Introduction

The deep marine subsurface is one of the largest unexplored biospheres on Earth, and is estimated to contain up to 3 × 1029 microbial cells, a number equivalent to the combined microbial biomass of the oceanic water column and terrestrial soil (Kallmeyer et al., 2012). Microbial communities in the subseafloor depend on the supply of energy substrates and growth factors from the overlying surface world (that is, land and ocean) and/or the underlying lithosphere (that is, earth’s crust and mantle). The significant abundance of microorganisms in the marine subsurface suggests that they have been involved in global biogeochemical cycles over geological timescales (Parkes et al., 2002, 2005; D’Hondt et al., 2002a, 2002b, 2004). Most of these bacteria and archaea are phylogenetically distinct from previously cultured microorganisms (Biddle and Teske, 2008; Biddle et al., 2008; Lever et al., 2013; Rinke et al., 2013), and consequently their metabolic characteristics as well as ecological roles remain largely unknown.

Molecular environmental surveys have shown that the phylum Chloroflexi is particularly widely distributed in many deep-sea sediments, representing up to 80% of the total bacterial 16S rRNA gene sequences at some sites (Parkes et al., 2002; Webster et al., 2004; Inagaki et al., 2006; Webster et al., 2006; Fry et al., 2008; Blazejak and Schippers, 2010). Despite the ubiquity of subsurface Chloroflexi, these microorganisms have so far evaded cultivation attempts in the laboratory, and therefore essentially nothing is known about their metabolism or eco-physiology (D’Hondt et al., 2004; Toffin et al., 2004; Batzke et al., 2007; Webster et al., 2011). The few cultured representatives from the phylum Chloroflexi cover a wide metabolic spectrum, including aerobic organotrophs, anoxygenic phototrophs, nitrate reducers and anaerobic halorespirers (Yamada and Sekiguchi, 2009; Tas et al., 2010, Bryant et al., 2012; Krzmarzick et al., 2012; Sorokin et al., 2012).

Among the Chloroflexi 16S rRNA gene sequences found in deep-sea subsurface environments are those affiliated with the distinct class-level clade Dehalococcoidetes, consisting of Dehalococcoides mccartyi and Dehalogenimonas sp. (Parkes et al., 2002; Inagaki et al., 2003, 2006; Webster et al., 2004; Biddle et al., 2008, 2011; Blazejak and Schippers, 2010; Siddaramappa et al., 2012; Loeffler et al., 2013). Dehalococcoidetes were first isolated from chloroethene-contaminated terrestrial aquifer environments, and are strictly anaerobic, slow-growing and highly niche-adapted Chloroflexi that use organohalide respiration via reductive dehalogenases (Rdh) as their sole mode of energy conservation. Their small genomes range in size from 1.3 to 1.7 Mb, and these microorganisms depend on a supporting microbial community for acquisition of electron donors and cofactors (for example, H2 and cobalamin derivatives). So far only nine Dehalococcoidetes strains have been cultivated (Maymo-Gatell et al., 1997; Muller et al., 2004; He et al., 2005; Miller et al., 2005; Cheng and He, 2009; Moe et al., 2009; Siddaramappa et al., 2012; Loeffler et al., 2013; Poritz et al., 2013).

While Dehalococcoidetes are mostly undetectable by molecular methods in non-contaminated freshwater environments, a pioneering study by Futagami et al. (2009) discovered Dehalococcoidetes and novel putative reductive dehalogenase genes (rdh) in deep-sea sediments from the southeast Pacific off Peru, the eastern equatorial Pacific, the Juan de Fuca Ridge flank off Oregon (USA) and the northwest Pacific off Japan. The abundant detection of both Dehalococcoidetes 16S rRNA gene sequences and rdh genes in conjunction with the previously identified terrestrial chloroethene-reducing Dehalococcoidetes suggested the presence of dissimilatory dehalorespiration in pristine marine subsurface sediments of the Pacific as an ecologically significant microbial activity (Futagami et al., 2009). However rdh genes have so far never been linked to Dehalococcoidetes from subsurface environments.

We therefore initiated a study probing for a linkage between deep-sea sediment Dehalococcoidetes 16S rRNA and rdh gene sequences in a non-contaminated deep-sea sediment sample obtained from the Peruvian Margin site 1230 (Ocean Drilling Program (ODP) expedition 201) (Supplementary Figure 1) (D’Hondt et al., 2003b). We employed molecular and single cell genomic approaches as the methods of choice to provide fundamental insights into the in situ metabolic lifestyle of Dehalococcoidetes-like Chloroflexi in these non-contaminated and poorly understood environments.

