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The Candidate Phylum Poribacteria by Single-Cell Genomics: New Insights into Phylogeny, Cell-Compartmentation, Eukaryote-Like Repeat Proteins, and Other Genomic Features

  • Janine Kamke,

    Affiliation Department of Botany II, Julius-von-Sachs Institute for Biological Sciences, University of Wuerzburg, Wuerzburg, Germany

  • Christian Rinke,

    Affiliation Department of Energy Joint Genome Institute, Walnut Creek, California, United States of America

  • Patrick Schwientek,

    Affiliation Department of Energy Joint Genome Institute, Walnut Creek, California, United States of America

  • Kostas Mavromatis,

    Affiliation Department of Energy Joint Genome Institute, Walnut Creek, California, United States of America

  • Natalia Ivanova,

    Affiliation Department of Energy Joint Genome Institute, Walnut Creek, California, United States of America

  • Alexander Sczyrba,

    Affiliations Department of Energy Joint Genome Institute, Walnut Creek, California, United States of America, Center for Biotechnology, Bielefeld University, Bielefeld, Germany

  • Tanja Woyke,

    Affiliation Department of Energy Joint Genome Institute, Walnut Creek, California, United States of America

  • Ute Hentschel

    ute.hentschel@uni-wuerzburg.de

    Affiliation Department of Botany II, Julius-von-Sachs Institute for Biological Sciences, University of Wuerzburg, Wuerzburg, Germany

The Candidate Phylum Poribacteria by Single-Cell Genomics: New Insights into Phylogeny, Cell-Compartmentation, Eukaryote-Like Repeat Proteins, and Other Genomic Features

  • Janine Kamke, 
  • Christian Rinke, 
  • Patrick Schwientek, 
  • Kostas Mavromatis, 
  • Natalia Ivanova, 
  • Alexander Sczyrba, 
  • Tanja Woyke, 
  • Ute Hentschel
PLOS
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Abstract

The candidate phylum Poribacteria is one of the most dominant and widespread members of the microbial communities residing within marine sponges. Cell compartmentalization had been postulated along with their discovery about a decade ago and their phylogenetic association to the Planctomycetes, Verrucomicrobia, Chlamydiae superphylum was proposed soon thereafter. In the present study we revised these features based on genomic data obtained from six poribacterial single cells. We propose that Poribacteria form a distinct monophyletic phylum contiguous to the PVC superphylum together with other candidate phyla. Our genomic analyses supported the possibility of cell compartmentalization in form of bacterial microcompartments. Further analyses of eukaryote-like protein domains stressed the importance of such proteins with features including tetratricopeptide repeats, leucin rich repeats as well as low density lipoproteins receptor repeats, the latter of which are reported here for the first time from a sponge symbiont. Finally, examining the most abundant protein domain family on poribacterial genomes revealed diverse phyH family proteins, some of which may be related to dissolved organic posphorus uptake.

Introduction

Single-cell genomics is a powerful tool to describe genomes of as yet uncultivated organisms from diverse environments [1], [2]. Recently it allowed a first glimpse into the vast functional diversity represented by genomes of previously largely uncharacterized candidate phyla [3]. This method further revealed the glycobiome of the candidate phylum Poribacteria, symbionts of marine sponges, based on six single-amplified genome (SAG) sequences [4]. In this study we further examined these SAGs for phylogenetic and additional functional features of Poribacteria. Poribacteria were first discovered as highly abundant symbionts of marine sponges [5] and as of now lack any cultivated representatives. Through amplicon sequencing studied based on 16S rRNA genes they were also detected in seawater albeit in low abundances [6][8]. Poribacteria are one of the most predominant taxa inhabiting the extracellular matrix (mesohyl) of sponge species around the world [9][11]. These symbionts are vertically transmitted over larval stages from the adult sponge to the next generation [7], [12]. Initially, the candidate phylum Poribacteria showed a moderate phylogenetic relationship to Planctomycetes, Verrucomicrobia, and Chlamydiae (PVC superphylum) based on monophyletic clustering in 16S rRNA gene analysis [5]. Later, Poribacteria were classified as members of the PVC superphylum although the exact position within the superphylum could not be completely resolved [13]. Similar to some members of the PVC superphylum Poribacteria were also suspected to have a compartmentalized cell plan [5]. In this study we revisited the features of phylogeny and cell compartmentalization based on the sequence data of six single-cell derived genomes from the candidate phylum Poribacteria. We further reveal a large abundance and diversity of eukaryote-like domain containing proteins as well as phyH-like proteins in Poribacteria.

Materials and Methods

Genome Annotation and Analysis

Six poribacterial single-cell genome sequences were included in this study, these being Candidatus Poribacteria WGA 3A, 3G, 4C, 4CII, 4E and 4G with Genbank accession numbers ADFK02000000, ASZN01000000, APGO01000000, ASZM01000000, AQTV01000000, AQPC01000000, respectively. These genomes were previously obtained by our group from uncultivated bacteria inhabiting the marine sponge Aplysina aerophoba by fluorescence activated cell sorting (FACS), multiple displacement amplification (MDA), and next generation sequencing [14], [4].

Please also note that the initial version of genome WGA 3A (first published as WGA A3 with accession number ADFK00000000 version ADFK01000000) [14] was found to be flawed. It was corrected accordingly and the submission to Genbank was updated (version ADFK02000000) [4]. All genomic information of WGA 3A in this manuscript is based on the latest version of the genome, which should be used for all future studies. For a detailed description of all steps from sample collection to genome assembly and annotation please refer to Kamke et al. [4]. Genome sequences were automatically annotated via the IMG pipeline [15] and manually curated in IMG/MER. All analyses were conducted using the tools in IMG/MER unless further specified.

Clustering analysis of PhyH family genes.

For clustering of pfam 05721-PhyH family proteins we used the fastclust algorithm in usearch [16] with an identity cutoff of 60% amino acidid.

