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1 Unité d'Ecologie, Systématique et Evolution, CNRS UMR 8079, Université Paris-Sud, 91405 Orsay Cedex, France
2 División de Microbiología and Evolutionary Genomics Group, Universidad Miguel Hernández, Campus de San Juan, 03550 San Juan de Alicante, Spain
Correspondence
Purificación López-García
puri.lopez{at}ese.u-psud.fr
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTS AND DISCUSSIONREFERENCES |
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The GenBank/EMBL/DDBJ accession numbers for the sequences reported in this paper are DQ267495 (DeepAnt-1F12) and DQ267496 (DeepAnt-32C6).
Supplementary figures are available with the online version of this paper.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTS AND DISCUSSIONREFERENCES |
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; Fuhrman et al., 1992; Giovannoni et al., 1990), opening the door to the application of this strategy to other environments and to the recognition that microbial diversity on our planet was far larger than previously thought (Pace, 1997). The continuous exploration of microbial diversity in different oceanic regions using a variety of cultivation-independent approaches has allowed the identification of various groups of non-cultivable organisms, some of which appear abundant and are probably major players in nutrient cycling (DeLong, 2001; Karner et al., 2001; Morris et al., 2002; Rappé & Giovannoni, 2003). However, the functional study of these micro-organisms is severely hampered by the lack of tools providing clues as to their physiological capabilities. Environmental genomics (or metagenomics) has recently been revealed as a powerful source of information about the gene content of non-cultivable organisms and, hence, by comparative genomics, a source of predicted metabolic activities that are testable. A paradigmatic example was the discovery of a novel type of phototrophy in a gammaproteobacterial lineage, SAR86, that is abundant and widespread in the photic zone (Beja et al., 2000a, 2001). This proteorhodopsin-based phototrophy appears to be common in other photic bacterial lineages as well (De La Torre et al., 2003; Venter et al., 2004). Nevertheless, in contrast to such fortuitously clear-cut examples and the relatively straightforward reconstruction of genome scaffolds by massive shotgun sequencing of low-diversity environments (Hallam et al., 2004; Tyson et al., 2004), most environmental genomic data accumulated to date are difficult to interpret. In many cases, putative genes bear resemblance to genes of unknown function; in others, they belong to large protein families whose precise function in the organism is difficult to predict. However, the accumulation of environmental data of this kind is a stepping stone for future comparative genomic studies that will eventually yield comprehensive conclusions.
Compared to the photic oceanic layers, the deep sea remains largely unexplored. Most efforts to describe its microbial diversity have been devoted to the study of deep-sea hydrothermal vents and, to a lesser extent, cold seep areas and deep-sea sediments (Inagaki et al., 2002; Jeanthon, 2000; Mills et al., 2004; Reysenbach & Cady, 2001). Paradoxically, despite their essential role in nutrient cycling, the planktonic communities inhabiting the vast biotope found between the photic region and the ocean floor are still poorly known. Only a few sparse molecular surveys of prokaryotic diversity in this biotope are available. A number of deep-sea-related archaeal and bacterial lineages have been identified in surveys carried out in 500-m- and 3000-m-deep Pacific and 1000-m-deep Atlantic samples (Fuhrman & Davis, 1997), and in 3000-m-deep Antarctic waters (López-García et al., 2001a, b). The diversity found in those surveys was remarkably different from that observed in surface 16S rDNA libraries, in accordance with the idea that vertical stratification is a major determinant in the water column and with reports concerning more superficial waters (Giovannoni et al., 1996; Gordon & Giovannoni, 1996).
