Environmental drivers of a microbial genomic transition zone in the ocean’s interior

Abstract

The core properties of microbial genomes, including GC content and genome size, are known to vary widely among different bacteria and archaea . Several hypotheses have been proposed to explain this genomic variability, but the fundamental drivers that shape bacterial and archaeal genomic properties remain uncertain . Here, we report the existence of a sharp genomic transition zone below the photic zone, where bacterial and archaeal genomes and proteomes undergo a community-wide punctuated shift. Across a narrow range of increasing depth of just tens of metres, diverse microbial clades trend towards larger genome size, higher genomic GC content, and proteins with higher nitrogen but lower carbon content. These community-wide changes in genome features appear to be driven by gradients in the surrounding environmental energy and nutrient fields. Collectively, our data support hypotheses invoking nutrient limitation as a central driver in the evolution of core bacterial and archaeal genomic and proteomic properties.

Strong Purifying Selection Contributes to Genome Streamlining in Epipelagic Marinimicrobia

“…3e). This observation is consistent with previous findings that carbon-rich proteins with respect to nitrogen are prevalent in surface waters and suggests that this feature may be advantageous under the conditions found in this environment (Mende et al 2017). Because we evaluated multiple genomic features that have been identified as indicators of streamlining (Giovannoni 2005;Giovannoni et al 2014), we performed a multivariate analysis to explore the effect of such genomic variables on streamlined and non-streamlined genomes differentiation.…”

“…3c). To analyze the carbon and nitrogen content of encoded proteins we estimated the carbon and nitrogen atoms per residue side chain (C-ARSC and N-ARSC, respectively), which have previously been used for this purpose (Grzymski & Dussaq 2012;Getz et al 2018;Mende et al 2017). The correlation between C-ARSC and dN/dS showed a negative relationship (Spearman's rho = -0.30, P< 0.0001; Fig.…”

“…For example, strong selection in mesopelagic waters would not necessarily lead to an increase in amino acid carbon content since carbon is relatively more limiting in deep waters compared to other macronutrients. The disparate genomic features of epipelagic and mesopelagic Marinimicrobia are therefore likely the result of differential nutrient availability along the water column; surfaces waters have long been characterized as nutrient-depleted (i.e., nitrogen and iron) but carbon-rich due to photosynthetic activities (Grzymski & Dussaq 2012;Mende et al 2017) in comparison to the mesopelagic zone, where photosynthesis is limited but particulated organic matter remineralization occurs, thus nitrogen is relatively more abundant (Karl 2002;Moore et al 2013;Grzymski & Dussaq 2012). Prochlorococcus are thought to have underwent genome reduction in the distant past, and it is therefore difficult to assess the strength of selection on these ancestral genomes during these transitions.…”

Phosphate‐limited ocean regions select for bacterial populations enriched in the carbon–phosphorus lyase pathway for phosphonate degradation

“…However, because many OM‐RGC sequences lack classification at various taxonomic levels we performed a phylogenetic analysis of the C–P lyase pathway protein PhnJ. We downloaded 201 reference C–P lyase (PhnJ) protein sequences available from eggNOG v4.5.1 (Huerta‐Cepas et al ., ) and five additional reference sequences obtained from NCBI belonging to Actinobacteria genomes, and aligned them with C–P lyase sequences from the OM‐RGC and from the Station ALOHA gene catalogue (Mende et al ., ). C–P lyase sequences in the Station ALOHA gene catalogue were identified by a BLASTN search using the OM‐RGC phnJ nucleotide sequences as queries.…”

Microbial communities across nearshore to offshore coastal transects are primarily shaped by distance and temperature

“…Marine microbiology has linked taxa and community patterns to potential environmental drivers by observing temporal or spatial patterns through either repeated sampling of coastal or open ocean time-series sites or single cruises across oceanic basins (Morris et al, 2005;Gilbert et al, 2012;Chow et al, 2013;Larkin et al, 2016;Mende et al, 2017). Yet, relatively little is known about how the microbial community changes across the sharp environmental gradients from the nearshore to the open ocean, including how these gradients interact with temporal dynamics (Fortunato et al, 2012;Fortunato et al, 2013).…”