A highly diverse, desert-like microbial biocenosis on solar panels … · 2015. 11. 30. · A highly diverse, desert-like microbial biocenosis on solar panels in a Mediterranean city

A highly diverse, desert-likemicrobial biocenosis on solarpanels in a Mediterranean cityPedro Dorado-Morales1,2, Cristina Vilanova1, Juli Pereto1,3, Francisco M. Codoner4,Daniel Ramon2 and Manuel Porcar1, 5,*

1Institut Cavanilles de Biodiversitat i Biologia Evolutiva, Universitat de Valencia, Paterna 46980, Spain2Biopolis S.L., Parc Cientıfic Universitat de Valencia, Paterna, Valencia, Spain3Departament de Bioquımica i Biologia Molecular, Universitat de Valencia, Burjassot 46100, Spain4Lifesequencing S.L., Parc Cientıfic Universitat de Valencia, Paterna, Spain.5Fundacio General de la Universitat de Valencia, Spain.*Address correspondence to Manuel Porcar: [email protected]. and C.V. contributed equally to this work.

Microorganisms colonize a wide range1

of natural and artificial environments2

although there are hardly any data3

on the microbial ecology of one the most4

widespread man-made extreme structures:5

solar panels. Here we show that solar pan-6

els in a Mediterranean city (Valencia, Spain)7

harbor a highly diverse microbial commu-8

nity with more than 500 different species per9

panel, most of which belong to drought-, heat-10

and radiation-adapted bacterial genera, and11

sun-irradiation adapted epiphytic fungi. The12

taxonomic and functional profiles of this mi-13

crobial community and the characterization14

of selected culturable bacteria reveal the ex-15

istence of a diverse mesophilic microbial com-16

munity on the panels surface. This bioceno-17

sis proved to be more similar to the ones in-18

habiting deserts than to any human or ur-19

ban microbial ecosystem. This unique mi-20

crobial community shows different day/night21

proteomic profiles; it is dominated by reddish22

pigment- and sphingolipid-producers, and is23

adapted to withstand circadian cycles of high24

temperatures, desiccation and solar radia-25

tion.26

Introduction 27

Today, photovoltaic panels cover around 4000 square 28

kilometers, and are forecasted to be the world’s main 29

electricity source by 2050 (http://www.epia.org). So- 30

lar panels are unique biotopes characterized by a 31

smooth flat glass or glass-like surface, minimum wa- 32

ter retention capacity and maximum sunlight expo- 33

sure, all of which determine circadian and annual 34

peaks of irradiation, desiccation and heat. Extreme 35

natural habitats such as thermal vents, mountain 36

plateaus or hyper arid deserts are known to host 37

microbial biocenoses adapted to those particular se- 38

lection pressures (1, 2, 3); and artificial or humanized 39

environments, such as industrial reactors (4), radioac- 40

tive waste (5) or oil spills (6) are also colonizable 41

by specialized microorganisms. However, despite the 42

popularity and the quick spreading of photovoltaic 43

panels, the microbial communities potentially asso- 44

ciated to these human-manufactured devices have 45

not been described to date. Our report documents 46

a complete bioprospection and characterization of 47

the microbial community on photovoltaic panels of a 48

Mediterranean city, using high throughput 16S/18S 49

analysis, metagenomic sequencing, metaproteomics, 50

and culture-based characterization of selected iso- 51

lates. 52

Page 1 of 13

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https://doi.org/10.1101/029660

