Metabolic pathways inferred from a bacterial marker gene illuminate ecological changes across South Pacific frontal boundaries

Global oceanographic monitoring initiatives originally measured abiotic essential ocean variables but are currently incorporating biological and metagenomic sampling programs. There is, however, a large knowledge gap on how to infer bacterial functions, the information sought by biogeochemists, ecol...

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Bibliographic Details
Published in:Nature communications 2021-04, Vol.12 (1), p.2213-12, Article 2213
Main Authors: Raes, Eric J, Karsh, Kristen, Sow, Swan L S, Ostrowski, Martin, Brown, Mark V, van de Kamp, Jodie, Franco-Santos, Rita M, Bodrossy, Levente, Waite, Anya M
Format: Article
Language:English
Subjects:
Bacteria
Bacteria - classification
Bacteria - genetics
Bacterial Physiological Phenomena
Biodegradation
Biodiversity
Ecology
Energy metabolism
Functionals
Gene sequencing
Genes, Bacterial - genetics
Markers
Metabolic Networks and Pathways - genetics
Metabolic pathways
Metabolism
Metagenome
Metagenomics
Metagenomics - methods
Monitoring
Organic matter
Pacific Ocean
Polls & surveys
RNA, Ribosomal, 16S - genetics
rRNA 16S
Sequence Analysis, DNA
Shotguns
Thermodynamics
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Summary:Global oceanographic monitoring initiatives originally measured abiotic essential ocean variables but are currently incorporating biological and metagenomic sampling programs. There is, however, a large knowledge gap on how to infer bacterial functions, the information sought by biogeochemists, ecologists, and modelers, from the bacterial taxonomic information (produced by bacterial marker gene surveys). Here, we provide a correlative understanding of how a bacterial marker gene (16S rRNA) can be used to infer latitudinal trends for metabolic pathways in global monitoring campaigns. From a transect spanning 7000 km in the South Pacific Ocean we infer ten metabolic pathways from 16S rRNA gene sequences and 11 corresponding metagenome samples, which relate to metabolic processes of primary productivity, temperature-regulated thermodynamic effects, coping strategies for nutrient limitation, energy metabolism, and organic matter degradation. This study demonstrates that low-cost, high-throughput bacterial marker gene data, can be used to infer shifts in the metabolic strategies at the community scale.
ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-021-22409-4