Phylogenetic 16S rRNA Gene Analysis

Sequences for 16S rRNA gene based phylogenetic analysis were selected from the SILVA 16S rRNA database version 108 [17] in the ARB software package (V5.3) [18]. All poribacterial 16S rRNA sequences (≥1100 bp) available in GenBank by June 2013 and the 16S rRNA sequences of poribacterial single-cell genomes were included. Additional sequences for the candidate phyla Aerophobetes (CD12) and Hydrogenedentes (NKB19) were obtained by blast searches [19] of reference sequences (accession number JN675971 for CD12 and CR933119 for NKB19) against Genbank nr/nt database in June 2013 and selecting the 100 best hits with >75% sequence ID and sequence length ≥1100 bp. All sequence added to the original database were aligned using the SINA aligner [20] and included into the ARB database for further manual refinement. Alignments were exported from ARB for phylogenetic tree construction using RAxML (v7.3.2) [21]. Maximum likelihood trees were constructed using sequences ≥1100 bp only and 50% conservation filters. Bootstrap analysis was carried out with 500 resamplings. Trees were reimported into ARB and sequences <1100 bp were added to the tree using the parsimony interactive tool in ARB without changing tree topology.

Phylogenetic Analysis of 83 Bacterial Marker Protein Sequences

For the calculation of the bacterial phylogenetic tree we followed the procedure described by Rinke et al. [3] based on a custom marker set of 83 bacteria specific markers (Table S1) described in the study. Briefly, single-cell genome assemblies of Poribacteria were translated into all six reading frames and marker genes were detected and aligned with hmmsearch and hmmalign included in the HMMER3 package [22] using HMM profiles obtained from phylosift (http://phylosift.wordpress.com/). Extracted marker protein sequences were used to build concatenated alignments of up 83 markers per genome. Alignments were included into the database constructed by Rinke and coworkers [3] and reference sequences were selected for phylogenetic tree construction. Phylogenetic inference methods used were the maximum likelihood based FastTree2 [23] and a custom RAxML bootstrap script originally provided by Christian Goll and Alexandros Stamatakis (Scientific Computing Group, Heidelberg Institute for Theoretical Studies, Germany) and modified by Douglas Jacobsen (Bioinformatics Computing Consultant, LBNL, Berkeley, USA). The script requires two input files, the alignment file as PHYLIP format and a starting tree calculated by RAxML-Light [24]. The script workflow is briefly summarized as follows: First RAxML version 7.3.5 [21] creates bootstrap replicates of the multiple sequence alignments and stepwise addition order parsimony trees as starting points for the maximum likelihood search, based on user defined rate heterogeneity and substitution models. Next RAxML-Light [24] is run on every bootstrap replicate. After all RAxML-Light runs are finished the resulting replicate trees are fed into RAxML to calculate the bootstrap support values which are drawn upon the starting tree. The rate heterogeneity and amino acid evolution models used were GAMMA and LG for the custom RAxML bootstrap script, and CAT approximation with 20 rate categories and Jones-Taylor-Thorton (JJT) for FastTree2. To evaluate the robustness of the protein trees we used seven different out-group taxon configurations (Table 1).

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Table 1. Summary of phylogenetic inference results from all phylogenomic tree calculations.

http://dx.doi.org/10.1371/journal.pone.0087353.t001

Results and Discussion

Phylogenetic Revision of Poribacteria

Analysis of phylogenetic interferences of up to 83 marker genes (hereafter termed phylogenomic analyses) showed that all poribacterial SAGs clustered, with 100% bootstrap support in all our tree calculations, in a monophyletic group distinct to the PVC superphylum (Table 1, Fig. 1). Poribacteria SAGs clustered with the recently proposed phyla Aerophobetes (CD12) and/or Hydrogenedentes (NKB19) [3] in most of our phylogenomic calculations (Table 1). This loosely affiliated clade, including other phyla such as Elusimicrobia, formed in some tree calculations a sister clade to the PVC superphylum (Fig. 1). Phylogenetic analysis of the 16S rRNA gene supported monophyletic clustering of Poribacteria with strong bootstrap support (Fig. 2). However, phylogenetic placement based on the 16S rRNA gene did not show the direct grouping with Aerophobetes (CD12) and/or Hydrogenedentes (NKB19) (Fig. 2). Instead Poribacteria were placed (bootstrap support 91%) separately within a larger cluster of other phyla including the PVC superphylum as well as the candidate phylum WS3, recently renamed as Latescibacteria [3] and a monophyletic lineage previously described as “sponge associated unclassified lineage” (SAUL) [10].

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Figure 1. Phylogenomic tree based on a concatenated alignment of up to 83 genes illustrating the phylogenetic position of the candidate phylum Poribacteria.

Bootstrap value (100 resamplings) are shown on tree nodes where support ≥50%. Number of genomes per group is displayed in group boxes. Outgroup consists of several species of Spirochaetes and Gammaproteobacteria. The scale bar represents 10% sequence divergence.

http://dx.doi.org/10.1371/journal.pone.0087353.g001

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Figure 2. 16S rRNA gene based maximum likelihood tree illustrating the phylogenetic position of the candidate phylum Poribacteria.

Bootstrap values (500 resamplings) ≥50% are shown on tree nodes. Numbers of sequences included per group is shown in group boxes. Outgroup consists of 80 sequences belonging to the Bacteroidetes. Scale bar represents 10% sequences divergence.

http://dx.doi.org/10.1371/journal.pone.0087353.g002

The inconsistency between phylogenomic and the 16S rRNA gene-based phylogeny might be due to the relatively low resolution provided by the single marker gene (16S rRNA) analysis compared to multiple genes analysis as has been suggested previously [3], [25]. On the other hand the phylogenomic analysis, limited to the relatively small amount of draft reference sequences available at the time of analysis, might not be able to properly resolve the general placement of the phylum. We expect that the position of the Poribacteria in the tree of life will be further refined as more genome sequences of Poribacteria and of other candidate phyla become available. Importantly, the phylogenetic analyses performed in this study (whether 16S rRNA gene or marker genes based) did not support a clustering of Poribacteria with the PVC superphylum, which is in contrast to what was suggested earlier [13].

