RESEARCH ARTICLE , Valme Jurado & Lejla Pasˇic´ et al 2012.pdf · (Fermentas), primers 27F...

R E S EA RCH AR T I C L E

Comparative analysis of yellow microbial communities growingon the walls of geographically distinct caves indicates a

common core of microorganisms involved in their formation

Estefania Porca1, Valme Jurado1, Darja Zgur-Bertok2, Cesareo Saiz-Jimenez1 & Lejla Pasic2

1Instituto de Recursos Naturales y Agrobiologia, IRNAS-CSIC, Seville, Spain; and 2Department of Biology, Biotechnical Faculty, University of

Ljubljana, Ljubljana, Slovenia

Correspondence: Lejla Pasic, Department of

Biology, Biotechnical Faculty, University of

Ljubljana, Vecna pot 111, 1000 Ljubljana,

Slovenia. Tel.: +386 1 320 33 88; fax:

+386 1 257 33 90; e-mail:

[email protected], [email protected]

Received 14 October 2011; revised 21 March

2012; accepted 2 April 2012.

Final version published online 27 April 2012.

DOI: 10.1111/j.1574-6941.2012.01383.x

Editor: Christian Griebler

Keywords

hypogean environments; 16S rRNA gene;

diversity; Bacteria; yellow microbial

communities; cave.

Abstract

Morphologically similar microbial communities that often form on the walls of

geographically distinct limestone caves have not yet been comparatively stud-

ied. Here, we analysed phylotype distribution in yellow microbial community

samples obtained from the walls of distinct caves located in Spain, Czech

Republic and Slovenia. To infer the level of similarity in microbial community

membership, we analysed inserts of 474 16S rRNA gene clones and compared

those using statistical tools. The results show that the microbial communities

under investigation are composed solely of Bacteria. The obtained phylotypes

formed three distinct groups of operational taxonomic units (OTUs). About

60% of obtained sequences formed three core OTUs common to all three sam-

pling sites. These were affiliated with actinobacterial Pseudonocardinae (30–50%of sequences in individual sampling site libraries), but also with gammaproteo-

bacterial Chromatiales (6–25%) and Xanthomonadales (0.5–2.0%). Another 7%

of sequences were common to two sampling sites and formed eight OTUs,

while the remaining 35% were site specific and corresponded mostly to OTUs

containing single sequences. The same pattern was observed when these data

were compared with sequence data available from similar studies. This compar-

ison showed that distinct limestone caves support microbial communities com-

posed mostly of phylotypes common to all sampling sites.

Introduction

Visible microbial communities often develop in karstic

caves. They can be observed both near the cave entrance

and in completely dark regions of the cave but never in

areas submerged in water. The communities first develop

on cave walls as distinct millimetre-sized spots, which can

be white, yellow, grey or pink in colour. In some caves,

this growth can become extensive and thin (up to 1 mm)

coatings, which resemble biofilm cover areas of carbonate

or clay-coated walls and ceilings ranging to up to several

square metres in size. Early studies on these microbial

communities focused on show caves in Spain, mainly on

the Altamira Cave, where their progressive development

caused biodeterioration of Palaeolithic paintings of cul-

tural value (Groth et al., 1999; Schabereiter-Gurtner

et al., 2002; Saiz-Jimenez et al., 2011).

Over the years, the cultivation efforts yielded substan-

tial taxonomical novelty (e.g. Jurado et al., 2006, 2008,

2009), but failed to identify the community structure.

Further insight into the microbial community composi-

tion was obtained when the spots containing either one

or several morphologies were analysed by DGGE finger-

printing and comparative phylogenetic 16S rRNA gene

analysis (Schabereiter-Gurtner et al., 2004; Portillo et al.,

2008, 2009). Most recently, an independent 16S rRNA

gene study reported the microbial diversity in multicol-

oured community developing in a cave in Slovenia (Pasic

et al., 2010). Although these studies have shown the

extent of microbial diversity in these subterranean com-

munities, they are not comparable as they differ in the

methodology used and are focused on one sampling site.

Thus, in the exploratory study presented here, the same

methodology was used to analyse microbial communities

FEMS Microbiol Ecol 81 (2012) 255–266 ª 2012 Federation of European Microbiological SocietiesPublished by Blackwell Publishing Ltd. All rights reserved

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similar in morphology, yet developing on the walls of

three selected European limestone caves. The selected

caves were geographically distinct and were Altamira in

Spain, Sloup-sosuvka caves in Czech Republic and

Pajsarjeva jama in Slovenia. We chose to study cave-wall

microbial communities that resemble yellow-coloured

spots as these were frequently observed in the studied

caves and their distribution pattern appears to be influ-

enced by nutrient availability. In Altamira Cave, these

communities are committed to the transitional area

between epigean and hypogean environment, and their

numbers tend to subside in the inner parts of the cave,

where rarely any spots are observed (Cuezva et al., 2009;

Saiz-Jimenez et al., 2011). The other two caves studied

receive substantial amounts of organic material through

flooding of subterranean river and from the adjacent for-

ests. Here, the yellow microbial communities can also be

observed in inner parts of the cave, especially in areas

where the organic material has been deposited through

dripping or as clay. At all sampling sites, we noted that

the microbial communities act as water condensation

points that retain absorbed vapour for long periods of

time. The water droplets on the individual spotsurface

reflect the gold-coloured light when illuminated in a

characteristic fashion.

