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Prokaryotic and Eukaryotic Community Structure in Field
and Cultured Microbialites from the Alkaline Lake
Alchichica (Mexico)
Estelle Couradeau
1,2,3
, Karim Benzerara
2
, David Moreira
1
, Emmanuelle Ge
´rard
3
,Jo
´zef Kaz
´mierczak
4
,
Rosaluz Tavera
5
, Purificacio
´nLo
´pez-Garcı
´a
1
*
1Unite
´d’Ecologie, Syste
´matique et Evolution, CNRS UMR 8079, Universite
´Paris-Sud, Orsay, France, 2Institut de Mine
´ralogie et de Physique des Milieux Condense
´s, CNRS
UMR 7590, Universite
´Pierre et Marie Curie, Paris, France, 3Institut de Physique du Globe de Paris, CNRS UMR 7154, Universite
´Paris Diderot, Paris, France, 4Institute of
Paleobiology, Polish Academy of Sciences, Warszawa, Poland, 5Departamento de Ecologı
´a y Recursos Naturales, Facultad de Ciencias, Universidad Nacional Auto
´noma de
Me
´xico, Distrito Federal, Mexico
Abstract
The geomicrobiology of crater lake microbialites remains largely unknown despite their evolutionary interest due to their
resemblance to some Archaean analogs in the dominance of in situ carbonate precipitation over accretion. Here, we studied
the diversity of archaea, bacteria and protists in microbialites of the alkaline Lake Alchichica from both field samples
collected along a depth gradient (0–14 m depth) and long-term-maintained laboratory aquaria. Using small subunit (SSU)
rRNA gene libraries and fingerprinting methods, we detected a wide diversity of bacteria and protists contrasting with a
minor fraction of archaea. Oxygenic photosynthesizers were dominated by cyanobacteria, green algae and diatoms.
Cyanobacterial diversity varied with depth, Oscillatoriales dominating shallow and intermediate microbialites and
Pleurocapsales the deepest samples. The early-branching Gloeobacterales represented significant proportions in aquaria
microbialites. Anoxygenic photosynthesizers were also diverse, comprising members of Alphaproteobacteria and
Chloroflexi. Although photosynthetic microorganisms dominated in biomass, heterotrophic lineages were more diverse.
We detected members of up to 21 bacterial phyla or candidate divisions, including lineages possibly involved in microbialite
formation, such as sulfate-reducing Deltaproteobacteria but also Firmicutes and very diverse taxa likely able to degrade
complex polymeric substances, such as Planctomycetales, Bacteroidetes and Verrucomicrobia. Heterotrophic eukaryotes
were dominated by Fungi (including members of the basal Rozellida or Cryptomycota), Choanoflagellida, Nucleariida,
Amoebozoa, Alveolata and Stramenopiles. The diversity and relative abundance of many eukaryotic lineages suggest an
unforeseen role for protists in microbialite ecology. Many lineages from lake microbialites were successfully maintained in
aquaria. Interestingly, the diversity detected in aquarium microbialites was higher than in field samples, possibly due to
more stable and favorable laboratory conditions. The maintenance of highly diverse natural microbialites in laboratory
aquaria holds promise to study the role of different metabolisms in the formation of these structures under controlled
conditions.
Citation: Couradeau E, Benzerara K, Moreira D, Ge
´rard E, Kaz
´mierczak J, et al. (2011) Prokaryotic and Eukaryotic Community Structure in Field and Cultured
Microbialites from the Alkaline Lake Alchichica (Mexico). PLoS ONE 6(12): e28767. doi:10.1371/journal.pone.0028767
Editor: Jack Anthony Gilbert, Argonne National Laboratory, United States of America
Received September 13, 2011; Accepted November 14, 2011; Published December 14, 2011
Copyright: ß2011 Couradeau et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This project was financed by the French Centre National de la Recherche Scientifique - CNRS Interdisciplinary program ‘‘Origines des plane
`tes et de la
vie’’ (PID OPV) and Institut National des Sciences de l’Univers - INSU program ‘‘InteractionsTerre/Vie’’ (InterrVie), and the Polish Ministry of Science and Higher
Education grant N307019. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: Purificacion Lopez-Garcia is an Academic Editor of PLoS ONE. This does not alter the authors’ adherence to all the PLoS ONE policies on
sharing data and materials.
* E-mail: puri.lopez@u-psud.fr
Introduction
Microbialites are organosedimentary structures formed by
microbially-mediated mineral precipitation and/or accretion [1].
Stromatolites are microbialites exhibiting a laminated macrofabric
[2]. Their fossils are found throughout the geological record [3,4],
the oldest being 3,43 Ga old (Pilbara Craton, Western Australia)
[5]. After having dominated the Precambrian, stromatolite
abundance declined steeply at the onset of the Phanerozoic
[6,7]. Today, stromatolites are confined to very few marine or
quasi-marine environments, such as the well-studied Shark Bay,
Australia [8,9] and Exuma Sound, Bahamas [10,11]. Microbialites
have also been described in alkaline lakes such as Lake Van,
Turkey [12,13], Pyramid Lake, USA [14], the Indonesian crater
lakes Satonda [15,16,17] and Niuafo’ou [18], but also in the
freshwater Ruidera pools [19] and the hypersaline lakes
LagoVermelha, Brazil [20] and Cuatro Cie´nagas, Mexico [21].
Despite their geological and evolutionary importance, the precise
stromatolite formation mechanisms remain poorly understood. It
has been proposed that net carbonate precipitation results from a
balance between concurrent microbial metabolisms [22]. Photo-
synthesis (both oxygenic and anoxygenic) and sulfate reduction lead
to local carbonate supersaturation, whereas heterotrophic metab-
olisms induce carbonate dissolution [23,24,25,26]. In addition,
massive cyanobacterial production of exopolymeric substances
(EPS), which efficiently sequester cations such as Ca
2+
or Mg
2+
,
PLoS ONE | www.plosone.org 1 December 2011 | Volume 6 | Issue 12 | e28767
can also inhibit carbonate precipitation [27]. Hence, microbialite
formation most likely results from the interplay between microor-
ganisms forming complex communities and their metabolic
activities under the influence of environmental conditions (e.g.
photoperiod, temperature) and local chemistry (ion availability).
The characterization of microbial diversity is thus crucial to
further understand microbe-mineral interactions in microbialites.
Most diversity studies using molecular methods have focused on
marine stromatolites, where Alpha- and Gammaproteobacteria,
Cyanobacteria and Planctomycetales appear to dominate
[28,29,30,31,32,33,34,35]. In contrast, knowledge about lacustrine
microbialites remains much sparser. Firmicutes, Gamma- and
Alphaproteobacteria were the most abundant taxa in Lake Van
microbialites, but these studies were carried out on 15 year-old dry
samples and, hence, probably biased [13]. Recent metagenomic
analysis of Cuatro Cie´nagas microbialites revealed a complex
community where Cyanobacteria, Alpha- and Gammaproteobac-
teria and Planctomycetales predominated, as in marine micro-
bialites, identifying functions potentially linked to complex redox-
dependent activities and the establishment of structured biofilms
[21]. Despite these pioneering studies, the precise role in
mineralization and biofilm dynamics of many bacterial taxa, but
also of the much less studied eukaryotic and archaeal communi-
ties, remains to be elucidated.
Understanding the role of microorganisms in stromatolite
formation and the environmental conditions promoting it requires
extending microbial diversity studies to other systems, including
non-hypersaline or freshwater microbialites. Indeed, lacustrine
microbialites may be better analogs for several Archaean
stromatolites. The fossil 3.5 Ga-old Australian stromatolites likely
formed in a caldera lake [36] and the exceptionally preserved
2,7 Ga-old massive stromatolites from Tumbiana also grew under
lacustrine conditions [37,38,39]. The alkaline (pH,8.9) Alchi-
chica crater lake in the Central Mexico Plateau is particularly
interesting from this perspective. Located at 2300 m above sea
level and with a maximum depth of 63 m, it harbors prominent
living microbialites down to at least 14 m deep [40]. Conspicuous
dry microbialites emerge on the shores due to the 3–5 m lowering
of the water level in the past three decades [41]. Alchichica is a
monomictic lake, i.e. stratified during most of the year, the
oxygenated surface water mixing with deep anoxic water only
during the winter season [42]. Hydrochemistry studies show that
water is Mg-rich (Mg/Ca = 40), oversaturated with magnesium
and calcium carbonates [40,43]. Accordingly, Alchichica micro-
bialites are predominantly composed of hydromagnesite
[Mg
5
(CO
3
)
4
(OH)
2
.4(H
2
O)] [40].