Previous studies based on concatenated alignments of protein data [26], [27] also showed the phylogenetic position of Poribacteria outside the PVC superphylum. However, these studies included only one poribacterial genome sequence available at that time, Candidatus Poribacteria sp. WGA A3 in its initial version (ADFK01000000). This version was later shown to be flawed by contaminating DNA and was replaced in Genbank (ADFK02000000) [4]. Since the previous studies examining poribacterial phylogeny [26], [27] were published before the release of the updated version they could not have revealed accurate placement of Poribacteria. Besides phylogenetic analysis, two marker proteins were described for members of the PVC superphylum [26], [28]. Blast searches using representatives sequences of these signature molecules [26], [28] as query against the poribacterial SAG sequences did not show the presence of any PVC marker. This lack of a PVC marker proteins provides further support for the independent phylogenetic position of Poribacteria.

Genomic Evidence for Microcompartments

Cell compartmentalization is one characteristic that has been proposed for Poribacteria based on ring shaped fluorescence in situ hybridization (FISH) signals and the electron microscopic observations of compartmentalized prokaryotic cells in the mesohyl of the sponge Aplysina aerophoba [5]. The observed structures appeared similar to those described for many members of the Planctomycetes [29] and most specifically for Gemmata obscuriglobus where the compartment was proposed to be a nucleus-like structure [30]. The existence of cell compartmentalization in members of the PVC superphylum was later connected to the occurrence of membrane coat like proteins encoded on the genome [31]. To further investigate the possibility of cell compartmentalization in Poribacteria, we searched poribacterial SAGs for possible genomic evidence of such features. We were not able to find membrane coat like proteins or any genomic indication of large cell compartments. This is in accordance with a recent study which challenged the concept of the existence of these compartments even in other bacteria and confutes the existence of a nucleus-like structure in G. obscuriglobus [32].

Our analysis did reveal evidence for a possible occurrence of bacterial microcompartments (BMCs) in Poribacteria. Four of six poribacterial SAGs encoded for genes with hits to either one of two pfam domains namely, pfam00936 BMC or pfam03319 EutN CcmL (Table 2). These domains are considered markers for BMC shell proteins. Specifically, we identified three regions with conserved genomic structure between different poribacterial SAGs (groups A-C) (Fig. 3) that encoded for genes with these domains. A fourth region (group D) was identified on SAG 4E with two BMC shell proteins enclosing a set of 21 genes (Fig. 3). A detailed description of these groups can be found in Text S1 and tables S2, S3, S4, and S5. BMCs are proteinaceous structures that enclose sets of enzymes of diverse functions performing a chain of reactions within the compartment [33]. BMC shell functions have been described as concentrating enzymes and substrates together to increase reaction efficiency, protection of e.g. oxygen sensitive enzymes, enclosure of toxic or volatile metabolites that are produced/consumed by enzymes in the shell, and concentrating metabolites to increase efficiency [33], [34]. Kerfeld et al. [33] suggested that at least two (or more) pfam00936 domain proteins and one pfam03319 domain protein might be required as building blocks of functional BMCs. Out of all poribacterial SAGs only 4E encoded for more than one pfam00936 domain and, with the exception of SAG 4CII, all poribacterial SAGs encoded for a higher number of pfam03319 than pfam00936 domains (Table 2). This is unusual when compared to most other BMC shell protein studied to date (Table S6). Poribacteria, together with Planctomycetes, the candidate phylum Atribacteria (OP9), and some additional phyla (Table S6), appear to be among the few exceptions containing more pfam03319 than pfam00936 domains.

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Figure 3. Schematic view of poribacterial BMC shell protein groups.

For a better overview all genes are displayed in 5′-3′ direction of the BMC shell protein gene. The actual strand orientation might be different and is indicated by plus or minus signs. Genes are shown with locus taq and amino acid identities based on IMG/MER homology searches are shown between genes where applicable. BMC shell protein genes are shown in white, other genes with homologies between different SAGs are shown in dark grey, other genes are shown in light grey.

http://dx.doi.org/10.1371/journal.pone.0087353.g003

The so far best described BMC functions are the carboxysome and BMCs containing enzymes for ethanolamine or propanediol utilization. Bioinformatic analysis of all available BMC shell protein encoding genomic regions at the time by Yeates et al. [35] revealed that functional proteins within the BMCs are often encoded in close proximity of the BMC shell proteins and identified a set of functions regularly occurring with BMC shell proteins. However, the genes in poribacterial BMC clusters did not show direct similarities to any of these previously described functions but some genes in poribacterial BMC clusters give an indication of potential functions. It is noteworthy that many of the described enzymatic reactions in previously described BMCs are co-factor dependent (often vitamin B12), and that the co-factor biosynthesis genes were often found in close proximity to BMC shell protein genes [33]. In poribacterial BMC group B we found genes for riboflavin (vitamin B2) biosynthesis, which might indicate a riboflavin dependent process occurring in poribacterial BMCs. Riboflavin is a major cofactor in many processes of the energy metabolism. To our knowledge riboflavin biosynthesis genes have so far not been described from other BMC shell gene clusters. Further investigations will reveal, whether there are indeed BMCs with riboflavin dependent reactions. Furthermore, poribacterial BMC gene clusters show similar regulatory systems to previously described clusters. A recent study by Jorda et al. [36] identified clusters of BMCs shared between different organisms by comparing similarities of genes in the genomic neighborhoods of BMC shell proteins. They identified two BMC clusters that are characterized by a two-component regulatory system with a signal transduction histidine kinase and response regulator receiver [36]. Poribacterial BMC clusters appear to be similarly regulated, since we also detected genes of a two-component regulatory system in three out of four described poribacterial BMC groups (see Fig. 3, text S1, and tables S2S5). However, none of the functional genes on poribacterial BMC clusters showed similarities to those on the clusters described by Jorda et al. [36] and therefore the true functions of poribacterial BMCs remain to be investigated.

