A metabolic network for an organism consists of all known metabolites and the enzymes that catalyze transformations between metabolites. By specifying a particular set of input conditions, e.g., glucose and oxygen uptake, we can use mathematical models to determine the accumulation of biomass and hence growth of a cell [1]. We are interested in applying these models to study the metabolism of pathogens under different conditions and exploit these networks to determine drug-dose responses.

Metabolism of intracellular pathogens

Metabolism is a dynamic concept as cells and pathogens adjust their metabolic requirements in different environments, e.g., when cells switch from one sugar source to another (diauxic shift). We are interested in the altered metabolisms of pathogens inside host cells and how this can be used to identify novel drug targets. We are primarily using flux balance analysis (FBA) [2] methods to determine metabolic requirements and ascertain gene essentiality, i.e., genes that are necessary for bacterial growth.

Drug dose response modeling

We are developing mathematical models to simulate the effects of inhibiting metabolic enzymes on bacterial growth. The realistic modeling of the metabolic network and link to bacterial growth will allow us to quantitatively model and predict the effect of selected drug molecules.