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FEMS Microbiology , 92, 2016, fiw051

doi: 10.1093/femsec/fiw051 Advance Access Publication Date: 4 March 2016 Research Article

RESEARCH ARTICLE Characterization of bacterial communities in lithobionts and soil niches from Victoria Valley, Marc W. Van Goethem1, Thulani P. Makhalanyane1,†, Angel Valverde1, Stephen C. Cary2 and Don A. Cowan1,∗

1Department of Genetics, Centre for and Genomics, University of Pretoria, Lynwood Road, Pretoria 0028, and 2Department of Biological Sciences, University of Waikato, Private Bag 3105, Hamilton 3120, New Zealand

∗Corresponding author: Department of Genetics, Centre for Microbial Ecology and Genomics, University of Pretoria, Pretoria, 0028, South Africa. Tel: +27-12-420-5873; E-mail: [email protected] One sentence summary: Characterization of general bacterial and cyanobacterial populations from soil and lithibiontic microbial communities ( and ) of Victoria Valley, Antarctica. Editor: Dirk Wagner †Thulani P. Makhalanyane, http://orcid.org/0000-0002-8173-1678

ABSTRACT

Here we provide the first exploration of microbial diversity from three distinct Victoria Valley edaphic , namely lithobionts (hypoliths, endoliths) and surface soils. Using a combination of terminal restriction fragment length polymorphism (T-RFLP) analysis and 16S rRNA gene amplicon pyrosequencing we assess structure and diversity patterns, respectively. Our analysis revealed that type (endolithic versus hypolithic versus surface soils) significantly influenced bacterial community composition, even though dominant phyla such as (41%of total reads) were common to all samples. Consistent with previous surveys in other Dry Valley , we found that lithobionts were colonized by a few highly dominant phylotypes (such as Gemmatimonas and Leptolyngbya). Our analyses also show that soil were more diverse and evenly distributed than initially expected based on previous evidence. In contrast to total bacteria, the distribution of was not strongly influenced by habitat type, although soil- and -specific cyanobacterial lineages were found. The detection of cyanobacterial lineages in these habitats appears to be influenced by the dispersal of aquatic inocula from lacustrine communities or benthic mats which are abundantin Victoria Valley. Together, our results provide insights into the phylogenetic variation and community structure across niche habitats in Victoria Valley.

Keywords: Antarctica; bacteria; Cyanobacteria; endolith; ; soil

INTRODUCTION Valleys of Antarctica are an ideal model system for assess- ing how adverse conditions may shape microbial diversity and Despite the recent advances in molecular analysis, we know functional processes (Cowan et al. 2014). Extremely low mois- comparatively little regarding the effect of environmental stres- ture availability, below-freezing temperatures, katabatic sors on microbial diversity and function. The McMurdo Dry

Received: 18 December 2015; Accepted: 25 February 2016 C FEMS 2016. All rights reserved. For permissions, please e-mail: [email protected]

