A highly diverse, desert-like microbial biocenosis on solar panels … · 2015. 11. 30. · A...
Transcript of A highly diverse, desert-like microbial biocenosis on solar panels … · 2015. 11. 30. · A...
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
was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted November 30, 2015. ; https://doi.org/10.1101/029660doi: bioRxiv preprint
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
Page 2 of 13
was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted November 30, 2015. ; https://doi.org/10.1101/029660doi: bioRxiv preprint
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
Page 3 of 13
was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted November 30, 2015. ; https://doi.org/10.1101/029660doi: bioRxiv preprint
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
Page 4 of 13
was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted November 30, 2015. ; https://doi.org/10.1101/029660doi: bioRxiv preprint
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
Page 5 of 13
was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted November 30, 2015. ; https://doi.org/10.1101/029660doi: bioRxiv preprint
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
Page 6 of 13
was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted November 30, 2015. ; https://doi.org/10.1101/029660doi: bioRxiv preprint
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
References18
1. Corliss JB, Dymond J, Gordon LI, Edmond JM,19
von Herzen RP, Ballard RD, Green K, Williams20
D, Bainbridge A, Crane K, van Andel TH. 1979.21
Submarine thermal sprirngs on the galapagos rift.22
Science 203:107383.23
2. Singh A, Lal R. 2009. Sphingobium24
ummariense sp. nov., a hexachlorocyclohexane25
(HCH)-degrading bacterium, isolated from HCH-26
contaminated soil. Int J Syst Evol Microbiol 59:1626.27
3. Neilson JW, Quade J, Ortiz M, Nelson WM,28
Legatzki A, Tian F, LaComb M, Betancourt JL,29
Wing RA, Soderlund CA, Maier RM. 2012. Life30
at the hyperarid margin: novel bacterial diversity31
in arid soils of the Atacama Desert, Chile. Ex-32
tremophiles 16:55366.33
4. Rosche B, Li XZ, Hauer B, Schmid A, Buehler34
K. 2009. Microbial biofilms: a concept for industrial35
catalysis? Trends Biotechnol 27:63643.36
5. Williamson AJ, Morris K, Law GTW, Rizoulis37
A, Charnock JM, Lloyd JR. 2014. Microbial reduc-38
tion of U(VI) under alkaline conditions: implications39
for radioactive waste geodisposal. Environ Sci Tech-40
nol 48:1354956.41
6. Pham N TA, Anonye BO. 2014. Vying over42
spilt oil. Nat Rev Microbiol 12:156.43
7. Sim K, Cox MJ, Wopereis H, Martin R, Knol44
J, Li M-S, Cookson WOCM, Moffatt MF, Kroll JS.45
2012. Improved detection of bifidobacteria with opti-46
mised 16S rRNA-gene based pyrosequencing. PLoS47
One 7:e32543.48
8. La Duc MT, Vaishampayan P, Nilsson HR, 49
Torok T, Venkateswaran K. 2012. Pyrosequencing- 50
derived bacterial, archaeal, and fungal diversity of 51
spacecraft hardware destined for Mars. Appl Environ 52
Microbiol 78:591222. 53
9. Edgar RC, Haas BJ, Clemente JC, Quince 54
C, Knight R. 2011. UCHIME improves sensitiv- 55
ity and speed of chimera detection. Bioinformatics 56
27:2194200. 57
10. Ames SK, Gardner SN, Marti JM, Slezak TR, 58
Gokhale MB, Allen JE. 2015. Using populations of 59
human and microbial genomes for organism detection 60
in metagenomes. Genome Res gr.184879.114. 61
11. Simpson JT, Wong K, Jackman SD, Schein 62
JE, Jones SJM, Birol I. 2009. ABySS: a parallel 63
assembler for short read sequence data. Genome Res 64
19:111723. 65
12. Zerbino DR, Birney E. 2008. Velvet: algo- 66
rithms for de novo short read assembly using de 67
Bruijn graphs. Genome Res 18:8219. 68
13. Besemer J, Lomsadze A, Borodovsky M. 2001. 69
GeneMarkS: a self-training method for prediction of 70
gene starts in microbial genomes. Implications for 71
finding sequence motifs in regulatory regions. Nucleic 72
Acids Res 29:260718. 73
14. Wu S, Zhu Z, Fu L, Niu B, Li W. 2011. Web- 74
MGA: a customizable web server for fast metage- 75
nomic sequence analysis. BMC Genomics 12:444. 76