Materials and Methods1

Sampling2

Sampling was performed during the summer solstice3

of 2013 and 2014. Sampling consisted of a simple har-4

vesting procedure, by pouring sterile PBS (sodium5

phosphate buffer) on the panel and immediately har-6

vesting the liquid by strongly scraping the surface7

with a modified window cleaner with an autoclaved8

silicone tube measuring 5 mm in diameter. The re-9

sulting suspension was collected by using a sterile10

plastic pipette and transferred to sterile Falcon tubes,11

placed on ice and immediately transported to the lab.12

In 2013, nine samples from solar panels on the three13

campuses of the University of Valencia (Valencia,14

Spain) were collected at noon (2 PM) and pooled.15

Air temperature was 33 C and relative humidity was16

60%. In 2014, samples from three independent solar17

panels in a single location (Faculty of Economics,18

University of Valencia, Valencia, Spain) were har-19

vested at noon (2 PM) and at night (4 AM) for the20

proteomic studies, whereas three additional samples21

(panels 1, 2 and 3) were sampled and used for both22

16S/18S rRNA taxonomic identification and metage-23

nomics (Figure 1A). Air temperature and relative24

humidity were 32 C and 56% (2 PM), and 23 C and25

83% (4 AM). The average temperature of the panels26

surface during the sampling process (at 2 PM) was27

51 C. The average solar irradiance in Valencia at 228

PM is 461.3 W/m2, whereas the accumulated solar29

irradiance during an average day is 19.6 kJ/m2.30

Microbiological media and growth31

conditions32

Aliquots of 100 L from the solar-panel samples were33

spread on Petri dishes containing LB medium (com-34

position in g/L: peptone 10.0, NaCl 10.0, yeast ex-35

tract 5.0) or marine medium (composition in g/L:36

peptone 5.0, yeast extract 1.0, ferric citrate 0.1, NaCl37

19.45, MgCl2 5.9, Na2SO4 3.24, CaCl2 1.8, KCl 0.55,38

NaHCO3 0.16, KBr 0.08, SrCl2 0.034, H3BO3 0.022,39

Na4O4Si 0.004, NaF 0.024, NH4NO3 0.0016 and40

Na2HPO4 0.008), and incubated at room temper-41

ature for 7 days. Individual colonies were indepen-42

dently re-streaked on new media and pure cultures43

were finally identified through 16S rRNA sequencing44

and crio-preserved in 20% glycerol (v/v) until re-45

quired. A total of 53 bacterial strains were character-46

ized under stress conditions and serially confronted47

with each other in solid medium to detect interactions48

in terms of resistance to harsh conditions.49

Strains stress tests 50

Each strain was subjected to a range of stress assays 51

to test tolerance to salinity, heat, low pH, and UV 52

radiation. Overnight liquid cultures were adjusted 53

to an OD600 value of 0.03. Then, stress tests were 54

carried out by plating several 20 L droplets of the 55

diluted culture on LB or marine agar with the fol- 56

lowing modifications. In the case of salinity stress, 57

increasing amounts of NaCl (from 1 to 9% w/v) were 58

added to the media (final concentration ranging from 59

1 to 26% w/v). To test pH resistance, culture media 60

was adjusted to pH 5, 6, and 8. In the case of heat, 61

plates were incubated overnight at 60 C; whereas 62

resistance to radiation was tested by applying UV 63

pulses of different length (30 s, 2 min, and 8 min) 64

with a VL-4C lamp (254 nm, 340 W cm-2; Labolan, 65

S.L., Spain). The XL1-Blue E. coli strain was used as 66

control. For each experiment, two independent repli- 67

cates were performed. In order to detect inhibition or 68

synergistic effects between strains, experiments were 69

performed as described above and strain suspensions 70

(20 ul) were closely (3 mm) placed on the same dish. 71

DNA isolation 72

Selected DNA purification methods were used to pro- 73

cess the solar panels samples and DNA yields were 74

compared (data not shown). Metagenomic DNA 75

was isolated using the Power Soil DNA Isolation 76

kit (MO BIO Laboratories) following the manufac- 77

turers instructions with an additional pretreatment 78

with DNA-free lysozyme at 37 C for 10 min. The 79

quantity and quality of the DNA was determined 80

on a 1.5% agarose gel and with a Nanodrop-1000 81

Spectophotometer (Thermo Scientific, Wilmington, 82

DE). 83

PCR amplification and 16S/18S rRNA 84

massive sequencing 85

A set of primers adapted to massive sequencing for 86

the Ion Torrent platform (Lifetechnologies) were used 87

to capture 16S (modified from (7)) and 18S (modified 88

from (8)) rRNA from the solar-panel DNA extraction 89

in a PCR reaction. PCR reactions were performed 90

with 30 ng of metagenomic DNA, 200 M of each of 91

the four deoxynucleoside triphosphates, 400 nM of 92

each primer, 2.5 U of FastStart HiFi Polymerase, and 93

the appropriate buffer with MgCl2 supplied by the 94

manufacturer (Roche, Mannheim, Germany), 4% of 95

20 g/mL BSA (Sigma, Dorset, United Kingdom), and 96

0.5 M Betaine (Sigma). Thermal cycling consisted 97

of initial denaturation at 94C for 2 minutes followed 98

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https://doi.org/10.1101/029660

