The increasing availability of the genome sequences of microorganisms involved 
in important bioremediation processes makes it feasible to consider developing 
genome-scale models that can aid in predicting the likely outcome of potential 
subsurface bioremediation strategies. Previous studies of the in situ 
bioremediation of uranium-contaminated groundwater have demonstrated that 
Geobacter species are often the dominant members of the groundwater community 
during active bioremediation and the primary organisms catalysing U(VI) 
reduction. Therefore, a genome-scale, constraint-based model of the metabolism 
of Geobacter sulfurreducens was coupled with the reactive transport model 
HYDROGEOCHEM in an attempt to model in situ uranium bioremediation. In order to 
simplify the modelling, the influence of only three growth factors was 
considered: acetate, the electron donor added to stimulate U(VI) reduction; 
Fe(III), the electron acceptor primarily supporting growth of Geobacter; and 
ammonium, a key nutrient. The constraint-based model predicted that growth 
yields of Geobacter varied significantly based on the availability of these 
three growth factors and that there are minimum thresholds of acetate and 
Fe(III) below which growth and activity are not possible. This contrasts with 
typical, empirical microbial models that assume fixed growth yields and the 
possibility for complete metabolism of the substrates. The coupled genome-scale 
and reactive transport model predicted acetate concentrations and U(VI) 
reduction rates in a field trial of in situ uranium bioremediation that were 
comparable to the predictions of a calibrated conventional model, but without 
the need for empirical calibration, other than specifying the initial biomass of 
Geobacter. These results suggest that coupling genome-scale metabolic models 
with reactive transport models may be a good approach to developing models that 
can be truly predictive, without empirical calibration, for evaluating the 
probable response of subsurface microorganisms to possible bioremediation 
approaches prior to implementation.