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episodes, frequent freeze-thaw cycles and very low levels of pre- cyanobacterial populations may be influenced by the transport cipitation all combine to render the Dry Valleys inhospitable to of lineages from surrounding aquatic systems on the basis of most higher (Cowan and Ah Tow 2004), resulting in previous findings (Wood et al. 2008). To enhance our understand- a simple dominated by microbial communities (Cary ing of community structure and diversity we performed micro- et al. 2010). There is evidence suggesting that abiotic factors are bial fingerprinting analysis, using terminal restriction fragment strong drivers of microbial community composition, which in- length polymorphisms (T-RFLP), and 16S rRNA gene amplicon clude the scarcity of water (Fell et al. 2006), local soil geochem- sequencing of bacterial communities. istry (Lee et al. 2012) and temperature (Hopkins et al. 2006). We now know that the controls on microbial community structure MATERIALS AND METHODS extend from local (Pointing et al. 2009) to regional scale differ- ences (Van Horn et al. 2013; Bottos et al. 2014). Whilst the growing Study site and sampling body of knowledge has suggested significant differences exist between lithobiontic and soil communities, very little is known All samples were retrieved from the Victoria Valley region of ◦  ◦  regarding community dynamics across various habitats espe- Eastern Antarctica (77 20 S, 161 39 E) during the austral sum- cially in understudied Dry Valleys such as the Victoria Valley. mer season of January 2013 (Fig. 1). A total of 15 samples, The Antarctic Dry Valleys are largely colonized by a variety five each of surface soils, endoliths and hypoliths were col- of cold-adapted (Cowan et al. 2014; Williams et lected. Ventrally-colonized quartz rocks (hypoliths) and inter- al. 2014; Makhalanyane et al. 2015b) that survive in an array of nally colonized sandstone rocks (endoliths) were randomly re- habitats such as hypolithic and endolithic environments (com- trieved and stored in sterile Whirl-Pak sample bags (Nasco, WI, munities that inhabit undersides and interstices of rocks, re- USA). The endolithic samples included both fungal-dominated spectively), moranic soils, and ice-covered lakes. Re- and Cyanobacteria-dominated communities. Soil samples were cent phylogenetic surveys have shown significant differences in transferred into sterile 50 ml tubes. Samples were maintained < ◦ hypolithic and surface soil community compositions (Pointing at 0 C in the field and during transit to the laboratory. Sample − ◦ et al. 2009; Makhalanyane et al. 2013a), which are broadly con- material was stored at 80 C upon arrival until required. sistent with the differences in community structure found be- tween these habitats in hot hyperarid deserts (Azua-Bustos et Environmental DNA isolation and T-RFLP analysis al. 2011; Makhalanyane et al. 2013b). In addition, it is known that Dry Valleys are highly heterogenous in terms of physicochemi- DNA was isolated from duplicate 1 g samples using a cal conditions, although the effect of these differences in shap- modified phenol/chloroform extraction method (Miller et al. ing microbial diversity is not yet fully understood (Lee et al. 2012; 1999). Hypolithic and endolithic sample material was re- Van Horn et al. 2013). moved from rock substrates with sterile razor blades. DNA was Lithic-associated communities are often dominated by eluted in 20 μl nuclease-free water and quantified using the Cyanobacteria, reviewed by Chan et al.(2012), which are al- NanoDrop 2000 spectrophotometer (NanoDrop Products, Wilm-  most certainly the major drivers of photosynthetic fixa- ington, DE, USA). For T-RFLP analysis, 6 carboxyfluorescein- tion and nitrogen cycling in desert ecosystems (Warren-Rhodes labelled forward (341F) and unlabelled reverse (908R) primers et al. 2006). Moreover, lithons comprise simple trophic systems amplified universal bacterial 16S rRNA genes (Lane et al. 1985) of primary producers involved in ecosystem processes (almost under cycling conditions described previously (Makhalanyane exclusively Cyanobacteria) and heterotrophic consumers and et al. 2013a). Following purification and digestion with MspIen- degraders (Pointing et al. 2009; Robinson et al. 2015). Further- donuclease, electrophoresis on an ABI3500xl genetic analyser more, lithons harbour variable microbial compositions (Makha- (Applied BiosystemsR , CA, USA) was performed to separate lanyane et al. 2013a, 2015b), with some endoliths dominated by restriction fragments. Fragments were analysed at SeqServe rather than Cyanobacteria (De Los R´ıos, Wierzchos and (Bioinformatics and Computational Biology, University of Pre- Ascaso 2014), and experience unique levels of environmental toria, South Africa; http://seqserve.bi.up.ac.za/). R scripts were stress resulting from lithic buffering (Warren-Rhodes et al. 2006). used to bin T-RF profiles into operational taxonomic units (OTUs) Cyanobacteria are also generally ubiquitous and widespread using increments previously prescribed (Abdo et al. 2006). A in Antarctic aquatic environments including lakes and nested PCR protocol was used to evaluate cyanobacterial com-  (Cowan and Ah Tow 2004). Lacustrine and benthic habitats are munities with the Cyanobacteria-specific primers 6 FAM-359F reported to serve as important sources of novel cyanobacterial and 781R (Nubel,¨ Garcia-Pichel and Muyzer 1997). The ampli- (and to a lesser extent heterotrophic bacterial) diversity, which fication of 442 bp products was achieved using the following ◦ may alter terrestrial community structures after introduction thermal cycling conditions: 5 min denaturation at 95 C, followed ◦ and colonization events occur (Wood et al. 2008). by 30 cycles of the following three steps; 95 C denaturation for ◦ ◦ Exposed Dry Valley soils generally support fewer cyanobac- 30 s, 64 C annealing for 30 s and 72 C elongation for 90 s; with a ◦ terial lineages than lithobiontic consortia and are dominated by final elongation step at 72 C for 10 min. All downstream analy- heterotrophic (Lee et al. 2012). Soil bacterial diversity fre- ses were performed as described above. quently exceeds that of lithic communities, in spite of lower mi- crobial (Cary et al. 2010). Interestingly, some Dry Valley 16S rRNA gene amplicon pyrosequencing soil communities are surprisingly rich in Cyanobacteria, such as and phylogenetic analysis the low-altitude maritime soils of Miers Valley (Wood et al. 2008). Roche 454 GS FLX+ titanium platform was used for tagged- Here we provide data on the phylogeny of microbial commu- amplicon pyrosequencing using DNA samples (0.5 ng) from each nities associated with lithobiontic and soils habitats from the habitat. We randomly selected single soil (S1) and hypolith (H3) Victoria Valley, in the northern region of the McMurdo Dry Val- samples, while we chose to sequence two morphologically- leys of Antarctica. We also focus on the distribution of Cyanobac- distinct endolithic communities, E2 and E5.1, which ap- teria in the different terrestrial communities, and suggest that peared to be visually dominated by fungal and cyanobacterial