Classical morphological observations and preliminary molecular
analyses focused on cyanobacteria suggested that Oscillatoriales
and Pleurocapsales dominate these microbialites [40]. Here, we
applied cultivation-independent molecular approaches to (i)
characterize the diversity of microorganisms of the three domains
of life, Bacteria, Archaea and Eucarya, in Alchichica microbialites
along a 0–14 m depth gradient, (ii) compare the microbial
community structure in lake microbialites with that of Alchichica
microbialites maintained for two years under controlled laboratory
conditions and (iii) identify microbial taxa potentially involved in
carbonate precipitation and microbialite formation.
Results
Microbial community fingerprinting analyses of field and
aquarium Alchichica microbialites
Field microbialites exhibited different colors depending on the
sampling depth (Table 1). Sub-fossil microbialites at the rim of
the lake, out of the water, were predominantly white. Submerged,
living microbialites close to the surface were dark brown to black,
those at 6–8 m depth intensely emerald-green and those at the
highest depth sampled (14 m) golden-brown (Figure 1). This
suggests that the dominant associated communities and/or their
photosynthetic and protective pigments vary according to light
intensity. These differences in color were also visible in the
samples set on the aquaria soon after collection (Figure S1),
though they disappeared with time and, after one year, all
microbialite fragments in aquaria showed a similar green color
(Figure 2A).
To rapidly evaluate the complexity of the microbial commu-
nities in these microbialites and select representative samples for
in-depth analyses, we obtained bacterial denaturing gel gradient
electrophoresis (DGGE) fingerprints of 13 samples from different
lake depths plus samples from the two aquaria (Figure S2). Cluster
analysis of DGGE profiles divided the samples in two major
groups. One corresponded to shallow samples (0.5–2 m), whereas
the second included deeper (3–14 m) and aquarium samples. This
was consistent with the fact that the aquarium fragments analyzed
(Figure S1) corresponded originally to 3 m (AQ1) and 6 m (AQ2)
depth and suggested that, at least partly, the native bacterial
community was maintained in culture. Fingerprints from deeper
samples displayed more bands, reflecting either a higher bacterial
diversity or the fact that a few phylotypes dominate surface
microbialites, masking minor components. The identity of some
dominant and characteristic bands was investigated subsequently.
Based on DGGE profiles, we selected the three samples AL31
(0.5 m), AL67 (4 m) and AL52 (14 m), which displayed charac-
teristic profiles and grouped in different clusters (Figure S2). More
importantly, they were well distributed along the depth gradient
and represented three phenotypic types in terms of color (Figure 1).
Table 1. Alchichica samples analyzed in this study.
Sample Origin Description
AL29 0,08 m microbialite fragment, black/dark brown
AL31* 0,5 m microbialite fragment, black/dark brown
AL27 0,8 m microbialite fragment, black/dark brown
AL43 1 m microbialite fragment, dark brown
AL36 1,5 m microbialite fragment, dark brown
AL38 2 m microbialite fragment, dark brown
AL70 3 m microbialite fragment, brown
AL67* 4 m microbialite fragment, brown/dark green
AL64 5 m microbialite fragment, dark green
AL61 6 m microbialite fragment, green
AL58 8 m microbialite fragment, intense emerald green
AL55 11 m microbialite fragment, intense green/yellowish
AL52* 14 m microbialite fragment, golden/brownish
AQ1* Aquarium 1 microbialite fragment
AQ1b Aquarium 1 aquarium glass wall biofilm
AQ1w Aquarium 1 water sample
AQ2* Aquarium 2 microbialite fragment
AQ2b Aquarium 2 aquarium glass wall biofilm
AQ2w Aquarium 2 water sample
Samples used for clone library construction are noted with an asterisk. AQ1,
aquarium 1; AQ2, aquarium 2.
doi:10.1371/journal.pone.0028767.t001
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Overview of bacterial diversity in Alchichica microbialites
Bacterial diversity in the selected samples was further charac-
terized by SSU rRNA gene libraries (Table 2). We used general
bacterial primers but also cyanobacterial-specific primers to get a
finer description of the diversity within this group, since
cyanobacteria usually dominate stromatolite microbial biomass,
including Alchichica microbialites (Figure 2) [40], and likely play a
major role in carbonate precipitation. In addition, since
cyanobacterial EPS sheaths may decrease DNA extraction yield
[44,45,46], using specific primers would help to detect underrep-
resented species. To further limit biases, we generated two
bacterial and two cyanobacterial SSU rDNA libraries for each
sample, except in cases when a single library allowed a coverage
.80% and a small number of singletons (Table 2). There were
only minor differences in the diversity obtained between the two
libraries for each sample, mostly in relative proportions, in
particular for a few cyanobacterial, alpha- and beta-proteobacter-
ial phylotypes. The only significant difference was the presence of
Firmicutes only in bacterial library 2. These differences are likely
due to local heterogeneities and/or to a different coverage
achieved by the libraries. However, despite these relatively minor
differences, there was a rather good agreement in the bacterial
diversity identified in the two libraries, which can therefore be
considered as replicates. This was also the case for the most
abundant cyanobacterial groups in both general and specific
libraries (Figure 3). Therefore, for each sample we compiled the
diversity from the two independent libraries for further inter-
sample comparison.
Figure 3 shows the taxonomic distribution of bacterial clones in
lake and aquarium samples. We identified members of 14 phyla
and 7 candidate divisions. Remarkably, bacterial diversity was
generally higher in aquaria than in field samples in terms of high-
rank taxa, in agreement with the DGGE analysis, which showed
more bands in the aquarium profiles (Figure S2). At phylum level,
AQ1 taxa resembled those of field microbialites, especially those
collected at higher depth. They were all dominated by
Cyanobacteria and the Alpha subdivision of the Proteobacteria
(60 to 75% of the total bacterial SSU rDNAs in field sample
libraries, Figure 3). AQ2 displayed similar taxonomic composition,
but Cyanobacteria and Alphaproteobacteria accounted for only
,15% of sequences. In contrast, Firmicutes, minor components in
the other libraries (0 to 2%), were dominant in AQ2 (29%). The
rest of bacterial taxa had variable relative proportions, probably
reflecting local spatial heterogeneities and/or depth-related
adaptation. For example, Betaproteobacteria represented 19% of
sequences in AL67 but less than 2% in other samples. The
proportion of Actinobacteria increased with depth (from 1% to
10%) whereas Bacteroidetes showed the opposite trend (from 4%
Figure 1. View of Alchichica and schematic depth profile showing the different sampling depths in the lake. Stromatolite fragments
from three different depths and colors are shown on the right.
doi:10.1371/journal.pone.0028767.g001
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to 1%). Planctomycetales was one of the most constant and
abundant phyla with nearly 10% of sequences in all samples,
except AL67 (only 4%). AQ1 contained larger proportions of
Gammaproteobacteria (8%), Deltaproteobacteria (9%) and Planc-
tomycetales (13%) than lake samples. In general, the relative
bacterial proportions in libraries appeared distributed more evenly
among phyla in the deepest sample and in aquaria samples. This
was in agreement with DGGE patterns, which showed more bands
in AL52, reinforcing the suggestion that diversity increased with
depth (especially among heterotrophic groups).
Cyanobacteria
Confirming microscopy observations, cyanobacteria constituted
the most abundant phylum in gene libraries (Figures 2 and 3).
Furthermore, the distribution among cyanobacterial orders of
sequences obtained with bacterial- and cyanobacterial-specific
primers was remarkably similar within each sample (Figure 3). The
only exception was AQ2, with relative proportions of Chroococ-
cales and Gloeobacterales obtained with bacterial primers much
higher than those obtained with cyanobacterial primers, domi-
nated by Oscillatoriales.
