ArticleNature communications2021
Towards omics-based predictions of planktonic functional composition from environmental data.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Water mass specific genes dominate the Southern Ocean microbiome.Nature communications · 2026Article
- Interactions between phytoplankton and bacterioplankton communities in Caohai plateau lake, revealed by environmental DNA metagenomics.BMC microbiology · 2026Article
- Metatranscriptomes-based sequence similarity networks uncover genetic signatures within parasitic freshwater microbial eukaryotes.Microbiome · 2025Article
- Gene content of seawater microbes is a strong predictor of water chemistry across the Great Barrier Reef.Microbiome · 2025Article
- Deciphering the key stressors shaping the relative success of core mixoplankton across spatiotemporal scales.ISME communications · 2025Article
- Metabolic activities of marine ammonia-oxidizing archaea orchestrated by quorum sensing.mLife · 2024Article
- The genomic potential of photosynthesis in piconanoplankton is functionally redundant but taxonomically structured at a global scale.Science advances · 2024Article
- The road forward to incorporate seawater microbes in predictive reef monitoring.Environmental microbiome · 2024Review
- Emergent Functional Organization of Gut Microbiomes in Health and Diseases.Biomolecules · 2023Article
- Identification of microbial metabolic functional guilds from large genomic datasets.Frontiers in microbiology · 2023Article
- Genomic differentiation of three pico-phytoplankton species in the Mediterranean Sea.Environmental microbiology · 2022Article
- Towards omics-based predictions of planktonic functional composition from environmental data.Nature communications · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Marine microbes play a crucial role in climate regulation, biogeochemical cycles, and trophic networks. Unprecedented amounts of data on planktonic communities were recently collected, sparking a need for innovative data-driven methodologies to quantify and predict their ecosystemic functions. We reanalyze 885 marine metagenome-assembled genomes through a network-based approach and detect 233,756 protein functional clusters, from which 15% are functionally unannotated. We investigate all clusters' distributions across the global ocean through machine learning, identifying biogeographical provinces as the best predictors of protein functional clusters' abundance. The abundances of 14,585 clusters are predictable from the environmental context, including 1347 functionally unannotated clusters. We analyze the biogeography of these 14,585 clusters, identifying the Mediterranean Sea as an outlier in terms of protein functional clusters composition. Applicable to any set of sequences, our approach constitutes a step towards quantitative predictions of functional composition from the environmental context.
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