Eoin Brodie, Berkeley Lab
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Abstract:
This presentation will outline a trait-based approach for exploring and simulating soil microbiomes, crucial biological components that govern key ecological processes like climate regulation and nutrient cycling. Given that the vast majority of microbial species remain uncultivated, genomic data is the primary window into their function. Soil microbiomes are complex, and to handle this complexity, our framework distills genomes into "Functional Traits" - attributes that mechanistically link a microbe's genes to its fitness and ecosystem-level impact. This approach achieves essential dimensionality reduction and is designed to unify genomic, phenotypic, and ecological data for cross-system generalizability. The core concept is the Genomes-to-Ecosystem (G2E) framework, which integrates these derived traits into complex ecosystem models such as ecosys/EcoSIM. This integration is critical for accurate parameterization of microbial functional groups and has demonstrated that predictions of biogeochemical fluxes, like methane emissions, are highly sensitive to the trait parameters used. Research leveraging this framework explores trade-offs in carbon and energy allocation, finding, for example, that Carbon Use Efficiency (CUE) can be manipulated by selecting for efficient organisms via specific substrate additions. Ultimately, the process needs to be improved through more consistent measurements, model-guided field sensing, and the introduction of AI-Agents to automate experimentation and make complex models accessible.
Bio:
Eoin Brodie, Ph.D. is a Senior Scientist at Lawrence Berkeley National Laboratory and Deputy Director of the Climate and Ecosystem Sciences Division, as well as an Adjunct Professor at University of California, Berkeley and Co-Director of the Joint Berkeley Initiative in Microbiome Sciences. A microbiologist and biogeochemist, he studies how microscopic life shapes the health and resilience of soils, ecosystems, and the planet. His research integrates molecular biology, advanced sensing, and trait-based computational modeling to predict microbial function from genes to entire watersheds, with the goal of harnessing microbiomes to advance sustainable agriculture, ecosystem resilience, and environmental restoration.