by 35 cycles of denaturation at 94C for 20 seconds,1

annealing at 50C for 30 seconds, and extension at2

72C for 5 minutes. Amplicons were combined in a3

single tube in equimolar concentrations. The pooled4

amplicon mixture was purified twice (AMPure XP5

kit, Agencourt, Takeley, United Kingdom) and the6

cleaned pool requantified using the PicoGreen as-7

say (Quant-iT, PicoGreen DNA assay, Invitrogen).8

Subsequently, sequencing on the Ion Torrent plat-9

form was performed at LifeSequencing S.L. (Valencia,10

Spain).11

Shotgun metagenomic sequencing12

The metagenomic DNA of two of the solar panels13

sampled in 2014 (solar panels 1 and 3, from which14

enough DNA was available) was shotgun sequenced.15

A Nextera Illumina library was built from 100 ng16

total DNA following the protocol indications marked17

by Illumina. Those libraries were sequenced in a18

MiSeq sequencer (Illumina) at Lifesequencing SL, in19

a combination of 500 cycles, in order to obtain 25020

bp paired-end sequences.21

Bioinformatic analysis22

16S/18S rRNA profiles The resulting sequences23

from the taxonomical identification, based on PCR24

capturing of the 16S and 18S rRNA, were split taking25

into account the barcode introduced during the PCR26

reaction, providing a single FASTQ file for each of27

the samples. We performed quality filtering (Q20)28

using fastx tool kit version 0.013, primer (16S and29

18S rRNA primers) trimming using cutadapt version30

1.4.1 and length (minimum 300 bp read length) trim-31

ming using in-house perl scripting over those FASTQ32

files to obtain a FASTQ file with clean data. Those33

clean FASTQ files were converted to FASTA files34

and UCHIME (9) program version 7.0.1001 was used35

to remove chimeras arising during the amplification36

and sequencing step. Those clean FASTA files were37

BLAST against NCBI 16S rRNA and fungi database38

using blastn version 2.2.29+. The resulting XML file39

were processed using a pipeline developed by Life-40

sequencing S.L. (Paterna, Valencia, Spain) in order41

to annotate each sequence at different phylogenetic42

levels (Phylum, Family, Genera and Species). Statis-43

tical analysis was performed using R version 3.1.1.44

A summary of sequencing statistics and results is45

available in Table S2.46

Taxonomic and functional analysis of47

metagenomic sequences Two FASTQ files per48

sample were obtained during the sequencing step,49

each coming from each of the directions on the 50

paired-end sequencing. Those files were trimmed 51

for adapters and low quality reads using cutadapt 52

version 1.4.1 with the paired-end option. Trimmed 53

sequences were used for taxonomical identification 54

using a local alignment tool against nt database 55

from NCBI as described before (10). The trimmed 56

sequences from each solar panel were also assem- 57

bled using different combinations of k-mers in Abyss 58

version 1.5.2 (11) and Velvet version 1.2.1 (12) in 59

order to find the best combination. The best as- 60

sembly in each solar panel was used to perform a 61

prediction of ORFs by using MetaGeneMark (13). 62

BLASTP against nr NCBI database was used for 63

annotation and webMGA (14) for COG assigna- 64

tion. All our data have been deposited in the MG- 65

RAST server, and is publicly available under ac- 66

cession numbers 4629146.3 and 4629747.3. In or- 67

der to compare the taxonomic profile of solar pan- 68

els with other environments, the taxonomic infor- 69

mation of 25 metagenomes belonging to different 70

habitats was obtained from the MG-RAST server 71

(IDs 4455835.3, 4455836.3, 4477803.3, 4477872.3, 72

4477873.3, 4441205.3, 4445129.3, 4445126.3, 4477903.3, 73

4477904.3, 4477901.3, 4514299.3, 4543019.3, 4543020.3, 74

4441347.3, 4441363.3, 4441215.3, 4441214.3, 4441679.3, 75

4441682.3, 4447192.3, 4447102.3, 4497390.3, 4497389.3, 76

4497397.3, 4516651.3, and 4516403.3). The differ- 77

ent profiles were processed with MEGAN. Data 78

were normalized, and the distances between pairs 79

of profiles calculated with the Bray-Curtis method. 80

Finally, the calculated distances were used to 81

build a Principal Coordinates Analysis. We em- 82

ployed the Statistical Analysis of Metagenomic Pro- 83

files (STAMP) (version 1.08; Faculty of Computer 84

Science, Dalhousie University) software to com- 85

pare the functional profile (according to subsys- 86

tems categories) of our samples with those of the 87

metagenomes previously cited. The functional data 88

of metagenomes 4455835.3, 4455836.3, 4477803.3, 89

4477872.3, 4477873.3, 4477903.3, 4477904.3, 4477901.3, 90

4514299.3 was poor or absent, and was thus elim- 91

inated from the analysis. This comparison was 92

represented in a heatmap, where the different 93

metagenomes are clustered according to their simi- 94

larity. The functional contents of solar panels 1 and 95

3 were compared to each other with a Fishers exact 96

test combined with the Newcombe-Wilson method 97

for calculating confidence intervals (nominal coverage 98

of 95%). As a multiple-hypothesis test correction, a 99

false-discovery-rate (FDR) method was applied. 100

Pangenome reconstruction Trimmed sequences 101

from both solar panels for the total DNA experiment 102

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https://doi.org/10.1101/029660

