EVALUATION OF AN IN SILICO GEOBACTER METALLIREDUCENS MODEL USING PROTEOMIC DATA FROM A FIELD BIOSTIMULATION EXPERIMENT

The field-calibrated Fe(III) terminal electron acceptor process (TEAP) reaction in a uranium bioremediation reactive transport simulation was recently replaced with a constraint-based genome-scale microbial in silico model. The goal was to better reflect microorganism functionality in response to spatial and temporal variations in environmental conditions during an acetate biostimulation field experiment. Biomass and proteomics data collected from the 2008 experiment at the Rifle IFRC site provided an unprecedented opportunity to assess the capabilities of a genome-scale metabolic model of Geobacter metallireducens to predict metal reduction, biomass yield and growth rate under dynamic field conditions. The constraint-based G. metallireducens in silico model of Sun et al. (2009) associates 747 genes and 697 reactions. 135 of the 279 G. metallireducens genes detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. The largest predicted fluxes through in silico model reactions generally correspond to high abundances of proteins linked to those reactions. While there are discrepancies, such as the prediction of shifts associated with nitrogen limitation, the future for this methodology appears promising.