Characterization and analysis of bacterial sugar utilization strategies employing regulated phenotypic heterogeneity

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This project studies bacterial regulation strategies for sugar uptake systems. In these systems, phenotypic heterogeneity is not only associated with a statistical distribution of phenotypes at a given point in time, but also with a significant cell-to-cell variability in the timing of phenotype switches. Our central goals are (i) to characterize heterogeneous timing as a dynamic gene regulation strategy and (ii) to analyze phenotypic heterogeneity in competing sugar utilization systems. In the first funding period of the SPP1617, we performed a detailed experimental and theoretical analysis of the phenomenon of heterogeneous timing in the single-cell gene expression dynamics of the arabinose system of E. coli. We found that the physiological switching behavior of this sugar utilization system is asymmetric, such that OFF-switching is always rapid and homogeneous, while ON-switching is slow and heterogeneously timed at sub-saturating inducer levels. We consolidated these and mutant behaviors within a single quantitative model. Regarding (ii), we studied cell growth on two competing PTS substrates, Sorbitol and N-acetylglucosamine (Nag), in a broad range of external substrate concentrations, while quantifying the expression of the Nag and Sorbitol utilization systems on the single-cell level. Our data supports a model of a hierarchical interaction that breaks down to allow stochastic co-utilization at low concentrations of the dominant sugar (Nag). For the second period of the SPP, we plan to study possible benefits of the observed phenotypic heterogeneity in the behavior of sugar utilization systems. Our theoretical analysis predicts that heterogeneous timing can be a useful bet-hedging strategy during stationary phase: Heterogeneous timing can minimize the risk of inducing costly gene expression after sensing nutrient sources that may be transient and disappear before a cell benefits from its expression investment. To quantify the cost of gene expression during stationary phase, we will measure the effects of gratuitous gene expression from inducible promoters on fitness indicators such as viability, metabolic activity, membrane potential, and membrane integrity. We will also seek to identify the pool of energy and/or resources that limits the total gene expression capacity of stationary phase cells. The obtained data will be integrated into a quantitative cost-benefit analysis of stationary phase gene expression, which will then be the basis for an experimentally well-founded theoretical analysis of beneficial regulation strategies. The other task for the modeling component of this proposal will be the analysis of a nutrient-sensing signaling network in E. coli that is activated at the transition to stationary phase.