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Figure 1. The sampling site in Victoria Valley (A) as well as the lithic habitats characterized; fungal-dominated endolith (B), cyanobacterial-dominated endolith (C) and hypolith (D). (Photographs courtesy of DAC).

morphotypes, respectively. PCR amplification was carried out The na¨ıve Bayesian rRNA classifier (Wang et al. 2007) was used under a modified bacterial tag-encoded FLX amplicon pyrose- to assign taxonomic affiliations to the OTUs at 80% confidence. quencing (bTEFAPR ) protocol (Dowd et al. 2008) for hypervari- Sequences were imported into ARB (Ludwig et al. 2004)and able regions V1–V3 of the 16S rRNA gene. An AgencourtR aligned using manual curation in addition to automated align- AMPureR XP PCR Purification system (Agencourt Bioscience ment. Reference sequences were selected from the GenBank Corporation, MA, USA) was used to purify equal concentra- database for tree reconstruction. Multiple alignments were ex- tions of pooled amplicons. Samples were sequenced at the ported from ARB and imported into the software package MEGA Molecular Research LP next-generation sequencing service v6.06 for tree annotation and visualization. The sequence data (http://www.mrdnalab.com/). Purification of the final ampli- have been made available on the NCBI Sequence Read Archive con products preceded unidirectional 454-pyrosequencing with under the accession number SRR2420889. GS FLX+ Titanium chemistry using standard protocols (Roche Diagnostics, CT, USA). Data analysis MOTHUR v.1.33.1 (Schloss et al. 2009) was used to anal- yse the raw pyrosequencing data following an established A Bray-Curtis dissimilarity matrix of Hellinger-transformed T- pipeline (Schloss, Gevers and Westcott 2011). Low-quality reads RFLP data (Bray and Curtis 1957; Legendre and Gallagher 2001; were removed from datasets using the shhh.flows command, Abdo et al. 2006) was used to visualize differences in community while sequence lengths below 200 bp and reads containing ho- composition; depicted using non-metric multidimensional scal- mopolymers longer than 8 bp or ambiguous bases (N) were ing (nMDS) ordination plots generated in R. Differences in the to- also removed. Dataset simplification was achieved with the tal bacterial and cyanobacterial compositions between habitats unique.seqs command. The UCHIME algorithm (v4.2; Edgar (hypolith versus soil versus endolith) was tested using ANOSIM et al. 2011; http://drive5.com/uchime/) was used in MOTHUR (Analysis of Similarity; Clarke 1993), after 9999 iterations. Intra- to remove chimeras. Alignments to the latest version of the habitat variation was tested using betadisper (permutation dis- SILVA 16S bacterial ribosomal reference database (Pruesse persion) (Anderson, Ellingsen and Mcardle 2006). We permit- et al. 2007; http://www.arb-silva.de/download/arb-files/)was ted singletons in the datasets as no effect on beta-diversity performed using align.seqs. A distance matrix was constructed patterns were found after their exclusion. The effect of habi- in MOTHUR using sequences defined as OTUs at a 97% cut-off. tat on microbial and diversity was assessed using

