Metabolomics & genome-scale metabolic modeling

We quantified approximately 85 core intracellular and six extracellular metabolites from E. coli grown in minimal media with and without mecillinam (a beta-lactam antibiotic). These absolute concentration data were used to estimate metabolite flux over 1-hour time intervals spanning exponential growth to provide quantitative insight into metabolic changes induced by beta-lactam antibiotics. We are creating state-specific genome-scale metabolic E. coli models by imposing the calculated flux values for each time point and condition as model constraints.

These models allow us to simulate reaction flux and network utilization for untreated and antibiotic-treated E. coli, providing a global view of metabolism and better understanding antibiotic mechanism. Thus far, the metabolomics data have shown that treatment causes changes such as an increased utilization of glucose and production of acetate, increased levels of TCA metabolites, increased oxidative stress, and accumulation of amino acids.