Considering all samples together, we retrieved OTUs belonging
to 7 of the 8 described cyanobacterial orders (only Stigonematales
were absent). The most remarkable observation was the shift of
relative abundance of Oscillatoriales with depth. They largely
dominated surface and intermediate microbialite sample libraries
(,80% in AL31 and 90% in AL67), whereas Pleurocapsales
dominated deep microbialite libraries (,80% of cyanobacterial
sequences in AL52, Figure 3). In addition, Gloeobacterales were
also very abundant, especially in aquarium samples (20–40% of
cyanobacterial sequences, Figure 3). Chroococcales, Nostocales
and Prochlorales were detected in low proportions in all samples,
whereas Acaryochlorales were exclusively amplified from the
deepest sample, AL52.
Figure 2. Images of biofilms associated to Alchichica microbialites. (A) Photomicrograph of a fresh biofilm associated with AQ2 microbialite
showing the abundance and diversity of Cyanobacteria. (B) and (C) Natural fluorescence CLSM pictures of transversal sections of AQ2 and AL66 (4 m)
microbialite surfaces, respectively. AL66 (C) was stained with DAPI and calcein. Mineral areas are indicated by stripes. Biofilm biomass was dominated
by photosynthetic organisms, mostly cyanobacteria of different orders, but also diatoms and green algae. Some distinguishable morphotypes are
highlighted; d, diatom; c, Chrooccocales; o, Oscillatoriales; n, Nostocales. Scale bars, 20 mm.
doi:10.1371/journal.pone.0028767.g002
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At a finer phylogenetic scale, we detected 38 cyanobacterial
OTUs (including 4 diatom chloroplast sequences): 9 OTUs only in
lake samples, 17 only in aquaria, and the remaining 12 were
shared (Figure 4). OTU diversity was thus larger in aquaria
microbialites compared to field microbialites. Oscillatoriales were
the most diverse group with 16 OTUs, including 3 of the most
abundant ones. These affiliated to the genus Leptolyngbya and were
also detected in AL31 and AL67. Pleurocapsales were the second
most diverse group with 5 OTUs. One of them (CyanoOTU35)
accounted for 69% of all cyanobacterial sequences in the 14 m-
deep sample AL52 (Figure 4). This phylotype was also present in
the other lake samples and in AQ1, though in lower proportions.
Its high abundance in deep samples was corroborated by DGGE
analyses, corresponding to one of the most intense bands in deep
sample fingerprints (band J in samples AL58, AL55 and AL52,
Figure S2 and Table 3).
In addition to Pleurocapsales, the Acaryochlorales OTU
CyanoOTU23 was relatively abundant at 14 m, in agreement
with the low-light-intensity adaptation characteristic of Acaryo-
chlorales [47]. We also detected 5 Chroococcales OTUs, one of
them (CyanoOTU32) particularly abundant at 8 m (AL58 sample)
as shown by DGGE analyses (band I in Figure S2 and Table 3).
Finally, we identified 3 very divergent OTUs belonging to the
deep-branching Gloeobacterales. Among them, CyanoOTU02,
identified in field sample AL31 (0.5 m), represented 18% and 20%
of AQ1 and AQ2 cyanobacterial sequences.
Other bacterial taxa with photosynthetic members
Apart from cyanobacteria, we identified phylotypes of other
bacterial phyla that comprise phototrophic, in addition to
heterotrophic, members: Alphaproteobacteria, Gammaproteobac-
teria and Chloroflexi. With ,30% of field sample clones,
Alphaproteobacteria was the second most abundant group after
Cyanobacteria (Figure 3). Their relative abundance was constant
with depth. They were also extremely diverse, with 68 OTUs: 35
Table 2. Summary of SSU rRNA gene sequences analyzed from bacterial, cyanobacterial and eukaryotic-specific gene libraries and
the associated diversity indices.
Clone libraries
No. of clones
analyzed No.of OTUs Ace Chao1
Chao1 95%
confidence interval singletons Coverage (%)
Bacteria AQ1 Library 1 84 56 198 169 104/323 43 49
AQ1 Library 2 192 93 243 215 153/339 61 68
AQ1 total (1+2) 276 126 423 313 228/468 87 68
AQ2 Library 1 65 42 181 147 81/328 33 49
AQ2 Library 2 200 57 82 74 63/103 30 85
AQ2 total (1+2) 265 86 149 134 108/190 48 82
AL31 Library 2 199 53 119 131 82/260 31 84
AL67 Library 2 202 31 43 42 34/73 12 94
AL52 Library 1 44 17 39 35 21/92 11 75
AL52 Library 2 196 67 137 113 88/171 39 80
AL52 total (1+2) 240 74 137 122 95/180 41 83
Cyanobacteria AQ1 Library 1 53 9 10 12 9/34 3 94
AQ1 Library 2 108 7 7 7 / 0 100
AQ1 total (1+2)161 161616/ 1 99
AQ2 Library 1 49 13 20 21 15/56 5 90
AQ2 Library 2 101 19 30 28 20/64 8 92
AQ2 total (1+2) 150 22 29 36 25/89 8 95
AL31 Library 2 63 8 11 9 8/23 3 95
AL67 Library 2 62 6 8 6 6/14 1 98
AL52 Library 1 39 5 5 5 / 1 97
AL52 Library 2 61 8 10 9 7/22 3 95
AL52 total (1+2) 100 11 21 26 14/79 6 94
Eukaryotes AQ1 95 21 32 28 22/53 9 91
AQ1 b 76 22 24 23 22/31 4 95
AQ1w 69 19743121/74 12 83
AQ2 117 23 30 27 23/45 7 94
AQ2 b 83 16 16 16 16/19 2 98
AQ2 w 72 11 20 21 13/63 5 93
AL31 48 1 0 1 1/1 0 100
AL67 38 1 0 1 1/1 0 100
AL52 38 5 7 6 6/14 2 95
AQ1b and AQ2b refer to aquarium wall-attached biofilm samples; AQ1w and AQ2w refer to plankton samples.
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exclusively identified in field samples, 23 in the aquaria and 10 in
both field samples and aquaria (Figure S3). The composition of the
deeper samples AL67 and AL52 was similar, with high
proportions of Rhodospirillales and Rhodobacterales, whereas
Rhizobiales were scarce in them but more abundant in the
shallowest sample AL31. The most abundant Rhodobacterales
OTU, AlphaOTU65 (34% and 24% of AL67 and AL52
sequences, respectively), was relatively close to members of the
metabolically versatile genus Rhodobacter. Many Rhodobacter species
are sulfur-oxidizing photosynthesizers and, in the context of the
lake, AlphaOTU65 might actually correspond to anoxygenic
photosynthesizers. Moreover, many Rhodospirillales (e.g. Rhodos-
pirillum), represented by the abundant phylotypes AlphaOTU20
and AlphaOTU21, and Rhizobiales (e.g. Rhodomicrobium), are also
anoxygenic photosynthesizers [48]. In contrast, the vast majority
of Gammaproteobacteria phylotypes likely have heterotrophic
metabolisms. However, some might be photosynthetic; for
example the Chromatiales GammaOTU06 (Figure S4), related
to environmental sequences from the Mexican alkaline lake
Texcoco [49], suggesting an adaptation to these particular alkaline
environmental conditions.
Chloroflexi (green non-sulfur bacteria) are typically anoxygenic
photosynthesizers, although an increasing number of non-
photosynthetic lineages (Anaerolineae, Caldilineae and Dehalo-
coccoides) has also been characterized [50]. Likely phototrophic
Alchichica representatives were ChlorofOTU1 and Chloro-
fOTU2, related to Chloroflexus and Chlorothrix, though probable
heterotrophic OTUs related to Anaerolinea and other environmen-
tal Chloroflexi were more diverse (Figure S5). In contrast to their
low proportion in gene libraries (Figure 3), DGGE analyses
suggested a high abundance of Chloroflexi in Alchichica
microbialites. Such difference may reflect a negative bias in the
general primers used for gene library construction, as already
noted in the study of Ruidera stromatolites [19,50]. In fact, seven
of the most intense DGGE bands from Alchichica field samples
(bands A, B, C, D, G, K and M; Figure S2 and Table 3) were
Figure 3. Phylogenetic distribution of bacterial, cyanobacterial and eukaryotic SSU rRNA gene sequences in Alchichica
microbialites. In the specific panel for cyanobacteria, the phylogenetic distribution of cyanobacterial clones retrieved with universal bacterial
primers (B) or with specific cyanobacterial primers (C) is shown for comparison. Sample names and origins are explained in Table 1. Non-Latin names
correspond to Candidate Divisions; Deino-Thermus, Deinococcus/Thermus group.