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Kruskal-Wallis (KW) tests which were considered significant Table 1. Univariate models of phylotype richness and diversity met- (P < 0.05) after post hoc Wilcoxon-Mann Whitney comparisons rics on the basis of T-RFLP analysis. were made. We used Fisher’s exact test to detect significant Hypolith Endolith Soil taxonomic differences between the communities after Bonfer- roni corrections using STAMP software (Statistical Analysis of α¯ 31.6 ± 5.9 31.2 ± 11.4 24.6 ± 4.7 Metagenomic Profiles; v2.1.3; Parks and Beiko 2010). γ 48 41 56 β (γ /¯α) 1.56 1.98 1.71 RESULTS AND DISCUSSION Shannon (H)3.77± 0.6 3.50 ± 1.0 3.42 ± 0.4 Gini-Simpson (1-λ) 1.048 ± 0.02 1.063 ± 0.01 1.064 ± 0.03 Recently, a number of studies have focused on characterizing the Betadisper 0.1815 0.2505 0.2024 lithic and soil-based microbial communities across a range of McMurdo Dry Valley niche habitats (De Los R´ıos, Cary and Cowan 2014; Yung et al. 2014). However, the majority of these studies have focused on the low-altitude maritime Miers Valley (Khan et al. 2011; Makhalanyane et al. 2013a), with few studies exploring other valleys (De Los R´ıos et al. 2007; Lee et al. 2012; Lacelle et al. 2013). Based on habitat heterogeneity these edaphic systems are hypothesized to be highly variable, but how this heterogeneity may alter microbial diversity remains unknown. Here we pro- vide the first characterization of microbial diversity of Victoria Valley lithobionts and soil niches. We explore bacterial diversity and focus on cyanobacteria, which are the likely drivers of major functional processes.

