Although the dynamic behavior of microbial populations in nonmixed systems is a central aspect of many problems in biochemical engineering and microbiology, the factors that govern this behavior are not well understood. In particular, the effects of bacterial chemotaxis (biased migration of cells in the direction of chemical concentration gradients) have been the subject of much speculation but very little quantitative investigation. In this paper, we provide the first theoretical analysis of the effects of bacterial chemotaxis on the dynamics of competition between two microbial populations for a single rate-limiting nutrient in a confined nonmixed system. We use a simple unstructured model for cell growth and death, and the most soundly based current model for cell population migration. Using numerical finite element techniques, we examine both transient and steady-state behavior of the competing populations, focusing primarily on the influence of the cell random motility coefficient,μ, and the cell chemotaxis coefficient, χ. We find that, in general, there are four possible steady-state outcomes: both populations die out, population 1 exists alone, population 2 exists alone, and the two populations coexist. We find that, in contrast to well-mixed systems, the slower-growing population can coexist and even exist alone if it possesses sufficiently superior motility and chemotaxis properties. Our results allow estimation of the value of χ necessary to allow coexistence and predominance for reasonable values of growth and random motility parameters in common systems. An especially intriguing finding is that there is a minimum value of χ necessary for a chemotactic population to have a competitive advantage over an immotile population in a confined nonmixed system. Further, for typical system parameter values, this minimum value of χ is the range of values that can be estimated from independent experimental assays for chemotaxis.Thus, in typical nonmixed systems, cell motility and chemotaxis properties can be the determining factors in governing population dynamics.

In this paper, we summarized our recent efforts toward accomplishing four key goals important for control of microbial population dynamics in nonmixed systems: (1) derivation of a cell population flux model based on individual cell properties; (2) measurement of the population random motility and chemotaxis parameters appearing in this model using a simple experimental assay; (3) quantitative understanding of the effects of cell motility and chemotaxis properties on microbial population dynamics; and (4) manipulation of chemotactic responses by genetic modification.

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