ORIGINAL ARTICLE

Global distribution and diversity of marineVerrucomicrobia

Sara Freitas1, Stephen Hatosy2, Jed A Fuhrman3, Susan M Huse4, David B Mark Welch4,Mitchell L Sogin4 and Adam C Martiny1,2

1Department of Earth System Science, University of California, Irvine, CA, USA; 2Department of Ecology andEvolutionary Biology, University of California, Irvine, CA, USA; 3Marine Environmental Biology Section,University of Southern California, Los Angeles, CA, USA and 4Josephine Bay Paul Center for ComparativeMolecular Biology and Evolution, Marine Biological Laboratory, Woods Hole, MA, USA

Verrucomicrobia is a bacterial phylum that is commonly detected in soil, but little is known about thedistribution and diversity of this phylum in the marine environment. To address this, we analyzed themarine microbial community composition in 506 samples from the International Census of MarineMicrobes as well as 11 coastal samples taken from the California Current. These samples from boththe water column and sediments covered a wide range of environmental conditions. Verrucomicrobiawere present in 98% of the analyzed samples, and thus appeared nearly ubiquitous in the ocean.Based on the occurrence of amplified 16S ribosomal RNA sequences, Verrucomicrobia constitutedon average 2% of the water column and 1.4% of the sediment bacterial communities. The diversity ofVerrucomicrobia displayed a biogeography at multiple taxonomic levels and thus, specific lineagesappeared to have clear habitat preference. We found that subdivision 1 and 4 generally dominatedmarine bacterial communities, whereas subdivision 2 was more frequent in low salinity waters.Within the subdivisions, Verrucomicrobia community composition were significantly different in thewater column compared with sediment as well as within the water column along gradients of salinity,temperature, nitrate, depth and overall water column depth. Although we still know little aboutthe ecophysiology of Verrucomicrobia lineages, the ubiquity of this phylum suggests that it may beimportant for the biogeochemical cycle of carbon in the ocean.The ISME Journal advance online publication, 9 February 2012; doi:10.1038/ismej.2012.3Subject Category: microbial population and community ecologyKeywords: Verrucomicrobia; bacterial communities; ICoMM

Introduction

The phylum Verrucomicrobia is ubiquitous in soilmicrobial communities, where it sometimes can bedetected in high abundance (O’Farrell and Janssen,1999; Buckley and Schmidt, 2001, 2003; Sangwanet al., 2005; Janssen, 2006; Kielak et al., 2008;Bergmann et al., 2011). In a recent study, Verruco-microbia was found in 499% of the analyzed soilsamples and constituted on average 23% of theribosomal RNA (rRNA) sequences (Bergmann et al.,2011). The phylum is related to Planctomycetes andChlamydiales, and cells affiliated with Verruco-microbia are morphologically diverse includinghaving intracellular compartments (Schlesner,1987; Hedlund et al., 1997; Schlesner et al., 2006).Nearly all isolates can grow chemoheterotrophicallyon many organic carbon compounds including

simple sugars—although not always the samecompounds (Schlesner et al., 2006; Yoon et al.,2007a, b, 2008a, b). Some strains can utilize methane(Pol et al., 2007) whereas others are facultativeanaerobes (Choo et al., 2007; Yoon et al., 2008a, b).At least in culture, Verrucomicrobia grow slowlyand many isolates from marine environments havea small cell diameter of approximately 1 mm (Yoonet al., 2007a, 2008b).

The phylum has been divided into seven subdivi-sions on the basis of the phylogeny of 16S rRNA(Hugenholtz et al., 1998; Schlesner et al., 2006). Themost common ones include subdivision 1 (Verruco-microbiae), 2 (Spartobacteria), 3 and 4 (Opitutae).Little is known about the ecological niche ofdifferent Verrucomicrobia subdivisions. In most soilcommunities, subdivision 2 is dominant, whereas 1,3 and 4 are found at a lower frequency (Sangwanet al., 2005; Kielak et al., 2008; Bergmann et al.,2011). In freshwater environments, subdivision 2 isalso abundant along with 4 (Arnds et al., 2010).

