Speaker
Description
We investigate coupled feedbacks between pore-scale hydrodynamics, nutrient transport, and bacterial behavior in heterogeneous pore spaces by relying on statistically robust metrics rooted in Information Theory. Bacterial motility and chemotaxis are main drivers of a variety of bacteria-mediated processes taking place in natural and engineered porous systems, including, e.g., bioremediation of contaminated areas, CO$_2$ biomineralization, or microbial-assisted drug delivery. Despite their importance, fundamental knowledge gaps remain regarding the way these behaviors are modulated by the complex hydrodynamic and structural heterogeneities inherent to porous architectures. The effectiveness of chemotaxis relative to (undirected) bacterial motility strongly depends on the access of bacteria to nutrient sources, which is governed by pore-scale flow characteristics such as local velocity magnitudes, shear stresses, and flow topology. The velocity field controls the spatial heterogeneity of nutrient distributions and poses constraints to the ability of bacteria to migrate upstream (i.e., against the flow). Disentangling the relative influence of hydrodynamic and transport processes on microbial dynamics requires a robust theoretical framework capable of accounting for their combined effects and inherent variability across the pore space. In this context, we consider key Lagrangian statistics from single-cell trajectories of non-motile, motile, and chemotactic bacteria within a microfluidic porous system. Experiments are conducted using an innovative quasi-two-dimensional microfluidic platform that enables direct, in situ visualization of bacterial trajectories under diverse controlled nutrient delivery, flow regimes, and degrees of pore-scale heterogeneity. Our statistical analyses rest upon Partial Information Decomposition. This theoretical framework is grounded on Shannon entropy and enables one to partition the variability of a target variable into unique, shared, and synergistic contributions from multiple variables, taken as information sources. While this approach has been applied in various fields such as, e.g., genetics, communication theory, and large-scale ecology, our study represents the first attempt to assess its transferability to pore-scale environments. Our results demonstrate the potential of this framework to quantitatively disentangle and rank contributions of hydrodynamic and transport processes in shaping microbial behavior in complex pore spaces.
| Country | Switzerland |
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