Abstract

Escherichia coli is a predominantly non-pathogenic species of bacteria present in the gut of most healthy adults. It plays a critical role in the health of the gut microbiome and is also widely used as a model organism in microbiology and synthetic biology studies. This thesis discusses results from two ongoing projects on E. Coli organization and emergent biophysical properties at two very distinct length scales. The first project focuses on using genetically modified engineered E. coli bacteria for early detection and intervention in colorectal cancer (CRC), a significant public health issue in the US. The success of these engineered bacteria relies on their survival, engraftment, and proliferation. We constructed a mathematical model which combines the generalized Lotka-Volterra equations of population dynamics with diffusion and advection of individual bacteria to study the impact of different microbial interactions and motilities in the spatiotemporal and population dynamics of native and engineered bacterial populations. By examining the linear stability analyses and the time evolution of the coupled partial differential equations in our model, we aim to provide insights into engineered bacteria’s long-time survival, spatial distribution, and their colonization potential in combating CRC, to inform experiments by our collaborators. The second project delves into results on how stressed E. Coli use phase separation to organize their DNA, facilitated by DNA-binding proteins known as Dps, which are crucial for DNA compaction and protection under oxidative stress. We use an agent-based model and active Brownian dynamics simulations, which are informed by experiments, to obtain a quantitative biophysical understanding of Dps-DNA phase separation dynamics, extending beyond simple condensate formation to examine mechanical and structural properties of these complexes. This integrated approach aims to enhance our knowledge of protein-induced phase separation and can potentially guide the development of antibiotics targeting bacterial organization influenced by DPS proteins, opening new paths for therapeutic interventions.

Publication Date

8-2026

Document Type

Dissertation

Student Type

Graduate

Degree Name

Mathematical Modeling (Ph.D)

Department, Program, or Center

Mathematical Sciences, School of

College

College of Science

Advisor

Moumita Das

Advisor/Committee Member

Poornima Padmanabhan

Advisor/Committee Member

Elio Abbondanzieri

Comments

This thesis has been embargoed. The full-text will be available on or around 11/10/2027.

Campus

RIT – Main Campus

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