Materials and methods

DNA extraction and screening

DNA was extracted and screened from 31 deep-sea sediment samples originating from the eastern equatorial Pacific, the southeast Pacific off Peru (Peruvian Margin, ODP Leg 201), the northeast Pacific at the Juan de Fuca Ridge flank off Oregon, USA (IODP Expedition 301), the northwest Pacific off Japan (JAMSTEC Chikyu Shakedown Expedition CK06-06) and the Nankai Trough Forearc Basin off Japan (ODP Expedition 315) (Supplementary Table 1). DNA was extracted from 5 to 8 g of sample using various methods, ranging from the method described by Futagami et al. (2009) to phenol-chloroform extraction and/or using the FastDNA SPIN Kit for Soil (MP Biomedicals, Solon, OH, USA). The best method to extract DNA, while avoiding excessive co-extraction of humic acids, was found to be a modified FastDNA SPIN Kit for Soil extraction protocol (for details, see Supplementary Information). One microliter of extracted DNA was amplified by multiple displacement amplification (MDA) (Lasken, 2007) in three independent reactions using the Repli-g Mini Kit for single cells (Qiagen, Hilden, Germany). Amplified DNA was then recovered using the QiAamp kit (Qiagen). DNA concentration for PCR screening ranged from 50 to 100 ng μl−1. 16S rRNA genes were amplified using broad eubacterial primers 27F (5′-AGAGTTTGATCMTGGCTCAG-3′) and 1391R (5′-GACGGGCRGTGWGTRCA-3′) (Lane, 1991), rdh genes using primers RFF2 (5′-SHMGBMGWGATTTYATGAARR-3′) and B1R (5′-CHADHAGCCAYTCRTACCA-3′) (Krajmalnik-Brown et al., 2004; Futagami et al., 2009) and ssrA genes using primers tmRNA_Dehalococcoidetes_U_dhg_f_deg (5′-GGGANGCGTGNNTTCGAC-3′) and rec02R (5′-TGCGGWATGCCVATGTGG-3′) (McMurdie et al., 2011). PCR was performed with 0.5 μM of each primer in 50 μl volumes. For details of PCRs, see Supplementary Table 2. PCR products were cloned using the TOPO TA cloning kit (Invitrogen, Carlsbad, CA, USA) and subsequently Sanger sequenced.

Nanoliter-qPCR screening

A panel of novel qPCR primer pairs was developed (Mayer-Blackwell and Spormann, 2014) (Supplementary Table 3) to detect a large fraction of known reductive dehalogenase genes (rdhA) at a single annealing temperature and buffer composition. Non-redundant full-length and near full-length rdhA gene sequences curated in the protein family Pfam PF13486 as of July 2012 (Punta et al., 2012) were clustered based on the percent identity (PID) using an all-vs-all blastp (Altschul et al., 1990). Sequences considered ranged between 350 and 700 amino acids. Specific assays were designed for 50 reference sequences, each with at least one known high PID homolog. Thousand of candidate primer pairs were generated using primer3 (Rozen and Skaletski, 2000) and filtered based on complementarity to at least three distinct sequences sharing high PID to the reference sequence. Where possible, lack of complementarity to homologs with lower PID was used as additional criteria in assay selection. Our overall collection of assays included two types of PCR primer sets. The first one was highly specific to an rdh reference sequence and those homologs with high PID (usually >90% at the amino-acid level) to the reference. The second type was of broader specificity to extend the number of sequences matched to include the reference sequence and as many homolog sequences as possible, regardless of the level of PID with the reference.

Over 600 candidate assays were physically tested in a nanoliter-qPCR platform (WaferGen Biosystems Inc., Fremont, CA, USA) against a collection of 500 bp linear DNA standards (Integrated DNA Technology, Coralville, IA, USA) that were diluted to approximate concentrations of 20 000, 2000, 200 and 20 copies per 100 nl reaction well. Of those 600 assays tested, 170 assays were selected on the basis of high PCR efficiency (>90%) and the sensitivity to detect target at <10 gene copies per reaction. In all, this validated panel of assays covered 233 of 389 distinct sequences in the dehalogenase protein family, including a third of the sequences previously recovered from the most comprehensive deep-sea sediment survey of reductive dehalogenases to date (Futagami et al., 2009). The other sequences not targeted by the panel had no high PID homologs, making them less-suitable candidates for assay development.

