Microbial activities on which humanity and ecosystems depend, and which influence climate and support biofuel production, are determined both by microbial community membership and by the resources and conditions in the microbes' local environments. In order to develop insight into controls over microbial community interactions and contributions to ecosystem function, a pervasive disconnect must be addressed: The size of a typical bacterium or archaeon is approximately one to five micrometers, yet environmental sampling meant to provide contextual insight into resources available to microbes, and environmental conditions influencing their activities, is often carried out at much larger scales. "Metadata" (pH, nutrient concentrations, availability of organic matter etc.) are measured from homogenized, coffee-mug-size (or larger) cores of soil or liters of water. Particularly in highly structured environments such as soil and sediment, this scale discrepancy makes it impossible to infer the micron-scale environments that the microbes are actually reacting to, and influencing. Also, microscale heterogeneity of soil conditions associated with the presence of e.g. plant roots, fungal hyphae, and soil fauna have long been recognized to spur localized booms and busts of microbial taxa and biogeochemical function. To understand how environmental microheterogeneity and 3D soil structure affect microbial activities and biogeochemical function at the scales microbes experience, a modeling framework is needed that operates at spatial scales relevant to microbes, that can incorporate 3D structural information from real soils, and that includes diffusion and advection of resources and biological signals, geochemical reactions, and microbial activities. This project contributes to development and testing of such a computational framework under development at EMSL, operating in high resolution at pore spatial scales. The project focuses on a physically simple test case exploring how diffusion and advection of the solute acetate and the gases H2 and CO2 affect measured and modeled gene expression associated with production of methane by the JGI-sequenced methanogen Methanosarcina barkeri str. Fusaro. M. barkeri is an extremely versatile methanogen, able to use multiple substrates and several pathways to produce methane, including the acetoclastic (acetate substrate) and hydrogenotrophic (H2+CO2 substrate) pathways. The work is designed to be a "proof of concept" using M. barkeri cultured in microcosms with known 3D pore-scale physical structure created by very accurately sized sand. Sand in the microcosms will be poised at varying degrees of saturation to differentially affect diffusion of solutes and gases and thus vary supply of substrates for methanogenesis. Transcriptomes (sequenced by JGI) will be gathered from M. barkeri cultured in microcosms hosting acetoclastic, hydrogeneotrophic, or mixed metabolisms. These gene expression data will be compared with methanogenesis pathway induction predicted for millions of microcosm locations modeled by the pore-scale computational framework, in which a genome-scale, flux-balance based model of M. barkeri metabolism will be embedded. The transcriptome data gathered during these experiments will also be valuable in themselves, revealing gene expression-linked characteristics of metabolic switching between hydrogenotrophic and acetoclastic methanogenic pathways driven by differential local availability of H2+CO2 and acetate.