At each sampling site, we aimed to (1) describe the

composition of microbial community and (2) define

major phylogenetic groups present in order to (3) deter-

mine the ratio of shared vs. site-specific phylotypes. To

answer these questions, we used phylogenetic analysis of

environmental 16S rRNA gene sequences obtained from

site-specific clone libraries. To determine the similarities

and the differences between the communities studied, the

sequence information in individual clone libraries was

further compared using currently available statistical

tools. The latter analysis also included sequence data

available from previous studies with similar methodology.

The obtained results point towards a common core of

microorganisms involved in the formation of yellow

microbial communities on cave walls and ceiling.

Materials and methods

Sample collection

Samples of macroscopic yellow spots were collected from

the Altamira Cave, Spain, Sloup-sosuvka caves, Czech

Republic, and Pajsarjeva jama, Slovenia, between 2009

and 2010.

Altamira Cave, Santillana del Mar, Spain (43°22′40″N,4°7′58″E), is, perhaps, one of the world’s best-studied

caves (Cuezva et al., 2009; Saiz-Jimenez et al., 2011), and

its microclimatic parameters are registered continuously.

The yellow microbial communities are located mainly in

the entrance hall, so-called Kitchen Hall, which receives a

direct input of organic matter and aerosols from the exte-

rior. There, the temperature ranges between 12.9 and

17.2 °C, relative humidity between 92% and 100% and

aerial CO2 concentration between 360 and 4660 μg g−1

(Cuezva et al., 2009). [Correction added after online pub-

lication 1 May 2012: μg mL−1 changed to μg g−1].

Sloup-sosuvka caves (49°24′37.72″N, 16°44′19.74″E),located in the Moravian Karst, not far from Brno, Czech

Republic, are constituted by a large complex of under-

ground domes, corridors and chasms created in two lev-

els. These caves are situated 470 m above sea level and

are eutrophicated owing to the presence of bat colonies

and the flooding of a subterranean river. The average

temperature is 8.7 °C.Pajsarjeva jama, 20 km south-west of Ljubljana, Slove-

nia (45°49′51″N, 14°16′15″E), is 555 m long and contains

a small stream exiting the underground at its entrance. It

is only occasionally visited by cavers and speleologists,

but pipes of a water supply for the small fish hatchery are

inserted into it (Pasic et al., 2010). The cave has modest

bat colonies, and it is also eutrophicated. The air temper-

ature, which is relatively constant all year round, was

12.0 °C, and the relative humidity was 100%.

The samples were taken by scraping off spots with a

sterile scalpel without touching the supporting rocks.

Upon collection, the samples were stored on ice and pro-

cessed or frozen within 2 h after collection.

DNA extraction, PCR amplification of 16S rRNA,

cloning and sequencing

Environmental DNA was extracted from samples taken

from Altamira Cave and Sloup-sosuvka caves using Fast-

DNA® SPIN Kit for Soil (QBiogene). For the extraction

of environmental DNA from Pajsarjeva jama cave, MoBio

PowerSoilTM DNA kit (MoBio) was used. Amplifications

of bacterial 16S rRNA gene were performed using respec-

tive environmental DNA templates, Taq DNA polymerase

(Fermentas), primers 27F (5′-AGA GTT TGA TCC TGG

CTC AG-3′), 1492R (5′-GGT TAC CTT GTT ACG ACT

T-3′) and the following programme: 94 °C (5 min), fol-

lowed by 25 cycles of 94 °C (1 min), 45 °C (45 s), 72 °C(1 min) and a 20-min extension step at 72 °C. Amplifica-

tions of archaeal 16S rRNA gene were attempted using

primers Arch21F (5′-TTC CGG TTG ATC CYG CCG

GA) and Arch958R (5′-YCC GGC GTT GAM TCC AAT

T) following the protocol described by DeLong (1992).

Amplifications of the 18S rRNA gene were attempted

using the primers EukA (5′-AAC CTG GTT GAT CCT

GCC AGT) and EukB (5′-TGA TCC TTC TGC AGG

TTC ACC TAC) from the study of Diez et al. (2001) fol-

ª 2012 Federation of European Microbiological Societies FEMS Microbiol Ecol 81 (2012) 255–266Published by Blackwell Publishing Ltd. All rights reserved

256 E. Porca et al.

lowing the protocol described by Jurado et al. (2009).