DNA samples were applied to nanoliter-qPCR chip at concentration ranging from 1 to 50 ng μl−1 (Supplementary Table 4). In separate wells, positive control standards for a larger fraction of assays were supplied at a concentration of 500 copies per reaction well. A chip wide positive control consisting of three Mus musculus gene fragments was spiked into the master mix at a concentration of 400 copies per reaction to test whether inhibitory compound—typical in DNA extractions from sediment environments—affected the rate of DNA amplification. The spike-in amplified uniformly across the samples suggesting that inhibitory effects were minimal if at all present. The reactions were carried out according to the instrument manual specifications with Roche (Basel, Switzerland) Lightcycler 480 SYBR Master Mix. The PCR program was as follows: 95 °C for 3 min, then 40 cycles of: 95 °C for 1 min and 60 °C for 1:10 min.

Single cell sorting via Fluorescent Activated Cell Sorting and amplification of single cell DNA using MDA

A frozen deep-sea sediment sample of the Peruvian Margin drill site 1230 (ODP 201), collected 7.3 meters below seafloor (mbsf) and stored at −80 °C without glycerol preservation for 8 years, was used for single cell genome analysis. Physical isolation of the single cells was performed by Fluorescent Activated Cell Sorting in two 384-well plates (630 single cells, 6 positive controls and 132 negative controls). The sample processing was performed at the Bigelow Laboratory Single Cell Genomics Center (www.bigelow.org/scgc). Single cells were lysed, and the DNA was amplified by MDA as described previously (Swan et al., 2011). In all, 250 wells showed good amplification with a Cp value of <10 h (∼40%). DNA was screened with broad eubacterial (27F-M13: 5′-AGRGTTYGATYMTGGCTCAG-3′/907R_degen-M13: 5′-CCGTCAATTCMTTTRAGTTT-3′) and archaeal (Arc_344F-M13: 5′-ACGGGGYGCAGCAGGCGCGA-3′/Arch_915R-M13R: 5′-GTGCTCCCCCGCCAATTCCT-3′) 16S rRNA primers (Lane, 1991; Shapiro, 2000; Zhu et al., 2005) and Sanger sequenced. Analysis with the RDB (Ribosomal Database) (Cole et al., 2009) yielded 33 hits (5.2% of all single cells sorted, 13.2% of successful MDA reactions), including three Chloroflexi single cells. The single Chloroflexi cells showed a 16S rRNA sequence by Sanger most similar to Dehalogenimonas (Figure 1). The first MDA products yielded 500–900 ng of DNA after clean up with the QIAamp DNA kit (Qiagen). The first MDA products of the three single cells were re-amplified in a second MDA. To avoid additional bias, the second MDA was performed in four separate reactions that were subsequently combined at the end.

Figure 1
figure 1

Phylogenetic tree of cultured and sequenced Chloroflexi including three single Dsc cells from a deep-sea sediment sample of the Peru Margin 1230 site collected 7.3 mbsf. The tree was generated using the Geneious tree builder software (Auckland, New Zealand) (gap cost matrix of 51% similarity (5.0/−3.0), gap open penalty of 12, gap extension penalty of 3, global alignment, Jukes Cantor genetic distance model and neighbor joining as tree building method with no outgroup). Two of the isolated Dsc single cells showed an identical 16S rRNA sequence. All three single cells belong to the class Dehalococcoidetes, including Dehalococcoides and Dehalogenimonas sp.The closest cultivated isolate was Dehalogenimonas lykanthroporepellens strain BL-DC-9, which had 83% sequence identity with the 16S rRNA gene of Dsc1 and 87% sequence identity with DscP2.

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Sequencing with Illumina HighSeq and PacBio RS

The first MDA products of the single cells were sequenced separately on an Illumina HighSeq platform (San Diego, CA, USA) using Nextera library preparation with an average yield of 15 000 Mb and 150 000 000 reads with 2 × 100 bp read length. The second MDA products were sequenced using the PacBio RS Magbead CLR sequencing technique (Menlo Park, CA, USA), resulting in a mean read length of over 2.5 Kb and ∼100 Mb raw sequence data. Sequencing was carried out according to the manufacturer’s instructions and resulted in 12 Mb raw sequence data for single cell 1 and 190 Mb for single cells 2 and 3.