were blasted against a database containing all se-1

quences for the genera Thermo/Deinococcus. Only2

sequences with a positive hit in against this database3

were used for assembly them using different k-mers4

with the Abyss assembler. We performed a genome5

annotation in different steps i) ORFs were predicted6

with GeneMark version 3.25 (13), ii) rRNA version7

1.2 (15) for rRNA prediction, and iii) tRNA-Scan8

(16) for tRNA prediction. The functional annota-9

tion using COG classification was performed using10

webMGA. DNAPlotter (17) from the Artemis Pack-11

age was used to represent a circular map of the12

pangenome.13

Proteomics14

Protein samples were precipitated with TCA15

(trichloroacetic acid) and pellets were dissolved with16

75 L of 50 mM ABC (ammonium bicarbonate). The17

protein concentration in the samples was determined18

by fluorometric analysis. Then, 10 g of each sample19

were digested as described in the following proto-20

col. Cysteine residues were reduced by 2 mM DTT21

(DLDithiothreitol) in 50 mM ABC at 60C for 20 min.22

Sulfhydryl groups were alkylated with 5 mM IAM23

(iodoacetamide) in 50 mM ABC in the dark at room24

temperature for 30 min. IAM excess was neutralized25

with 10 mM DTT in 50 mM ABC, 30 min at room26

temperatura. Ecah sample was subjected to trypsin27

digestion with 250 ng (100 ng/l) of sequencing grade28

modified trypsin (Promega) in 50 mM ABC at 37C29

overnight. The reaction was stopped with TFA (tri-30

fluoroacetic acid) at a final concentration of 0.1%.31

Final peptide mixture was concentrated in a speed32

vacuum and resuspended in 30L of 2% ACN, 0.1%33

TFA. Finally, 5 l of each sample were loaded onto34

a trap column (NanoLC Column, 3 C18CL, 75um35

x15cm; Eksigen) and desalted with 0.1% TFA at36

2l/min during 10 min.37

The peptides were then loaded onto an analytical38

column (LC Column, 3 C18CL, 75umx25cm, Eksi-39

gen) equilibrated in 5% acetonitrile 0.1% FA (formic40

acid). Elution was carried out with a linear gradient41

of 5:35% B in A for 40 min (A: 0.1% FA; B: ACN,42

0.1% FA) at a flow rate of 300 nl/min in a label free43

mode. Peptides were analyzed in a mass spectrome-44

ter nanoESI qQTOF (5600 TripleTOF, ABSCIEX).45

The tripleTOF was operated in informationdepen-46

dent acquisition mode, in which a 0.25s TOF MS47

scan from 350 to 1250 m/z, was performed, followed48

by 0.05s product ion scans from 100 to 1500 m/z on49

the 25 most intense 25 charged ions.50

ProteinPilot default parameters were used to gen-51

erate a peak list directly from 5600 TripleTof wiff 52

files. The Paragon algorithm of ProteinPilot was 53

