, 27:142-149.
5. Regueiro L, Veiga P, Figueroa M, Lema JM, Carballa M: Influenceof transitional states on the microbial ecology of anaerobicdigesters treating solid wastes. Appl Microbiol Biotechnol 2014,98:2015-2027.
6.�
Ali Shah F, Mahmood Q, Maroof Shah M, Pervez A, Ahmad Asad S:Microbial ecology of anaerobic digesters: the key players ofanaerobiosis. Scientific World J 2014, 2014.
Recent general overview about the anaerobic process (stages, inoculuminfluence), anaerobic microorganisms (highlighting the role of Methano-sarcina and syntrophic acetate oxidizers) and molecular techniquesapplied.
7. Lee C, Kim J, Hwang K, O’Flaherty V, Hwang S: Quantitativeanalysis of methanogenic community dynamics in threeanaerobic batch digesters treating different wastewaters.Water Res 2009, 43:157-165.
8. Steinberg LM: Regan JM: mcrA-targeted real-time quantitativePCR method to examine methanogen communities. ApplEnviron Microbiol 2009, 75:4435-4442.
9. Ziganshin AM, Liebetrau J, Proter J, Kleinsteuber S: Microbialcommunity structure and dynamics during anaerobicdigestion of various agricultural waste materials. ApplMicrobiol Biotechnol 2013, 97:5161-5174.
www.sciencedirect.com
10. Kundu K, Bergmann I, Klocke M, Sharma S, Sreekrishnan TR:Impact of abrupt temperature increase on the performance ofan anaerobic hybrid bioreactor and its intrinsic microbialcommunity. Biores Technol 2014, 168:72-79.
11. Regueiro L, Carballa M, Lema JM: Outlining microbialcommunity dynamics during temperature drop andsubsequent recovery period in anaerobic co-digestionsystems. J Biotechnol 2014, 192:179-186.
12. Nelson MC, Morrison M, Yu Z: A meta-analysis of the microbialdiversity observed in anaerobic digesters. Biores Technol 2011,102:3730-3739.
13.��
Sundberg C, Al-Soud WA, Larsson M, Alm E, Yekta SS,Scvensson BH, Sorenson SJ, Karlsson A: 454 pyrosequencinganalyses of bacterial and archaeal richness in 21 full-scalebiogas digesters. FEMS Microbiol Ecol 2013, 85:612-626.
The authors examined extensively the microbial community of 21 full-scale anaerobic reactors using 454 pyrosequencing of 16S rRNA genesequences, correlating the microbial composition to substrate differ-ences and operational temperature.
14. Wagner AO, Lins P, Malin C, Reitschuler C, Illmer P: Impact ofprotein-, lipid- and cellulose-containing complex substrateson biogas production and microbial communities in batchexperiments. Sci Total Environ 2013, 458:256-266.
15. Zhang W, Werner JJ, Matthew AT, Angenent LT: Substrates typedrives variation in reactor microbiomes of anaerobicdigesters. Biores Technol 2014, 151:397-440.
16. Ho DP, Jensen PD, Batstone DJ: Effects of temperature andhydraulic retention time on acetotrophic pathways andperformance in high-rate sludge digestion. Environ Sci Technol2014, 48:6468-6476.
17. Lee S-H, Kang H-J, Lee YH, Lee TJ, Han K, Choi Y, Park H-D:Monitoring bacterial community structure and variability intime scale in full-scale anaerobic digesters. J Environ Monit2012, 14:1893-1905.
18. Jang HM, Lee JW, Ha JH, Park JM: Effects of organic loadingrates on reactor performance and microbial communitychanges during thermophilic aerobic digestion process ofhigh-strength food wastewater. Biores Technol 2013, 148:261-269.
19. Leclerc M, Delgenes JP, Godon JJ: Diversity of the archaealcommunity in 44 anaerobic digesters as determined by singlestrand conformation polymorphism analysis and 16S rDNAsequencing. Environ Microbiol 2004, 6:809-819.