Molecular analyses of marine microbial commu-nities have revealed many previously unrecognized

Received 26 September 2011; revised 9 December 2011; accepted14 December 2011

Correspondence: AC Martiny, Department of Earth SystemScience, University of California, Irvine, CA 92697, USA.E-mail: amartiny@uci.edu

The ISME Journal (2012), 1–7& 2012 International Society for Microbial Ecology All rights reserved 1751-7362/12

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groups. It is clear that many bacterial phyla beyondProteobacteria and Cyanobacteria are present in theocean (Giovannoni and Stingl, 2005). This includesBacteriodetes, Actinobacteria and Planctomycetes,which have important biogeochemical roles likedegradation of many polymers or anammox. Lessis known about the distribution and diversityof Verrucomicrobia in the ocean (Rappe andGiovannoni, 2003). However, this phylum has beendetected in some marine samples from the watercolumn (Bano and Hollibaugh, 2002; Jackson andWeeks, 2008; Zaikova et al., 2010) and sediment(Urakawa et al., 1999). In addition, marine strainshave been isolated from a variety of marineenvironments including seawater (Yoon et al.,2007b), sediment (Yoon et al., 2008a) and marineanimals (Choo et al., 2007; Yoon et al., 2007a). Thissuggests that Verrucomicrobia is present in manymarine environments but the extent and diversityare currently unknown as well as factors influencingthe distribution of different lineages.

As part of the International Census of MarineMicrobes (IcoMM), the 16S rRNA diversity of 4500bacterial communities from a range of marineenvironments was determined using high-through-put sequencing (Zinger et al., 2011). On the basisof this survey and additional samples from theCalifornia Current, here we show that Verruco-microbia are common in the marine environmentand then examine the group’s biogeographicpatterns in detail.

Materials and methods

IcoMM analysisAs described previously, the hypervariable V6region of the 16S rRNA gene was PCR-amplifiedusing a mixture of five forward and four reverseprimers targeting all bacteria, and sequencedusing 454 technology as part of the ICoMM project(Zinger et al., 2011) (see Supplementary Table S1 forsample details). Notably, DNA was extracted differ-ently for different samples; for instance, samplesfrom the water column were treated differentcompared with sediment sample (see also http://www.icomm.mbl.edu/microbis/project_pages/pp_by_name/ for details). Chimeras and primer sequences,and fragments o50 bp were removed before analy-sis. To define operational taxonomic units, thesequences were initially pre-clustered to removesequencing error (denoising) using a modifiedsingle-linkage method at 98% sequence similarity,followed by an average neighbor clustering using a97% sequence similarity cut-off (Huse et al., 2010).Taxonomic assignment was based on a combinationof the taxonomic scheme in Silva version 102(Pruesse et al., 2007) and Bergey’s Manual usingthe GAST pipeline (Huse et al., 2008). The Silva 16SrRNA database was also used to test for primerspecificity to Verrucomicrobia.

PCR and sequencing analysis of California CurrentsamplesThe California Current data set comprised 11monthly coastal samples taken from Newport Pier(CA, USA) (location: 33.611N 117.941W). In all, 2lsamples were prefiltered through a 2.7-mm GF/D(Whatman, Piscataway, NJ, USA) filter and thencollected on a 0.22-mm Sterivex (Millipore, Billerica,MA, USA) filter (Supplementary Table S1). DNA wasextracted using a combination of lysozyme andproteinase K pretreatment and phenol-chloroformextraction (Bostrom et al., 2004). For PCR, we usedVerrucomicrobia-specific primers VER57F andEUB338_3R (Arnds et al., 2010) with at an annealingtemperature of 56 1C and 30 cycles. We then removedexcess primers with ExoSAP (Affymetrix, SantaClara, CA, USA) and ran another 10 PCR cyclesusing primers consisting of a LibL 454 adaptor, abarcode and the Verrucomicrobia primers describedabove. We used Verrucomicrobium spinosium aspositive control. Next, we sequenced the 11 samplesusing 454-pyrosequencing and analyzed them withQIIME (Caporaso et al., 2010) to denoise and removechimeras. We only included sequences 4200 bp inlength (average¼ 329 bp). In parallel to the ICoMMsamples, we then clustered the sequence using a 97%16S rRNA sequence similarity cut-off and assignedtaxonomic rankings based on Silva version 102.