used to search NCBI protein database with the fol- 54

lowing parameters: trypsin specificity, cysalkylation, 55

no taxonomy restriction, and the search effort set to 56

through. To avoid using the same spectral evidence 57

in more than one protein, the identified proteins 58

were grouped based on MS/MS spectra by the Pro- 59

teinPilot Progroup algorithm. The PeakView v 1.1 60

(ABsciex) software was used to generate the peptides 61

areas from Protein Pilot result files and to perform 62

a principal component (PCA) and a ttest analysis. 63

Results 64

Culturing of solar panel samples from the 2013 sol- 65

stice on both rich (LB) and marine media yielded 66

a relatively high number of colony forming microor- 67

ganisms, mostly bacteria, displaying a wide range 68

of color and shapes. Many of the isolates displayed 69

red, orange or pink pigmentation (Figure 1B), par- 70

ticularly those incubated on marine agar. A total of 71

53 pigmented isolates were selected and subjected to 72

taxonomic (16S rRNA) characterization and tested 73

for resistance to heat (incubation at 60C), UV expo- 74

sure (2 to 30 s pulses of a 340 W cm-2 UV light), high 75

NaCl contents (1 to 26%) and different pH values (5 76

to 9). 77

Figure 1C shows that, in general, the solar-panel 78

isolates displayed strong resistance to very high salt 79

concentrations, moderately high resistance to low pH 80

and relatively low resistance to UV light or extreme 81

(60C) heat. Interestingly, during these characteri- 82

zation assays we were able to identify isolates able 83

to restore the growth of nearby isolates under con- 84

ditions of extreme salt or pH values, in the latter 85

case because of local buffering of the pH of the plate 86

(Figure S1). Full characterization of the 53 isolates 87

is provided in Table S1 and Figure S2. 88

The taxonomic composition of bacterial and eu- 89

karyotic taxa was first studied through 16S and 90

18S rRNA genes massive sequencing; the results are 91

shown in Figure 2. As many as 800 different bacterial 92

species were identified in the 2013 pool (nine solar 93

panels from different locations within the University 94

of Valencia); and around 500 different species were 95

found in each of the individual panels sampled from 96

a single building in 2014 (Table S2). Two orders, 97

Sphingobacteriales (families Flexibacteriaceae and 98

Sphingomonadaceae) and Deinococcales comprised 99

the highest number of species. Deinococcus, Sphin- 100

gomonas, Novosphingobium or Hymenobacter were 101

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https://doi.org/10.1101/029660

