Ocean biogeochemistry modeled with emergent trait-based genomics

Functional ocean biogeography Marine ecosystems are well represented in metagenomic and transcriptomic data. These data are not routinely used to test ecosystem models that explore ocean biogeography or biogeochemistry. Coles et al. built a model in which genes for a range of functions were assigned to different suites of simulated microbes (see the Perspective by Rynearson). Communities emerged from the model with realistic biogeographical and biogeochemical profiles when compared to microbial data collected from the Amazon River plume. However, functional composition trumped the details of taxonomy, and different, coevolving community compositions emerged that provided similar biogeochemical outcomes. Science, this issue p. 1149; see also p. 1129 Results of genomic-based microbe community modeling resemble real-world observations from the Amazon River plume. Marine ecosystem models have advanced to incorporate metabolic pathways discovered with genomic sequencing, but direct comparisons between models and “omics” data are lacking. We developed a model that directly simulates metagenomes and metatranscriptomes for comparison with observations. Model microbes were randomly assigned genes for specialized functions, and communities of 68 species were simulated in the Atlantic Ocean. Unfit organisms were replaced, and the model self-organized to develop community genomes and transcriptomes. Emergent communities from simulations that were initialized with different cohorts of randomly generated microbes all produced realistic vertical and horizontal ocean nutrient, genome, and transcriptome gradients. Thus, the library of gene functions available to the community, rather than the distribution of functions among specific organisms, drove community assembly and biogeochemical gradients in the model ocean.