Among the Bacteria, the Deltaproteobacteria appear to be one of the groups that increase in quantitative and qualitative representation in 16S rDNA libraries with depth. The Deltaproteobacteria groups organisms that can be classified into four major types according to their lifestyle (Segerer & Stetter, 1999). Some lineages are dissimilatory sulfate- or sulfur-reducers, being widespread in anoxic sediments all around the world. Many of these lineages, such as Geobacter species (Lovley et al., 2004), are not only able to reduce sulfur species, but also oxidized metals such as Fe(III) or Mn(IV). Others are fermenters that live in syntrophic symbioses with hydrogen-consuming methanogens (e.g. Syntrophus, Syntrophobacter). Some others are unusual bacterial predators, such as Bdellovibrio spp. (Rendulic et al., 2004). Finally, the myxobacteria constitute a unique group of heterotrophs displaying well developed cell-to-cell communication and complex developmental life cycles, which include cellular differentiation and multicellular stages (Dawid, 2000; Dworkin, 1996; Reichenbach, 1999). Although thought to be exclusively aerobic for a long time, anaerobic myxobacteria have been isolated from various soils, sediments and the subsurface that are able to respire aryl-compounds and, similarly to other Deltaproteobacteria, Fe(III) (He & Sanford, 2003; Sanford et al., 2002). In the deep ocean, sulfate-reducing members of the Deltaproteobacteria are frequently detected in sediments, cold seeps and anoxic regions in the water column, such as the Cariaco basin (Inagaki et al., 2002; Madrid et al., 2001). Bdellovibrio and myxobacteria-related sequences are also well represented in deep-sea sediments around hydrothermal vents (López-García et al., 2003). Among planktonic organisms, a novel lineage related to the Deltaproteobacteria, SAR324, was identified in lower-surface-level waters at the Sargasso Sea at a depth of 250 m (Wright et al., 1997) that was also detected in far deeper waters (López-García et al., 2001a).
We previously constructed a genomic library of plankton from a depth of 500 m in the size range 0·2–5 µm from the Antarctic Polar Front, from which two archaeal clones have been analysed previously (López-García et al., 2004; Moreira et al., 2004). We have extended this library and screened 3200 additional clones. The only two bacterial cosmid clones, designated DeepAnt-32C6 and DeepAnt-1F12, carrying 16S–23S rDNA intergenic spacers (ITSs) distinguishable from the host Escherichia coli strain belonged to the Deltaproteobacteria. We have sequenced and analysed the genome fragments borne by these clones and found them to be very divergent from known Deltaproteobacteria, defining a novel group branching as a sister group to the myxobacteria.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTS AND DISCUSSIONREFERENCES |
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) with 3200 additional genomic clones (
150 Mbp environmental DNA). Clones were obtained using E. coli EPI305, which is genetically deficient in both recombination and restriction systems to avoid the rearrangement or loss of clones in vivo (Epicentre). The 3200 clones were PCR-screened for the presence of bacterial 16S rRNA genes. To differentiate the host E. coli 16S rDNA amplicons from those potentially present in its cosmids, we used the primers 1055F (5'-ATGGCTGTCGTCAGCTCGT-3') and 230R (5'-TGCCAAGGCATCCACCGT-3') allowing the amplification of the last third of the 16S rRNA gene plus the ITS separating it from the 23S rRNA gene. Two bacterial clones, designated DeepAnt-32C6 and DeepAnt-1F12, were detected among the 3200 clones in this way. 16S rDNAs were then amplified using B-27F (5'-AGAGTTTGATCCTGGCTCAG-3') and 1492R (5'-GGTTACCTTGTTACGACTT-3'), completely sequenced and compared by using BLAST (Altschul et al., 1997) to database sequences.
Cosmid sequencing.
DeepAnt-32C6 and DeepAnt-1F12 were fully sequenced (Genome Express, France). Cosmid DNA was purified from overnight 350 ml cultures. Shotgun libraries were then constructed by subcloning mechanically sheared DNA fragments (2·5–5 kbp) into pUC18. Plasmid inserts were sequenced using vector primers in 3730XL capillary sequencers (Applied Biosystems). After cleaning vector sequences, DeepAnt-32C6 yielded one contig of 36 661 bp with a mean coverage of 8·8x. In the case of DeepAnt-1F12, two contigs of 12 354 bp (9·5x mean coverage) and 26 067 bp (10·4x mean coverage) were initially obtained that were finally assembled into one single contig of 38 421 bp.