15. Lagesen K, Hallin P, Rdland EA, Staerfeldt 77
H-H, Rognes T, Ussery DW. 2007. RNAmmer: con- 78
sistent and rapid annotation of ribosomal RNA genes. 79
Nucleic Acids Res 35:31008. 80
16. Lowe TM, Eddy SR. 1997. tRNAscan- 81
SE: a program for improved detection of transfer 82
RNA genes in genomic sequence. Nucleic Acids Res 83
25:95564. 84
17. Carver T, Thomson N, Bleasby A, Berriman 85
M, Parkhill J. 2009. DNAPlotter: circular and lin- 86
ear interactive genome visualization. Bioinformatics 87
25:11920. 88
18. Rmling U, Galperin MY, Gomelsky M. 2013. 89
Cyclic di-GMP: the first 25 years of a universal bac- 90
terial second messenger. Microbiol Mol Biol Rev 91
77:152. 92
19. Diaconu M, Kothe U, Schlnzen F, Fischer N, 93
Harms JM, Tonevitsky AG, Stark H, Rodnina M V, 94
Wahl MC. 2005. Structural basis for the function 95
of the ribosomal L7/12 stalk in factor binding and 96
GTPase activation. Cell 121:9911004. 97
20. Baykov AA, Malinen AM, Luoto HH, Lahti R. 98
2013. Pyrophosphate-fueled Na+ and H+ transport 99
in prokaryotes. Microbiol Mol Biol Rev 77:26776. 100
Page 7 of 13
was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted November 30, 2015. ; https://doi.org/10.1101/029660doi: bioRxiv preprint
21. Etchegaray JP, Inouye M. 1999. CspA, CspB,1
and CspG, major cold shock proteins of Escherichia2
coli, are induced at low temperature under conditions3
that completely block protein synthesis. J Bacteriol4
181:182730.5
22. Cascales E, Bernadac A, Gavioli M, Lazzaroni6
J-C, Lloubes R. 2002. Pal Lipoprotein of Escherichia7
coli Plays a Major Role in Outer Membrane Integrity.8
J Bacteriol 184:754759.9
23. Rothfuss H. 2006. Involvement of the S-layer10
proteins Hpi and SlpA in the maintenance of cell11
envelope integrity in Deinococcus radiodurans R1.12
Microbiology 152:27792787.13
24. Zhang Q, Liu C, Tang Y, Zhou G, Shen P,14
Fang C, Yokota A. 2007. Hymenobacter xinjiangensis15
sp. nov., a radiation-resistant bacterium isolated16
from the desert of Xinjiang, China. Int J Syst Evol17
Microbiol 57:17526.18
25. Zhang G, Niu F, Busse H-J, Ma X, Liu19
W, Dong M, Feng H, An L, Cheng G. 2008. Hy-20
menobacter psychrotolerans sp. nov., isolated from21
the Qinghai–Tibet Plateau permafrost region. Int J22
Syst Evol Microbiol 58:121520.23
26. Yi TH, Han C-K, Srinivasan S, Lee KJ, Kim24
MK. 2010. Sphingomonas humi sp. nov., isolated25
from soil. J Microbiol 48:1659.26
27. Kim MK, Schubert K, Im W-T, Kim K-H, Lee27
S-T, Overmann J. 2007. Sphingomonas kaistensis28
sp. nov., a novel alphaproteobacterium containing29
pufLM genes. Int J Syst Evol Microbiol 57:152734.30
28. Buczolits S, Denner EBM, Kmpfer P, Busse31
H-J. 2006. Proposal of Hymenobacter norwichen-32
sis sp. nov., classification of Taxeobacter ocella-33
tus, Taxeobacter gelupurpurascens and Taxeobacter34
chitinovorans as Hymenobacter ocellatus sp. nov.,35
Hymenobacter gelipurpurascens sp. nov. and Hy-36
menobacter chitinivo. Int J Syst Evol Microbiol37
56:20718.38
29. Dastager SG, Lee J-C, Ju Y-J, Park D-J, Kim39
C-J. 2008. Rubellimicrobium mesophilum sp. nov.,40
a mesophilic, pigmented bacterium isolated from soil.41
Int J Syst Evol Microbiol 58:1797800.42
30. Fujii K, Satomi M, Morita N, Motomura T,43
Tanaka T, Kikuchi S. 2003. Novosphingobium tar-44
daugens sp. nov., an oestradiol-degrading bacterium45
isolated from activated sludge of a sewage treatment46
plant in Tokyo. Int J Syst Evol Microbiol 53:4752.47
31. Tian B, Hua Y. 2010. Carotenoid biosynthe-48
sis in extremophilic Deinococcus-Thermus bacteria.49
Trends Microbiol 18:51220.50
32. Gutman J, Kaufman Y, Kawahara K, Walker51
SL, Freger V, Herzberg M. 2014. Interactions of52
glycosphingolipids and lipopolysaccharides with silica53
and polyamide surfaces: adsorption and viscoelastic 54
properties. Biomacromolecules 15:212837. 55
33. Rainey FA, Ray K, Ferreira M, Gatz BZ, 56
Nobre MF, Bagaley D, Rash BA, Park M-J, Earl 57
AM, Shank NC, Small AM, Henk MC, Battista JR, 58
Kmpfer P, da Costa MS. 2005. Extensive diver- 59
sity of ionizing-radiation-resistant bacteria recovered 60