Community structure analysis via T-RFLP

We observed a total of 66 bacterial OTUs across all samples (n = 15) of which 33 (50%) were cosmopolitan (so-called habitat gen- eralists) to the three habitats. In contrast, only 20 OTUs (30%) were specific to a particular habitat, which is visualized asa low level of community dissimilarity between the three habi- tats (Fig. 2). The number of bacterial OTUs per individual sample (α-diversity) ranged from 19 to 48 [29 (mean) ± 7 (SD)]. Consis- Figure 3. The bacterial community structures of the unique edaphic habitats tent with previous studies conducted in the Dry Valleys and in (hypolith, endolith and soil) are visualized in an nMDS ordination plot. Single points represent entire community fingerprints on the basis of Bray-Curtis dis- other hyperarid deserts (Pointing et al. 2007; Azua-Bustos et al. similarities of 16S rRNA variation. The distances between samples reflect dis- 2011; Makhalanyane et al. 2013a), lithobionts had higher average similarity thus proximally clustered samples are less dissimilar in community α OTU numbers ( ¯ ) than soils (Table 1). Both the Shannon diversity composition. index (H) and the Gini-Simpson index (1-λ) remained relatively constant between habitat types suggesting similar diversity lev- veys showing significant differences between soil and hypolithic els between lithobionts and soils (KW test, P > 0.05; Table 1). bacterial community structures (Pointing et al. 2009;Khanet al. Exposed surface soils had the highest levels of γ -diversity; 20% 2011; Makhalanyane et al. 2013a). Habitat type also plays an im- higher than the lithobionts on average. portant role in driving maritime Antarctic microbial commu- nMDS ordination plots showed that bacterial communities nity structure (Yergeau et al. 2007), overall assembly in hyperarid grouped according to habitat type (Fig. 3; ANOSIM, Global R = deserts (Makhalanyane et al. 2013b) as well as functional poten- 0.38, P < 0.05). Furthermore, we found significant pairwise dif- tial (Chan et al. 2013). To further explore community diversity ferences between soils and endolithic communities (R = 0.42, patterns, we tested the homogeneity of group dispersions (An- P < 0.01) and between soils and hypolithons (R = 0.492, P < derson, Ellingsen and Mcardle 2006). The lithobiontic commu- 0.02). Lithic communities did not differ significantly from one nities showed higher beta diversity trends, although these were another (P > 0.05). These results support previous Dry Valley sur- not significantly different when compared to soil. While some (14%) of the general bacterial community varia- tion could be explained by habitat type alone, our analysis sug- gests that this is not the case for cyanobacterial populations. T- RFLP analysis showed 27 cyanobacterial OTUs across all sam- ples, which ranged from 3 to 16 OTUs per individual sample [8.2 (mean) ± 3.9 (SD)], and represented ∼41% of the total bacterial diversity. Ten OTUs (37% of the cyanobacterial OTUs) were found in all samples, while 11 OTUs (41%) were habitat-specific. In con- trast to the general bacterial diversity, soils supported more di- verse populations of Cyanobacteria than lithobionts (data not shown). The lack of distinction between cyanobacterial popu- lations from distinct habitat types is proposed to be the re- sult of introduced aquatic Cyanobacteria derived from proximal Figure 2. Bubble plot representing individual T-RFs (columns) per sample (rows). lacustrine and benthic communities. The mechanism of Bubbles are sized by the relative abundance at which the T-RF was observed. aeolian redistribution is thought to play a significant role in