Assembly and bioinformatics

After quality assessment, trimming and/or normalization of the sequencing reads, bioinformatics tools were used to conduct the assembly, open reading frame calling and annotation of the genes (see Supplementary Information). Analysis with PRINSEQ (http://prinseq.sourceforge.net/) revealed a high exact duplication rate (>90%) in all three raw Illumina data sets. Analysis of the reads showed differences in coverage of up to 4 orders of magnitude, indicating large bias in the first MDA reaction (Supplementary Figure 2). Different strategies were applied to assemble the reads of the individual cells and improve the assembly with gap-closing strategies (Supplementary Table 4) (Bankevich et al., 2012; Koren et al., 2012). Single cells 2 and 3 were assembled together since they showed almost 100% identity at the nucleotide level after individual assembly (Figure 2). At this stage, a 0.32-Mb assembly was contained in 126 contigs for single cell 1 and a 1.38-Mb assembly in 327 contigs for the co-assembly of single cells 2 and 3.

Figure 2
figure 2

Nucleotide identity comparison of the individual assemblies of single cells Dsc1, 2 and 3. An all-vs-all blastn was conducted on predicted coding nucleotide sequences (RAST, Aziz et al 2008) from each isolate, using Dsc single cell 2 as the reference genome. The default blastall parameters were used with an e-value cutoff of 0.001. A custom python script was used to sort the best single alignment (if any) for each predicted coding gene in the reference genome and comparison genomes. Alignments shorter than 50 bp in length were excluded. A density plot of the percent identity for each alignment is visualized using the R statistical environment.

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Genome annotation, estimation of completeness and size

Assembled contigs were submitted to the Integrated Microbial Genomes database annotation pipeline (IMG, version 4.1) (Markowitz et al., 2010) and to the Rapid Annotations using Subsystems Technology pipeline (RAST, version 4.0) (Aziz et al., 2008) in 2013. Some computationally assigned annotations were manually changed based on the inspection of evidence for the assigned annotations, orthologs in related genomes and gene neighborhoods. Pathways were predicted using RAST, IMG and KEGG (Kyoto Encyclopedia of Genes and Genomes) (Kanehisa and Goto, 2000; Aziz et al., 2008; Markowitz et al., 2010). Nucleotide and amino-acid sequences of genes were blasted (Altschul et al., 1990; Altschul and Koonin, 1998) as query sequences against the NCBI databases (using an e-value threshold of 10−5). Gene annotations described in Results section together with the fasta nucleotide and amino-acid sequences of Dcs1 and DscP2 (for deep-sea C hloroflexi (Dsc) population) including annotations are listed in Supplementary Documents 1 (Dcs1.faa), 2 (Dcs1.fna), 3 (DscP2.faa) and 4 (DscP2.fna), respectively.

Sequence accession

The genomic data (contigs longer than 200 bp) are present as BioProjects with the accession numbers PRJNA222231 for Dsc1 and PRJNA227210 for DscP2 and has been deposited at GenBank under the accession JARM00000000 for Dsc1 and JARN00000000 for DscP2. The version described in this paper is version JARN01000000 and JARM01000000, respectively.

Results and discussion

Single cell source

We analyzed total DNA extracted from several deep-sea sediments from the Peruvian Margin and other Pacific sites for the presence of Dehalococcoidetes 16S rRNA and rdh genes by PCR and nanoliter-qPCR (Supplementary Tables 1 and 4). On the basis of these screening results, we identified a sample obtained from the Peruvian Margin trench site 1230, collected at 7.3 mbsf as promising for further investigation by single cell genomics. Consequently, cells from this site were extracted, sorted by Fluorescent Activated Cell Sorting in 384-well plates, lysed and amplified via MDA. A flow diagram of the procedure is shown in Supplementary Figure 3. Out of 630 single cells sorted we identified three Chloroflexi cells, designated as Dsc (Deep-sea Chloroflexi) 1, 2 and 3.

Site 1230 is located on the lower slope of the Peru Trench at 5086 m water depth. Sediments of this area are part of an accretionary wedge just landward of the Peru Trench (Suess and von Huene, 1988) (Supplementary Figure 1). The surface waters at the Peruvian Margin are part of Peru’s upwelling system and are biologically highly productive, with a total organic content of ∼2–3 wt% (D’Hondt et al., 2003a, 2003b). The upper 20 m of the sediment column contains a narrow suboxic zone with a steep sulfate gradient, and sulfate reduction is the dominant mineralization process. The gradient is nearly linear indicating that most of the net sulfate reduction takes place at the sulfate/methane interface (Iversen and Jorgensen, 1985; Borowski et al., 1996, 2000; Niewohner et al., 1998), and methane builds up steeply at the sulfate boundary. There was also visual evidence of methane hydrates (Kvenvolden et al., 1990; Kvenvolden and Kastner, 1990; Suess et al., 1990) (Supplementary Figure 4).