Community composition analysisTo identify the difference in community composi-tion between different samples, we did multipleanalyses including step-wise linear regression,multidimensional scaling, analysis of similarities(ANOSIM) and partial Canonical CorrespondenceAnalysis. The step-wise linear regression was donein Matlab. For multidimensional scaling, we firstcalculated the pair-wise sample similarity withsquare-root-transformed Bray–Curtis similarity in-dices determined in PRIMER v6 (Primer-E, Lutton,UK). Sample similarity was visualized after multi-dimensional scaling using Kruskal fit scheme 1 anda minimum stress of 0.01. In order to have abalanced sample set for pair-wise statistical compar-isons for ANOSIM, we randomly selected an equalnumber of samples from each environment (that is,water column versus sediment or water temperaturelower or higher than 15 1C—79 and 80 samples,respectively). We only used samples containing4100 Verrucomicrobia sequences for the analysis.This was repeated 100 times. We next randomlypicked 100 sequences from each sample to ensurethat each sample contained an equal number ofsequences. This was also repeated 100 times. Then,we used ANOSIM from the vegan package in R todetermine any significant differences (999 permuta-tions) (Oksanen et al., 2011). The variance contribu-tion of multiple environmental factors on communitycomposition was determined with Canonical Corre-spondence Analysis (forward selection, a¼ 0.05 and

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999 perturbations) using Canoco (ver. 4.5, Micro-computer Power, Ithaca, NY, USA) (ter Braak, 1986),and ordination plots were visualized in CanoDraw. Itis worth noting that a subset of samples were used forcomparisons between environmental variation andcommunity composition, as we were unable toretrieve environmental data for all samples. There-fore, the total number of samples does not match thenumber of samples used in many comparisons.

Results

Distribution of total VerrucomicrobiaICoMM (http://www.icomm.mbl.edu) covered 506samples collected from all major ocean basins acrossa broad range of environmental conditions (Figure 1).This included 391 water column and 115 sedimentsamples. A total of 9.7 million 16S rRNA sequences(average¼ 19 198) were analyzed with an average of309 Verrucomicrobia sequences from each ICoMMsample (Table 1 and Supplementary Table S1). Inaddition to this global data set, we also identifiedthe diversity at a California Current coastal site.Here, we analyzed a total of 103 583 Verrucomicro-bia sequences among 11 samples (average¼ 9416)collected over a 1-year period. From the two samplesets, we identified Verrucomicrobia in 98% of thesamples and can conclude that this phylum is

nearly ubiquitous in the marine environment.Verrucomicrobia constituted on average 1.8% ofthe sequences and was the sixth most commonphylum in the water column (Supplementary FigureS1). The group was more frequent in PCR librariesfrom the water column (2.0%) compared with thesediment (1.4%) bacterial community (Welch t-test,Po0.0003, n¼ 517). Using a step-wise linear regres-sion model for the water column samples, we alsofound that the Verrucomicrobia fraction were higherin shallow coastal water versus open ocean sites(n¼ 281, Po0.0074). However, other common ocea-nographic parameters including salinity, tempera-ture, sample depth or nitrate concentrations werenot significant correlated with the frequency ofVerrucomicrobia. The highest proportions overallwere found in slightly brackish samples (salinity:30.8–33.4) from a coastal site near a small island(Helgoland) 46 km offshore of Northern Germany.Samples from this area were taken from two filterfractions (0.2–3 mm and 3–10 mm) (SupplementaryTable S1). Verrucomicrobia were marginally signi-ficantly higher (Student’s paired t-test, n¼ 10,P¼ 0.056) in the larger filter fraction (up to 32% ofthe sequences) compared with the smaller fraction(up to 5.6%). The larger filter fraction likelyrepresented bacteria attached to particles, whichsuggested that Verrucomicrobia may be more fre-quent on particles compared with free-living in

90E 135W 180W 135W 90W 45W 0

90S

45S

0

45N

90N

45 E

ICOMM samples Coastal California Current site

Figure 1 Geographical locations of International Census of Marine Microbe (ICoMM) and California Current samples that were analyzedas part of this study.

Table 1 Sample summary

Samples Samples w/oVerrucomicrobia

Sequences Verrucomicrobiasequences

Water column 391 7 7 129 838 121 441Coastala 204Open oceana 187

Sediment 115 3 2 580 022 34 960Coastal California Current 11 0 N/A 103 583

Total 517 10 9 709 860 259 984

aDefined as samples with a water column depth of below or above 200 m.