Amplifications of fungal internal transcribed spacer (ITS)

regions were attempted using forward primers ITS1

(5′-TCC GTA GGT GAA CCT GCG G), ITS1F (5′-CTTGGT CAT TTA GAG GAA GTA A-3′) and ITS5 (5′-GGAAGT AAA AGT CGT AAC AAGG-3′) and reverse primer

ITS4 (5′-TCC TCC GCT TAT TGA TAT GC-3′) as

described previously (White et al., 1990; Gardes & Bruns,

1993). Each 50-lL reaction mixture contained 10 ng of

extracted environmental DNA, 2.5 U Taq DNA polymer-

ase (Fermentas), 19 Taq polymerase buffer, 1 mM

MgCl2, 0.2 mM deoxyribonucleotide phosphate and

0.1 lM of each primer. Positive and negative controls

were included in all amplification experiments.

A 16S rRNA gene library was prepared as follows: ampli-

fied rRNA products of an individual PCR reaction were

excised from the gel, purified using Qiaquick Gel Extraction

Kit (Qiagene), cloned using the pGEM®-T Easy Cloning

Kit (Promega) and used to transform competent Escherichia

coli JM109 cells (Promega) according to manufacturers’

instructions. Insert-positive clones were picked and trans-

ferred to multiwell plates containing Luria–Bertani medium

supplemented with 100 lg mL�1 ampicillin and 15% w/v

glycerol and were stored at �80 °C. We constructed nine

clone libraries, three for each sample collected. Each library

contained an average of 3000 clones. Sequencing of 64

clones randomly selected from each library prepared was

performed at Macrogen Inc. (Seoul, Korea) using universal

bacterial primers 27F and 1492R.

Sequence processing

Sequences shorter than 750 bp and with average quality

values below 20 were removed from the data set. Putative

chimeric sequences were identified using chimera.slayer

as implemented in MOTHUR (Schloss et al., 2009). The

final data set contained 474 sequences and was compared

to three different sequence databases. These were Gen-

Bank (http://www.ncbi.nlm.nih.gov, BLASTN algorithm),

GREENGENES (http://greengenes.lbl.gov, ‘Compare’ tool)

and the Ribosomal Database Project (http://rdp.cme.msu.

edu/, ‘Classifier’ tool). The sequences were then affiliated

with a phylum if the sequence identity was > 90% over

the alignment length of > 600 bp in different databases

searched.

For phylogenetic tree reconstruction, alignment of rep-

resentative clone sequences and related sequences

obtained from databases was generated by MUSCLE (Edgar,

2004), and its quality was checked by CORE available

from T-COFFEE web server (http://tcoffee.vital-it.ch/

cgi-bin/Tcoffee/tcoffee_cgi/index.cgi). Gaps and ambiguously

aligned positions were excluded. This data set was analy-

sed by maximum likelihood (ML) by applying a general

time-reversible model (GTR) of sequence evolution and

taking among-site variation into account using a four-

category discrete approximation of a Γ distribution with

a portion of invariable sites using MEGA (Tamura et al.,

2011). ML bootstrap support values were assessed by

1000 bootstrap replications.

Operational taxonomic unit (OTU)-based

sequence analysis

We used MOTHUR (Schloss et al., 2009) to define OTUs,

calculate diversity indices and generate rarefaction curves.

To this aim, the clone sequences were aligned to Silva-

based template alignment (available from http://

www.mothur.org/wiki/Silva_reference_alignment), and the

uncorrected pairwise distances between aligned sequences

were calculated. Then, the OTUs were defined using the

furthest neighbour-clustering algorithm at evolutionary

distances of 3%, 5% and 20%. Total richness of the sam-

ple was extrapolated from the observed OTUs with three

nonparametric estimators: Jackknife (Burnham & Over-

ton, 1978, 1979), ACE (Chao et al., 1993) and Chao 1

(Chao, 1984).

Statistical comparisons of the clone libraries

We assessed the probability that the sampled communities

have the same structure by chance using MOTHUR (Schloss

et al., 2009). To this aim, we used the integral form of

Cramer-von Mises test statistics implemented in ∫-Libshuff(Schloss et al., 2004) and estimated homogeneity of

molecular variance (HOMOVA). HOMOVA is a nonpara-

metric analogue of Bartlett’s test for homogeneity of vari-

ance, which has been used in population genetics to test

the hypothesis that the genetic diversity within two or

more populations is homogeneous (Schloss, 2008). With

an experimentwise error rate of 0.05 and taking into

account a Bonferroni’s correction for multiple compari-

sons, the libraries were considered significantly different if

the P value was < 0.0013 (HOMOVA) or if either of the

two P values generated for an individual pairwise compar-

ison was lower than 0.0007 (∫-Libshuff). We further com-

pared our data with data obtained in a study on yellow

microbial mat growing on lava tube walls in Hawai’i

(USA) and Azores (Portugal) (Northup et al., 2011); clone

library sequences obtained in a study of multicoloured

microbial community growing on the walls of Pajsarjeva

jama in Slovenia (Pasic et al., 2010); and 23 DGGE

sequences obtained from yellow spots growing on the

walls of Altamira cave in Spain (Portillo et al., 2008). The

GenBank accession numbers were HM445833–HM445541,

HM545238; FJ535064–FJ535113, AY960218–AY960221,AY960224, AY960225, AY960228–AY960231, AY960233,


Comparative analysis of cave-wall microbial communities 257

AY960234, AY960236, AY960248–AY960250, AY960253,

AY255254, AY960256–AY960258, AY960269 and

AY960272. In ∫-Libshuff comparisons, our libraries were

considered significantly different from those constructed

from lava tube and Pajsarjeva jama environmental DNA,

if the P value was < 0.0006 and 0.0125, respectively. We

also compared community structure by accounting for

OTU abundance and estimated OTUs specific to one

library or shared by two or more libraries. This allowed us

to distinguish the shared OTUs and the number of

sequences in each OTU.