Gene annotation and analysis of sequence features.
ORFs were characterized using the ORF-finder software at the National Center for Biotechnology Information (www.ncbi.nlm.nih.gov/gorf/gorf.html). Several criteria were used to define bona fide ORFs among all the potential ORFs detected. First, only sequences encoding peptides longer than 50 aa, preferentially non-overlapping, were retained. Second, when putative ORFs were detected in different reading frames, we selected those that had known homologues (as detected by BLAST searches) and third, in the case of various putative overlapping ORFs in different reading frames with no known homologues, we selected the ORFs that had the longest sequence. We used the programs PSI-BLAST, TBLASTN and BLASTP (Altschul et al., 1997) to look for sequence similarity in each ORF product with published protein sequences. The analyses of predicted conserved domains and transmembrane segments were carried out using CDART (www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi; Geer et al., 2002) and TMPRED (Hofmann & Stoffel, 1993), respectively. Predicted proteins were classified according to the Clusters of Orthologous Groups of proteins (COGs) database (www.ncbi.nlm.nih.gov/COG/; Tatusov et al., 1997, 2000). The presence of tRNA genes was explored with the program tRNAscan (Lowe & Eddy, 1997). tRNAs were absent from both the DeepAnt-32C6 and DeepAnt-1F12 cosmids. The presence of tandem repeats was analysed with the Tandem Repeats Finder (http://tandem.bu.edu/tools.html; Benson, 1999) and Oligonucleotides Repeats Finder (wwwmgs.bionet.nsc.ru/mgs/programs/oligorep/InpForm.htm). GC composition was studied with the GC Content Grapher (http://plantst.sdsc.edu/plantst/html/geneGC.shtml).
Phylogenetic analysis.
In the case of 16S rRNA genes, the closest relatives to the DeepAnt-32C6 and DeepAnt-1F12 cosmids identified by BLASTN were incorporated into an alignment containing 17 000 prokaryotic sequences. Sequences were aligned automatically using the program BABA (H. Philippe, personal communication) and the alignment was refined manually using the program ED of the MUST package (Philippe, 1993). Gaps and ambiguously aligned positions were excluded from phylogenetic tree reconstruction analyses. Preliminary trees with a large selection of species from the different bacterial divisions were constructed by neighbour-joining (using the MUST package) to identify the phylogenetic ascription of the two cosmids. More accurate trees including close relatives to our sequences were constructed by applying the Bayesian methods implemented in the program MRBAYES (Ronquist & Huelsenbeck, 2003) and maximum-likelihood using TREEFINDER (Jobb et al., 2004). Maximum-likelihood phylogenetic reconstruction was done using a GTR+
model of sequence evolution, using eight rate categories. Maximum-likelihood bootstrap analysis was carried out on 1000 replicates. In the case of proteins, the sequences homologous to the DeepAnt-32C6 and DeepAnt-1F12 ORFs identified by BLAST were retrieved from GenBank. Amino acid alignments for each ORF product were constructed using CLUSTALW (Thompson et al., 1994) and inspected manually with the program ED of the MUST package (Philippe, 1993). All ambiguously aligned regions were excluded from phylogenetic analyses. For all alignments, preliminary neighbour-joining trees were constructed using MUST. Bayesian phylogenetic trees with a representative selection of species were then constructed using MRBAYES. All individual alignments and the corresponding phylogenetic trees are available upon request.
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RESULTS AND DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTS AND DISCUSSIONREFERENCES |
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; Moreira et al., 2004) by generating 3200 additional clones. These were screened for the presence of bacterial 16S rRNA genes using specific primers allowing the amplification of the last third of the bacterial 16S rDNA plus the ITS (see Methods). Since the ITS is highly variable in sequence and length, clones yielding an amplification pattern different from that of E. coli alone would carry bacterial 16S rDNA-containing cosmids (Beja et al., 2000b) although, obviously, the fraction of total 16S rRNA-containing clones in the library may be underestimated by this procedure. Only two bacterial clones, DeepAnt-32C6 and DeepAnt-1F12, were identified using this strategy. Once purified, their full-length 16S rDNAs were amplified, sequenced and compared to sequences deposited in non-redundant and environmental databases by BLAST.
DeepAnt-32C6 and DeepAnt-1F12 appeared clearly related to deltaproteobacterial sequences, but sequence identity to their close relatives was very low. Only in the case of DeepAnt-1F12 did the closest 16S rDNA sequence in the databases exhibit more than 90 % identity. This closest match was the environmental sequence GR-WP33-58 (AJ296570), which was retrieved from a uranium waste pile (Selenska-Pobell, 2002). The second closest BLAST hit was only 89 % identical and corresponded to the highly versatile metal-reducer Geobacter sulfurreducens (Methe et al., 2003). In the case of DeepAnt-32C6, the situation was even more extreme. The closest BLAST hit, Pelobacter propionicus (X70954), was only 89 % identical; the second closest hit corresponded again to G. sulfurreducens (88 % identity). No close relatives were observed among the environmental Sargasso Sea surface sequences released recently (Venter et al., 2004); the closest hits to our DeepAnt clones identified in the Sargasso Sea database were proteobacterial sequences not belonging to the delta subclass (not shown). To determine the correct phylogenetic position of DeepAnt-32C6 and DeepAnt-1F12, we incorporated their 16S rDNA sequences and those from their closest BLAST-detected relatives to a prokaryotic alignment containing 17 000 sequences, and we carried out various preliminary phylogenetic analyses using diverse widely distributed taxon samples. In all cases, the two DeepAnt clones grouped together with the environmental clone GR-WP33-58 within the Deltaproteobacteria and, although their position within this group was not clear, it tended to branch as a sister group to the myxobacteria (not shown). Therefore, we chose a representation of proteobacterial sequences including a broad sampling of myxobacteria and other Deltaproteobacteria to carry out more exhaustive phylogenetic analyses (Fig. 1). The degree of divergence of this novel clade is comparable to that existing between the different deltaproteobacterial orders. In addition to defined orders, we also included representative sequences of SAR324 (Wright et al., 1997). Sequences belonging to this cluster had been identified at a depth of 3000 m in the water column of the Antarctic Polar Front, i.e. 2500 m deeper than the depth from which samples used to construct our genomic library were collected (López-García et al., 2001a), suggesting that SAR324 was indeed specific to the aphotic water column. Furthermore, the group B sequences identified by Fuhrman & Davis (1997) in samples from depths of 1000 and 3000 m in the Pacific and Atlantic clearly belong to SAR324 (data not shown), but they were not included in this analysis because they are partial. Nevertheless, although SAR324 appears to be associated with mesopelagic and far deep-sea waters in various oceanic regions, the two DeepAnt clones identified in our genomic library were not related to it. On the contrary, they form a monophyletic cluster together with GR-WP33-58, branching as a sister group to the myxobacteria, although with only moderate support (Fig. 1).
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; López-García et al., 2001a; Wright et al., 1997), but also an increase in their relative proportion with depth. Thus, in a recent comparative study of 1438 bacterial 16S rDNAs from libraries obtained from surface (50 m depth) and deep sea (2000 and 3000 m depth) in two oceanic locations, a significant and concordant increase of deltaproteobacterial clones was observed with depth. Deltaproteobacterial clones increased from 2·5 to 12·4 % in the Ionian Sea at the Mediterranean basin, and from 1·4 to 12·3 % in the North Atlantic close to Greenland (Zaballos et al., 2006). Although these percentages should be viewed with caution, it is interesting to note that the proportion of deltaproteobacterial sequences obtained by an independent approach in the surface of the Sargasso Sea, around 2·5 % (Venter et al., 2004), is in fair agreement with the proportion of surface deltaproteobacterial clones in the other two locations.
From its intermediate phylogenetic position between versatile metal-reducers (such as Geobacter) and myxobacteria, inferring the general features and lifestyle of this novel myxobacteria-related group (MRG) is a highly speculative exercise. Nevertheless, although most known myxobacteria are heterotrophic aerobes, anaerobic Fe(III)-respiring myxobacteria have been described (Petrie et al., 2003). It is therefore tempting to suggest that the ability to reduce not only sulfate, a property most likely ancestral to all Deltaproteobacteria (Woese, 1987), but also other oxidized metallic species, was ancestral to the myxobacteria and might also be found in the MRG. Clearly, the study of the full sequence of the two clones, DeepAnt-32C6 and DeepAnt-1F12, could provide information not only about genome organization and gene content of the MRG but, if genes involved in metabolic pathways were identified, also clues about their possible physiology. Hence, we completely sequenced the two genomic clones.
Genomic organization of DeepAnt-1F12 and DeepAnt-32C6
The sizes of the genomes of our two deltaproteobacterial clones, DeepAnt-1F12 and DeepAnt-32C6, were 38 421 and 36 589 bp, respectively. Both clones harboured a complete rRNA operon with 16S and 23S rRNA genes. However, tRNA genes, which are commonly found in the bacterial 16S–23S rDNA ITSs, including those of Deltaproteobacteria (Heidelberg et al., 2004; Methe et al., 2003; Rabus et al., 2004; Rendulic et al., 2004), were absent in both clones. In addition to the rRNA genes, we identified 15 ORFs in DeepAnt-1F12 and 18 in DeepAnt-32C6 (Fig. 2). None of these ORFs was shared by the two clones, but for most of them, clear homologues could be identified by BLAST searches in public databases (Tables 1 and 2). In fact, only three ORFs, one in DeepAnt-32C6 and two in DeepAnt-1F12, lacked close homologues in the databases. Gene density was much higher in DeepAnt-32C6 (with ITSs of 163 bp on average) than in DeepAnt-1F12 (with ITSs of 858 bp on average). Most ORFs in DeepAnt-1F12 (11 out of 15) and DeepAnt-32C6 (9 out of 16) were oriented in the same direction as the rRNA genes (Fig. 2).
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). On the contrary, the only region in DeepAnt-32C6 with a divergent, much lower G+C content corresponded to the rRNA operon. Interestingly, the G+C content of the protein-coding regions was very similar in both clones, 62·45 mol% in DeepAnt-1F12 and 63·93 mol% in DeepAnt-32C6. Therefore, the much lower mean G+C content of DeepAnt-1F12 is due to the relatively AT-rich intergenic regions, which are much larger in this clone, occupying approximately one-third of its total length.
Protein-coding genes
DeepAnt-1F12 and DeepAnt-32C6 carried a variety of genes encoding proteins with both informational and operational functions. Some of these proteins, particularly those of an informational nature (e.g. a DNA polymerase I subunit, ORF 8, in DeepAnt-32C6, or an RNA polymerase subunit, ORF 12, in DeepAnt-1F12), were highly conserved, and their phylogenetic analysis unambiguously confirmed the deltaproteobacterial affinity of the two clones (Tables 1 and 2, and data not shown). Other proteins were much less conserved and did not allow us to make robust phylogenetic inferences. Finally, a few proteins were conserved and gave a good phylogenetic signal, but their position in phylogenetic trees was very distant from other Deltaproteobacteria. This could be explained by hidden paralogies (i.e. independent gene duplications and losses), but it would require the occurrence of an improbably huge number of paralogues (Koonin, 2003). Therefore, we interpreted these phylogenetic positions as possible evidence for horizontal gene transfer (HGT) events. In most cases, these putative HGTs involved both low-G+C and high-G+C Gram-positives (Tables 1 and 2). One clear example is that of DeepAnt-32C6 ORF 3 encoding an adenosylmethionine-8-amino-7-oxononanoate aminotransferase that is closely related to high-G+C Gram-positive homologues with a strong statistical support (supplementary Fig. S1, available with the online version of this paper). In other, less frequent cases, transferred genes appear to have been acquired from other bacterial groups (Tables 1 and 2). An interesting example corresponds to DeepAnt-1F12 ORF 8, encoding a conserved transposase domain. Transposases are enzymes involved in the mobilization of DNA segments, being important agents of gene transfer (Osborn & Boltner, 2002). The transposase present in our clone is widespread in Gammaproteobacteria, but it is also found in one alphaproteobacterium (Sphingobium herbicidovorans) and one betaproteobacterium (Delftia acidovorans), and in one high-G+C Gram-positive (Arthrobacter aurescens) species with an almost identical sequence, suggesting a very recent acquisition from the Gammaproteobacteria (supplementary Fig. S2, available with the online version of this paper). However, in the case of DeepAnt-1F12, the gene is truncated and very divergent, indicating that this was a more ancient acquisition and that it has probably become a pseudogene.
Interestingly, DeepAnt-1F12 has one gene (ORF 10) encoding a Cys-rich protein that was clearly related to eukaryotic homologues. Although default BLAST searches against the non-redundant database in GenBank gave exclusively eukaryotic hits, in-depth searches in bacterial incomplete genome sequences allowed the identification of a homologue in the myxobacterium Myxococcus xanthus (Fig. 3). This might be indicative of an actual closer relationship between the new deltaproteobacterial group defined by our DeepAnt clones, GR-WP33-58 and the myxobacteria, although DeepAnt-1F12 was not a sister to M. xanthus in the phylogenetic analysis. In fact, the gene is fast-evolving and the statistical support for the separation of the two sequences was very low. In addition, this gene is present in multiple paralogous copies in eukaryotes (e.g. at least six paralogues in Homo sapiens; see Fig. 3), so that it is possible that the sequences found in DeepAnt-1F12 and M. xanthus belong to different paralogous families. In addition, BLAST searches in the Sargasso Sea environmental database identified two closely homologous sequences, IBEA_CTG_UEAYZ23TF and IBEA_CTG_UAANF02TF, that matched with only eukaryotic proteins (data not shown). However, both of these Sargasso Sea sequences are truncated and, since these clones correspond to small DNA fragments (<1000 bp) that do not carry other phylogenetic markers, it is very difficult to know the actual organismal origin. Nevertheless, IBEA_CTG_UAANF02TF was so similar to sea urchin sequences that an echinodermal source is highly probable. The surprising similarity of DeepAnt-1F12 ORF 10 with several eukaryotic proteins reinforces the idea that this MRG group is truly related to the myxobacteria, since the latter share a number of features, including many genes, with eukaryotes, mostly related to cell–cell communication and differentiation (Dworkin, 1996). This gene would therefore belong to the pool of eukaryotic-like genes carried by myxobacteria. The closest BLAST homologues to DeepAnt-1F12 ORF 10, i.e. EtMIC4 and EmTPF250 from the apicomplexan parasites Eimeria tenella and Eimeria maxima (Tomley et al., 2001; Witcombe et al., 2003), have an unknown function. Nevertheless, all the homologues found contain several repetitions of a Ca2+-binding epidermal growth factor (EGF) domain. EGFs are involved in protein–protein interaction and are found in numerous eukaryotic extracellular and membrane proteins important for motility, signalling, adhesion and development (Beckingham et al., 1998). Hence, the protein in myxobacteria and in this novel deltaproteobacterial group could be a membrane protein (ORF 10 has two predicted strong transmembrane domains) with Ca2+-binding activity. Based on this, it would be tempting to speculate that this novel deltaproteobacterial group shares some of the complex features of social behaviour and development typical of the myxobacteria.
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). VIT domains are frequently associated with vWFA domains, which are transmembrane peptides. Although previously thought to be exclusive to eukaryotic proteins, the association of VIT-vWFA domains could also be found by BLAST searches in many bacterial proteins, but the combination of these domains with RpoN appears to be unique.
Many of the protein-coding genes found in our two metagenomic clones encoded proteins involved in housekeeping functions universally distributed in prokaryotes (e.g. DNA replication, RNA synthesis), so that they were not informative about the possible physiological characteristics of the new MRG defined by DeepAnt-1F12 and DeepAnt-32C6. One interesting exception was ORF 14 of DeepAnt-32C6, which encoded a thiamine-dependent acetolactate synthase. This enzyme is found in several strictly or facultatively anaerobic bacteria, including Deltaproteobacteria (Lovley et al., 1995) and Archaea, and is required for 2,3-butanediol fermentation, one of the known pathways for glucose fermentation (Syu, 2001). 2,3-Butanediol, CO2, H2, ethanol and lactate are the major products of this fermentative pathway, which strongly decreases acid formation (butanediol is neutral) in comparison with other glucose fermentation pathways that typically produce much larger amounts of acid (such as acetate). The presence of this gene in DeepAnt-32C6 suggests that this deltaproteobacterium is able to carry out 2,3-butanediol fermentation and, therefore, anaerobic energy metabolism. The presence of fermentative micro-organisms in the deep-sea might be surprising, since this region of the ocean is characterized by a large amount of dissolved O2. However, the recent analysis of the complete genome sequence of the deep-sea gammaproteobacterium Idiomarina loihiensis has revealed that this species relies primarily on amino acid fermentation as a source of both carbon and energy (Hou et al., 2004), suggesting that fermentation may be important even in oxygenated deep-sea waters. Interestingly, ORF 13, immediately upstream and with a 127 bp overlap with the thiamine-dependent acetolactate synthase gene (Table 2), encoded a multidomain protein that is most probably involved in signal transduction. It contained a conserved PAS domain, which is known to bind a variety of ligands and to act as a sensor for oxygen (Makino et al., 2001; Zhulin et al., 1997). The presence of this conserved signal transduction protein in DeepAnt-32C6 suggests that this deltaproteobacterium is indeed able to sense changes in environmental O2 concentration and regulate gene expression accordingly. Interestingly, both this protein and the adjacent thiamine-dependent acetolactate synthase appeared to have been acquired by HGT from high-G+C Gram-positive bacteria, as deduced from phylogenetic analyses (not shown).
Another gene in DeepAnt-32C6 with potential metabolic information is ORF 1, encoding an esterase (Table 2). Closely related homologues were found in a variety of bacterial species. They are involved in the extracellular degradation of complex compounds containing ester bonds and cyclic structures to produce simpler molecules, which are subsequently incorporated and metabolized in the cell (e.g. cyclododecanone; Kostichka et al., 2001). This might also be the case for DeepAnt-32C6 ORF 1, since it contains two predicted strong transmembrane helices, suggesting that it is most probably membrane-bound. Therefore, the presence of this gene, as well as ORFs 13 and 14, suggested that this species is capable of both anaerobic growth and degradation of complex extracellular compounds. Since, as mentioned above, deep-sea water is rather oxygenated and poor in dissolved organic matter, one possibility could be that this deltaproteobacterium thrives, at least temporarily, within the suspended particles that form particulate organic matter, where anaerobic microniches rich in organic matter are frequent (del Giorgio & Duarte, 2002).
Conclusions
Our metagenomic analysis of a mesopelagic library has revealed the existence of a novel deltaproteobacterial group, the MRG, in marine plankton. The number of MRG deltaproteobacterial clones found in our library suggests that this group may be relatively abundant in deep-sea plankton. The phylogenetic position of the MRG is very interesting; since they branch at the base of the myxobacteria (Fig. 1), they could define an intermediate group between the very complex myxobacteria and the classical sulfate-reducing Deltaproteobacteria. Although the analysis of a small number of genes is insufficient for the inference of metabolic traits, our data suggest that at least one of the two deep-sea MRG Deltaproteobacteria might be capable of anaerobic growth based on fermentation. This emphasizes the necessity of further studies of the deep-sea microbial community, which appears to have a taxonomic and quantitative composition very different from that of the surface community and that may display metabolic properties (e.g. carbon and energy metabolism based on fermentation) relatively unexpected from the overall physico-chemical features of their biotope (Hou et al., 2004).
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ACKNOWLEDGEMENTS |
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Received 8 June 2005;
revised 31 October 2005;
accepted 6 November 2005.
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