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seawater—at least in this area. However, no otherICoMM samples contained both filter fractions, sowe were unable to explore this pattern further. Wedid not detect the phylum in 10 samples includingseveral samples from deep-sea hydrothermal vents.In summary, the relative occurrence of Verrucomi-crobia appears to be highest in coastal ocean waterand lowest in sediments—in particular aroundhydrothermal vents.

Distribution and diversity of subdivisionsWe observed clear differences in the frequency anddistribution of the different Verrucomicrobia sub-divisions. Overall, we found that subdivisions 1 and4 dominated PCR libraries from marine commu-nities—both in the water column (average 73%) andin sediments (85%) (Figure 2). Subdivisions 2 and3 were only detected at a lower frequency. Around,22% of the Verrucomicrobia sequences in the watercould not be classified below phylum. Many of thesesequences originate from samples from the deepocean. The sequences from the ICoMM data setare too short to accurately build a phylogeny, but theinability to assign those sequences to even asubdivision suggests that a large fraction of theVerrucomicrobia sequences could be associatedwith unknown lineages.

To identify environmental factors influencing thedistribution of subdivisions, we first found asignificant difference in the overall compositionbetween the water column and the sediment(ANOSIM, n¼ 350, Po0.05). For example, subdivi-sion 4 was significantly more frequent in the watercolumn, whereas subdivision 1 was more commonin the sediment. A Canonical CorrespondenceAnalysis revealed that salinity, depth, temperature,nitrate concentration and water column depth

(which we view as a proxy for coastal influence)all significantly influenced the distribution ofsequences associated with different subdivisions inthe water column (Figure 3 and SupplementaryTable S2). More specifically, we observed that theoccurrence of subdivision 4 sequences were highestin the surface photic zone and negatively correlatedwith depth (Supplementary Figure S2).

Subdivision 2 is the most common group in mostterrestrial environments, but was generally found atlow frequency in the ocean and marine sediments.Within marine samples, the occurrence of subdivi-sion 2 was negatively related to salinity. It was thedominant group in samples from several areas withlow salinity including the Baltic Sea, BeaufortSea and coastal samples from the North Sea. Forexample, the subdivision constituted on average50% of the Verrucomicrobia sequences (max-imum¼ 69.7%) in the Baltic Sea. However, we didnot observe subdivision 2 in two other low salinityareas—the Black Sea and the Hood Canal on thewest coast of the United States. These two areashave an unusual seawater chemistry that couldinfluence the presence of subdivision 2. Thus, cellsaffiliated with subdivision 2 are generally confinedto areas with low salinity environments but thatother factors may influence the distribution.

Distribution and diversity within subdivisionsWe next examined the distribution of Verrucomicro-bia diversity within the subdivisions. We firstclustered the sequences on the basis of 16S rRNAsequence similarity (97% cut-off) from samplesassociated with the ICoMM project. This resulted in2831 operational taxonomic units. Within subdivi-sion 1, the genera Roseibacillus, Persicirhabdus andRubritalea were the most common (Supplementary

Unclassified

Subdivision 1 Subdivision 2 Subdivision 3

Subdivision 4

57%

27%

SedimentWater column

31%

40%

Figure 2 Average frequency of amplified 16S rRNA sequencesaffiliated with Verrucomicrobia subdivisions in water column andsediment samples from this study. The frequency of eachsubdivision was normalized to the frequency of total Verrucomi-crobia (nwater¼ 395 and nsediment¼ 112).

-1.0 1.0-0.6

0.8

Unclassified

Subdivision 1

Subdivision 2

Subdivision 3Subdivision 4

Temperature

Nitrate

DepthWater column depth

Salinity

Figure 3 Relationship between environmental factors and theoccurrence of Verrucomicrobia subdivisions amplified 16S rRNAsequences in the water column (n¼ 281). The ordination plot isbased on a partial canonical correspondence analysis withforward selection. See also Supplementary Table S2 for detailsof ranking and significance values of each environmentalparameter.

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Figure S3 and Supplementary Table S1). Roseibacil-lus constituted 33% of subdivision 1 sequences inthe water column and 9% of the sequences fromsediment samples. In contrast, Persicirhabdus wasmore frequent in the sediment (17% versus 10%). Wealso detected at low frequency in surface watersamples the occurrence of operational taxonomicunits related to the genus Acidomethylosilex. Severalstrains from this genus are capable of methanotrophy.The presence of this genus in surface waters suggeststhat Verrucomicrobia cells might contribute tomethane oxidation here. In subdivision 4, the generaCoraliomargarita, Lentimonas, Cerasicoccus, Opitu-tus and Pelagicoccus were the most common (Sup-plementary Figure S4). Although many sequencesfrom subdivision 4 were unclassified at the genuslevel (39.4% in water and 33.1% in sediment), wefound that all were associated with the family ofPuniceicoccaceae.

A comparison between the water column andsediment communities revealed—with a few excep-tions—that communities from these two environ-ments were completely separated (ANOSIM:R¼ 0.52, n¼ 79, Po0.001) (Figure 4). We also foundsignificant difference in community compositionwithin the water column along salinity, depth, watercolumn depth, nitrate and temperature gradients(Supplementary Table S2). For example, commu-nities living below 15 1C were very differentfrom communities living at higher temperature(ANOSIM: R¼ 0.17, n¼ 80, Po0.001) (Figure 4).

We observed that most environmental factors influ-ence the distribution of genera within both subdivi-sions (Supplementary Figure S5 and Supplementary

Table S2). However, it was not obvious whichenvironmental factor control the individual distribu-tion of most genera. It appeared that Acido-methylosilex is mostly found in surface waters,whereas we found Opitutus and Fucophilus at highestfrequency in brackish waters. Further, Cerasicoccuswas almost exclusively found deeper in the watercolumn. Thus, there appeared to be some degree ofecological separation at the genus level of Verrucomi-crobia, but further quantitative studies are needed toconfirm these patterns.

Discussion

In this global study, we have shown that Verruco-microbia is nearly ubiquitous in the marine envir-onment and is found in almost all marineenvironments across a range of environmentalconditions. On the basis of the average occurrenceof amplified 16S rRNA sequences, Verrucomicrobiamay be the sixth most abundant bacterial phylum inocean water after Proteobacteria, Bacteriodetes,Deferribacteres, Actinobacteria and Cyanobacteria.Overall, the frequency of Verrucomicrobia 16S rRNAsequences appeared to be lower in marine environ-ments compared with what has been observedin soil (Bergmann et al., 2011). We did not findVerrucomicrobia near the hydrothermal vents,although this could be because of the detectionlimit of the method and deeper sequencing, or theuse of specific primers may reveal in Verrucomicro-bia in this environment as well. In contrast, Verru-comicrobia constituted a high proportion of bacterialsequences in several samples taken from slightlybrackish coastal waters. This included what arelikely free-living as well as particle-attached bacterialcommunities. The coastal sites with the highestfrequency of Verrucomicrobia were adjacent to twovery small offshore islands (1 km2 and 0.7 km2) withlimited river or groundwater outflow. This suggeststhat terrestrial run-off is not the main cause for thehigh proportion of Verrucomicrobia here.

It is important to recognize that the data presentedhere is based on PCR amplification of 16S rRNAfollowed by pyrosequencing. This can introduceseveral biases based on variation in DNA extraction,primer specificity, PCR amplification and so on.DNA from individual samples was extractedwith different protocols. Thus, specific extractionmethods can fail to capture certain sublineages ofVerrucomicrobia and otherwise introduce biases inthe estimation of the frequency of lineages observed.The primer mixture used for analyzing the ICoMMsamples had a perfect match to 97% of theVerrucomicrobia sequences. Primers specificallytargeting Verrucomicrobia in the California Currentwere recently designed by Arnds et al. (2010). Theyreported that the forward primer (VER47F) captured478% of all known Verrucomicrobia whereasthe reverse primer (EUB338_3R) captured 496%,

2D Stress: 0.19

Sediment

Water column (> 15C)

Water column (< 15C)

Figure 4 Factors influencing Verrucomicrobia communitycomposition using multidimensional scaling. The communitycomposition was based on the distribution of operationaltaxonomic units defined by at least 97% 16S rRNA sequencesimilarity. The Verrucomicrobia community composition insediments and water column (ntreatment¼79) and between watercolumn samples above or below 15 1C is significantly different(ntreatment¼80).