The sequences obtained in this study were deposited in

the EMBL databank under accession numbers HE602782–HE602931.

Results and discussion

Statistical comparisons of clone libraries

To determine the reproducibility of the methods, the ori-

ginal samples were collected in triplicate. These were trea-

ted as different samples from the DNA extraction step to

sequencing and sequence analysis. Environmental DNA

extracted from these samples was used as a template in

amplifications of SSU rDNAs of bacterial, archaeal, fungal

and other Eukaryota origin. However, only 16S rRNA

gene amplifications involving Bacteria-specific primers

were successful, and these fragments were then used in

the preparation of clone libraries. Thus, nine gene

libraries were constructed, and a total of 474 high-quality

partial (� 800 bp) 16S rRNA gene sequences were

obtained upon removal of chimeric sequences. The simi-

larity between libraries was estimated in terms of similar-

ity in microbial community membership using ∫-Libshuffanalysis (Schloss et al., 2004; Schloss, 2008) and in terms

of similarity of microbial community structure using

HOMOVA (Schloss, 2008).

In libraries built in parallel, ∫-Libshuff analysis found

significant probability that the closest relative of each

sequence is from the same community (P > 0.05,

Table 1). In fact, ∫-Libshuff analysis found only two of

the nine libraries constructed to support microbial com-

munities differing in membership. These corresponded to

two individual libraries constructed from environmental

DNA obtained from Slovenian and Czech Republic sam-

ples. Likewise, HOMOVA indicated that the structure of

microbial community was not the same in all nine

libraries studied (Table 1) and differed in libraries con-

structed from Czech Republic samples. The observed dif-

ferences could perhaps be attributed to a difference in

methodologies used to obtain environmental DNA (see

Materials and methods). The latter were recently reported

Table 1. ∫-LIBSHUFF and HOMOVA comparisons of clone libraries constructed in this study

Sample

Clone

library no.

Altamira Cave (Spain)

Sloup-sosuvka caves

(Czech Republic) Pajsarjeva jama (Slovenia)

1 2 3 1 2 3 1 2 3

∫-LIBSHUFFAltamira Cave (Spain) 1 0 0.0622 0.0719 0.0256 0.0017 0.0072 0.0184 0.0409 0.0121

2 0.8532 0 0.7874 0.7093 0.1243 0.0138 0.1504 0.0854 0.0723

3 0.7926 0.5051 0 0.9014 0.4902 0.1696 0.533 0.2923 0.7742

Sloupsko-sosuvske

(Czech Republic)

1 0.0200 0.4655 0.0221 0 0.5885 0.0194 0.0044 0.0821 0.0982

2 0.0026 0.0259 0.0136 0.4993 0 0.0926 0.0034 0.0194 0.012

3 0.2450 0.1292 0.2323 0.9839 0.7324 0 0.3852 0.1243 0.0797

Pajsarjeva jama (Slovenia) 1 0.0670 0.0313 0.1796 0.2953 0.0012 0.0022 0 0.5023 0.3143

2 0.0576 0.0195 0.3655 0.6036 0.0030 0.0005 0.5574 0 0.0933

3 0.4539 0.4332 0.2104 0.6586 0.1640 0.0307 0.1833 0.2810 0

HOMOVA

Altamira Cave (Spain) 1 0

2 0.7200 0

3 0.1620 0.1890 0

Sloup-sosuvka caves

(Czech Republic)

1 0.0010 0.0010 0.0390 0

2 0.4170 0.2580 0.3300 0.0010 0

3 0.6820 0.8870 0.0600 < 0.0010 0.2200 0

Pajsarjeva jama (Slovenia) 1 0.0200 0.0300 0.6020 0.0840 0.1400 0.0120 0

2 0.0070 0.0190 0.3040 0.1510 0.0360 0.0020 0.6150 0

3 0.0080 0.0230 0.1860 0.4010 0.0230 0.0050 0.3180 0.5870 0

With an experiment wise error rate of 0.05 and taking into account a Bonferroni’s correction for multiple comparisons, the libraries were consid-

ered significantly different (marked in bold) if the P value was inferior to 0.0013 (HOMOVA) or if either of the two P values generated for an indi-

vidual pairwise comparison was lower than 0.0007 (∫-Libshuff).


