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, 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 7000km 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. Extracting functional information from 16S rRNA data surveys would provide a valuable tool for large-scale functional ecology. Here, the authors use PICRUSt2 to infer metabolic functions from bacterial marker gene data across the South Pacific Ocean, and compare them with rate data, biomass estimators and predictions based on shotgun metagenomes.

Automated summary

This study demonstrates the use of 16S rRNA gene data to infer metabolic pathways in global monitoring campaigns, revealing metabolic processes across a 7000km transect in the South Pacific Ocean. The findings suggest that low-cost, high-throughput bacterial marker gene data can be utilized to infer shifts in metabolic strategies at the community scale.