2024
DOI: 10.1038/s41467-024-46374-w
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Genome-scale community modelling reveals conserved metabolic cross-feedings in epipelagic bacterioplankton communities

Nils Giordano,
Marinna Gaudin,
Camille Trottier
et al.

Abstract: Marine microorganisms form complex communities of interacting organisms that influence central ecosystem functions in the ocean such as primary production and nutrient cycling. Identifying the mechanisms controlling their assembly and activities is a major challenge in microbial ecology. Here, we integrated Tara Oceans meta-omics data to predict genome-scale community interactions within prokaryotic assemblages in the euphotic ocean. A global genome-resolved co-activity network revealed a significant number of… Show more

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“…Recent studies have taken this approach a step further by inferring a global ocean association network based on genome activities that were inferred by integrating genome-wide abundance and transcript levels. As an example, the integration of Tara Oceans metagenomes and metatranscriptomes data from 71 samples allowed prediction of genome-scale interactions within prokaryotic communities [ 100 ]. The mapping of Tara Oceans on a database of 7658 genomes—including MAGs, SAGs and whole-genome sequences—was used as input to perform a species metabolic coupling analysis to infer the level of competition and metabolic interdependencies between species within co-active consortia.…”
Section: In Silico Approaches For Community-level Studiesmentioning
confidence: 99%
“…Recent studies have taken this approach a step further by inferring a global ocean association network based on genome activities that were inferred by integrating genome-wide abundance and transcript levels. As an example, the integration of Tara Oceans metagenomes and metatranscriptomes data from 71 samples allowed prediction of genome-scale interactions within prokaryotic communities [ 100 ]. The mapping of Tara Oceans on a database of 7658 genomes—including MAGs, SAGs and whole-genome sequences—was used as input to perform a species metabolic coupling analysis to infer the level of competition and metabolic interdependencies between species within co-active consortia.…”
Section: In Silico Approaches For Community-level Studiesmentioning
confidence: 99%