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

Abstract

Bacterioplankton of the SAR11 clade are the most abundant microorganisms in marine systems, usually representing 25% or more of the total bacterial cells in seawater worldwide. SAR11 is divided into subclades with distinct spatiotemporal distributions (ecotypes), some of which appear to be specific to deep water. Here we examine the genomic basis for deep ocean distribution of one SAR11 bathytype (depth-specific ecotype), subclade Ic. Four single-cell Ic genomes, with estimated completeness of 55%-86%, were isolated from 770 m at station ALOHA and compared with eight SAR11 surface genomes and metagenomic datasets. Subclade Ic genomes dominated metagenomic fragment recruitment below the euphotic zone. They had similar COG distributions, high local synteny and shared a large number (69%) of orthologous clusters with SAR11 surface genomes, yet were distinct at the 16S rRNA gene and amino-acid level, and formed a separate, monophyletic group in phylogenetic trees. Subclade Ic genomes were enriched in genes associated with membrane/cell wall/envelope biosynthesis and showed evidence of unique phage defenses. The majority of subclade Ic-specfic genes were hypothetical, and some were highly abundant in deep ocean metagenomic data, potentially masking mechanisms for niche differentiation. However, the evidence suggests these organisms have a similar metabolism to their surface counterparts, and that subclade Ic adaptations to the deep ocean do not involve large variations in gene content, but rather more subtle differences previously observed deep ocean genomic data, like preferential amino-acid substitutions, larger coding regions among SAR11 clade orthologs, larger intergenic regions and larger estimated average genome size.

Mare Incognitum: A Glimpse into Future Plankton Diversity and Ecology Research

“…Complementary to a "bulk" screening of marine biodiversity, single-cell genomics approaches allow matching of phenotype and genotype, and have been used to investigate the phylogenetic affinities of microbial dark matter (i.e., currently unculturable microbial organisms; Rinke et al, 2013;Hug et al, 2016) and to uncover niche partitioning within globally distributed lineages of marine microbes (Kashtan et al, 2014). In combination, bulk and targeted approaches could unravel the taxonomic composition of planktonic organisms, as well as aspects of their ecological function (Thrash et al, 2014;Louca et al, 2016) and genome evolution to new environments (Mock et al, 2017).…”

Metagenome Mining Reveals Hidden Genomic Diversity of Pelagimyophages in Aquatic Environments

“…1). Host assignment within different SAR11 subclades was not possible (except for group D [see below]) due to (i) lack of tRNA genes (only 18 genomes had them, and the ones present were all under 95% identity to SAR11 known tRNAs), which suggests that either we do not have genome representatives for the hosts they infect, or they have a broad host range, (ii) similarity of shared proteins provided inconclusive results (same identity to distantly related host-groups) and (iii) there is only one report of a CRISPR-cas system in SAR11, which is found only in the bathypelagic ecotype Ic (34). The enormous diversity of the SAR11 clade probably complicates the process of host assignment.…”

“…Together, these findings increased sixfold the SAR11 myophage repertoire and allowed us to discover different PMP clades, including the first myophage specific of the freshwater genus Ca. Fonsibacter and the bathypelagic SAR11 phylogroup Ic (9,34). This recovery effort has increased their genome diversity enough to be able to perform genomic comparisons with the closest well-studied CMPs to elucidate peculiarities of the PMP infection model.…”

Isolation and cultivation of planktonic freshwater microbes is essential for a comprehensive understanding of their ecology

“…2). Indeed, fragment recruitment of meta genomic reads to full genome sequences has been repeatedly used to identify hypervariable regions or metagenomic islands hinting at a high level of microdiversification within closely related strains in the environment (Rodriguez-Valera et al 2009, Cordero & Polz 2014, Thrash et al 2014. Genome sequences can also be retrieved from metatranscriptomes and -proteomes (Fig.…”