258 E. Porca et al.

as unable to provide a uniform and unbiased subsample

of environmental DNA from soil-related samples

(Delmont et al., 2011). The fact that there was significant

probability that the libraries built in parallel originate

from the same population (regardless of how well they

represent the population in terms of community struc-

ture) allowed us to pull site-specific sequence data

together and further consider them as three separate sam-

ples. However, we kept in mind that the community

structure as depicted by the analysis of samples taken in

Czech Republic might be biased.

Evaluation of diversity coverage and richness

of the clone libraries

To evaluate the level of information contained in differ-

ent libraries constructed, several approaches were used.

We compared OTU richness in different samples using

Shannon and Simpson indices. The value of Shannon

index increases with species evenness and richness (Shan-

non & Weaver, 1949). The values of Simpson index,

which measures diversity while taking into account the

number of species present and their relative abundance,

range from 0 to 1, with 0 representing infinite diversity

and 1 no diversity (Simpson, 1949). Both indices indi-

cated that at an evolutionary distance of 3%, a rough

approximation of the species, the microbial diversity

encountered was highest in Slovenian sample and was fol-

lowed by diversity encountered in samples taken from

caves in Czech Republic and Spain (Table 2). Then, we

estimated the total number of OTUs in each sample

through nonparametric Jackknife but also Chao 1 and

ACE estimators, which are sensitive to the number of

phylotypes observed only once (Table 2). The estimated

total numbers of OTUs were much higher than the

observed number of OTUs, indicating that additional

sampling would have showed additional diversity. The

same trend was observed when rarefaction and collector

curves were calculated as no stationarity was reached at

levels below phylum, approximated by an evolutionary

distance of 20% (Fig. 1).

The distribution of 16S rRNA gene clone

sequences among different phyla

The distribution of different phyla among the three caves

sampled is summarized in Fig. 2. Only two major phylo-

genetic groups were encountered in clone libraries

obtained. These were Actinobacteria and Gammaproteo-

bacteria. These represented up to 75% of analysed

sequences. The relative proportions of these sequences

varied among different sampling sites. Besides, all sam-

ples supported members of Acidobacteria, Alphaproteobac-

teria and Planctomycetales. These were found in small

proportions and generally represented < 5% of the

sequences sampled. Furthermore, members of Bacteroide-

tes, Betaproteobacteria, Chloroflexi, Deltaproteobacteria,

Firmicutes, Gammaproteobacteria, Nitrospirae and Ver-

rucomicrobia were observed in similar frequencies yet

were not necessarily present in all cave samples studied.

We also recovered sequences affiliated with candidate

phyla Elusimicrobia (formerly Termite group 1), NC10

(originating from flooded Nullarbor caves in Australia),

OP3, SBR1093, SM2F11, ZB2 and ZB3. We refer to these

sequences as ‘minor groups’ as they represented less than

1% of respective library sample.

Comparisons of libraries based on OTU

clustering

To cluster sequences into OTUs and to distinguish

between the shared and sample-specific OTUs, all

sequence data were pooled together and analysed using

MOTHUR. At the approximate species level (evolutionary

distance of 3%), the analysed sequences formed 139

OTUs. These could be divided into three categories: (1)

core OTUs shared by all three sampling sites, (2) OTUs

shared by two sampling sites and (3) site-specific OTUs.

The distribution of these three types of OTUs was similar

within the individual sampling sites (Fig. 3). The core of

each sampled community was represented by only

three OTUs, which, in turn, represented a vast majority

(54–65%) of individual sampling site sequences. Further

Table 2. Comparison of diversity estimators and coverage for cave-wall microbial community 16S rRNA libraries constructed in this study

Cave

No. of

OTUs

No. of

sequences

Richness estimation*

ACE Chao 1 Shannon Simpson

Altamira Cave (Spain) 42 163 291 (151–620) 172 (97–360) 2.16 (1.84–2.47) 0.35

Sloup-sosuvka caves

(Czech Republic)

46 157 140 (85–272) 233 (110–592) 2.62 (2.37–2.89) 0.16

Pajsarjeva jama

(Slovenia)

54 154 370 (184–821) 291 (142–685) 2.79 (2.51–3.06) 0.15

*Values in parentheses are the 95% confidence intervals.



eight OTUs were shared among two of three sampling

sites and represented 4–9% of individual sample site

sequences. The proportion of site-specific OTUs was the

largest as they represented 70–80% of all OTUs. However,

the relative proportion of these sequences in an individual

sample was much lower (20–27% of analysed sequences).

Fig. 1. Rarefaction curves (a) and Chao 1 richness estimator collector’s curves (b) for Altamira Cave (Spain), Sloup-sosuvka caves (Czech

Republic) and Pajsarjeva jama (Slovenia) microbial communities on yellow spots. Rarefaction curves (a) and Chao 1 richness estimator collector’s

curves have been calculated at evolutionary distances of 0%, 3%, 5% and 20%.


260 E. Porca et al.

The vast majority (84%) of these OTUs contained single

sequences.

