Analysis of Microbial Population Dynamics Using the Visualizing Evolution In Real Time (VERT) System

Adaptive evolution has been harnessed to improve industrially relevant strain qualities such as inhibitor tolerance, product titer, and product yield for decades. Despite the importance of this tool in industry and academia, many questions remain concerning how new adaptive mutants compete within a population. Sampling populations for adaptive mutants requires lengthy analysis of isolated mutants and provides only indirect information concerning the relative proportion of each mutant within the entire population. However, even in light of these difficulties, much progress has been made in experimental and theoretical analysis of evolutionary dynamics.

Unlike previous attempts to quantify or model population dynamics in response to an external stressor, the Visualizing Evolution in Real Time (VERT) system is capable of tracking fluorescently labeled subpopulations during adaptive evolution in the laboratory. We exploit this unique feature of VERT to compare the population dynamics of three evolving microbial species in order to provide new insight into process of adaptive evolution and quantify parameters of interest, such as the number of possible adaptive mutations in a given environment. Based on the observed population dynamics data, an algorithm capable of autonomously detecting adaptive mutants within a population is also developed and validated against experimental data. Together, these results represent an important advance in the understanding of laboratory adaptive evolution.