from Sonoran Desert soil and description of nine new 61
species of the genus Deinococcus obtained from a sin- 62
gle soil sample. Appl Environ Microbiol 71:522535. 63
34. de Groot A, Chapon V, Servant P, Christen R, 64
Saux MF-L, Sommer S, Heulin T. 2005. Deinococ- 65
cus deserti sp. nov., a gamma-radiation-tolerant 66
bacterium isolated from the Sahara Desert. Int J 67
Syst Evol Microbiol 55:24416. 68
35. Hirsch P, Ludwig W, Hethke C, Sittig M, 69
Hoffmann B, Gallikowski CA. 1998. Hymenobacter 70
roseosalivarius gen. nov., sp. nov. from continen- 71
tal Antartica soils and sandstone: bacteria of the 72
Cytophaga/Flavobacterium/Bacteroides line of phy- 73
logenetic descent. Syst Appl Microbiol 21:374383. 74
36. Nbel U, Garcia-Pichel F, Muyzer G. 2000. 75
The halotolerance and phylogeny of cyanobacteria 76
with tightly coiled trichomes (Spirulina Turpin) and 77
the description of Halospirulina tapeticola gen. nov., 78
sp. nov. Int J Syst Evol Microbiol 50 Pt 3:126577. 79
37. Alarico S, Rainey FA, Empadinhas N, Schu- 80
mann P, Nobre MF, da Costa MS. 2002. Rubritep- 81
ida flocculans gen. nov., sp. nov., a new slightly 82
thermophilic member of the alpha-1 subclass of the 83
Proteobacteria. Syst Appl Microbiol 25:198206. 84
38. Yoon J-H, Kang S-J, Lee S-Y, Oh T-K. 2008. 85
Sphingomonas insulae sp. nov., isolated from soil. 86
Int J Syst Evol Microbiol 58:2316. 87
39. Pradhan S, Srinivas TNR, Pindi PK, Kishore 88
KH, Begum Z, Singh PK, Singh AK, Pratibha MS, 89
Yasala AK, Reddy GSN, Shivaji S. 2010. Bacte- 90
rial biodiversity from Roopkund Glacier, Himalayan 91
mountain ranges, India. Extremophiles 14:37795. 92
40. Yang Y, Itoh T, Yokobori S, Itahashi S, Shi- 93
mada H, Satoh K, Ohba H, Narumi I, Yamagishi A. 94
2009. Deinococcus aerius sp. nov., isolated from the 95
high atmosphere. Int J Syst Evol Microbiol 59:18626. 96
41. Yoo S-H, Weon H-Y, Noh H-J, Hong S- 97
B, Lee C-M, Kim B-Y, Kwon S-W, Go S-J. 2008. 98
Roseomonas aerilata sp. nov., isolated from an air 99
sample. Int J Syst Evol Microbiol 58:14825. 100
42. Crous PW, Summerell BA, Mostert L, Groe- 101
newald JZ. 2008. Host specificity and speciation 102
of Mycosphaerella and Teratosphaeria species as- 103
sociated with leaf spots of Proteaceae. Persoonia 104
20:5986. 105
43. Slvikov E, Vadkertiov R, Vrnov D. 2007. 106
Page 8 of 13
was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted November 30, 2015. ; https://doi.org/10.1101/029660doi: bioRxiv preprint
Yeasts colonizing the leaf surfaces. J Basic Microbiol1
47:34450.2
44. Zakharova K, Tesei D, Marzban G, Dijkster-3
huis J, Wyatt T, Sterflinger K. 2013. Microcolonial4
fungi on rocks: a life in constant drought? Myco-5
pathologia 175:53747.6
45. Rosselli R, Fiamma M, Deligios M, Pintus7
G, Pellizzaro G, Canu A, et al. (2015). Microbial8
immigration across the Mediterranean via airborne9
dust. Sci Rep 5:16306.10
46. Shirakawa MA, Zilles R, Mocelin A, Gaylarde11
CC, Gorbushina A, Heidrich G, Giudice MC, Del12
Negro GMB, John VM. 2015. Microbial colonization13
affects the efficiency of photovoltaic panels in a trop-14
ical environment. J Environ Manage 157:160167.15
Page 9 of 13
was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted November 30, 2015. ; https://doi.org/10.1101/029660doi: bioRxiv preprint
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).
Page 10 of 13
was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted November 30, 2015. ; https://doi.org/10.1101/029660doi: bioRxiv preprint
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.
Page 11 of 13
was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted November 30, 2015. ; https://doi.org/10.1101/029660doi: bioRxiv preprint
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).
Page 12 of 13
was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted November 30, 2015. ; https://doi.org/10.1101/029660doi: bioRxiv preprint
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.
Page 13 of 13
was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (whichthis version posted November 30, 2015. ; https://doi.org/10.1101/029660doi: bioRxiv preprint