Date of Award

8-31-2026

Document Type

Open Access Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Integrative Biosciences

First Advisor

Mohamed Amine Gharbi

Abstract

Active matter systems are self-driven units that consume energy to generate motion and mechanical stresses, producing non-equilibrium states of broad physical significance. Examples include synthetic microswimmers and migrating cells. Motile bacteria are a widely studied biological example because their self-propelled motion, hydrodynamic interactions, and collective organization are strongly coupled to local environmental conditions. Their swimming is sensitive to interfacial viscoelasticity, ordering, confinement, and hydrodynamic boundary effects, making them useful for investigating how interfaces regulate active biological motion. Because bacterial accumulation and attachment at interfaces are central to colonization and biofilm formation, these interactions are relevant to both active matter physics and antimicrobial strategies.

Although bacterial swimming is well studied in bulk simple fluids and near solid boundaries, the effects of complex interfaces remain less understood. Here, we use a liquid crystal (LC)-based interfacial system to investigate how interfacial composition and ordering influence bacterial motility and organization, focusing on swimming speed, trajectories, orientation, and residence time. We find that changes in interfacial properties alter residence time, swimming speed, and trajectory direction, demonstrating that interfaces actively regulate microbial motion rather than simply serving as physical boundaries.

We also investigate how bacteria and bacterial secretions affect the LC interface. Exploiting the optical response of LCs to interfacial perturbations, we demonstrate the platform’s biosensing potential using amphiphilic biomolecules and further functionalize the interface for specific insulin detection. Overall, these results provide insight into microbial dynamics near complex interfaces and support LC-based platforms for sensing, interpreting, and potentially controlling bacterial behavior.

Comments

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