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but the authors noted it is likely the forward primercaptured a higher percentage of Verrucomicrobia asmany 16S rRNA sequences in this region were oflower quality. These biases could affect the observedbiogeographical patterns in unknown ways. How-ever, one should also note that past observeddistributions of marine microbial lineages usingPCR-amplified 16S rRNA sequence librarieshave demonstrated important trends (for example,high abundance of SAR11 and Prochlorococcus orthe biogeography of specific ecotypes within theselineages (Giovannoni et al., 1990; Fuhrman et al.,1993; Martiny et al., 2009)) that largely matchedlater quantitative studies. On the basis of this, weexpect that the observed biogeography of Verruco-microbia using 4500 samples generally is robust.

At this point we still have a limited under-standing of the biology of Verrucomicrobia in theocean, but the biogeographical patterns observedhere point toward important physiological differ-ences among specific lineages. We observed cleardifference in community composition between thewater column and sediment, as well as alonggradients of common oceanographic environmentalvariables including salinity, water temperature,nitrate concentration, depth and water columndepth (proxy for coastal influence). This was seenat multiple taxonomic levels.

At the subdivision level, previous studies haveshown that subdivision 2 dominates many soilcommunities, but we found that this group wasprimarily confined to brackish waters. In contrast,subdivision 1 appeared to be very common in theocean and to some extent in lakes (Allgaier andGrossart, 2006; Arnds et al., 2010), but detected rarelyin soil samples (Bergmann et al., 2011). Thus, thislineage may have its primary niche in aquaticenvironments. Finally, subdivision 4 was morefrequent in PCR libraries from the surface ocean.Thus, there appears to be differential distributionpatterns of the major phylogenetic lineages withinVerrucomicrobia, which suggest that these groups areecologically distinct. Superimposed on this distinc-tion between subdivisions found on land or in theocean, we also saw specific Verrucomicrobia commu-nities inhabit sediment and specific water columnenvironments. Thus, our study here demonstratesthat Verrucomicrobia is nearly ubiquitous in themarine environment but the phylum appears toconsist of several ecologically distinct lineagesthat occupy unique niches and are differentiallydistributed along environmental gradients. We hopethat this can form the basis of more detailed studies inorder to further define the environmental range andbiogeochemical role of Verrucomicrobia ecotypes.

Acknowledgements

We thank the UCI Undergraduate Research Oppor-tunity Program (SF), the National Science Foundation

(OCE-0928544 and OCE-1046297, ACM) and the AlfredP Sloan Foundation (SH, DMW, MS) for supporting thework.

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Supplementary Information accompanies the paper on The ISME Journal website (http://www.nature.com/ismej)

Verrucomicrobia in the oceanS Freitas et al

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The ISME Journal

Page 1 of 2

Figure S1. Average occurrence of amplified 16S rRNA sequences affiliated with bacterial phyla

in water column and sediment samples from this study (nwater = 402 and nsediment= 115).

Figure S2. Relationship between water column sample depth and relative occurrence of

Subdivision 4 (Opitutae) (n = 281). The frequency of Subdivision 4 was normalized to the

frequency of Verrucomicrobia. 5

Figure S3. Average frequency of amplified 16S rRNA sequences affiliated with

Verrucomicrobia Subdivision 1 genera in water column and sediment samples from this study

(nwater = 365 and nsediment= 98). The frequency of each genus was normalized to the frequency of

Subdivision 1.

Figure S4: Average frequency of amplified 16S rRNA sequences affiliated with 10

Verrucomicrobia Subdivision 4 genera in water column and sediment samples from this study

(nwater = 370 and nsediment= 100). The frequency of each genus was normalized to the frequency of

Subdivision 4.

Figure S5: Relationship between environmental factors and the occurrence of Verrucomicrobia

Subdivision 1 and 4 genera in the water column (nsubdiv1 = 256 and nsubdiv4 = 262). The ordination 15

plots are based on a partial canonical correspondence analysis with forward selection. See also

Table S2 for details of ranking and significance values of each environmental parameter.

Table S1: Extended sample summary including sample location, environmental data, number of

sequences, and frequency of Verrucomicrobia and Verrucomicrobia subdivisions and genera.

Table S2: Summary of the statistical comparison of Verrucomicrobia community composition in 20

water column samples using partial canonical correspondence analysis with forward selection.

Page 2 of 2

This includes a comparison of the relative frequency of subdivisions, OTUs based on a 97% 16S

rRNA sequence similarity cut-off, and genera within Subdivision 1 and 4.