Comparative Metagenomic Analysis of a Microbial Community Residing at a Depth of 4,000 Meters at Station ALOHA in the North Pacific Subtropical Gyre

Abstract

The deep sea (water depth of >2,000 m) represents the largest biome on Earth. Yet relatively little is known about its microbial community's structure, function, and adaptation to the cold and deep biosphere. To provide further genomic insights into deep-sea planktonic microbes, we sequenced a total of ϳ200 Mbp of a random whole-genome shotgun (WGS) library from a microbial community residing at a depth of 4,000 m at Station ALOHA in the Pacific Ocean and compared it to other available WGS sequence data from surface and deep waters. Our analyses indicated that the deep-sea lifestyle is likely facilitated by a collection of very subtle adaptations, as opposed to dramatic alterations of gene content or structure. These adaptations appear to include higher metabolic versatility and genomic plasticity to cope with the sparse and sporadic energy resources available, a preference for hydrophobic and smaller-volume amino acids in protein sequences, unique proteins not found in surface-dwelling species, and adaptations at the gene expression level. The deep-sea community is also characterized by a larger average genome size and a higher content of "selfish" genetic elements, such as transposases and prophages, whose propagation is apparently favored by more relaxed purifying (negative) selection in deeper waters.The oceans cover over two-thirds of our planet, with an average depth of ϳ3,800 m. Microbes dominate the oceans' interior (42) and thus drive the biochemical cycles that sustain life in this habitat. Yet our knowledge of deep-sea bacteria and archaea has been severely impeded by the difficulties in isolating naturally important organisms and in simulating the in situ conditions of high pressure, low temperature, and low energy availability in the laboratory (45). Most of the deep-sea microbes studied to date either represent allochthonous and piezotolerant bacteria or are copiotrophic piezophiles isolated in rich media. There are very few isolates (with the possible exception of some relatively abundant Alteromonas species) that appear to be truly representative of predominant deep-sea planktonic microbes (9, 23). Therefore, the common characteristics that typify free-living planktonic deep-sea microbes remain largely unknown.Some initial insights into microbial adaptations to the cold and high-pressure environment have started to emerge from recently completed genomic projects (recently reviewed in reference 23). For example, the genome of Photobacterium profundum, an organism isolated from a depth of 2,500 m, indicated that metabolic versatility encoded in a rather large genome (6.4 Mbp) (39) and flagellum-based motility (11) might be essential for survival in the deep-sea environment. Colwellia psychrerythraea, a psychrophilic marine bacterium living in ambient atmospheric pressure, employs several mechanisms to cope with low environmental temperatures, including changes to membrane fluidity and uptake and synthesis of compounds conferring cryotolerance (26). This and other studies (41, 43) have also implied ...

Genome-enabled transcriptomics reveals archaeal populations that drive nitrification in a deep-sea hydrothermal plume

“…Normalization of read numbers by gene length resulted in a roughly equivalent copy number of amoA and 16S genes (amoA:16S ratio of B1.4), indicating that the majority of GB MGI cells have amoA and are thus capable of ammonia oxidation. These findings are consistent with those of Konstantinidis et al (2009) from 4000 m depth at station ALOHA and distinct from those of Agogué et al (2008), which found smaller amoA:16S ratios in deep Atlantic waters.…”

“…Both C. symbiosum and N. viennensis contain urease genes (Hallum et al, 2006;Tourna et al, 2011); however, N. maritimus lacks any recognizable genes for urea utilization. Thus, our results and other recent environmental studies (Konstantinidis et al, 2009;Yakimov et al, 2011;Tully et al, 2012) highlight an important difference in N acquisition between natural populations of MGI and N. maritimus.…”

Single-cell enabled comparative genomics of a deep ocean SAR11 bathytype

“…COG distribution among SAR11 genomes was part of data supplied by IMG (Supplementary Table S1). Patterns of amino-acid substitution between surface and deep-water strains of SAR11 were analyzed as described in Konstantinidis et al (2009). Fold-change abundance of amino acids across similar and non-similar substitutions was calculated from all vs all BLASTP output within homologous clusters.…”

“…Bacterioplankton of the SAR11 clade are the most numerous in marine systems, typically comprising B25% of all prokaryotic cells (Morris et al, 2002;Schattenhofer et al, 2009). Although the majority of research has focused on the SAR11 clade in the euphotic and upper mesopelagic zones, multiple studies have demonstrated evidence of substantial SAR11 populations deeper in the mesopelagic, as well as in the bathy-and even hadopelagic (46000 m) realms (Martin-Cuadrado et al, 2007;Konstantinidis et al, 2009;Schattenhofer et al, 2009;Quaiser et al, 2010;Swan et al, 2011;Eloe et al, 2011a, b;King et al, 2013). SAR11, or the 'Pelagibacterales,' is a diverse group, spanning at least 18% 16S rRNA gene divergence, and is comprised of subclades with unique spatiotemporal distributions (ecotypes) that follow seasonal patterns (Field et al, 1997;Carlson et al, 2009;Giovannoni and Vergin, 2012;Grote et al, 2012;Vergin et al, 2013).…”

“…Thus, it remains uncertain how widespread the known adaptations of cultivated isolates are among deep ocean microorganisms. Metagenomic analyses have provided evidence for common genomic features in the deep ocean, such as increased proliferation of transposable elements and phage, amino-acid content changes, and increased average genome size (DeLong et al, 2006;Konstantinidis et al, 2009). Single-cell genomic analyses provide another powerful means to understand the metabolism and evolution of organisms eluding cultivation-based techniques (Stepanauskas, 2012;Blainey, 2013;Lasken, 2013;Rinke et al, 2013).…”