Our sample from 7.3 mbsf is located in the transition zone between the sulfate-rich surface layers and the sulfate-depleted, methanogenic deeper sediment layers. Microbiological sampling of site 1230 showed that methanogenic activity and steep sulfate depletion appeared to be driven by methane ascending from deeper deposits. This suggests microbial communities with activities in hydrate-bearing sediments rich in organic material. Acetate and formate are generated as fermentation products and are used as substrates by sulfate-reducing or methanogenic prokaryotes. Methanogenesis, microbial sulfate reduction and anaerobic methane oxidation appear to have major roles in this particular deep-sea sediment (D’Hondt et al., 2003a, 2003b).

Previous quantification of 16S rRNA gene copies at 1 m depth from the Peruvian Margin showed Chloroflexi numbers to be nearly equivalent to the total bacterial counts (Blazejak and Schippers, 2010). A metagenomic study of site 1229 (Supplementary Figure 1) also revealed high levels of Chloroflexi genes at 1, 16, 32 and 50 mbsf (Biddle et al., 2008, 2011). It has also been speculated that subsurface Chloroflexi are active since their 16S rRNA sequences could be recovered from the surface of an in situ colonization experiment of polished and sterilized rock chips placed within a borehole, indicating recent growth (Orcutt et al., 2011). Data from a 16S rRNA gene clone library that we prepared from the sample collected at site 1230 7.3 mbsf indicated that Chloroflexi may constitute >70% of the detected bacterial phyla (data not shown). On the basis of these cumulative findings and the data collected by the Shipboard Scientific Parties in 1988 and 2003, site 1230 provides an excellent opportunity for assessing the nature of Chloroflexi and their metabolic potential in hydrate-bearing sediments rich in organic material and under high hydrostatic pressure.

Genome statistics and analysis

Phylogenetic 16S rRNA gene sequence analysis grouped Dsc1, 2 and 3 within the previously termed ‘subphylum II’ clade of the Chloroflexi (Inagaki et al., 2006). All nine known Dehalococcoidetes species (Dehalococcoides mccartyi strain BAV1, CBDB1, VS, GT, DCMB5, GY50, BTF08, Dehalococcoides ethenogenes 195 and Dehalogenimonas lykanthroporepellens BL-DC-9) share about 83% sequence identity at the 16S rRNA gene level with Dsc1 and 87% sequence identity with Dsc2 and 3.

The 16S rRNA gene of Dsc2 and 3 had an 81.7% pairwise nucleotide identity with Dsc 1 (ClustalW alignment with IUB cost matrix, gap open cost 15 and gap extent cost 6.66) (Figure 1). Comparing the Sanger sequenced 16S rRNA gene of Dsc2 and 3 revealed that they were identical over a range of 1364 nucleotides, and all other shared genes showed almost 100% pairwise identity on the nucleotide level after individual assembly (Figure 2). Therefore, we considered Dsc2 and 3 to be part of a coherent local Dsc population and combined the individual genomic sequence reads into one assembly, designated as DscP2 (for Deep-sea Chloroflexi population derived from Dsc2 and 3).

For Dcs1, a 0.32-Mb and for DscP2, a combined 1.38-Mb genome were assembled, respectively. On the basis of size of contigs (bp), number of tRNAs and reference marker genes (from http://phylosift.wordpress.com/tutorials/scripts-markers/ and Chloroflexi marker genes, obtained from IMG), we conservatively estimated that the genomes of Dcs1 and DscP2 are 35% and 85% complete, respectively. Due to the bias of the amplification reaction (Supplementary Figure 2) (Lasken 2007, 2012; Lasken and Stockwell, 2007; Marcy et al., 2007) it is unlikely that the genomes can be closed with the current data. The genome of Dcs1 was assembled into 126 contigs, ranging in size from 109 to 42 543 bp. In all, 42% of these contigs were longer than 1000 bp and 11% were longer than 10 000 bp. The N50 weighted median statistic of genome completeness was calculated as 12 440 bp. DscP2 was assembled into 327 contigs, ranging in size from 94 to 51 893 bp. In all, 52% of these contigs were longer than 500 bp, 37% were longer than 1000 bp and 12% were longer than 10 000 bp. The N50 weighted median statistic of genome completeness was calculated as 19 540 bp (Supplementary Table 5) (http://prinseq.sourceforge.net/; Earl et al., 2011). Despite being unfinished, the assembled genome of DscP2 still appears to provide a reasonable representation of a DscP species. Genome statistics are shown in Table 1.

Table 1 Genome statistics of DscP1 and DscP2
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The most common contaminants in single cell genome studies are Delftia, Pseudomonas and Ralstonia, which stem from the reagents used in the MDA reaction; others can be Propionibacterium and Lactobacillus (Woyke et al., 2011). No genes from these known common contaminants were found in our genomic data. Another source of contamination may be in the form of free DNA associated with the sample that is sorted and carried through during the Fluorescent Activated Cell Sorting procedure with the single cell. We therefore performed an additional manual screening of the data. While there are no clear rules on the identification and removal of contamination (that is, phage or horizontal gene transfer may be difficult to discriminate from contamination), a principle component analysis of the tetramer frequency and GC content of the scaffolds showed no suspicious open reading frames (Markowitz et al., 2010). In addition, the absence of eukaryotic or viral genes in the scaffolds strongly indicated that the genetic material was not significantly, if at all, contaminated.

Blastp and blastn analyses (Altschul et al., 1990) revealed a coherent phylogenetic composition of the DscP2 genome. Over 75% of the DscP2 genes had the best Blast hit to genes of known Chloroflexi with a sequence identity of larger than 90%. Forty-eight percent of all encoded protein sequences had a 60% or better pairwise identity to proteins found in Dehalogenimonas. Twenty-three percent of all protein-encoding genes showed the best hit to phylogenetically unassigned bacteria. For Dcs1, 51% of the genes had the best closest hit to genes in the phyla Chloroflexi with a sequence identity over 90%; 47% of the hits were to phylogenetically unassigned bacteria (Supplementary Tables 6 and 7). More than 100 genes in Dcs1 and 500 genes in DscP2 are encoding hypothetical proteins. Tetramer frequency analysis using the IMG software suggested that horizontal gene transfer of some genes might have occurred into Dcs1 and DspP2.

Predicted metabolic properties

Despite the grouping of the 16S rRNA gene sequence of Dcs1 and DscP2 into the class of Dehalococcoidetes, we only found one gene putatively encoding a conserved domain of a reductive dehalogenase in DscP2 (DscP2_00865) (Supplementary Figure 5). However, no associated membrane-bound anchor proteins or transcriptional regulators, which are commonly associated with respiration of organohalide compounds, were found in the genomic data (McMurdie et al., 2009). The amino-acid sequence of this iron–sulfur cluster protein shows only 27% identity to a putative reductive dehalogenase found in Dehalococcoides ethenogenes 195 and Dehalococcoides mccartyi BAV1, and has 40–50% identity to putative reductive dehalogenases found in Firmicutes, such as Desulfitobacterium and Dehalobacter and γ-Proteobacteria, for example, Shewanella (e-values range from 10−7 to 10−4). Extended searches for reductive dehalogenases genes using PCR and nanoliter-qPCR with primers targeting these genes on the MDA-derived DNA as template did also not provide evidence for the presence of rdh (Supplementary Table 4). This apparent absence of rdh genes in a genome derived from a deep-sea sediment Dehalococcoidetes is intriguing, considering that some marine subsurface Dehalococcoidetes-affiliated bacteria were hypothesized to perform reductive dehalogenation (Adrian et al., 2009; Futagami et al., 2009; Valentine, 2010; Durbin and Teske, 2011; Wagner et al., 2012). In terrestrial Dehalococcoidetes strains, the rdh operon is embedded in horizontally acquired genomic islands that integrated at the single-copy tmRNA gene, ssrA. The genomes of most sequenced Dehalococcoidetes contain two high-plasticity regions around the origin of replication that harbor the vast majority of putative rdh (Kube et al., 2005; McMurdie et al., 2009). While the absence of rdh genes, as found in this study, is not an unambiguous proof for a non-halorespiring metabolism, the presence of rdh genes in a Dehalococcoidetes-like structure in DscP2 is unlikely, based on the estimated 85% or greater completeness of the genome and the >30% genome occupation of high-plasticity region in Dehalococcoidetes. rdhAB and genes believed to be involved in assembly and maturation (rdhF-I) or regulation (rdhD, R) comprise between 3.5% and 8.6% of Dehalococcoidetes genomes by length (McMurdie et al., 2009). Thus, although the two Dsc genomes show most similarity to genomes of previously sequenced Dehalococcoides and Dehalogenimonas sp., Dsc1 and DscP2 appear considerably different in terms of overall gene content and do not harbor canonical rdh genes similar to those found in terrestrial Dehalococcoidetes strains.

