Machine learning and metagenomics identifies uncharacterized taxa inferred to drive biogeochemical cycles in a subtropical hypereutrophic estuary.

ABSTRACT: Anthropogenic influences have drastically increased nutrient concentrations in many estuaries globally, and microbial communities have adapted to the resulting hypereutrophic ecosystems. However, our knowledge of the dominant microbial taxa and their potential functions in these ecosystems has remained sparse. Here, we study prokaryotic community dynamics in a temporal-spatial dataset, from a subtropical hypereutrophic estuary. Screening 54 water samples across brackish to marine sites revealed that nutrient concentrations and salinity best explained spatial community variations, whereas temperature and dissolved oxygen likely drive seasonal shifts. By combining short and long read sequencing data, we recovered 2,459 metagenome-assembled genomes, proposed new taxon names for previously unc

SUBMITTER: Prabhu A 

PROVIDER: S-EPMC11758582 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature