Downloaded from www.microbiologyresearch.org by IP: 54.157.13.203 On: Sun, 07 Feb 2016 13:34:16 Metagenomic analysis of mesopelagic Antarctic plankton reveals a novel deltaproteobacterial group David Moreira, 1 Francisco Rodrı ´guez-Valera 2 and Purificacio ´n Lo ´ pez-Garcı ´a 1 Correspondence Purificacio ´n Lo ´ pez-Garcı ´a puri.lopez@ese.u-psud.fr 1 Unite ´ d’Ecologie, Syste ´ matique et Evolution, CNRS UMR 8079, Universite ´ Paris-Sud, 91405 Orsay Cedex, France 2 Divisio ´ n de Microbiologı ´a and Evolutionary Genomics Group, Universidad Miguel Herna ´ ndez, Campus de San Juan, 03550 San Juan de Alicante, Spain Received 8 June 2005 Revised 31 October 2005 Accepted 6 November 2005 Phylogenetic screening of 3200 clones from a metagenomic library of Antarctic mesopelagic picoplankton allowed the identification of two bacterial 16S-rDNA-containing clones belonging to the Deltaproteobacteria, DeepAnt-1F12 and DeepAnt-32C6. These clones were very divergent, forming a monophyletic cluster with the environmental sequence GR-WP33-58 that branched at the base of the myxobacteria. Except for the possession of complete rrn operons without associated tRNA genes, DeepAnt-1F12 and DeepAnt-32C6 were very different in gene content and organization. Gene density was much higher in DeepAnt-32C6, whereas nearly one-third of DeepAnt-1F12 corresponded to intergenic regions. Many of the predicted genes encoded by these metagenomic clones were informational (i.e. involved in replication, transcription, translation and related processes). Despite this, a few putative cases of horizontal gene transfer were detected, including a transposase. DeepAnt-1F12 contained one putative gene encoding a long cysteine-rich protein, probably membrane-bound and Ca 2+ -binding, with only eukaryotic homologues. DeepAnt-32C6 carried some predicted genes involved in metabolic pathways that suggested this organism may be anaerobic and able to ferment and to degrade complex compounds extracellularly. INTRODUCTION Marine microbiology has benefited greatly in the last 20 years from the development of molecular tools to analyse the genetic diversity of microbial communities. The first molecular surveys based on 16S rRNA gene amplification of oceanic picoplankton revealed the existence of novel groups of Bacteria and Archaea (DeLong, 1992; 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 appro- aches 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; Rappe ´& 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 gammapro- teobacterial lineage, SAR86, that is abundant and wide- spread 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 straightfor- ward 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. Abbreviations: HGT, horizontal gene transfer; ITS, intergenic spacer; MRG, myxobacteria-related group. 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. 0002-8254 G 2006 SGM Printed in Great Britain 505 Microbiology (2006), 152, 505–517 DOI 10.1099/mic.0.28254-0