20. Karakashev D, Batstone DJ, Angelidaki I: Influence ofenvironmental conditions on methanogenic compositionsin anaerobic biogas reactors. Appl Environ Microbiol 2005,71:331-338.
21. Nelson MC, Morrison M, Schanbacher F, Yu Z: Shifts in microbialcommunity structure of granular and liquid biomass inresponse to changes to infeed and digester design inanaerobic digesters receiving food-processing wastes. BioresTechnol 2012, 107:135-143.
22. De Vrieze J, Hennebel T, Boon N, Verstraete W: Methanosarcina:the rediscovered methanogen for heavy duty biomethanation.Biores Technol 2012, 112:1-9.
23. De Vrieze J, Saunders A, He Y, Verstraete W, Boon N: Operationalconditions determine the anaerobic digestion microbiome.Biogas Microbiology, 2nd International Conference, Book ofAbstracts. 2014.
24. Sousa DZ, Pereira MA, Stams AJM, Alves MM, Smidt H: Microbialcommunities involved in anaerobic degradation ofunsaturated or saturated long-chain fatty acids. Appl EnvironMicrobiol 2007, 73:1054-1064.
25. Steinberg LM, Regan JM: Response of lab-scale methanogenicreactors inoculated from different sources to organic loadingrate shocks. Biores Technol 2011, 102:8790-8798.
26. Bialek K, Kumar A, Mahony T, Lens PN, O’Flaherty V: Microbialcommunity structure and dynamics in anaerobic fluidized-bedand granular sludge-bed reactors: influence of operational
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110 Environmental biotechnology
temperature and reactor configuration. Microbial Biotech 2012,5:738-752.
27. Ma J, Zhao B, Frear C, Zhao Q, Yu L, Li X, Chen S:Methanosarcina domination in anaerobic sequencing batchreactor at short hydraulic retention time. Biores Technol 2013,137:41-50.
28.��
Werner JJ, Garcia ML, Perkins SD, Yarasheski KE, Smith SR,Muegge BD, Stadermann FJ, DeRito CM, Floss C, Madsen EL,Gordon JI, Angenent LT: Microbial community dynamics andstability during an ammonia-induced shift to syntrophicacetate oxidation. Appl Environ Microbiol 2014, 80:3375-3383.
Authors observed a clear shift from acetoclastic methanogenesis to analternative acetate-consuming pathway of syntrophic acetate oxidation(SAO) as a response to an increase in the ammonia loading. Bacterialphylotypes became more uneven after perturbation, but they returned tomore even communities once SAO bacteria allowed reactors maintainstable performance.
29. Hanreich A, Schimpf U, Zakrzewski M, Schluter A, Benndorf D,Heyer R, Rapp E, Puhler A, Reichl U, Klocke M: Metagenome andmetaproteome analyses of microbial communities inmesophilic biogas-producing anaerobic batch fermentationsindicate concerted plant carbohydrate degradation. Syst ApplMicrobiol 2013, 36:330-338.
30. Li A, Chu YN, Wang X, Ren L, Yu J, Liu X, Yan J, Zhang L, Wu S,Li S: A pyrosequencing-based metagenomic study ofmethane-producing microbial community in solid-statebiogas reactor. Biotechnol Biofuels 2013, 6:3.
31. Vanwonterghem I, Jensen PD, Dennis PG, Hugenholtz P,Rabaey K, Tyson GW: Deterministic processes guide long-termsynchronised population dynamics in replicate anaerobicdigesters. ISME J 2014 http://dx.doi.org/10.1038/ismej.2014.50.
32. Tracy BP, Jones SW, Fast AG, Indurthi DC, Papoutsakis ET:Clostridia: the importance of their exceptional substrate andmetabolite diversity for biofuel and biorefinery applications.Curr Opin Biotechnol 2012, 23:364-381.
33. Merlino G, Rizzi A, Schievano A, Tenca A, Scaglia B, Oberti R,Adani F, Daffonchio D: Microbial community structure anddynamics in two-stage vs single-stage thermophilic anaerobicdigestion of mixed swine slurry and market bio-waste. WaterRes 2013, 47:1983-1995.