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shaping terrestrial communities in Miers Valley, Antarctica quences). Previous surveys have found this genus to be abun- (Wood et al. 2008). We used pyrosequencing to identify the dom- dant and widespread in Antarctic mineral soils, including in the inant from each habitat and to explore whether McMurdo Dry Valleys (Babalola et al. 2009), in Northern Victoria there is evidence of cyanobacterial phylotypes which may have Land (Niederberger et al. 2008) and Schirmacher Oasis (Shivaji et originated from aquatic sources. al. 2004). Members of the Gemmatimonas may contribute to local biogeochemical cycling through phosphate (Zhang Pyrosequencing analysis of lithonbionts and soils et al. 2003), while predicted cold tolerance proteins have been linked with the group (Grzymski et al. 2006). After read curation and chimera removal, a total of 724 bacte- The order Acidimicrobiales (phylum Actinobacteria) was rial OTUs (97% identity) were obtained from 10 665 sequences, also abundant in all samples (133 OTUs). Three genera within the majority of which belonged to Actinobacteria (41% of total the Acidimicrobiales, Iamia, Aciditerrimonas and Ilumatobacter, OTUs). Cyanobacteria (18%) represented the primary photoau- were abundant in all samples, suggesting that these taxa may totrophs in each community, while ubiquitous heterotrophic have important functional roles. Members of the Aciditerrimonas members included (15%), genus, such as Aciditerrimonas ferrireducens, are thought to be ca- (13%) and (4%) (Table 2). These bacterial groups pable of reducing in environmental soils (Itoh et al. 2011). are common colonists of terrestrial Dry Valley habitats (Lee et al. Actinobacteria are major colonists of inland Dry Valley soils 2012; Bottos et al. 2014; Yung et al. 2014) and are prevalent in other (Cary et al. 2010) and are minor components of high-altitude hy- desert soils (Makhalanyane et al. 2013b; Robinson et al. 2015), al- polith communities (Wong et al. 2010). Largely consistent with beit at different relative abundances. Overall, bacterial diversity other studies (Smith et al. 2006; Niederberger et al. 2008) we found spanned 11 phyla (Fig. 4), all of which, barring Chlorobi, were to be poorly represented (4% of total assigned se- present in the soil community. The lithobionts harboured fewer quences) in all communities. bacterial phyla than the soil community, and were colonized by Cyanobacteria are the dominant bacterial members of lithic six to eight phyla. Surprisingly, heterotrophic members, rather and communities in hyperarid deserts (Warren- than Cyanobacteria, comprised the majority of recoverable phy- Rhodes et al. 2006;Caryet al. 2010;Cowanet al. 2014). Stud- lotypes in lithobionts. Rarefaction curves and Chao1 estimates ies have shown that Cyanobacteria are important colonizers of of richness suggest that sequencing had not reached saturation, soil communities in high-altitude Dry Valleys (Smith et al. 2006) which may have led to underestimates of diversity. Univariate and in hot hyperarid soils of the Namib desert (Makhalanyane tests were used to estimate sample richness and showed that et al. 2015a). Cyanobacteria were abundant in all samples anal- soils were the most diverse communities at the phylum level ysed here, comprising 7%–21% of the sequences. For example, (Table 3). the genus Leptolyngbya accounted for 14%–54% of cyanobacte- Approximately 12% of the classified sequences were present rial populations (Fig. 5). Leptolyngbya are frequently identified in fewer than five times in the global dataset, underlining theim- lake communities (Taton et al. 2006;Biondiet al. 2008)andin portance of rare members to community structure. Rare groups maritime Antarctic assemblages (Komarek,´ Elster and Komarek´ included the candidate phyla WS3 and TM7 which were not 2008). Another oscillatorian genus, Phormidium, was abundant present in all samples. We could not detect archaeal signa- (27%–38%) in most communities, but was completely absent tures in any samples, which may be the result of extreme xeric from one endolithic consortium. Members of Phormidium are stress in Victoria Valley. Critically low water bioavailability has some of the most common colonists of water-saturated soils been suggested to prevent from persisting in hyperarid in low elevation valleys, similar to mat communities in ponds deserts (de la Torre et al. 2003; Pointing et al. 2009). Consistent (Broady 2015). Altogether, these results appear to indicate that with expectations, we found copiotrophic taxa (including mem- the diversity of terrestrial communities in Victoria Valley may be bers of the and Proteobacteria phyla) to be under- influenced by proximal aquatic systems, as has been suggested represented in these highly oligotrophic habitats (Fierer et al. in Miers Valley (Wood et al. 2008). 2012a). Members of these phyla are reliant on high organic soil While Oscillatoriales phylotypes dominated all samples, carbon content, while the majority of Antarctic habitats, partic- were found exclusively in soils and hypoliths. ularly in the Dry Valleys, are extremely nutrient poor (Cowan This is in contrast to a survey showing Chroococcidiopsis phylo- et al. 2014). We observed the opposite distribution for olig- types to dominate endolithic consortia (Pointing et al. 2009). The otrophic Acidobacteria which were found in all communities. process of in both hot and cold deserts is The phylum-assigned sequences indicated that there were thought to be strongly mediated by members of Chroococcidiop- diverse microbial taxa in all habitat types, with both similarities sis (Tracy et al. 2010;Bahlet al. 2011). Although members of the and significant differences between communities. In all three phyla Chlorobi (found in hypoliths) and (found in communities, the most dominant sequences were Actinobacte- soils and endoliths) may also mediate anoxygenic photosynthe- ria, although we found significant over-representations of the sis in those communities (Bryant et al. 2012). phylum in sample E5.1 (endolith) in comparison to the other Interestingly, soils shared 88% and 85% of the total bacte- samples (Fisher’s exact test; P < 0.0001). Furthermore, the pro- rial OTUs with hypolithic and endolithic communities, respec- portions of Cyanobacteria (P < 0.05) and Verrucomicrobia (P < tively. The high number of shared OTUs between soil and lithic 0.05) were significantly under-represented in E5.1 relative to all communities may be due to a number of possible reasons, other communities. We also found unclassified bacteria to be including positive synergistic ecological interactions between significantly more abundant in lithic-associated consortia rela- species or due to proposed mechanisms in which lithobionts tive to the soil community (S1) (P < 0.05), while the abundance of serve as reservoirs of terrestrial biota (Pointing et al. 2009). An members belonging to Proteobacteria differed significantly be- alternative explanation may be the aeolian transport of viable tween the two endolithic communities (P < 0.001). cells in the Dry Valley aerosphere. Many of the lineages found Gemmatimonas phylotypes (phylum Gemmatimonadetes) here, such as Oscillatoriales and Chroococcales, are common were highly represented in all samples and contributed 109 colonists of aquatic habitats in the Dry Valleys (Wood et al. 2008; OTUs across the four samples (15% of the total assigned se-