It is suspected that novel BMC functions will be revealed in the future [36] especially from genomes with a more scattered operon structure [33]. This might also be the case for Poribacteria where the identified genomic regions with BMC shell protein genes (group A-C) appear scattered across the genome. For example, the different BMC shell protein genes (with pfam00936 and pfam03319) are generally in different genomic regions on poribacterial genomes and not encoded together within one region, as it is the case for many so far functionally characterized BMC types [33]. Functional components of poribacterial BMCs might therefore also be encoded on different genomic regions. Alternatively, the existence of only one pfam00936 domain and the occurrence of transposase genes in BMC gene clusters B and D (see text S1) might indicate lack of function [33]. Future efforts are needed to resolve this issue for Poribacteria.

Eukaryote-like Repeat Proteins

Eukaryote-like repeat domain containing proteins have received much recent attention in sponge microbiology and their involvement in mediating host-microbe interactions has been postulated. Especially ankyrin (ANK) and tetratricopeptide repeats (TPR) have been in focus of such investigations [37][39]. To examine the role of these domains on poribacterial SAGs we searched for proteins with pfam hits to repeat and eukaryote-like domains in the IMG/MER database and also compared these to all finished genomes of free-living marine bacteria available in the IMG database in July 2013 (n = 98). We detected 41 such domains on poribacterial SAGs. The majority of these showed a higher domain frequency per total genes on at least one poribacterial SAG when compared to the average frequency of this domain on genomes of free-living marine bacteria (Fig. 4, Table S7). For 14 pfam domains the frequency on poribacterial genomes was even higher than the maximum frequency of this domain on the genome of any free-living marine bacterium. Many domains occurred simultaneously on the same genes with a total of 668 domains in all poribacterial SAGs on 490 encoded proteins (3A: 15 domains on 11 genes, 3G: 335 domains on 240 genes, 4C: 95 domain on 75 genes, 4CII: 24 domains on 16 genes, 4E: 181 domains on 135 genes, and 4G: 17 domains on 8 genes).

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Figure 4. Bar plot showing frequency of eukaryote-like pfam domains found on poribacterial SAGs in comparison to the average and maximum frequency on all finished genomes of marine free-living bacteria available in IMG in July 2013.

http://dx.doi.org/10.1371/journal.pone.0087353.g004

Among the most abundant domains were TPRs with pfams 013414, 00515, 07719, 13432, 13174, and 13181, which were also represented by eight other pfams (13424, 13374, 13371, 09976, 13431, 13429, 13428, and 13176) but in lower abundances. We were also able to find Sel1 repeat like proteins domains encoded on poribacterial SAGs 3G and 4E (0.02 and 0.15% of total genes, respectively) which have a similar structure to TPRs [40]. In total TPRs represented the highest frequency of repeat domains on poribacterial SAGs. Furthermore WD40 domains (pfam00400) were highly abundant on poribacterial SAGs, as well as two-copy leucin rich repeats (LRR) (pfam 12799), and the VCBS domain (pfam 13517) which is a domain found in high numbers in the genera Vibrio, Colwellia, Bradyrhizobium and Shewanella. Pfam domain 07593- ASPIC and UNbV was also present on several poribacterial SAGs in multiple copies. ANK repeat domains were detected (pfam 12796, 13637, 13857, and 00023) in lower numbers on a total of 14 genes on SAGs 3G, 4C and 4E (Table S7). The frequency of genes with pfam domains representing ankyrin repeats was often higher than average compared to the genomes of free-living marine bacteria (Table S7).

The occurrence of low-density lipoprotein (LDL) receptor repeat class B domains (pfam00058) on poribacterial genomes seemed noteworthy. We found these domains on one gene in each SAG 4C and 4E as well as on five genes in SAG 3G. Outside of Poribacteria this domain has only been found in proteins of 14 bacterial genomes but not in archaeal genomes publically available at the IMG/MER database in July 2013. Most of these bacterial hits however do not show the tandem repeats that are characteristic for this domain in eukaryotes. Such tandem repeats were only detected in the poribacterial proteins and proteins of four other bacterial genomes. Amongst these were free-living marine cyanobacteria (Cyanothece species, Pleurocapsa sp. PCC 7327), the marine deep sea piezophile Mortiella sp. PE36, and the strictly anaerobic bacterium Paludibacter propionicigenes WB4, DSM 17365. The LDL receptor is best described in mammals where they transport ligands into the cell for degradation by lysosomes and plays a role in cholesterol homeostasis [41]. The LDL repeat domain class B is part of the region of the LDL receptor which is responsible for ligand release and receptor recycling [42]. Virtually nothing is known about such domains in bacteria and it remains to be investigated whether there is a real connection to eukaryotic domains.

Although the limited data did not allow for any functional assignments of the LDL receptor genes, a role on the cell surface seems very likely in Poribacteria since all of the discovered genes with these domains had predicted transmembrane helices (TMHs) (∼86%) with the majority of the protein located outside of the cell or signal peptides (SPs) (∼14%). TMHs and SPs were also frequently predicted on genes representing other eukaryote-like proteins of Poribacteria (Table S8 and S9). High abundances (≥50% of genes with this pfam) of either TMHs or SPs were found on genes also encoding for bacterial Ig like domain protein genes, PQQ enzyme repeat containing genes, fibronectin type III domain and cadherin domain genes. Also genes with some of the pfams domains representing LRR and TPRs showed strong representation of TMH and SPs. Additionally, many poribacterial eukaryote-like domain genes (especially WD40 repeats) encoded for a domain potentially belonging to the Por secretion system C-terminal sorting domain family (TIGR04183) (Table S9), which is characteristic of proteins with outer membrane locations [43][45]. Since structural genes of the Por secretion system were not found on poribacterial genomes a potential secretion pathway for gene products with this domain remains to be revealed.