the dominant genera, with 9.2% or 28% of the as-1

signed sequences (H. chitinivorans in panel 1 and D.2

hopiensis in panel 3, respectively). The remaining3

sequences were distributed among 17 phyla and 1464

families. Other well-represented genera, in order of5

abundance, were Rubellimicrobium, Adhaeribacter,6

Acidicaldus, Segetibacter, or Modestobacter. In the7

case of fungi, lower biodiversity was found (Fig. 2B).8

Taxonomic eukaryotic profiles were dominated by the9

phylum Ascomycota and the families Pleosporaceae10

and Teratosphaeriaceae, with genera Phaeothecoidea11

and Alternaria representing the majority in the 201312

and 2014 samples, respectively.13

In 2014, the metagenomic DNA of two independent14

solar panels was shotgun sequenced. As shown in15

Figure 2C, the bacteria:fungi ratio was close to 50%,16

and species distribution was similar to that found for17

16S and 18S sequencing. A summary of sequencing18

statistics and diversity indexes can be accessed in19

Table S3. Genus Deinococcus, one of the clearest20

taxonomic markers of extremophily, again proved21

highly abundant in all our samples. We analyzed22

Deinococcus sequences from our metagenomic analy-23

sis and a draft Deinococcus solar panel pangenome24

of 2098 contigs was obtained, covering more than25

0,8 Mb (25%) of standard Deninococcus genomes26

(3.3Mb with 2 chromosomes and 2 plasmids), with27

2166 and 149 ORFs and tRNAs, respectively (Fig-28

ure 2D). The low identity level of the solar panel29

pangenome with previously sequenced Deinococcus30

species strongly suggests that at least one previously31

undescribed Deinococcus species is present in the32

sampled panels.33

Regarding the functional profile, that of two inde-34

pendent solar panels (1 and 3) was deduced from the35

metagenomic data, and statistically analyzed with36

the STAMP software. When compared to a range37

of metagenomes from diverse habitats, solar-panel38

functional profiles clustered together with those de-39

scribed for polar microbial mat and saline desert40

datasets, and distant to other environments such41

as air or sediments (Figure 3A). Both solar pan-42

els proved very similar to each other in terms of43

functions, as shown in Figure 3B. The bioactivity44

of the biocenosis was studied through a metapro-45

teomic analysis conducted on solar panels sampled46

at noon (solar time) and at night (4 AM). Protein47

composition differed between the day and night sam-48

ples (Figure 3C). Significantly, a protein involved in49

modulating bacterial growth on surfaces and biofilm50

formation (18) (diguanylate cyclase) was particularly51

abundant. Also among the more expressed proteins,52

we identified fungal and bacterial enzymes involved in53

respiration and ATP synthesis or ribosomal proteins 54

(bacterial L7/L12 and archaeal L7, the latter being 55

a moonlighting protein involved in rRNA processing 56

(19). Other abundant proteins have been reported 57

to confer resistance/tolerance to the extreme condi- 58

tions found in solar panels, namely, salt stress and 59

drought (membrane-bound proton-translocating py- 60

rophosphatase mPP) (20), nutrient starvation (mPP 61

and cold-shock protein) (21), heat-shock (molecular 62

chaperone GroEL), as well as proteins involved in 63

the preservation of membrane integrity under harsh 64

conditions (22, 23) (S-layer protein, lipoprotein 1; 65

Table S4). 66

Discussion 67

Despite the harsh conditions to which microorgan- 68

isms deposited -or permanently inhabiting- the so- 69

lar panels of a Mediterranean city during summer, 70

standard culturing resulting in important microbial 71

growth, with a diversity in shape, color and textures 72

of colony forming microorganisms from the 2013 73

solstice suggesting high biodiversity of the environ- 74

ment. Although culturable isolates are typically only 75

a small fraction of the global biocenosis, we were 76

able to identify several strain-to-strain effects that 77

proved able to restore the sensitivity of neighboring 78

isolates to stress factors (salinity and low pH). These 79

results suggest that microbial interactions and the 80

particular physical location of microorganisms on the 81

solar panels, rather than individual cell properties, 82

might play a major role in bacterial survival on solar 83

panels. 84

High throughput sequencing allowed confirming 85

the high diversity of the habitat in the form of a 86

sun-adapted taxonomic profile. Indeed, and in ac- 87

cordance with the majoritary phenotype observed 88

within culturable isolates, most of the species identi- 89

fied by high throughput sequencing, and particularly 90

the most frequent ones, are known to produce pink 91

(H. xingiangensis (24)), H. psychrotolerans (25)), 92

orange (Sphingomonas humi (26)), orange-red (S. 93

kaistensis (27)) or reddish pigments (Hymenobac- 94

ter chitinivorans (28), Rubellimicrobium mesophilum 95

(29)), in most cases carotenoids; as well as sphin- 96

golipids (Sphingomonas spp. (26, 27), Novosphingo- 97

bium spp. (30)). Carotenoids have been reported to 98

play a major role in radiation tolerance in bacteria 99

(31) and sphingolipids have recently been described 100

to mediate bacteria-to-silica and polyamide adhe- 101

sion (32). Therefore, carotenoids and sphingolipids 102

are candidates accounting for the sunlight resistance 103

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and fixation properties that microorganisms need to1

