Modeling migration of motile bacteria in confined porous media

Abstract:

Diverse processes such as bioremediation, biomineralization, and microbial drug
delivery rely on bacterial migration in porous media. However, how pore-scale confinement
alters bacterial motility is unknown due to the inherent heterogeneity in porous media.
As a result, our ability to accurately model bacterial migration under realistic conditions
is limited.
In order to analyze how pore-scale confinement and microbial activity individually
influence bacterial transport in confined porous media, we focus on the experimental scenario
reported by Bhattacharjee and Datta (2019). These authors discussed the run-and-tumble
paradigm of Escherichia coli by directly visualizing their individual trajectories in a
confined porous medium. We use a random walk particle-tracking (RWPT) approach that
employs pattern recognition techniques from direct visualization of bacterial migration
to extract statistical parameters used as input, and two stochastic alternating motility
states consisting of hops and trapping re-orientation. Results show that bacteria in
confined media display systematic shorter jumps due to grain obstacles and individual cellular
activity. The RWPT model is able to efficiently simulate the spreading dynamics of the
motile bacteria as it captures the impact of cell-cell interaction and pore confinement,
which produces superdiffusive motion at early and subdiffusion behavior at late times.
Furthermore, the model is able to qualitatively reproduce the observed directional
persistence, which enables bacteria to explore the space for resources or evade regions with
unfavourable conditions. We finally observe that the paradigm of run-and-tumble
motility is dramatically altered in the confined porous medium and discuss its implications on
large-scale transport.