To study the differences between individual groups of

OTUs, the representative sequences were subjected to

phylogenetic analysis (Fig. 4a, Table 3). The relative

abundance of shared OTUs is represented in Fig. 4b. The

most abundant of three core OTUs, called OTU III,

represented 30–50% of obtained sequences and was

related to Actinobacteria, more precisely to the suborder

Pseudonocardinae. On the phylogenetic tree, OTU III

representative sequence branched independently from the

currently described genera. Its closest relatives were clone

sequences obtained from a subsurface of Alpine dolomite

rocks (AB257641, 99% sequence identity, Horath &

Bachofen, 2009) and yellow microbial mat growing on

lava tube walls (e.g. HM445251, 99% sequence identity,

Northup et al., 2011). OTU II followed in abundance,

representing 6–23% of recovered sequences, and was affil-

iated with gammaproteobacterial Chromatiales. Again, this

OTU was unrelated to any cultivated species, and the 16S

rRNA sequence was most similar to Thiohalomonas

denitrificans (EF117909, 93% sequence identity). However,

OTU II was closely related to sequences recovered from

the yellow microbial mat growing on lava tube walls

(HM445440, 98% sequence identity, Northup et al.,

2011) but also to sequences recovered from Oregon caves

in the USA (e.g. DQ823220, 98% sequence identity). This

indicates that the sequences forming OTUs III and II

might be typical of subterranean environments. On the

other hand, the five sequences forming OTU I were affili-

ated with Xanthomonadales, genus Steroidobacter and

environmental sequences from soils and were not recov-

ered in previous studies on cave-wall microbial commu-

nities.

The OTUs shared between two of the sampling sites

were related to six phyla. Sampling sites in Spain and

Slovenia were found to support sequences related to both

Nitrospirae and Deltaproteobacteria. These were affiliated

with genus Nitrospira (OTU XI, 97% sequence identity

with Nitrospira moscoviensis), while deltaproteobacterial

OTUs were again related to environmental sequences

originating from the lava tube microbial mats. The latter

Fig. 2. Distribution of major phylogenetic groups in 16S rRNA gene

clone libraries constructed from environmental DNA obtained from

the Altamira Cave (Spain), Sloup-sosuvka caves (Czech Republic) and

Pajsarjeva jama (Slovenia) yellow microbial communities.

Fig. 3. Proportion of shared and specific OTUs in three cave-wall microbial communities studied.



was noted also for Acidobacteria and Actinobacteria phylo-

types common to Spanish and Czech sampling sites

(OTUs VIII, IX, X). Finally, Slovenian and Czech sam-

pling sites shared environmental sequences (OTUs IV, V

and VI) affiliated with environmental soil phylotypes of

Alphaproteobacteria, Bacteroidetes and Acidobacteria. The

majority of site-specific OTUs were affiliated with either

phylum Acidobacteria or Gammaproteobacteria (Fig. 4c),

yet the relative abundance of these and other phyla dif-

fered between sampling sites studied.

Comparisons of libraries obtained in this and

previous studies based on OTU clustering

To determine whether our core group OTUs had been

found in other studies, we compared them with GenBank

sequences using BLAST. We found that these OTUs were

previously reported in two studies on cave-wall microbial

communities. Both studies involved 16S rRNA gene

libraries constructed from environmental samples and

corresponded to multicoloured microbial communities

growing on the walls of Pajsarjeva jama in Slovenia (171

sequence, Pasic et al., 2010) and to yellow microbial mat

growing on lava tube walls in Big Island of Hawai’i

(USA) and Terceira Island (Azores, Portugal) (416

sequences, Northup et al., 2011). The available sequence

data were retrieved and included in the final data set that

contained 1061 environmental 16S rRNA sequences

obtained from eleven sampling sites located in five differ-

ent countries on two continents. ∫-Libshuff analysis foundseveral clone libraries to support microbial communities

similar in membership (Table 4). These were clone

Fig. 4. Molecular data from 16S rRNA gene sequences in samples from Altamira Cave (Spain), Sloup-sosuvka caves (Czech Republic) and Pajsarjeva

jama (Slovenia) yellow microbial communities. (a) The ML tree showing phylogenetic relationships among the shared OTU representative sequences

(bold) and relevant sequences extracted from GenBank. Bootstrap supports > 75% are indicated at nodes. Descriptions of environmental sequences

are followed by their isolation source. (b) The distribution of shared OTUs at individual sampling sites. The meaning of each colour is shown to the

left. (c) The distribution of site-specific OTUs among different bacterial phyla. The meaning of each colour is shown to the left.


262 E. Porca et al.

libraries constructed from samples obtained in Altamira

(Spain) and clone libraries constructed from samples

obtained in Bird Park lava tube, Epperson’s lava tube

(Hawai’i, USA), Gruta de Achada lava tube and Gruta

dos Principiantes lava tube (Azores, Portugal). Further-

more, clone libraries constructed from samples obtained

in Pajsarjeva jama (Slovenia) were found similar to

libraries constructed from samples obtained in Bird Park

Lava tube (Hawai’i, USA) and Gruta de Achada lava tube

(Azores, Portugal).