Our findings support previous reports of repeat and eukaryote-like domains being highly abundant in symbionts of marine sponges. The identification of proteins with these domains from the microbial communities of the sponge Cymbastella concentrica by ways of metaproteogenomics [46] might point towards an active functional role of these proteins. ANK domain proteins of sponge symbionts have been suspected to be involved in preventing phagocytosis by the sponge host as in analogy to similar functions of ANK domain proteins in bacterial pathogens Legoniella pneumophila or Coxiella burnetti [39], [47]. Indeed, in a recent paper Nguyen et al. [48] were able to show that ANK proteins from a marine sponge symbiont that were expressed in E.coli prevent phagocytosis of the bacterial cells by amoeba. The authors suggested this to be a function of sponge symbionts to avoid digestion by their host [48]. Thus, poribacterial ANK proteins may also facilitate similar functions.

LRRs have been found in proteins of pathogenic bacteria such as Yersinia species where LRRs are part of important virulence factors [49] or Listeria monocytogenes which encodes for LRR containing protein InlB that aids in host cell invasion [50]. Also TPRs were shown to be involved in different functions of pathogenesis [51] and fibronectin domains were shown to play a role in host-pathogen interactions as well, although in this case bacterial proteins bind to the fibronectin domains of the host protein [52], [53]. It would be interesting to explore whether bacterial fibronectin domains might be used in a similar way. Furthermore, fibronectin III domains have been found in polysaccharide degrading extracellular enzymes of Clostridium thermocellum [54]. Hentschel et al. [47] speculated that such functions in sponge symbionts could be connected to interactions with molecules of the sponge host extracellular matrix and our recent investigations of poribacterial carbohydrate degradation potential [14] support this hypothesis. However, at the current stage, we are just beginning to decipher the real functions of eukaryote-like proteins in Poribacteria. As many of these proteins may not be located outside of the poribacterial cell, as indicated by the large amount of proteins detected without TMHs or SPs (Table S9), it appears likely that at least some may mediate intracellular protein-protein interactions.

High Abundance of phyH -domain Containing Proteins

Among poribacterial genomes we found a remarkably high occurrence of genes encoding for proteins with pfam domain pfam05721-phyH (Table S10). This pfam describes a protein family containing eukaryotic phytanoyl-CoA dioxygenase proteins, ectoine hydroxylases from eukaryotes and prokaryotes, and several bacterial deoxygenases of mostly unknown function (http://pfam.sanger.ac.uk/family/PF05721). These proteins are Fe(II) and 2-oxoglutarate dependent oxygenases that catalyze a wide range of oxidative reactions Among bacterial phyH genes are some potentially involved in quorum sensing [55], [56], synthesis of the compatible solute 5-hydroxyectoine [57], and utilization of phosphorous sources [58], [59]. We screened for this domain in all genomes publically available in the IMG/MER database in July 2013. All poribacterial genomes showed a frequency of more than 1.9% genes with this domain per total number of genes (Table S10). All other genomes available in the database at the time (independent of its domain Bacteria, Archaea, or Eukaryota) showed a frequency of less than 0.049% of genes with this domain per total genes. This large abundance of genes belonging to the same pfam family might indicate an importance of the related functions for Poribacteria.

A clustering analysis of poribacterial sequences showed that there was large diversity amongst poribacterial phyH family genes with 305 sequences clustering in 193 clusters with 60% aa id threshold (Table S11). For the majority of poribacterial genes with this domain a reliable functional annotation could not be made. Best homologies were usually between genes of poribacterial SAGs, despite the high diversity indicated by the clustering analysis. Some of the poribacterial phyH family genes also showed homology to another uncharacterized deoxygenase encoded on the first genome fragment sequence from a poribacterial metagenome clone 64K2 [60]. This might indicate Poribacteria-specific functions within the phyH family.

Although the majority of poribacterial phyH genes remained without further functional characterization, we were still able to make functional predictions in some cases. Poribacterial SAGs 3G and 4E encoded for phyH genes (OID 2265144857 and 2265139858, respectively) with homologies (40% aa id each) to a 2-aminoethylphosphonate (2-AEPn) utilization gene (phnY) for which function was experimentally proven [59]. These poribacterial genomes also encoded directly upstream of this gene for a protein of the HD phosphohydrolase family (phnZ) (OID 2265144856 in 3G and 2265139857 in 4E), which is the only other gene involved in this 2-AEPn utilization pathway [59]. Both poribacterial genomes further encoded for another predicted phosphohydrolase downstream of the previously described genes with as of yet unknown function in this pathway. 2-AEPn is assumed to be one of the biggest sources of dissolved organic phosphorous in the oceans [61], [62] and represents an alternative phosphorous source to the often limited dissolved inorganic phosphorous. The use of dissolved organic phosphorous i.e. phosphonates by many marine bacteria has been described before [63], [64]. Phosphonates such as 2-AEPn are found largely in phospholipids of marine invertebrates including sponges and are also produced by some marine bacteria [65][68]. Therefore organic phosphorous sources should be largely available in the sponge mesohyl and the ability to utilize 2-AEPn as a phosphorous source might therefore be a competitive advantage. The presence of both genes identified as essential for 2-AEPn utilization [59] indicated the presence of this pathway also in Poribacteria and elucidated one possible function of phyH superfamily genes in this candidate phylum.

Conclusion

Our study demonstrates the power of single-cell genomics to reveal novel features of the candidate phylum Poribacteria which are almost exclusively found in association with marine sponges. Here we show by use of phylogenetic and phylogenomic analyses that Poribacteria are not members of the PVC superphylum, but rather form a distinct monophyletic phylum in close proximity. We provide genomic evidence for bacterial microcompartments in Poribacteria that show no similarity to any previously described BMCs. Further novel functions might be hidden in the various eukaryote-like protein domains, which may be involved in mediating host-microbe interactions within the sponge holobiont. The high abundance of diverse phyH-domain containing proteins points to important and potentially specific functions in Poribacteria. Most of these functions remain to be revealed in future studies but some show the genomic potential for organic phosphorous utilization. Our analyses show how genome sequences can help to revisit past hypotheses and at the same time open the way for new investigations by revealing novel functional features. Challenges for the future will be to experimentally demonstrate function and to ultimately understand the implications for symbiosis.

Supporting Information

Table S1.

83 marker genes used for phylogenetic analysis.

doi:10.1371/journal.pone.0087353.s001

(PDF)

Table S2.

BMC group A genes with annotation.

doi:10.1371/journal.pone.0087353.s002

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Table S3.

BMC group B genes with annotation.

doi:10.1371/journal.pone.0087353.s003

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Table S4.

BMC group C genes with annotations.

doi:10.1371/journal.pone.0087353.s004

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Table S5.

BMC group D genes with annotation.

doi:10.1371/journal.pone.0087353.s005

(PDF)

Table S6.

BMC shell protein pfam domain distribution on all genomes with either domain in IMG in July 2013.

doi:10.1371/journal.pone.0087353.s006

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Table S7.

Overview of gene copy numbers (no) and percentage of genes per total genes on genome (%) of repeat proteins and eukaryote like protein domain genes on poribacterial SAGs and the maximum and average number of gene copies found on X finished genomes of marine free-living bacteria (n = 101).

doi:10.1371/journal.pone.0087353.s007

(PDF)

Table S8.

List of all repeat and eukaryote like domain protein encoding genes on poribacterial SAGs. Information is shown as available in IMG/MER system. THM: number of predicted transmembrane helicies. SP: signal peptide predicted yes (Y) or no (N).

doi:10.1371/journal.pone.0087353.s008

(PDF)

Table S9.

List of total repeat and eukaryote like protein domain encoding genes of poribacterial SAGs showing the number of genes (# genes), the number of genes with transmemebrane helicies (# TMH), percentage of genes with transmembrane helicies (% TMH), number of genes with signal peptide (# SP), and percentage of genes with signal peptide (% SP) for each domain.

doi:10.1371/journal.pone.0087353.s009

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Table S10.

phyH domain distribution on publically available genomes.

doi:10.1371/journal.pone.0087353.s010

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Table S11.

Poribacterial phyH gene clusters based on 60% amino acid identity.

doi:10.1371/journal.pone.0087353.s011

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Text S1.

Genomic evidence for microcompartments in Poribacteria. (extended description of genomic architecture)

doi:10.1371/journal.pone.0087353.s012

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Acknowledgments

We gratefully acknowledge Dr. Kristina Bayer (University of Wuerzburg) for logistical support.

Author Contributions

Conceived and designed the experiments: JK UH. Performed the experiments: JK. Analyzed the data: JK CR PS KM NI AS TW. Contributed reagents/materials/analysis tools: JK CR TW UH. Wrote the paper: JK UH.

References

  1. 1. Kamke J, Bayer K, Woyke T, Hentschel U (2012) Exploring symbioses by single-cell genomics. Biol Bull 223: 30–43.
  2. 2. Stepanauskas R (2012) Single cell genomics: an individual look at microbes. Curr Opin Microbiol 15: 613–620.
  3. 3. Rinke C, Schwientek P, Sczyrba A, Ivanova NN, Anderson IJ, et al. (2013) Insights into the phylogeny and coding potential of microbial dark matter. Nature 499: 431–437.
  4. 4. Kamke J, Sczyrba A, Ivanova N, Schwientek P, Rinke C, et al. (2013) Single-cell genomics reveals complex carbohydrate degradation patterns in poribacterial symbionts of marine sponges. ISME J 7: 2287–2300.
  5. 5. Fieseler L, Horn M, Wagner M, Hentschel U (2004) Discovery of the novel candidate phylum “Poribacteria” in marine sponges. Appl Environ Microb 70: 3724–3732.
  6. 6. Pham VD, Konstantinidis KT, Palden T, DeLong EF (2008) Phylogenetic analyses of ribosomal DNA-containing bacterioplankton genome fragments from a 4000 m vertical profile in the North Pacific subtropical gyre. Environ Microbiol 10: 2313–2330.
  7. 7. Webster NS, Taylor MW, Behnam F, Lücker S, Rattei T, et al. (2010) Deep sequencing reveals exceptional diversity and modes of transmission for bacterial sponge symbionts. Environ Microbiol 12: 2070–2082.
  8. 8. Taylor MW, Tsai P, Simister RL, Deines P, Botte E, et al. (2013) “Sponge-specific” bacteria are widespread (but rare) in diverse marine environments. ISME J 7: 438–443.
  9. 9. Lafi FF, Fuerst JA, Fieseler L, Engels C, Goh WWL, et al. (2009) Widespread distribution of Poribacteria in Demospongiae. Appl Environ Microb 75: 5695–5699.
  10. 10. Schmitt S, Tsai P, Bell J, Fromont J, Ilan M, et al. (2012) Assessing the complex sponge microbiota: core, variable and species-specific bacterial communities in marine sponges. ISME J 6: 564–576.
  11. 11. Taylor MW, Radax R, Steger D, Wagner M (2007) Sponge-associated microorganisms: Evolution, ecology, and biotechnological potential. Microbiol Mol Biol R 71: 295–347.
  12. 12. Schmitt S, Angermeier H, Schiller R, Lindquist N, Hentschel U (2008) Molecular microbial diversity survey of sponge reproductive stages and mechanistic insights into vertical transmission of microbial symbionts. Appl Environ Microb 74: 7694–7708.
  13. 13. Wagner M, Horn M (2006) The Planctomycetes, Verrucomicrobia, Chlamydiae and sister phyla comprise a superphylum with biotechnological and medical relevance. Curr Opin Biotech 17: 241–249.
  14. 14. Siegl A, Kamke J, Hochmuth T, Piel J, Richter M, et al. (2011) Single-cell genomics reveals the lifestyle of Poribacteria, a candidate phylum symbiotically associated with marine sponges. ISME J 5: 61–70.
  15. 15. Markowitz VM, Kyrpides NC (2007) Comparative genome analysis in the integrated microbial genomes (IMG) system. Methods Mol Biol 395: 35–56.
  16. 16. Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26: 2460–2461.
  17. 17. Quast C, Pruesse E, Yilmaz P, Gerken J (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 41: D590–D596.
  18. 18. Ludwig W, Strunk O, Westram R, Richter L, Meier H, et al. (2004) ARB: A software environment for sequence data. Nucleic Acids Res 32: 1363–1371.
  19. 19. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990) Basic local alignment search tool. J Mol Biol 215: 403–410.
  20. 20. Pruesse E, Peplies J, Glöckner FO (2012) SINA: accurate high-throughput multiple sequence alignment of ribosomal RNA genes. Bioinformatics 28: 1823–1829.
  21. 21. Stamatakis A (2006) RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics 22: 2688–2690.
  22. 22. Finn RD, Clements J, Eddy SR (2011) HMMER web server: interactive sequence similarity searching. Nucleic Acids Res 39: W29–W37.
  23. 23. Price MN, Dehal PS, Arkin AP (2010) FastTree 2–approximately maximum-likelihood trees for large alignments. PLoS ONE 5: e9490 doi:10.1371/journal.pone.0009490.
  24. 24. Stamatakis A, Aberer AJ, Goll C, Smith SA, Berger SA, et al. (2012) RAxML-Light: a tool for computing terabyte phylogenies. Bioinformatics 28: 2064–2066.
  25. 25. Wu D, Hugenholtz P, Mavromatis K, Pukall R, Dalin E, et al. (2009) A phylogeny-driven genomic encyclopaedia of Bacteria and Archaea. Nature 462: 1056–1060.
  26. 26. Gupta RS, Bhandari V, Naushad HS (2012) Molecular signatures for the PVC clade (Planctomycetes, Verrucomicrobia, Chlamydiae, and Lentisphaerae) of bacteria provide insights into their evolutionary relationships. Front Microbio 3. doi: 10.3389/fmicb.2012.00327.
  27. 27. Lang J, Lang J, Lang J, Darling A, Darling A, et al. (2013) Phylogeny of bacterial and archaeal genomes using conserved genes: supertrees and supermatrices. PLoS ONE 8: e62510 doi:10.1371/journal.pone.0062510.
  28. 28. Lagkouvardos I, Jehl MA, Rattei T, Horn M (2013) The signature protein of the PVC superphylum. Appl Environ Microbiol published ahead of print. doi:10.1128/AEM.02655-13.
  29. 29. Fuerst JA (2005) Intracellular compartmentation in planctomycetes. Annu RevMicrobiol 59: 299–328.
  30. 30. Fuerst JA, Webb RI (1991) Membrane-bounded nucleoid in the eubacterium Gemmatata obscuriglobus. Proc Natl Acad Sci USA 88: 8184–8.
  31. 31. Santarella-Mellwig R, Franke J, Jaedicke A, Gorjanacz M, Bauer U, et al. (2010) The compartmentalized bacteria of the Planctomycetes-Verrucomicrobia-Chlamydiae superphylum have membrane coat-like proteins. Plos Biol 8: e1000281 doi:10.1371/journal.pbio.1000281.t002.
  32. 32. Santarella-Mellwig R, Pruggnaller S, Roos N, Mattaj IW, Devos DP (2013) Three-dimensional reconstruction of bacteria with a complex endomembrane system. Plos Biol 11: e1001565 doi:10.1371/journal.pbio.1001565.s014.
  33. 33. Kerfeld CA, Heinhorst S, Cannon GC (2010) Bacterial Microcompartments. Annu Rev Microbiol 64: 391–408.
  34. 34. Yeates TO, Crowley CS, Tanaka S (2010) Bacterial microcompartment organelles: protein shell structure and evolution. Annu Rev Biophys 39: 185–205.
  35. 35. Yeates TO, Thompson MC, Bobik TA (2011) The protein shells of bacterial microcompartment organelles. Curr Opin Struc Biol 21: 223–231.