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assigned to Chloroflexi after sequencing, including four (C, D, G
and M) related to the two likely anoxygenic photosynthesizers
ChlorofOTU1 and ChlorofOTU2. Bands C, G and M, 100%
identical to the corresponding ChlorofOTU2 sequence, were
detected in nearly all field samples, suggesting that this OTU was
abundant at all depths. In contrast, typical photosynthetic
Chloroflexi were not detected in aquaria (Figure 3).
Typical heterotrophic bacterial taxa
Along with the potential photosynthetic OTUs mentioned
above, many microbialite bacteria belonging to Alphaproteobac-
teria, Gammaproteobacteria (Figures S3 and S4), Chloroflexi,
Chlorobi and Acidobacteria are most likely heterotrophic
(Figures S5 and S6). In addition, we found 19 OTUs of
Deltaproteobacteria (Figure S4), including several Myxoccocales
and others corresponding most likely to sulfate-reducing bacteria
(SRB). Betaproteobacteria, with 15 OTUs, were detected in all
microbialite samples and particularly abundant in AL67 and
AQ2 (Figures 3 and S7). The most abundant betaproteobacterial
OTU in field samples (BetaOTU03) corresponded to Delftia
acidovorans, a strict aerobe able to degrade diverse complex
compounds [51].
Planctomycetales were moderately abundant (5–15% of se-
quences) but highly diverse, with 62 OTUs (Figure S8).
Planctomycetales are able to oxidize a large range of substrates,
including many different polysaccharides, which explains their
frequent association to microbialites, where they probably degrade
cyanobacterial EPS [13,52]. As Planctomycetales, Bacteroidetes
were also diverse (27 OTUs, Figure S9). They are known to
oxidize complex organics like cell wall polymers [53].
We also identified Gram positive bacteria. Firmicutes were
relatively diverse (18 OTUs) but quasi-exclusively in AQ2,
including several sequences related to strict fermentative anaer-
obes (e.g. Clostridiales) and phylotypes from anoxic environments.
Actinobacteria were also diverse (17 OTUs), many from AL52
(Figure S10). Some were Rubrobacterales (ActinoOTU3 specifi-
cally related to Rubrobacter radiotolerans), known for their high
resistance to UV and ionizing radiation [54]. This could reflect the
fact that Alchichica is at high altitude and, therefore, exposed to
strong UV radiation.
Although most Chlorobi (green sulfur bacteria) are photosyn-
thetic [48], the only Alchichica OTU from this group was related
to the chemoheterotroph Ignavibacterium album (Figure S5).
Likewise, a phototrophic lifestyle could not be predicted for the
Acidobacteria sequences (Figure S6), very distantly related to the
photoheterotroph Chloracidobacterium [55]. Finally, we identified
bacteria belonging to eleven additional phyla or candidate
divisions: Verrucomicrobia, Spirochaeta, with several OTUs
related to sequences detected in alkaline or hypersaline micro-
bialites and microbial mats, the nitrite-oxidizing Nitrospira,
Thermus/Deinococcus, and the candidate divisions OP11, WS6,
SBR1, BRC1, NKB19, TM6 and OP3 (Figures S8 and S11).
Archaeal diversity
Despite of the use of different archaeal-specific primers and
PCR conditions, we failed to amplify archaeal sequences from field
samples selected for detailed study (AL31, AL67, AL52). From the
rest of samples, we only retrieved two archaeal phylotypes from
AL70 (3 m) and the aquarium sample AQ1 (Figure S12 and
Table 1). ArchaeOTU01 was a singleton related to euryarchaeotal
hot spring or hypersaline mat environmental clones. Archae-
aOTU02, detected in both AL70 and AQ1, was close to the
Thaumarchaeota Cenarchaeum and Nitrosopumilus and, thus, prob-
ably an ammonium-oxidizer [56]. These results suggest that
archaea are present in the microbialites but in minor proportions
and very low diversity.
Figure 4. Maximum likelihood (ML) phylogenetic tree of SSU rDNA of cyanobacteria and chloroplasts from Alchichica microbialites.
Numbers at nodes indicate bootstrap values. Sequences from this study are in bold. Relative proportions of the different OTUs in each sample are
indicated by circles of proportional size on the right. The number (n) indicates the number total of clones analyzed for each sample. Asterisks indicate
OTUs also identified in DGGE patterns. The scale bar indicates the number of substitutions per site for a unit branch length.
doi:10.1371/journal.pone.0028767.g004
Table 3. Closest Alchichica microbialite OTUs to sequences of DNA fragments amplified from DGGE bands.
Band First hit Identity Taxonomy Corresponding OTU
AContig_AL67_2_1B_154 84% Bacteria; Chloroflexi ChlorofOTU11 (Fig. S5)
BContig_AL67_2_1B_105 98% Bacteria; Chloroflexi ChlorofOTU10 (Fig. S5)
CContig_AL31_2_B_35 100% Bacteria; Chloroflexi ChlorofOTU02 (Fig. S5)
DContig_AL67_2_1B_187 86% Bacteria; Chloroflexi ChlotofOTU01 (Fig. S5)
EContig_AL67_2_1B_14 91% Bacteria; Bacteroidetes BactOTU10 (Fig. S9)
FContig_AQ2_2_1B_199 97% Bacteria; Bacteroidetes BactOTU07 (Fig. S9)
GContig_AL31_2_1B_35 100% Bacteria; Chloroflexi ChlorofOTU02 (Fig. S5)
HContig_AL67_2_1B_14 98% Bacteria; Bacteroidetes BactOTU10 (Fig. S9)
IContig_AQ2_2_1C_40 97% Bacteria; Cyanobacteria; Chroccocales CyanoOTU32 (Fig. 4)
JContig_AL52_1_1C_37 97% Bacteria, Cyanobacteria, Pleurocapsales CyanoOTU35 (Fig. 4)
KContig_AQ1_1_1B_10 99% Bacteria; Chloroflexi ChlorofOTU07 (Fig. S5)
LContig_AL52_1_1C_07 91% Bacteria; Cyanobacteria; Prochlorales CyanoOTU09 (Fig. 4)
MContig_AL31_2_1B_35 100% Bacteria; Chloroflexi ChlorofOTU02 (Fig. S5)
NContig_AQ2_2_1B_212 98% Bacteria; Actinobacteria; Rubrobacteridae ActinoOTU03 (Fig.S10)
Bands correspond to those labeled in Figure S2.
doi:10.1371/journal.pone.0028767.t003
Alchichica Crater Lake Microbialite Communities
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Protist diversity
Although protists are conspicuous microbialite inhabitants [57],
their diversity in these environments has been rarely studied. To
prevent library saturation with animal sequences, we amplified
SSU rRNA genes using the primer UNonMet, biased towards
non-metazoan eukaryotes [58]. In addition to libraries from the
selected samples AL31, AL67, AL52 and aquarium microbialites,
we amplified protist SSU rDNAs from the aquarium plankton
(AQ1w and AQ2w) and non-calcified biofilms growing on
aquarium walls (AQ1b and AQ2b). These samples should serve
as controls to identify specific protist phylotypes associated with
growing microbialites. The number of clones analyzed for each
sample is summarized in Table 2.
There were important differences between field and aquarium
samples and also between plankton and microbialites in the
aquaria, whereas the aquarium non-calcified biofilms were similar
to the aquarium microbialites (Figure 3). Field microbialites were
dominated by one single chlorophyte (ChlorophytOTU05, related
to the sessile genera Pseudendoclonium and Blidingia), representing
,90% of all sequences in AL31 and AL67, and ,70% in AL52
(Figure 5). Two additional chlorophytes were identified in AL52:
ChlorophytOTU06, also related to those two genera, and
ChlorophytOTU01, very close to Rhizoclonium hieroglyphicum,an
entangling filamentous algae widespread in microbial mats in fresh
or brackish waters [59]. AL52 also contained a dinoflagellate
OTU related to the photosynthetic genus Woloszynskia. No other
photosynthetic eukaryotes were found in the lake, although they
certainly exist since living diatoms were observed by microscopy
(Figure 2) and their chloroplast SSU rRNA genes were detected in
sample AL31 (see above). Field samples were thus dominated by
green algae, which possibly masked other eukaryotes present in
minor proportions. Thus, only two additional non-photosynthetic
phylotypes were identified in AL31, both corresponding to fungi
(Figure S13).