We kept in mind that ∫-Libshuff neglects phylotype fre-

quency, and therefore, the sampling sites sharing abun-

dant OTUs and differing in site-specific OTUs will be

considered significantly different by this approach

(Schloss, 2008). Thus, we once again estimated the pro-

portions of shared and sample-specific OTUs. Again, the

core of the community was formed by three dominant

OTUs (38% of data set sequences) affiliated with ten of

eleven sampling sites. Not surprisingly, these corresponded

to core group OTUs II (Chromatiales) and III (Pseudono-

cardinae) but also to OTU X (Nitrospira) described above.

Members of OTU II were not retrieved in clone libraries

originating from Gruta de Achada lava tube (Azores, Por-

tugal), members of OTU III were absent in Bird Park lava

tube (Hawai’i, USA) and members of OTU X were absent

from Sloup-sosuvka caves (Czech Republic). Again, in

accordance with the above findings, the remaining 378

OTUs could be divided into two groups. An approximate

one-third of sequences (29.4%) formed 82 OTUs shared

by two to six sampling sites, while the remaining 33%

sequences formed 296 site-specific OTUs.

Finally, we tried to compare our data with that avail-

able from a DGGE study on yellow microbial communi-

ties growing as spots on Altamira Cave walls in Spain (23

sequences, Portillo et al., 2008). Given the difference in

methodology used, we were only able to infer a level of

similarity in community composition by grouping the

phylotypes sharing 97% sequence identity. We found that

two sequences were more than 97% identical to sequences

recovered in this study, and both corresponded to the

most abundant core OTU III. The remaining sequences

shared < 97% sequence identity with our data set. Again,

this discrepancy could perhaps be attributed to a differ-

ence in methodologies used to obtain environmental

DNA (Delmont et al., 2011).

Based on the findings of this and previous studies, we

conclude that the yellow microbial communities growing

on the walls of geographically separated caves share bacte-

ria that are morphologically similar and related in phylog-

eny. The core of these communities is composed of

phylotypes affiliated with actinobacterial Pseudonocardinae,

gammaproteobacterial Chromatiales and genus Nitrospira,

yet they also support diverse site-specific phylotypes.Table

3.Compositionan

ddistributionofcore

OTU

san

dOTU

sshared

betweentw

osamplingsites

Samplingsite

Altam

ira

Cave(Spain)

Sloup-sosuvka

caves(Czech

Rep

ublic)

Pajsarjeva

jama

(Slovenia)

Totalnumber

ofsequen

ces

Phylogen

etic

affiliation

Nearest-neighbour

Gen

Ban

kaccessionnumber

%ofsequen

ce

iden

tity

Core

OTU

s

I0.61

0.65

1.91

5Gam

map

roteobacteria

EU979067

99

II6.75

23.38

17.83

75

Gam

map

roteobacteria

DQ823220

99

III58.28

29.87

33.76

194

Actinobacteria

AB257641

99

Total

65.64

53.90

53.50

274

OTU

sshared

betweentw

osamplingsites

IV0.61

0.00

0.65

2Deltaproteobacteria

HM445448

95

V0.00

0.64

0.65

2Acidobacteria

HQ190392

98

VI

0.00

0.64

0.65

2Bacteroidetes

GQ396974

96

VII

0.00

0.64

0.65

2Alphap

roteobacteria

DQ833466

98

VIII

0.61

0.64

0.00

2Acidobacteria

HM445238

98

IX0.61

0.64

0.00

2Acidobacteria

FJ478551

98

X1.23

1.27

0.00

4Acidobacteria

HM445321

99

XI

4.29

0.00

6.49

17

Nitrospirae

GQ500751

99

Total

7.36

4.46

9.09

33

Thecontributionofeach

samplingsite

isrepresentedas

thepercentageofthetotalnumber

ofsequen

cesin

libraries

constructed

from

thesite.



Conclusion

It should be mentioned that the microbial communities

growing as yellow spots have been reported from a num-

ber of other caves. For example, Galan & Nieto (2010)

and Galan (2011) attributed their morphology to slime

moulds (Mycetozoa), based on scanning electronic

microscopy studies of samples collected in Northern

Spain caves. On the contrary, taxonomical studies on yel-

low spot samples collected in caves of Southern Spain

suggested no relation with mycetozoans, in spite of a dis-

tant similarity of the plasmodium of some mycetozoan

species to the yellow spots studied (Lado & Moreno,

1981; Lado & Ronikier, 2009). We found the morphology

of the above-mentioned samples to be similar to that

observed in samples from Altamira Cave (Cuezva et al.,

2009). Besides, when analysing environmental DNA iso-

lated from samples taken in Altamira and other caves

studied, we repeatedly failed to amplify any DNA of

eukaryotic origin despite the methodology used. Thus, in

case of samples collected in Northern Spain by Galan &

Nieto (2010), further phylogenetic studies are needed to

confirm their taxonomic position.