  36. 36. Jorda J, Lopez D, Wheatley NM, Yeates TO (2013) Using comparative genomics to uncover new kinds of protein-based metabolic organelles in bacteria. Protein Sci 22: 179–195.
  37. 37. Thomas T, Rusch D, DeMaere MZ, Yung PY, Lewis M, et al. (2010) Functional genomic signatures of sponge bacteria reveal unique and shared features of symbiosis. ISME J 4: 1557–11567.
  38. 38. Siegl A, Hentschel U (2009) PKS and NRPS gene clusters from microbial symbiont cells of marine sponges by whole genome amplification. Environ Microbiol Rep 2: 507–513.
  39. 39. Fan L, Reynolds D, Liu M, Stark M, Kjelleberg S, et al. (2012) Functional equivalence and evolutionary convergence in complex communities of microbial sponge symbionts. Proc Natl Acad Sci USA 109: E1878–E1887.
  40. 40. Mittl PR, Schneider-Brachert W (2007) Sel1-like repeat proteins in signal transduction. Cell Signal 19: 20–31.
  41. 41. Hussain MM, Strickland DK, Bakillah A (1999) The mammalian low-density lipoprotein receptor family. Annu Rev Nutr 19: 141–172.
  42. 42. Davis CG, Goldstein JL, Südhof TC, Anderson RG, Russell DW, et al. (1987) Acid-dependent ligand dissociation and recycling of LDL receptor mediated by growth factor homology region. Nature 326: 760–765.
  43. 43. Sato K, Naito M, Yukitake H, Hirakawa H, Shoji M, et al. (2010) A protein secretion system linked to bacteroidete gliding motility and pathogenesis. Proc Natl Acad Sci USA 107: 276–281.
  44. 44. Suen G, Weimer PJ, Stevenson DM, Aylward FO, Boyum J, et al. (2011) The complete genome sequence of Fibrobacter succinogenes S85 reveals a cellulolytic and metabolic specialist. PLoS ONE 6: e18814 doi:10.1371/journal.pone.0018814.
  45. 45. Nguyen KA, Travis J, Potempa J (2007) Does the importance of the C-terminal residues in the maturation of RgpB from Porphyromonas gingivalis reveal a novel mechanism for protein export in a subgroup of gram-negative bacteria? J Bacteriol 189: 833–843.
  46. 46. Liu MY, Kjelleberg S, Thomas T (2010) Functional genomic analysis of an uncultured delta-proteobacterium in the sponge Cymbastela concentrica. ISME J 5: 427–435.
  47. 47. Hentschel U, Piel J, Degnan SM, Taylor MW (2012) Genomic insights into the marine sponge microbiome. Nat Rev Micro 10: 641–654.
  48. 48. Nguyen MTHD, Liu M, Thomas T (2013) Ankyrin-repeat proteins from sponge symbionts modulate amoebal phagocytosis. Mol Ecol. In press. doi:10.1111/mec.12384.
  49. 49. Viboud GI, Bliska JB (2005) Yersinia outer proteins: role in modulation of host cell signaling responses and pathogenesis. Annu Rev Microbiol 59: 69–89.
  50. 50. Bierne H, Cossart P (2002) InlB, a surface protein of Listeria monocytogenes that behaves as an invasin and a growth factor. J Cell Sci.115: 3357–67.
  51. 51. Cerveny L, Straskova A, Dankova V, Hartlova A, Ceckova M, et al. (2013) Tetratricopeptide repeat motifs in the world of bacterial pathogens: Role in virulence mechanisms. Infect Immun 81: 629–635.
  52. 52. Schwarz-Linek U, Werner JM, Pickford AR (2003) Pathogenic bacteria attach to human fibronectin through a tandem beta-zipper. Nature 423: 177–181.
  53. 53. Schwarz-Linek U, Höök M, Potts JR (2004) The molecular basis of fibronectin-mediated bacterial adherence to host cells. Mol Microbiol 52: 631–641.
  54. 54. Kataeva IA, Seidel RD, Shah A, West LT, Li XL, et al. (2002) The fibronectin type 3-like repeat from the Clostridium thermocellum cellobiohydrolase CbhA promotes hydrolysis of cellulose by modifying its surface. Appl Environ Microb 68: 4292–4300.
  55. 55. Schofield CJ, McDonough MA (2007) Structural and mechanistic studies on the peroxisomal oxygenase phytanoyl-CoA 2-hydroxylase (PhyH). Biochem Soc Trans 35: 870–875.
  56. 56. Hao Y, Winans SC, Glick BR, Charles TC (2010) Identification and characterization of new LuxR/LuxI-type quorum sensing systems from metagenomic libraries. Environ Microbiol 12: 105–117.
  57. 57. Reuter K, Pittelkow M, Bursy J, Heine A, Craan T, et al. (2010) Synthesis of 5-hydroxyectoine from ectoine: Crystal structure of the non-heme Iron(II) and 2-oxoglutarate-dependent dioxygenase EctD. PLoS ONE 5: e10647 doi:10.1371/journal.pone.0010647.
  58. 58. White AK, Metcalf WW (2007) Microbial metabolism of reduced phosphorus compounds. Annu Rev Microbiol 61: 379–400.
  59. 59. Martinez A, Tyson GW, DeLong EF (2010) Widespread known and novel phosphonate utilization pathways in marine bacteria revealed by functional screening and metagenomic analyses. Environ Microbiol 12: 222–238.
  60. 60. Fieseler L, Quaiser A, Schleper C, Hentschel U (2006) Analysis of the first genome fragment from the marine sponge-associated, novel candidate phylum Poribacteria by environmental genomics. Environ Microbiol 8: 612–624.
  61. 61. Kolowith LC, Ingall ED, Benner R (2001) Composition and cycling of marine organic phosphorus. Limnol Oceanogr 46: 309–320.
  62. 62. Clark LL, Ingall ED, Benner R (1999) Marine organic phosphorus cycling: novel insights from nuclear magnetic resonance. Am J Sci 299: 724–737.
  63. 63. Villarreal-Chiu JF, Quinn JP, McGrath JW (2012) The genes and enzymes of phosphonate metabolism by bacteria, and their distribution in the marine environment. Front Microbio 3. doi: 10.3389/fmicb.2012.00019.
  64. 64. Dyhrman ST, Chappell PD, Haley ST, Moffett JW, Orchard ED, et al. (2006) Phosphonate utilization by the globally important marine diazotroph Trichodesmium. Nature 439: 68–71.
  65. 65. Mukhamedova KS, Glushenkova AI (2000) Natural Phosphonolipids. Chemistry of Natural Compounds 36: 329–341.
  66. 66. Dembitsky VM, Rezanka T, Srebnik M (2003) Lipid compounds of freshwater sponges: family Spongillidae, class Demospongiae. Chemistry and Physics of Lipids 123: 117–155.
  67. 67. Dembitskii VM (1988) Lipids of marine origin. IV. 1,2-Di-O-alkylglycerophospho- and -phosphonolipids from the marine sponge Ectyodoryx kovdaicum. Chem Nat Compd 24: 642–643.
  68. 68. Dyhrman ST, Benitez-Nelson CR, Orchard ED, Haley ST, Pellechia PJ (2009) A microbial source of phosphonates in oligotrophic marine systems. Nature Geosci 2: 696–699.