34. Ito T, Yoshiguchi K, Ariesyada HD, Okabe S: Identification andquantification of key microbial trophic groups ofmethanogenic glucose degradation in an anaerobic digestersludge. Biores Technol 2012, 123:599-607.
35. Marzorati M, Wittebolle L, Boon N, Daffonchio D, Verstraete W:How to get more out of molecular fingerprints: practical toolsfor microbial ecology. Environ Microbiol 2008, 10:1571-1581.
36. Carballa M, Smits M, Etchebehere C, Boon N, Verstraete W:Correlations between molecular and operational parametersin anaerobic lab-scale continuous stirred tank reactors. AppMicrobiol Biotechnol 2011, 89:303-314.
37. Werner JJ, Knights D, Garcia ML, Scalfone NB, Smith S,Yarasheski K, Cummings TA, Beers AR, Knight R, Angenent LT:Bacterial community structures are unique and resilient infullscale bioenergy systems. Proc Natl Acad Sci USA 2011,108:4158-4163.
38.�
De Vrieze J, Verstraete W, Boon N: Repeated pulse feedinginduces functional stability in anaerobic digestion. MicrobBiotechnol 2013, 6:414-424.
This study demonstrates how the feeding pattern (continuous vs. pulsefeeding) affects functional stability in anaerobic digesters, showing thatpulse-feeding promotes higher capacity to confront perturbations.
39. Kundu K, Sharma S, Sreekrishnan TR: Effect of operatingtemperatures on the microbial community profiles in a highcell density hybrid anaerobic bioreactor. Bioresourcetechnology 2012, 118:502-511.
40.�
Pycke BFG, Etchebehere C, Van de Caveye P, Negroni A,Verstraete W, Boon N: A time-course analysis of four full scaleanaerobic digesters in relation to the dynamics of change theirmicrobial communities. Water Sci Technol 2013, 63:769-775.
This study monitors microbial community richness, dynamics and orga-nization in four full-scale anaerobic digesters over 45 days, highlighting
Current Opinion in Biotechnology 2015, 33:103–111
that communities in full-scale anaerobic digesters are unique to theinstallation and that community properties are dynamic.
41. Allison SD, Martiny JB: Colloquium paper: resistance,resilience, and redundancy in microbial communities. ProcNatl Acad Sci USA 2008, 105:11512-11519.
42. Wittebolle L, Marzorati M, Clement L, Balloi A, Daffonchio D,Heylen K, De Vos P, Verstraete W, Boon N: Initial communityevenness favours functionality under selective stress. Nature2009, 458:623-626.
43. Fernandez A, Huang S, Xing J, Hickey R, Criddle C, Tiedje J: Howstable is stable? Function versus community composition.Appl Environ Microbiol 1999, 65:3697-3704.
44. Briones A, Raskin L: Diversity and dynamics of microbialcommunities in engineered environments and theirimplications for process stability. Curr Opin Biotechnol 2003,14:270-276.
45. Regueiro L, Veiga P, Figueroa M, Alonso-Gutierrez J, Stams AJ,Lema JM, Carballa M: Relationship between microbial activityand microbial community structure in six full-scale anaerobicdigesters. Microbiol Res 2012, 167:581-589.
46. Goncalves MR, Costa JC, Marques IP, Alves MM: Inoculumacclimation to oleate promotes the conversion of olive millwastewater to methane. Energy 2011, 36:2138-2141.
47. Hidalgo D, Martın-Marroquın J: Effects of inoculum source andco-digestion strategies on anaerobic digestion of residuesgenerated in the treatment of waste vegetable oils. J EnvironManage 2014, 142:17-22.
48. Karlsson A, Einarsson P, Schnurer A, Sundberg C, Ejlertsson J,Svensson BH: Impact of trace element addition on degradationefficiency of volatile fatty acids, oleic acid and phenyl acetateand on microbial populations in a biogas digester. J BiosciBioeng 2012, 114:446-452.