survive on a smooth, south-facing surface.2

A review of the ecology of the main bacterial taxa3

we identified gives more insights of the extremophile4

character of the solar panel bacteriome. Indeed,5

several of the most frequent Deinococcus spp. and6

other solar-panel bacteria have been described as7

inhabitants of relatively mild desertic areas as well8

as polar environments. D. hopiensis was isolated9

from the Sonora desert (33), while other Deinococ-10

cus species that we detected were first described in11

the Sahara desert (34). Regarding other very abun-12

dant species, such as Hymenobacter xingiangensis13

or Sphingomonas kaistensis, they have previously14

been reported on the high Tibet plateau (25), on15

dry Antarctic valleys (35), or in the Chinese desert16

of Xingiang (24). Others were first reported in high17

salinity areas (36), thermal springs (37) or during bio-18

prospections of soil (38, 39), or air samples (40, 41).19

A systematic review of the locations where the 5020

most abundant solar panel bacteria were first isolated21

reveals their adaptation to extreme environments:22

most of them occur in drought, high radiation and/or23

high temperature habitats. Most of the species we24

found on solar panels were originally reported to25

inhabit a relatively narrow geographical band in the26

temperate zone of the Northern hemisphere. The27

distribution of others in the dry Antarctic valleys28

suggests a major role of radiation as a key selective29

factor (Figure 4A), and the PCoA analysis of the30

solar-panel taxonomic profile compared with other31

metagenomes reveals a clear link with extremophile32

environments, such as temperate and cold deserts33

(Figure 4B).34

Regarding fungi, the ecological niches of several35

of the most frequent genera (Neocatenulostroma,36

Xenophacidiella and Metschnikowia) are sunny habi-37

tats, such as the phylloplane: (42, 43); or the surface38

of rocks (Coniosporium spp., particularly abundant39

in the 2013 samples) (44). As in the case of bacte-40

ria, this taxonomic profile strongly suggests sunlight41

exerts a major selective pressure, shaping the fun-42

gal community on the panels. The abundance and43

diversity of microorganisms in solar panels can be44

solely due to wind-deposition or correspond to an in45

situ active ecological community. Protein composi-46

tion differed significantly between the day and night47

samples (Figure 3C), implying that the microbial48

communities populating the solar panel surface are49

biologically active. The abundance of proteins in-50

volved in resistance to harsh conditions and biofilm51

formation on surfaces proves the presence of stress-52

response mechanisms in the microbial communities53

inhabiting solar panels. These results, along with 54

the abundance of radiation-resistant taxa and the 55

desert-like taxonomic profile of the solar samples, 56

that strikingly plot within desert microbiomes (Fig- 57

ure 4B), strongly suggest an in situ adaptation from 58

(probably) wind-transported microorganisms that 59

are immediately subjected to selection with radia- 60

tion, heat and dessication as main shapers of this 61

microbial ecosystem. Indeed, the solar panels mi- 62

crobiome proved taxonomically very distant from 63

that associated to air samples from a similar latitude 64

(see metagenomes 4516651.3 and 4516403.3 in Figure 65

4B). Furthermore, a recent analysis of air samples in 66

Sardinia (45), a known Mediterranean crossroad of 67

dust-conveying winds from Saharan Africa, revealed 68

an extremely low abundance of extremophiles such 69

as Deinococcus-Thermus species (less than 1% of 70

relative abundance, in contrast to up to 30% in solar 71

panels). Taken together, all these results strongly 72

suggest that the diverse biocenosis on solar panels 73

we report here is not a mere consequence of physical 74

accumulation of air-driven microorganisms, but a 75

resident microbial community adapted to desert-like 76

selection pressures. 77

This is the first report of a highly diverse microbial 78

community on solar panels. A recently published 79

study reported limited microbial diversity on solar 80

panels in Brazil, including some fungal species which 81

hindered the panels photovoltaic efficiency (46). Our 82

data show for the first time that solar panels of a tem- 83

perate Mediterranean city support a highly diverse 84

and active ecological community, one of the richest 85

extremophile biocenoses described to date. Moreover, 86

this community is metabolically active and displays 87

striking taxonomic and functional similarities with 88

highly irradiated environments: temperate deserts 89

and polar environments. The detailed analysis of the 90

habitats where the solar panel microorganisms have 91

