Population Dynamics of Enteric Bacteria in Surface Water: Role of Mutation and Growth. Laboratory Experiments and Agent Based Modeling

Predicting the fate and transport of enteric bacteria in surface water is important for assessing and managing the risk that these organisms may pose to public health. The historical water quality modeling approach assumes that the bacteria density decreases exponentially (i.e. first-order decay) in the surface water environment. However, a number of field and laboratory studies report observations of (1) biphasic decay and (2) growth, which are inconsistent with the first-order kinetic formulation. The aim of this research is to increase the understanding of the mechanisms affecting the fate of enteric bacteria in surface water. Various hypotheses are tested using laboratory experiments and mathematical models. First, a set of microcosm experiments with Escherichia coli inoculated in phosphate buffer solution at different initial densities was conducted to test the hypothesis that a density effect (quorum sensing) is responsible for the biphasic decay in surface water. These experiments showed a change in rate occurring at the same time rather than at the same density which is inconsistent with this mechanism. A second set of experiments was conducted to test the biphasic decay is due to a growth advantage in stationary phase (GASP) mechanism. Results from these tests showed that (1) the biphasic decay pattern is due to growing sub-population and (2) these sub-populations are made of GASP-type mutants. In order to further test the hypothesis that a GASP-type mutation is responsible for the survival of enteric bacteria in a real water body, an agent-based model (ABM) for E. coli, which includes growth and mutation processes, was developed and its predictions were compared to field data for the lower Charles River, Boston. The model reproduces the main patterns observed in the data for time series and spatial transects, consistent with the underlying hypothesis. The same ABM framework was also applied to study the population dynamics of microbial communities in wastewater treatment applications for biological phosphorous removal. The model resolves the heterogeneity in extra- and intra-cellular nutrient concentrations observed from bulk measurements and Raman microscopy single-cell data, providing insights on different sources of heterogeneity. This research sheds new light on the bacterial dynamics in surface water and confirms the ABM approach as a powerful tool for simulating and understanding the dynamics of microbial communities in the environment.