High-resolution Experimental Study and Numerical Modeling of Population Dynamics in a Bacteria Culture

TL;DR

This study combines high-resolution experiments and numerical modeling to analyze E. coli population dynamics, revealing detailed growth phases and oscillations due to intra-species interactions and mixing.

Contribution

It introduces a simple differential equation model capturing spatial distribution, competition, dispersion, and oscillatory behavior in bacterial populations.

Findings

Experimental observation of all growth phases with high temporal resolution

Identification of oscillatory population behavior in stationary phase

Modeling suggests intra-species mixing causes oscillations and limits growth

Abstract

In this paper, experimental data is presented and a simple model is developed for the time evolution of a F-amp \textit{E. Coli} culture population. In general, the bacteria life cycle as revealed by monitoring a culture's population consists of the lag phase, the growth (or exponential) phase, the log (or stationary) phase, and finally the death phase. As the name suggests, in the stationary phase, the population of the bacteria ceases to grow exponentially and reaches a plateau before beginning the death phase. High temporal resolution experimental observations using a unique light-scattering technique in this work reveal all the expected phases in detail as well as an oscillatory population behavior in the stationary phase. This unambiguous oscillation behavior has been suggested previously using traditional surveys of aliquots from a given population culture. An attempt is made to model these experimental results by developing a differential equation that accounts for the spatial distribution of the individual cells and the presence of the self-organizing forces of competition and dispersion. The main phases are well represented, and the oscillating behavior is attributed to intra-species mixing. It is also observed, that the convective motion arising out of intra-species mixing while plays a key role in limiting population growth, scales as $t^{-\alpha}$, where $\alpha$ is bounded by model parameters.