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Marine ecosystem models now simulate metagenomes and metatranscriptomes, revealing that the community

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Area of Science:

  • Marine microbial ecology
  • Computational biology
  • Genomic and transcriptomic modeling

Background:

  • Marine ecosystem models increasingly integrate genomic data on metabolic pathways.
  • A gap exists in directly comparing these models with empirical metagenomic and metatranscriptomic data.
  • Simulating microbial community assembly and function from first principles is challenging.

Purpose of the Study:

  • To develop a novel model simulating metagenomes and metatranscriptomes for direct comparison with observational data.
  • To investigate the drivers of microbial community assembly and biogeochemical gradients in a model marine ecosystem.
  • To assess the role of gene function distribution versus community composition in shaping ecosystem properties.

Main Methods:

  • Developed a computational model to directly simulate metagenomes and metatranscriptomes.
  • Randomly assigned genes for specialized functions to model microbes within a 68-species community.
  • Simulated ecological dynamics in a virtual Atlantic Ocean, including organism replacement based on fitness.

Main Results:

  • The model self-organized to generate emergent community genomes and transcriptomes.
  • Simulations consistently produced realistic vertical and horizontal gradients of nutrients, genomes, and transcriptomes.
  • These realistic patterns emerged regardless of the initial distribution of gene functions among microbes.

Conclusions:

  • The collective library of gene functions within a microbial community is a primary driver of its assembly and biogeochemical function.
  • Community-level gene repertoire, not the specific distribution among organisms, dictates ecosystem structure and gradients.
  • This modeling approach provides a framework for linking genomic potential to ecosystem function in marine environments.