Aquaria samples were far more diverse. Among photosynthetic
protists, ChlorophytOTU05, dominant in field microbialites, was
also abundant in aquarium microbialites, especially AQ1.
However, it was absent from both the aquarium plankton and
the non-calcified biofilms (Figure 5). It thus seems specifically
associated to microbialites, opening the possibility that it plays a
role in their formation or stability. A few other chlorophytes and
several other photosynthetic lineages were identified in aquaria,
notably diatoms (StramenoOTU05-07) and chrysophytes (Stra-
menoOTU03, frequent in plankton). Concerning heterotrophic
eukaryotes, ciliates (Figure 5) and very diverse opisthokonts were
found in the aquaria (Figure S13). The latter included most
notably Fungi, with typical Ascomycota, Basidiomycota and
Chytridiomycota, but also OTUs of the environmental LKM11
group, now classified as Rozellida or Cryptomycota [60]. A
relatively large diversity of Amoebozoa and choanoflagellates was
also found, the latter almost exclusively in AQ1 and never in the
planktonic fraction. We also identified nucleariids and several
divergent sequences at the base of the Choanoflagellida/
Icthyosporea and at the base of the Metazoa without close
relatives (Figure S13).
Discussion
To address the long-term question of understanding microbial-
mineral interactions and how microbialites form, we first aimed at
characterizing microbial communities inhabiting Alchichica mi-
crobialites at different depths. The recurrent presence of particular
abundant lineages may point out to specific metabolisms and lead
to hypotheses about their role in carbonate precipitation and
microbialite formation. Another important issue is the possibility
to preserve a significant fraction of the original microbial
communities in laboratory aquaria. This would allow mineraliza-
tion experiments under controlled conditions using complex and
fairly genuine diverse microbial communities. Thus, we studied
the diversity of microorganisms belonging to the three domains of
life in an integrative approach rarely undertaken for this kind of
systems.
Alchichica field microbialite community structure and its
variation with depth
Field microbialites at all depths were largely dominated by
Cyanobacteria and Alphaproteobacteria. As in Shark Bay
stromatolites, where ,10% of the Alphaproteobacteria were
potential anoxygenic photosynthesizers [29], many Alchichica
Alphaproteobacteria are likely photosynthetic. Most likely, Alchi-
chica alphaproteobacterial phylotypes display diverse metabolisms
going from autotrophy to heterotrophy which, together with their
richness, suggests an important role in microbialite biofilm
organization and activity. Chloroflexi, present in all samples and
probably abundant according to DGGE fingerprinting, was the
third Alchichica bacterial group with photosynthetic members. In
addition to photosynthesizers, typical heterotrophs such as
Planctomycetales, Bacteroidetes and Actinobacteria, were recur-
rently present at relative high frequency, whereas Beta-, Gamma-
and Deltaproteobacteria and Firmicutes showed more variable
proportions (Figure 3). The dominant Cyanobacteria and
Alphaproteobacteria, accompanied by relatively abundant Planc-
tomycetales, Firmicutes and Bacteroidetes have been reported in
comparable systems including Cuatro Cie´nagas [21], Bahamas
[34,35] and Shark Bay [29,33]. In addition, many of the closest
relatives to Alchichica sequences come from alkaline systems,
notably the giant microbialites of Lake Van, more similar by its
physico-chemical characteristics to Alchichica microbialites than
marine or hypersaline lake ones [13]. This observation was
statistically confirmed by comparing the bacterial community
composition of Alchichica samples with those of Shark Bay,
Bahamas and Lake Van. All Alchichica samples clustered
together, forming two clusters, one for lake samples, with 0.5
and 4 m depth samples more closely related, and the other for
aquarium microbialites (Figure 6). From the other samples,
although much more distant, Lake Van was closer to Alchichica
samples than the marine stromatolites.
Two important observations can be outlined from Alchichica
microbialite bacterial diversity. First, even if many photosynthetic
lineages are present, the relative abundance of typical heterotro-
phic lineages suggests that they play an important role. Second,
the most remarkable change along the depth gradient was the
marked shift in the cyanobacterial community composition,
dominated by filamentous Oscillatoriales in surface and interme-
diate depths (.90% of sequences at 0.5 and 4 m) and by
Pleurocapsales in deeper samples (.80% of sequences, contribut-
ed mostly by the phylotype CyanoOTU35). This shift was
detected by gene library comparison but also by sequencing
intense DGGE bands (Figure S2 and Table 3). Although variation
of the cyanobacterial composition at larger spatial scales (.few
centimeters), as evidenced in Hamelin Pool [29,33] and Bahamas
[32], cannot be discarded, the Oscillatoriales-to-Pleurocapsales
dominance transition with depth in Alchichica is likely related to
adaptation to depth and light intensity. Oscillatoriales are indeed
adapted to high light intensity [61], whereas Pleurocapsales
actively search low light (Waterbury and Stanier, 1978). This
correlates with microscopy observations showing that filamentous
Oscillatoriales tend to grow at the microbialite surface (e.g.
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Figure 2A), where their massive presence can obscure that of other
microbialite-associated bacteria, whereas the coccoid or pseudo-
filamentous Pleurocapsales are intimately associated to the mineral
matrix (unpublished observations). The differential presence of
these morphologically dissimilar cyanobacteria may have a
significant impact on the organization of the microbialite biofilms.
In contrast with the recognized importance of bacteria in
microbialite formation and dynamics, archaea and microbial
eukaryotes might have been overlooked in the past. Our results
show that archaea are present in Alchichica microbialites but in
minor proportions and very low diversity. This confirms
observations from Shark Bay (7% of sequences, [29], Bahamas
(1–2%, [31] and Cuatro Cie´nagas [21] stromatolites. Consequent-
ly, the role of archaea in microbialite formation is probably minor.
Inversely, some reports based on microscopy observations suggest
that microbial eukaryotes could be relevant in microbialites
[57,62], though their diversity has rarely been assessed. The only
available molecular studies, done in Shark Bay and Bahamas
stromatolites [34], detected a very low diversity of eukaryotes
compared to bacteria. However, protist diversity might have been
underestimated with general eukaryotic primers, which lead to
rapid saturation of gene libraries by metazoan sequences,
especially nematodes [34]. Thus, very little is known about protist
contribution to biofilm biodiversity, biomass, structure and
lithification. Here, we avoided gene library saturation by
metazoans using primers biased against animal sequences. Despite
so, we found a low eukaryotic diversity in field microbialites,
corresponding essentially to chlorophytes, with some fungi in the
deepest sample. Therefore, the major eukaryotic players in
Alchichica appear to be green algae, with a same phylotype
(ChlorophytOTU05) dominating along the depth gradient.
Finally, although a variety of physico-chemical parameters were
measured in the water column during sampling as well as
subsequent microbialite mineralogical and isotopic analyses [40],
establishing correlations of these with microbialite microbial
community composition is difficult because of the inherent
heterogeneity of these systems. Microbialites are irregular,
exhibiting different orientations to light at a same depth, and are
spatially structured, offering a variety of niches with different
physico-chemical parameters at microscale. Establishing mean-
ingful correlations between local environmental parameters and
microbial diversity will require further studies at microscale.
Field versus aquaria microbialites
The observation of a large microbial diversity in microbialites
maintained for two years in the laboratory was unexpected for two
reasons. First, only relatively small microbialite fragments were
installed in aquaria, which might not carry individuals of all the
microbial species living in the lake microbialites. Second, since the
laboratory conditions were much more stable (e.g., a remarkably
constant pH, Figure S1), we expected that a few, perhaps
opportunistic, lineages became dominant and excluded the rest
of the native microbial diversity. However, not only the diversity of
most of the abundant lineages found in the lake was maintained,
but bacteria and eukaryotes were much more diverse in laboratory
microbialites (Table 2). Indeed, bacterial communities in aquaria
were, despite their differences, more similar between them than to
the lake samples (Figure 6).
The increase of microbial diversity in aquaria concerns very
diverse groups thriving at pH 8.9. This minimizes the possibility of
potential contaminants coming from the laboratory, which would
be outcompeted by the well-adapted Alchichica alkaliphiles. The
stable conditions in aquaria appear not only to have maintained
organisms dominant in the different field samples, but also favored
the growth of microbes that were in low proportions in the lake.
To our knowledge, there is only another example that compares
the diversity of cultured versus natural microbialites [28].
Although in this case cultured microbialites were artificial (fused
oolitic sand grains inoculated with Bahamian stromatolite
microorganisms), a good preservation of the community compo-
sition after 1.5 years was inferred by comparison of Shannon
indices. These observations suggest a remarkable resilience of
microbialite communities.
Gloeobacterales offer an example of increased diversity and
abundance in aquaria microbialites (Figure 3). These cyanobac-
teria have raised much attention because of their basal position in
phylogenetic trees, being the only group branching before
chloroplasts, and because unusual features such as the lack of
thylakoids and particular photosystems [63,64,65,66,67]. For
many years, the only cultured species was Gloeobacter violaceous,
isolated from calcareous rock [65,68]. More recently, ‘‘Synechococcus
sp. C9’’ was isolated from a mat in Yellowstone alkaline Octopus
spring [63,69]. Several environmental sequences were recently
added to the group, mostly coming from microbial mats or
microbialites, such as the Shark Bay stromatolites [30,33],
suggesting that the whole group may be adapted to this kind of
environments. Our very distant Alchichica sequences encompass
the whole known diversity within this order (Figure 4).
The larger diversity in aquarium microbialites was particularly
manifest in the case of microbial eukaryotes. Whereas a few green
algal phylotypes dominated lake microbialites, cultured micro-
bialites contained those lineages but also a wide variety of other
photosynthetic species, including diatoms and chrysophytes,
diverse other stramenopiles and ciliates (Figure 5) and many
opisthokonts (Figure S13). Possibly, most of these protists were
Figure 5. ML phylogenetic tree of bikont eukaryotic SSU rDNA sequences from Alchichica microbialites. Numbers at nodes indicate
bootstrap values. Sequences from this study are in bold. Numbers of clones retrieved from each sample for each OTU are given on the right. The scale
bar indicates the number of substitutions per site for a unit branch length.
doi:10.1371/journal.pone.0028767.g005
Figure 6. Hierarchical clustering analysis (UPGMA) of bacterial
communities associated to microbialites of various settings
based on pairwise UniFrac metrics. Pairwise comparisons were all
significantly different (p value,0.001).
doi:10.1371/journal.pone.0028767.g006
Alchichica Crater Lake Microbialite Communities
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present in the lake but throve to large, detectable amounts under
stable laboratory conditions. The diversity of opisthokonts was
remarkable. Several fungal lineages were detected in microbialites,
notably members of the Rozellida [70] or Cryptomycota [60],
which constitute the deepest lineage of fungi and groups parasitic
flagellates very common in freshwater systems [71]. The diversity
of choanoflagellates, amoebae, nucleariids, and several divergent
sequences at the base of the Choanoflagellates/Icthyosporea and
at the base of the Metazoa (Figure S13), makes these microbialites
interesting to explore lineages placed at the onset of metazoan
evolution.
Microbial metabolism-based model of microbialite
formation
Taking into account the most likely metabolisms of the
microorganisms detected in field and aquarium microbialites, we
propose to extend the model of formation of microbialites
originally build on marine Bahamian stromatolites [22] to
Alchichica (Figure S14). Microbialite formation would be the net
result of a balance between metabolic activities favoring carbonate
precipitation or dissolution, which would in turn depend on light
availability (day or night) and on local physico-chemical conditions
(e.g. oxic or anoxic microenvironments) [22].
As in the Bahamas case, the most important metabolism
involved is probably bacterial photosynthesis, in particular the
oxygenic photosynthesis carried out by the very abundant
cyanobacteria. Photosynthesis drives the alkalinity engine towards
carbonate precipitation by consuming bicarbonate [22] and
increasing local pH [72,73]. Although much less studied,
eukaryotic photosynthesizers may play a similar role since many
eukaryotic algae induce comparable changes in pH and CO
2
concentration [74]. In addition, eukaryotic algae can provide
nucleation sites [62] and trap particles [75]. Similarly, anoxygenic
photosynthetic bacteria, such as the phototrophic Chloroflexi
likely abundant in Alchichica, also increase local alkalinity and
induce carbonate precipitation [76]. In addition, part of the H
2
S
consumed by anoxygenic photosynthesis may come from the
activity of SRB, represented in Alchichica by Deltaproteobacteria
and Firmicutes. Sulfate reduction generates carbonate ions, thus
being another activity potentially leading to carbonate precipita-
tion [23,24,25,77]. This process, independent of light availability,
can take place during day and night.
Alchichica microbialites also contain diverse and abundant
heterotrophic bacteria, including Planctomycetales, Bacteroidetes,
Acidobacteria, many Proteobacteria and various others. They can
induce carbonate dissolution due to respiration of organic matter
and production of protons [27] but they can also promote
carbonate precipitation by liberating cations sequestered by EPS
and other macromolecules, making them available for precipita-
tion. Indeed, many of these heterotrophs are known to degrade
complex polymeric compounds, including EPS [78]. The balance
between these processes determines the net formation of
carbonate.
Even if the major role in carbonate precipitation and dissolution
is probably due to activities of the largely dominant bacterial
community, the role of eukaryotes should not be neglected.
Photosynthetic algae may have a direct role on carbonate
precipitation and an indirect role associated to chemical properties
of the cell walls that provide nucleation centers for crystal growth
[79,80]. In addition to their photosynthetic activity, diatoms
embedded in the carbonates could be relevant for secondary
silicification since, after death, their frustules supply Si. Finally,
Alchichica fungi, some of which may be endolithic, also deserve
further study. They could make the system more fragile by
forming pervasive microborings but also serve as new calcification
centers [81]. At any rate, protists play an important role as grazers
and predators, exerting a control over bacteria and being involved
in the fine-tuning of the community structure and its activities.
Materials and Methods
Sampling and maintenance of living microbialites in
aquaria
Samples were collected from Lake Alchichica (N 19u25.119; W
97u23.860, Puebla State, Mexico) in July 2007. No specific permits
were required for the described field studies, the location is not
privately-owned or protected and the field studies did not involve
endangered or protected species. Several physico-chemical
parameters were measured in the water column at different
depths including total dissolved solutes, pH, temperature,
concentrations of Cl-, SO
4
22
,Br
2
,F
2
,Na
+
,Mg
2+
,K
+
,Ca
2+
,
Li
+
,O
2
, Si, NO
2
2
,NO
3
2
,PO
4
32
,NH
4
+
, N/P ratios, conduc-
tivity, alkalinity, suspended matter and the saturation index for
several minerals [40]. Similarly, bulk mineralogical and isotopic
(d
13
C and d
18
O) analyses of microbialites at different depths were
carried out [40]. Living microbialite fragments were collected by
scuba diving along a depth gradient from immediately below
surface down to 14 m in depth. Samples for microbiology studies
were picked up with gloves and sterile forceps to minimize all
possible contamination, introduced in Falcon tubes and fixed in
situ in ethanol (80% final concentration). They were kept at room
temperature during transport, then stored at 4uC until processing.
Several larger microbialite fragments (.10 cm) were placed in
sterile plastic containers filled with lake water for transfer to
laboratory aquaria. A layer of small (1 cm) fragments of sub-fossil,
rim Alchichica microbialites was deposited at the bottom of
aquaria in order to buffer the solution pH and chemical
composition. Living microbialite fragments were deposited in
aquarium 1 (AQ1, fragments collected at 30 cm, 3 m and 8 m
depth) and aquarium 2 (AQ2, fragments collected at 80 cm, 1 m
and 6 m depth). Aquaria were illuminated with 15w 210 lumens/
W fluorescent tubes producing solar spectral wavelength. Photo-
periods were adjusted to 12 h of daylight for AQ1 and 16 h of
light for AQ2. Temperature and pH were measured once a month
and water loss due to evaporation replaced by distilled water.