49. Facchin V, Cavinato C, Fatone F, Pavan P, Cecchi F, Bolzonella D:Effect of trace element supplementation on the mesophilicanaerobic digestion of foodwaste in batch trials: the influenceof inoculum origin. Biochem Eng J 2013, 70:71-77.
50. Banks CJ, Zhang Y, Jiang Y, Heaven S: Trace elementrequirements for stable food waste digestion at elevatedammonia concentrations. Biores Technol 2012, 104:127-135.
51.�
Williams J, Williams H, Dinsdale R, Guwy A, Esteves S: Monitoringmethanogenic population dynamics in a full-scale anaerobicdigester to facilitate operational management. Biores Technol2013, 140:234-242.
In this study, a full-scale reactor exhibited a highly dynamic environment(methanogenic populations changed constantly due to substrates avail-ability and inhibitors), but control actions such as organic loadingdecrease, addition of trace elements or alkalinity allowed maintenanceof digester stability.
52. Feng XM, Karlsson A, Svensson BH, Bertilsson S: Impact of traceelement addition on biogas production from food industrialwaste–linking process to microbial communities. FEMSMicrobiol Ecol 2011, 74:226-240.
53. Schmidt T, Nelles M, Scholwin F, Proter J: Trace elementsupplementation in the biogas production from wheatstillage — optimization of metal dosing. Biores Technol 2014,168:80-85.
54. Nielsen HB, Mladenovska Z, Ahring BK: Bioaugmentation of atwo-stage thermophilic (68 -C/55 -C) anaerobic digestionconcept for improvement of the methane yield from cattlemanure. Biotech Bioeng 2007, 97:1638-1643.
55. Cavaleiro AJ, Sousa DZ, Alves MM: Methane production fromoleate: assessing the bioaugmentation potential ofSyntrophomonas zehnderi. Water Res 2010, 44:4940-4947.
56. Schauer-Gimenez AE, Zitomer DH, Maki JS, Struble CA:Bioaugmentation for improved recovery of anaerobicdigesters after toxicant exposure. Water Res 2010, 44:3555-3564.
57. Tale VP, Maki JS, Struble CA, Zitomer DH: Methanogencommunity structure–activity relationship and
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Microbial management of anaerobic digestion Carballa, Regueiro and Lema 111
bioaugmentation of overloaded anaerobic digesters. WaterRes 2011, 45:5249-5256.
58. Duran M, Tepe N, Yurtsever D, Punzi V, Bruno C, Mehta R:Bioaugmenting anaerobic digestion of biosolids with selectedstrains of Bacillus, Pseudomonas, and Actinomycetes speciesfor increased methanogenesis and odor control. Appl MicrobiolBiot 2006, 73:960-966.
59.�
Fotidis IA, Wang H, Fiedel NR, Luo G, Karakashev DB, Angelidaki I:Bioaugmentation as a solution to increase methaneproduction from an ammonia-rich substrate. Environ SciTechnol 2014, 48:7669-7676.
One of the very few studies about bioaugmentation with Archaea. A fastgrowing hydrogenotrophic methanogen (Methanoculleus bourgensis)was bioaugmented in reactor with high ammonia levels (5 g/L), which
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resulted in an increased methane production of 31% respect to thecontrol.
60. Fotidis IA, Karakashev D, Angelidaki I: Bioaugmentation with anacetate-oxidising consortium as a tool to tackle ammoniainhibition of anaerobic digestion. Biores Technol 2013,146:57-62.
61. Cavaleiro AJ, Salvador AF, Alves JI, Alves MM: Continuous highrate anaerobic treatment of oleic acid based wastewater ispossible after a step feeding start-up. Environ Sci Technol 2009,43:2931-2936.
62. Schmidt T, Proter J, Scholwin F, Nelles M: Anaerobic digestion ofgrain stillage at high organic loading rates in three differentreactor systems. Biomass Bioener 2013, 55:285-290.
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