Uncovering the Genetic Fitness Landscape Behind Bacterial Motility in Complex Environments

Abstract: Bacterial motility is a complex phenomenon that plays a fundamental role in widespread biological processes including pathogenesis and bioremediation. Motile bacteria perform chemotaxis – migration under the influence of a chemical gradient – to find conditions optimal for their fitness and survival. This movement can be either towards (positive chemotaxis) or away from (negative chemotaxis) a chemical stimulant. One important feature of this network is its ability to adapt to changes in the environment, allowing cells to maintain a high sensitivity to their environment over a wide range of chemical backgrounds. In natural environments, this sensory process also takes place in a cluttered and noisy mechanical background, as cells are constantly exposed to heterogeneous, variable physical cues. Despite this, the vast majority of studies into bacterial motility and chemotaxis have been performed in unconfined liquid media or along flat surfaces. In this project, we aim to develop both mechanistic and evolutionary insights into bacterial motility and adaptation under various environmental conditions. A key impact of the environment is posed by limiting the free path length for the bacteria. We will characterize the corresponding chord-length statistics and develop a modeling framework that takes into account geometric constraints. We will also revise the current theoretical models on chord-length statistics (Levitz&Tchoubar, 1992), as they rely on assumptions that are not valid in the planned experiments, leading to qualitative differences. We will also develop a hyper-network framework to infer fitness consequences of changes in the chemotactic gene regulatory network. Combining biophysical experiments using a novel microfluidic setup and modeling with predictive hyper-network analysis, we outline an investigation to characterize how the chemotactic sensing pathway adapts over multiple timescales to improve bacterial performance and fitness in a range of complex, naturalistic environments.