As hypothesized previously, the particular yellow color-

ation of these microbial communities could perhaps be a

consequence of carotenoid production by members of

Xanthomonadales (Portillo et al., 2008). Indeed, Steroidob-

acter denitrificans, a close relative of phylotypes ascribed

to OTU I produces yellow colonies on solid medium

(Fahrbach et al., 2008). Besides, several members of

Pseudonocardinae (relatives of OTU III) were recently

reported to produce yellow pigments and could contrib-

ute to the coloration observed (Maskey et al., 2003; Qin

et al., 2008).

The overall similarity of geographically distant commu-

nities studied here probably reflects the similarity of

karstic caves in terms of environmental parameters, geo-

chemistry, and availability and nature of organic matter.

Barton et al. (2007) demonstrated that the chemical com-

position of underlying rock affects both the diversity and

the structure of cave microbial communities. Likewise,

comparative phylogenetic analysis of nearly full-length

environmental 16S rRNA sequences retrieved from 60

caves studied worldwide concluded that the overall distri-

bution of bacterial phyla was similar in geochemically

similar caves (Lee et al., 2012). In limestone caves, the

predominant phyla included both Actinobacteria and

Proteobacteria (Lee et al., 2012); on a deeper phylogenetic

level, Pseudonocardia-related phylotypes were particularly

abundant and often represented over 80% of retrieved

sequences (Barton et al., 2007; Stomeo et al., 2008). We

further hypothesize that the composition of studied com-

munities is influenced by percolating water as universal

and often the most important nutrient source in caves

(Culver & Pipan, 2009). Its scarce organic components

are related to recalcitrant humic substances and lignocel-

lulose (Saiz-Jimenez & Hermosin, 1999) and are available

only to metabolically versatile organisms. Among them

are the cultivated relatives of the most abundant OTU III,

for example members of genera Pseudonocardia and

Rhodococcus (McCarthy, 1987; Groth et al., 1999; Ahmad

et al., 2011; Zhao et al., 2011). Besides, to efficiently

exploit nutrients, the cave microorganisms could develop

cooperative and mutualistic associations as recently sug-

gested (Barton & Jurado, 2007). These complex relation-

ships could explain the broad distribution of bacterial

phyla in these nutrient-limited environments. However,

to understand whether the presence of a certain species at

Table 4. ∫-LIBSHUFF comparisons of clone libraries constructed in this study and clone library sequences constructed from yellow microbial mat

growing on lava tube walls in Hawai’i and Portugal (Northup et al., 2011) and from multicoloured microbial mat growing in Pajsarjeva jama in

Slovenia (Pasic et al., 2010)

Clone library

Number of 16S

rRNA sequences Altamira Cave (Spain)

Sloup-sosuvka caves

(Czech Republic)

Pajsarjeva jama

(Slovenia)

Big Island of Hawai’i (USA)

Kaumana lava tube 38 0.5794 0.0000 0.8274 0.0000 0.7994 0.0000

Bird Park lava tube 62 0.7168 0.0860 0.0000 0.0001 0.2515 0.0366

Epperson’s lava tube 38 0.9332 0.1197 0.9470 0.0000 0.5541 0.0001

Azores, Terceira (Portugal)

Gruta de Achada lava tube 31 0.5242 0.0015 0.7705 0.0000 0.4154 0.0007

Gruta de Balcoes lava tube 100 0.0000 0.0527 0.0000 0.0373 0.0000 0.0302

Gruta Blanca lava tube 55 0.0672 0.0000 0.0001 0.0000 0.0481 0.0000

Gruta dos Principiantes lava tube 92 0.0116 0.0148 0.0000 0.0000 0.0002 0.0000

Slovenia

Pajsarjeva jama 171 0.0000 0.0006 0.0000 0.0000 0.0000 0.0198

With an experiment wise error rate of 0.05 and taking into account a Bonferroni’s correction for multiple comparisons, the libraries were consid-

ered significantly different (indicated in bold) if either of the two P values generated for an individual pairwise comparison was < 0.0006 and

0.0125, respectively. The data are shown in two columns corresponding to reciprocal comparisons.


264 E. Porca et al.

a sampling site is a measure of its ecological preference

and to reveal the existence of a relationship between com-

munity structure and habitat heterogeneity, environmen-

tal and geochemical data should be incorporated into the

available data sets and statistically analysed. The above

data indicate that the microorganisms constituting the

core of yellow microbial communities might be true cave

dwellers. As assumed previously (Culver & Pipan, 2009)

and based on the results of our phylogenetic analysis, we

hypothesize that the colonization of caves with these

microorganisms occurred through water infiltration from

the overlaying rock, possibly at as the habitat was being

formed.

Acknowledgements

This research was supported by the Spanish Ministry of

Science and Innovation, Consolider programme, project

CSD2007-00058 and the Slovenian Research Agency

research program P1-0198. E.P. was supported by a CSIC

JAE-Predoctoral grant.

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