Despite some temperature variation over time for over 3 years
after collection, pH remained remarkably constant at 8.9
(Supplementary Figure S1). The aquarium microbialite samples
collected for molecular analyses were taken from the fragments
from 3 m (AQ1) and 6 m (AQ2) depth.
Optical and confocal laser scanning microscopy
Fresh aquarium microbialite-associated biofilms were examined
using a Zeiss Axioplan 2 optical microscope and photographed
with a Canon PowerShot G5 camera. We also prepared
microbialite inclusions in resin for the observation of transversal
sections using confocal laser scanning microscopy (CLSM). Several
samples were stained with 49,69-diamidino-2-phenylindole or
DAPI (1 mg/ml; 10 minutes at room temperature) and/or calcein
(0.1 mg/ml; 36 h at 4uC) prior to inclusion. Microbialite
fragments were dehydrated in a gradual series of ethanol baths
(30%, 50%, 70%, 90%, and 100%), and progressively impreg-
nated with hard grade LR-white resin (Polysciences, Inc.). Samples
were incubated for 18 h at 4uC in (1/1) then (2/1) mixture of LR-
white/ethanol and finally in pure LR-white resin. After 3 h at
room temperature, samples were embedded in pure LR-white
resin for 1 h at 40uC and then for 24 h at 60uC. After
polymerization, transverse cross-sections were cut with a diamond
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wire and polished (diamond powder Jmm). These sections were
examined using a FluoViewTM FV1000 confocal laser scanning
microscope with a spectral resolution of 2 nm (Olympus). The
FluoViewTM FV1000 was equipped with a 405 nm laser diode,
and multi-line argon (458 nm, 488 nm, and 515 nm), helium-neon-
green (543 nm) and helium-neon-red (633 nm) lasers. Fluorescence
images of the microbialite transversal sections were obtained with
concomitant excitation at wavelengths of 405 nm, 488 nm, and
543 nm and collection of the emitted fluorescence between 425–
475 nm, 500–530 nm, and 560–660 nm, respectively.
DNA purification
Total genomic DNA was extracted 1) from ethanol-fixed field
samples selected along a depth profile in the lake and 2) from
aquaria microbialites 2 years after collection. A small fragment
(,1cm
3
) from each microbialite sample was ground using a sterile
agate mortar. 200 ml of the resulting powder were transferred to
an eppendorf tube. Carbonates were largely dissolved by adding
100 ml of HCl at 33% for 30 s then neutralized with 1 ml of a 1:1
mixture of PBS pH 7 and 0.5 M EDTA pH 9. Samples were
centrifuged for 5 min at 12500 rpm. DNA was extracted from the
pellet using two different methods. In a preliminary assay, DNA
was purified with the QuickPick
TM
gDNA Kit (Bio-Nobile,
Parainen, Finland) following the instructions of the manufacturer
except that samples were previously incubated for 3 h at 56uC
with 0,5 ml of Proteinase K extra (20 mg/ml) and 1,5 mlof
ViscozymeH. In a second assay DNA was purified using the
MoBioPowerSoil DNA kit (MoBio, Carlsbad, CA, USA) after a
first incubation step with 2 ml of ViscozymeH(Sigma-Aldrich,
Buchs, Switzerland) (1 h at 37uC) in order to enhance degradation
of the abundant exopolymeric substances. According to prelimi-
nary tests (data not shown), the second protocol produced a better
extraction yield and was thus applied on every sample selected
along the depth gradient. However, we include in the present
study the results of libraries constructed using DNA purified with
the first method as replicates. Libraries constructed using DNA
purified by the first method were labeled Library 1; those made
with the second one are labeled Library 2.
Denaturing gel gradient electrophoresis (DGGE) analysis
SSU rDNA fragments of approximately 150 bp were amplified
from DNA purified from different microbialite samples using the
MoBio kit with the specific bacterial forward primer 341F-
GCclamp (CGCCCGCCGCGCGCGGCGGGCGGGGCGGG-
GGCACGGGGGG CCTACGGGAGGCAGCAG) and the re-
verse bacterial primer 543R (ATTACCGCGGCTGCTGG) [82].
Polymerase chain reactions (PCR) were performed under the
following conditions: an initial denaturation step at 94uC for
3 min, 30 cycles consisting of a denaturation step at 94uC for 15 s,
an annealing step of 30 s (a touch down procedure with a
decreasing annealing temperature from 65uCto55uC for the 10
first cycles was applied followed by a hybridization temperature of
55uC for the following 20 cycles) and a polymerization step at
72uC for 1.5 min, and a final step of 1 h extension at 72uC
(modified from [82]). Migration of PCR products was done in a
denaturing gradient gel using the CBS Scientific (California, USA)
electrophoresis system. Urea and formamide were used as
denaturing agents with a concentration gradient from 30% to
60%. 50 bp-ladder markers (Promega, Lyon, France) were
intercalated every three samples. The gels were stained with
SYBR Gold (Invitrogen, Carlsbad, CA, USA) and photographed
under UV light. Gels were normalized according to the ladder
migration using the software BionumericsH(AppliedMaths, Sint-
Martens-Latem, Belgium). A distance matrix based on the
presence/absence of bands in the different samples was used for
cluster analysis of samples using the Jaccard coefficient [83].
Small subunit rRNA gene library construction
We constructed SSU rDNA libraries specific for archaea,
bacteria, cyanobacteria and microbial eukaryotes from five
selected samples: three field samples from three different depths
AL31 (0.5 m), AL67 (3 m), AL52 (14 m) and two samples from the
two aquaria. Samples from aquarium microbialites used in this
study were collected after 17 months (Libraries 1) and 27 months
(Libraries 2). To amplify SSU rDNA, the following sets of specific
primers were used: B-27F (AGAGTTTGATCCTGGCTCAG)
and 1492R (GGTTACCTTGTTACGACTT) for bacteria;
CYA106F (CGGACGGGTGAGTAACGCGTGA) [44] and
23S30R (CTTCGCCTCTGTGTGCCTAGGT) for cyanobacte-
ria; Ar109 (AC(G/T)GCTGCTCAGTAACACGT) and 1492R
for archaea and 82F (GAAACTGCGAATGGCTC) and UN-
onMet (TTTAAGTTTCAGCCTTGCG) for non-metazoan eu-
karyotes [58]. PCR reactions were performed under the following
conditions: 30 cycles (denaturation at 94uC for 15 s, annealing at
50–55uC for 30 s, extension at 72uC for 2 min) preceded by 2 min
denaturation at 94uC, and followed by 7 min extension at 72uC.
Clone libraries were constructed using the TopoTA cloning kit
(Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s
instructions. Clone inserts were partially sequenced (,800 bp) by
Beckman Coulter Genomics (Takeley, United Kingdom) using
first the reverse primer 1492R for bacteria (including cyanobac-
teria) and archaea and the forward primer 82F for eukaryotes. At
least one representative clone per phylotype or Operational
Taxonomic Unit (OTU, group of sequences sharing .97%
identity) was fully sequenced for detailed phylogenetic analysis.
Sequences were deposited in GenBank with accession numbers
JN825302–JN825705.
Phylogenetic analyses
A total of 1143 bacterial clones excluding cyanobacteria
amplified with specific cyanobacterial primers, 526 cyanobacterial
clones (in addition to cyanobacterial clones retrieved with general
bacterial primers) and 598 eukaryotic clones were analyzed. The
closest relatives to these sequences were identified by BLAST
[84,85] and retrieved from GenBank (http://ncbi.nlm.nih.gov/).
Several datasets (one for each life domain and one specific for
cyanobacteria) were constructed and aligned using MAFFT [86].