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Table 2. The most abundant OTU taxa are presented, sequences were detected at least five times in the dataset. Numbers in parenthesis indicate the relative abundance of each genus in the sample. No detection is marked with a 0.

H3 (%) S1 (%) E2 (%) E5.1 (%) Overall (%)

Actinobacteria Actinobacteria Acidimicrobiales Acidimicrobineae Aciditerrimonas 17 (4.68) 5 (2.86) 2 (2.33) 9 (9.00) 33 (4.56) Iamiaceae Iamia 40 (11.02) 12 (6.86) 3 (3.49) 10 (10.00) 65 (8.98) Acidomicrobiaceae Ilumatobacter 15 (4.13) 12 (6.86) 5 (5.81) 3 (3.00) 35 (4.83) Actinomycetales Nocardioidaceae Aeromicrobium 1 (0.28) 6 (3.43) 0 0 7 (0.97) Marmoricola 3 (0.83) 7 (4.00) 0 6 (6.00) 16 (2.21) Nocardioides 9 (2.48) 16 (9.14) 0 3 (3.00) 28 (3.87) Angustibacter 2 (0.55) 0 1 (1.16) 2 (2.00) 5 (0.69) Unclassified Kineosporiaceae 3 (0.83) 0 2 (2.33) 0 5 (0.69) Micrococcaceae Arthrobacter 1 (0.28) 1 (0.57) 2 (2.33) 1 (1.00) 5 (0.69) Sporichthyaceae 2 (0.55) 1 (0.57) 1 (1.16) 1 (1.00) 5 (0.69) Mycobacteriaceae Unclassified Mycobacteriaceae 1 (0.28) 2 (1.14) 0 2 (2.00) 5 (0.69) Euzebyales Euzebyaceae Euzebya 7 (1.93) 0 3 (3.49) 18 (18.00) 28 (3.87) Gemmatimonadetes Gemmatimonadetes Gemmatimonadales Gemmatimonadaceae Gemmatimonas 52 (14.33) 25 (14.29) 18 (20.93) 14 (14.00) 109 (15.06) Verrucomicrobia Verrucomicrobiae Verrucomicrobiales Verrucomicrobiaceae Luteolibacter 33 (9.09) 8 (4.57) 9 (10.47) 0 50 (6.91) Verrucomicrobium 15 (4.13) 4 (2.29) 0 0 19 (2.62) Opitutae Opitutales Opitutaceae Opitutus 7 (1.93) 3 (1.71) 0 1 (1.00) 11 (1.52) Spartobacteria Unclassified Spartobacteria 4 (1.10) 0 2 (2.33) 0 6 (0.83) Cyanobacteria Cyanobacteria Family I GpI 20 (5.51) 13 (7.43) 2 (2.33) 4 (4.00) 39 (5.39) Family IV GpIV 33 (9.09) 13 (7.43) 12 (13.95) 0 58 (8.01) Family XIII GpXIII 6 (1.65) 6 (3.43) 0 0 12 (1.66) Unclassified Cyanobacteria 5 (1.38) 3 (1.71) 0 1 (1.00) 9 (1.24) Acidobacteria Acidobacteria Family Gp1 Gp1 3 (0.83) 2 (1.14) 0 0 5 (0.69) Acidobacteria Family Gp4 Gp4 6 (1.65) 11 (6.29) 0 0 17 (2.35) TM7 4 (1.10) 2 (1.14) 0 1 (1.00) 7 (0.97) Unclassified Bacteria 40 (11.02) 3 (1.71) 5 (5.81) 11 (11.00) 59 (8.15) Taxa found fewer than Five times in the dataset 34 (9.37) 20 (11.43) 19 (22.09) 13 (13.00) 86 (11.88)

