Fitness and Flux in Bacterial MetabolismView all posters
Paris Descartes University, United States
Metabolic engineers seek to direct endogenous metabolic fluxes toward valuable or interesting products. Evolution tends to redistribute these same fluxes in ways that maximize host fitness. To what extent can these two conflicting forces be reconciled? How much can a flux profile be perturbed before host growth begins to suffer? Can we predict how a chassis organism will respond to a perturbed and suboptimal (from an evolutionary perspective) central metabolism? Our work builds on widely used MFA models that treat metabolism as a problem of optimization under constraint. Metabolic reaction rates are constrained to obey thermodynamics and the conservation of mass. Natural selection may work within these constraints to optimize metabolism for some objective, for example fast growth. Yet because of redundancies in the metabolic network, many different flux profiles can be equally optimal for a given objective. Here we formulate a mathematical objective function that accounts for this degenerate optimality. In our model, some fluxes may assume a wide range of values while still allowing near-optimal growth. These same fluxes are shown to be more variable in sets of enzymatic and transcription factor deletion mutants. We suggest that metabolic regulation may tolerate significant fitness-neutral variation. This variation may be exploited to expand the limits of fitness-neutral metabolic engineering, and to better predict host responses to altered metabolism in general.