Our finding is interesting in the light of a recent report on the spatial distribution of dehalogenation activity in the Nankai Trough plate-subduction zone of the northwest Pacific off the Kii Peninsula (Japan). Incubation experiments with slurries of sediment collected at various depths and locations showed that degradation of several organohalides occurred in the shallow sedimentary basin and rdhA genes were detected in the sediments. Interestingly, DNA fragments obtained from those positive enrichment cultures showed best BLAST hits to known Dehalococcoides. However, no functionally known dehalogenation-related gene such as rdhA was found. This indicates the need to improve the molecular approach to assess functional genes for reductive dehalogenation and to probe other classes of enzymes responsible for organohalide respiration (Futagami et al., 2013).

Interestingly, the assembled genome of DscP2 revealed the presence of a predicted haloacid dehalogenase (HAD) gene (DscP2_01004). This finding is similar to that recently made in the genome of a Dehalococcoidetes isolated from a metagenome derived from floodplain sediments deposited by the Colorado River (Hug et al., 2013). This class of enzymes catalyzes the hydrolytic dehalogenation of halogenated organic acids. The HAD and Rdh families are none-homologous, mechanistically different, and have evolved independently. The HAD may confer the ability to utilize iodated, chlorinated and/or brominated compounds, which occur naturally in sediments, by converting halogenated organic compounds into halogen-free organic compounds, which can then be used in canonical carbon degradation pathways. Intriguingly, also genes encoding for putative HAD superfamily enzymes are found (DscP2_01698, 0889), one being located next to the putative rdh (DscP2_0864). HAD superfamily enzymes are also found in known Dehalococcoidetes strains (Moe et al., 2009; Loeffler et al., 2013).

With the apparent absence of putative reductive dehalogenases in the genomes, we attempted to predict central catabolic pathways for DscP2 from the genome annotations. Therefore, we analyzed pathways using RAST, IMG and KEGG (Kanehisa and Goto, 2000; Aziz et al., 2008; Markowitz et al., 2010). IMG annotation seemed in general more precise when compared with the NCBI database than the ones from RAST; however, all potentially interesting proteins were blasted against the NCBI database as well, to confirm annotations and to avoid over-annotation. In addition, the absence or presence of certain gene encoding proteins was confirmed by performing BLAST analysis against the genome of DscP2. However, we could not identify a complete gene set encoding enzymes for a known canonical energy-conserving pathway (Table 2).

Table 2 Key metabolic genes found in DscP2
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A number of genes encoding putative enzymes found to be involved in methanogenesis were found, such as heterodisulfide reductase (Hdr) subunits. HdrA is very well conserved in many anaerobic microorganisms from terrestrial and aquatic environments (Kaster et al., 2011b). The finding of heterodisulfide reductase-like enzymes in strict anaerobes, such as sulfate reducers, acetogens and methanogens (Stojanowic et al., 2003; Strittmatter et al., 2009; Kaster et al., 2011a; Callaghan et al., 2012), supports the notion that Dsc sp. may have a primarily strict anaerobic metabolism. In addition, an archaeal type H+ ATPase (subunits ABCDEFI) was present.

Multiple genes and operons encoding for hydrogenase accessory proteins were identified (hypABCDEF) as well as genes encoding for the ‘periplasmic’ [NiFe]-hydrogenases, F420-reducing hydrogenase subunits alpha, delta and gamma. A putative F390 synthetase was identified, which in some methanogens synthesize 8-hydroxyadenylylated coenzyme F420 (coenzyme F390) (Vermeij et al., 1996). The function of coenzyme F390 is yet unclear, although studies suggest that it is involved as a response regulator for sensing changing cellular hydrogen concentrations (Vermeij et al., 1997). However, no gene encoding a membrane-bound energy-conserving hydrogenase was found. The DscP2 genome apparently also lacks a standard electron transport chain including cytochromes, quinones or methanophenazine, but contains ferredoxins, flavodoxins and iron–sulfur flavoprotein, as well as iron transporters and many iron-sulfur assembly proteins.

Some genes encoding for enzymes of the Wood-Ljungdahl pathway were discovered: one encoding a formate dehydrogenase and a formyltetrahydrofolate synthetase; a carbonmonoxide dehydrogenase/CO-methylating acetyl-CoA synthase complex (alpha and beta subunit) and a methyltetrahydrofolate reductase were found (clustered with a methyltetrahydrofolate methyltransferase). An acetyl-CoA synthetase was present as well. However, genes encoding for a methenyltetrahydrofolate cyclohydrolase and methylenetetrahydrofolate dehydrogenase were apparently absent. Genes encoding subunits of the carboxylating pyruvate:ferredoxin oxidoreductase were found and may provide a link between the reductive acetyl-CoA pathway (Wood-Ljungdahl pathway) and other anabolic pathways. The genes found above are present only in strictly anaerobic prokaryotes, and are also present in terrestrial Dehalococcoidetes. Since some genes found in the Wood-Ljungdahl pathway can also be used to synthesize acetate from H2 and CO2, it does not allow us to distinguish whether DscP2 could be an acetate oxidizer, a homoacetogen, or assimilate CO2 via the Wood-Ljungdahl pathway (Klenk et al., 1997; Anderson et al., 2011; Berg, 2011).

There is also some evidence for anabolic nitrogen metabolism. Genes encoding for a nitrite and nitro reductase were found, as well as several nitrogen-fixing NifU protein domains. In addition, a gamma-glutamyltranspeptidase and a putative glutathione transporter for potential utilization of glutathione as a sulfur source were found as well as an enzyme containing a domain of a putative dissimilatory sulfite reductase.

Recently, a partial genome of a Dehalococcoidetes species found in the Aarhus Bay in Denmark was reported (DEH-J10) (Wasmund et al., 2013), sharing 92% 16S rRNA identity with Dcs1 and 85% with DscP2. However, analysis and comparison of the overall amino-acid sequence content showed that the DEH-J10 genome is significantly different from Dsc1 and DscP2 (Supplementary Figure 6). Also, in DEH-J10 no evidence for a dehalorespiring lifestyle was discovered. The data indicated that this genome likely confers metabolic versatility to the organism and the authors suggested that DEH-J10 could employ the beta-oxidation pathway to use various organics as a source for carbon and reducing equivalents.

Concluding remarks

Single cell genomics is a highly promising approach to obtain some physiological and genomic insights into uncultured microorganisms from rare samples in the biosphere. Our data on the deep-sea sediment Dehalococcoidetes (Dsc1 and DscP2) suggest that these microorganisms have an anaerobic core metabolism that is consistent with a strictly anaerobic lifestyle and which does not involve canonical electron transfer pathways. Although single cell genomics rarely retrieves complete genomes, it is nevertheless currently the only way of linking information about metabolic potentials of an organism that cannot be cultured. Our identification of three partial Dsc single cell genomes is especially remarkable, in the sense that Chloroflexi single amplified genomes from different environments are extremely difficult to obtain, despite their numerical abundance (Tanja Woyke, JGI, personal communication). This fact may be due to inefficient lysis of this type of bacteria and/or their usually high GC content, both factors making a successful amplification via MDA less likely.

Assuming that our DscP2 genome is reasonably complete, although not closed, it is tempting to speculate on the core lifestyle of non-dehalogenating Dehalococcoidetes and their adaptation to dehalorespiration. Terrestrial Dehalococcoidetes isolated from chloroethene-contaminated sites exhibit clear signatures of strong niche adaptation to reductive dehalogenation as sole catabolic metabolism. This is supported by the observation that, most, if not all, rdh genes are horizontally transferred and located within two high-plasticity regions, which are essentially specialized integration sites for acquisition of genomic islands (McMurdie et al., 2007, 2009, 2011). The conventional hypothesis on the lifestyle has been that under non-contaminated conditions, Dehalococcoidetes use naturally occurring organohalogens as the electron acceptor, and that exposure to anthropogenic chlorinated solvents selects for genetic variants that adapted involving horizontal gene transfer to utilization of anthropogenic organohalogens (McMurdie et al., 2007, 2011). This hypothesis implies that Dehalococcoidetes from non-contaminated environments such as from pristine deep-sea sediments would reveal a non-adapted dehalogenating lifestyle. In this study, we found no evidence for the presence of rdh genes or organohalogen respiration in Dsc1 or DscP2, which confirms previous observations (Wasmund et al., 2013). Thus, these findings collectively suggest that reductive dehalogenation of Dehalococcoidetes-like Chloroflexi is a recently acquired trait that became beneficial and selectable because reductively dehalogenating enzymes integrated mechanistically easily into some distinctive, strictly anaerobic non-dehalogenating core metabolism similar to that inferred for DscP2. The Rdh domain protein found in DscP2 might also be a precursor that could be an ancestor of a fully functional Rdh, once halogenated compounds are introduced.