previously been detected indicates their strong adap- 92

tation to sun exposure, which can only be partially 93

reproduced by stress characterization on pure micro- 94

bial cultures. Microbial interactions (including pH 95

and salinity tolerance restoration), physical effects 96

such as shading, DNA repair mechanisms and pro- 97

duction of pigments and adhesion molecules might 98

play a major role in the adaptation of a unique mi- 99

crobial ecosystem to the abrupt circadian cycles in 100

desert-like conditions. This previously undescribed 101

ecosystem is the first urban microdesert reported to 102

date, and it may provide a valuable new source of 103

compounds with biotechnological applications. 104

105

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Funding information1

Biopolis SL funded this work. C.V. is a recipient of2

a FPU (Formacion de Personal Universitario) grant3

from the Spanish MECD (Ministerio de Educacion,4

Cultura y Deporte).5

6

Acknowledgments7

Data reported in this paper have been deposited8

in the MG-RAST server, and are publicly available9

under accession numbers 4629146.3 and 4629147.3.10

The authors are indebted to the Vicerrectorat dIn-11

fraestructures (Universitat de Valencia) for their sup-12

port before and during sampling. We also thank13

the proteomics service (SCSIE) of the University14

of Valencia for its technical support and Fabiola15

Barraclough for English revision. P.D. and C.V. con-16

tributed equally to this work.17

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Figures1

Figure 1: Characterization of the solar-panel microbiome. Sampling of photovoltaic panels carried out on the threecampuses of the University of Valencia in 2013 and 2014, and experimental set up (A). Microbial coloniesgrowing on LB incubated at room temperature for two weeks (B). Venn diagrams (C) displaying thenumber of isolates exhibiting resistance to heat shock (60C), low pH (5) and different NaCl concentrations(w:vol) and UV pulses (340 W cm-2).

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Figure 2: Taxonomic diversity of solar-panel biocenosis, deduced by culture-independent techniques. Diversity ofbacteria (A) and fungi (B) analyzed by 16S and 18S rRNA gene sequencing, respectively, of solar panelssampled during the Summer solstice of 2013 and 2014. Histograms show the relative abundance (%) ofthe species identified, as described in materials and methods. Species representing less than 1% of totalreads were clustered and labeled as ”Other”. Taxonomic diversity of one of the panels (panel 3) sampledin the summer solstice of 2014 as deduced from shotgun metagenomic sequencing (C). Carotenoid andsphingolipid-producing bacteria are highlighted in red and brown, respectively. Radiation-resistant phylaare highlighted in orange. The taxonomic diversity of solar panel 1 is represented in Figure S3. Circularrepresentation of the Deinococcus solar panel pangenome (D) obtained from the metagenomic sequencesof panels 1 and 3. The map includes (from the outer to the inner circle) the ORFs in forward and reversesense, a colour-coded COG functional annotation, the predicted tRNAs and rRNAs, the GC count, andthe GC skew.

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Figure 3: Functional analysis of the solar-panel metagenomes. Heatmap representation (A) based on the functionalprofiles of solar panels 1 and 3 compared with a range of metagenomes from different environments. Setof functions in the metagenomes of solar panels 1 and 3 (B). Each dot corresponds to one function of thesubsystems classification. Principal Component Analysis (C) performed with the proteomic profile of solarpanels sampled at noon (yellow dots) and night (dark blue).

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Figure 4: Biogeographical context of the solar-panel microbiomes as deduced from their taxonomic profile. Geographicdistribution (A) of the 50 most abundant (more than 1% of the reads) bacterial species detected by high-throughput sequencing of 16S rRNA amplicons in solar panels sampled at the University of Valencia in2014. Each circle corresponds to a different species and the size of the circles is proportional to the numberof reads. Species found at a frequency higher than 3.5% are shown. Colors indicate type of environment.Principal Coordinates Analysis (B) performed with the taxonomic profile of a range of metagenomes fromdiverse ecosystems. The solar-panel metagenomes (panels 1 and 3 from the 2014 sampling, grey dots)map within desert and circumpolar metagenomes.

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A highly diverse, desert-like microbial biocenosis on solar panels … · 2015. 11. 30. · A highly diverse, desert-like microbial biocenosis on solar panels in a Mediterranean city