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macher Oasis and Windmill Hills (Pankow, Haendel and Richter 1991; Ling and Seppelt 1998), and are important components of Wright Valley ponds and streams (Novis et al. 2015). The M. vagi- natus phylotypes from this study clustered strongly with Mojave and Chihuahuan desert sequences (Fig. 6). We propose that aeo- lian transport may reduce the strong deterministic effects of soil physicochemistry and habitat type in structuring the edaphic microbial communities of Victoria Valley. By implication, ran- dom introduction and colonization events are likely to dispro- portionately affect the structure in this environment (Bottos et al. 2014; Pointing and Belnap 2014). Figure 4. The taxonomic distribution of bacterial OTUs on the basis of 16S rRNA Hypolithic and endolithic communities were shown to clus- gene assignments obtained from single samples selected from each habitat (hy- polith, soil, fungal-dominated endolith and Cyanobacteria-dominated endolith). ter separately from soils despite sharing a majority of the bacte- Bars show the relative abundances of bacteria assigned at the phylum level. rial OTUs found here. Even though generalist lineages colonized Taxonomies were provided after comparisons to the latest Ribosomal Database all of the edaphic habitats analysed in this desert, we observed Project (RDP) Release at a confidence of 80%. higher variation in lithic community composition compared to exposed soils which are likely driven primarily by stringent abi- Kleinteich et al. 2014), but are typically absent from hyperarid otic factors such as very low soil pH (Fierer et al. 2012b; Van Horn soils (Pointing et al. 2009; Makhalanyane et al. 2013a). This con- et al. 2013). Many phylotypes were unclassified (∼8%) although cept is further supported by the detection of Microcoleus vagi- this is not uncommon for desert microbial communities which natus in the soil community. Microcoleus vaginatus phylotypes are hindered by rRNA gene variability (Niederberger et al. 2008; have been found in maritime Antarctic locations such as Schir- Lee et al. 2012; Makhalanyane et al. 2013a). We suggest that lakes

Table 3. Estimates of community richness including the total number of sequences obtained and OTU distributions on the basis of pyrotag data.

Sample Habitat Reads OTUs % of Unique OTUs Chao1 1-λ H

H3 Hypolith 5089 362 18 305.5 [± 94.6 (SD)] 0.28 2.0 E5.1 Endolith 3273 103 21 107.1 [± 43.0 (SD)] 0.20 2.3 E2 Endolith 1340 83 22 67.1 [± 20.2 (SD)] 0.06 3.8 S1 Soil 963 176 14 165.1 [± 53.3 (SD)] 0.02 4.3

Figure 5. Line graph of the cyanobacterial lineages present in the four samples (97% cut-off). Taxonomic affiliations were provided by the Ribosome Databaseoject Pr Classifier (RDP) at 80% confidence.

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Figure 6. Maximum likelihood tree showing the phylogenetic relationships between cyanobacterial phylotypes recovered from Victoria Valley samples.

and ponds in the Dry Valleys may serve as sources of cyanobac- FUNDING terial diversity for terrestrial habitats which is largely consistent We wish to thank the following funding organizations: The with the concept proposed by Wood et al.(2008). This work pro- South African National Antarctic Program (Grant ID: 93074) vides insights into the bacterial community structures of Victo- (DAC), the South African National Research Foundation (MWVG, ria Valley habitats for the first time. Future studies are required TPM, AV, DAC), the Genomics Research Institute (TPM, AV, DAC). to expand the understanding of these systems by assessing the We also wish to thank Antarctica New Zealand for field logistics biological functions of these important consortia. support.

Conflict of interest. None declared. ACKNOWLEDGEMENTS REFERENCES Logistical support to perform field research was provided by Antarctica New Zealand. We thank the Sequencing Facility at Abdo Z, Schuette UM, Bent SJ et al. Statistical methods for char- the University of Pretoria for performing T-RFLP analysis. acterizing diversity of microbial communities by analysis of

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