A preliminary phylogenetic analysis of all partial sequences was
done by distance methods (neighbor-joining, NJ), allowing the
identification of identical or nearly identical sequences and the
selection of representative clones for subsequent analysis. The
multiple alignment was then manually edited using the program
ED from the MUST package [87]. Final phylogenetic trees
included our sequences together with their closest relatives in
GenBank and some representative cultivated species. Maximum
likelihood (ML) phylogenetic trees were reconstructed using
TREEFINDER [88] applying a general time reversible (GTR)
model of sequence evolution, and taking among-site rate variation
into account by using a four-category discrete approximation of a
Cdistribution. Maximum likelihood bootstrap proportions were
inferred using 1,000 replicates. Phylogenetic trees were viewed
using FIGTREE [89].
Estimates of microbial diversity and community
comparison analyses
Distance matrices were generated for each clone library using
ClustalX software [90]. They were used as input for the software
Alchichica Crater Lake Microbialite Communities
PLoS ONE | www.plosone.org 13 December 2011 | Volume 6 | Issue 12 | e28767
DOTUR [91], which was used to cluster sequences in OTUs using
an identity cut-off of 0.03. Richness estimations (Chao1 and Ace)
were calculated using DOTUR with default settings. Coverage
values were calculated using the Good estimator [92] following the
equation C = (12n/N)6100, where C is the percentage of
coverage of the library, n the number of singletons and N the
total number of clones examined. To compare the composition of
bacterial communities associated to Alchichica microbialites with
those associated to Bahamas [31] and Shark Bay [29] stromatolites
as well as to the alcaline Lake Van microbialites [13], we
recovered the SSU rDNA bacterial sequences from those studies
and constructed an alignment containing 3040 sequences using
MAFFT [86]. We then constructed an approximately maximum
likelihood phylogenetic tree based on 338 unambiguously aligned
positions using FastTree [93]. We then compared ß-diversity
measurements and obtained pairwise p-values using UniFrac [94]
as implemented in the software MOTHUR [95].
Supporting Information
Figure S1 Alchichica microbialites maintained in laboratory
aquaria. A. Initial setting of microbialites fragments in aquaria
with different photoperiods. B. Microbialites after one year of
cultivation in aquaria. C. Measurements of pH and temperature
over time. Orange symbols (aquarium 1); blue symbols, aquarium
2. Red bars indicate points at which aquaria were sampled for the
clone Library 1 and Library 2 construction of the present study.
(TIF)
Figure S2 Cluster analysis of DGGE fingerprints of bacteria
associated to Alchichica microbialites. The name and depth of
each sample are given on the right. AQ1 and AQ2 correspond to
samples from laboratory aquaria. The scale bar above the
dendrogram shows distances (%) between samples based on
presence/absence of bands. Grey bars at nodes indicate the
standard deviation. Bands labeled with capital letters were cut for
sequencing. Samples labeled with an asterisk were chosen for
detailed molecular diversity analyses.
(TIF)
Figure S3 Maximum likelihood (ML) phylogenetic tree of
alphaproteobacterial SSU rDNAs from Alchichica microbialites.
Numbers at nodes indicate bootstrap values. Sequences from this
study are in bold. Relative proportions of the different OTUs in
each sample are indicated by circles of proportional size on the
right. The number (n) indicates the number total of clone analyzed
for each sample. The scale bar indicates the number of
substitutions per site for a unit branch length.
(TIF)
Figure S4 Maximum likelihood (ML) phylogenetic tree of SSU
rDNA sequences of Deltaproteobacteria and Gammaproteobac-
teria from Alchichica microbialites. Numbers at nodes indicate
bootstrap values. Sequences from this study are in bold. Numbers
of clones retrieved from each sample for each OTU are given on
the right. The scale bar indicates the number of substitutions per
site for a unit branch length.
(TIF)
Figure S5 Maximum likelihood phylogenetic tree of SSU rDNA
sequences of Chloroflexi and Chlorobi from Alchichica micro-
bialites. Numbers at nodes indicate bootstrap values. Sequences
from this study are in bold. Numbers of clones retrieved from each
sample for each OTU are given on the right. Asterisks indicate
OTUs also identified in DGGE patterns. The scale bar indicates
the number of substitutions per site for a unit branch length.
(TIF)
Figure S6 Maximum likelihood (ML) phylogenetic tree of SSU
rDNA sequences of Gemmatimonadetes and Acidobacteria from
Alchichica microbialites. Numbers at nodes indicate bootstrap
values. Sequences from this study are in bold. Numbers of clones
retrieved from each sample for each OTU are given on the right.
The scale bar indicates the number of substitutions per site for a
unit branch length.
(TIF)
Figure S7 Maximum likelihood (ML) phylogenetic tree of SSU
rDNA sequences of Betaproteobacteria from Alchichica micro-
bialites. Numbers at nodes indicate bootstrap values. Sequences
from this study are in bold. Numbers of clones retrieved from each
sample for each OTU are given on the right. The scale bar
indicates the number of substitutions per site for a unit branch
length.
(TIF)
Figure S8 Maximum likelihood (ML) phylogenetic tree of SSU
rDNA sequences of Planctomycetales and Verrucomicrobia from
Alchichica microbialites. Numbers at nodes indicate bootstrap
values. Sequences from this study are in bold. Numbers of clones
retrieved from each sample for each OTU are given on the right.
The scale bar indicates the number of substitutions per site for a
unit branch length.
(TIF)
Figure S9 Maximum likelihood (ML) phylogenetic tree of SSU
rDNA sequences of Bacteroidetes from Alchichica microbialites.
Numbers at nodes indicate bootstrap values. Sequences from this
study are in bold. Numbers of clones retrieved from each sample
for each OTU are given on the right. Asterisks indicate OTUs also
identified in DGGE patterns. The scale bar indicates the number
of substitutions per site for a unit branch length.
(TIF)
Figure S10 Maximum likelihood (ML) phylogenetic tree of SSU
rDNA sequences of Actinobacteria and Firmicutes from Alchi-
chica microbialites. Numbers at nodes indicate bootstrap values.
Sequences from this study are in bold. Numbers of clones retrieved
from each sample for each OTU are given on the right. Asterisks
indicate OTUs also identified in DGGE patterns. The scale bar
indicates the number of substitutions per site for a unit branch
length.
(TIF)
Figure S11 Maximum likelihood (ML) phylogenetic tree of SSU
rDNA sequences of CD OP11, CD WS6, Deinoccocus-Thermus,
CD SBR1, CD BRC1, CD NKB19, Nitrospira, CD TM6, CD
OP3 and Spirochaeta from Alchichica microbialites. Numbers at
nodes indicate bootstrap values. Sequences from this study are in
bold. Numbers of clones retrieved from each sample for each
OTU are given on the right. The scale bar indicates the number of
substitutions per site for a unit branch length.
(TIF)
Figure S12 Maximum likelihood (ML) phylogenetic tree of SSU
rDNA sequences of Archaea from Alchichica microbialites.
Numbers at nodes indicate bootstrap values. Sequences from this
study are in bold. Numbers of clones retrieved from each sample
for each OTU are given in brackets. The scale bar indicates the
number of substitutions per site for a unit branch length.
(TIF)
Figure S13 Maximum likelihood (ML) phylogenetic tree of SSU
rDNA sequences of Unikonts (Amoebozoa plus Opisthokonta)
from Alchichica microbialites. Numbers at nodes indicate
bootstrap values. Numbers of clones retrieved from each sample
Alchichica Crater Lake Microbialite Communities
PLoS ONE | www.plosone.org 14 December 2011 | Volume 6 | Issue 12 | e28767
for each OTU are given on the right. The scale bar indicates the
number of substitutions per site for a unit branch length.
(TIF)
Figure S14 Hypothetical model of carbonate formation dynam-
ics based on known metabolisms of microbial lineages detected in
Alchichica microbialites. The panels represent the activities that
would occur during day (left) and; night (right) in areas where
oxygenic (upper panels) or anoxygenic (lower panels) photosyn-
thesis predominates.
(TIF)
Acknowledgments
We thank warmly B. Kramer (Foundation for Polish Science) for her role
in co-organizing the 2007 Alchichica Lake expedition. We also thank S.
Kempe and H.V. Henschel for their participation to our sampling
expedition.
Author Contributions
Conceived and designed the experiments: PL-G DM KB. Performed the
experiments: EC EG. Analyzed the data: EC PL-G DM. Contributed
reagents/materials/analysis tools: PL-G KB. Wrote the paper: EC PL-G
DM KB. Field work: PL-G DM JK RT.
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