Modeling heterogeneity in the microbial world

No two living cells are identical. Like tiny, squishy snowflakes, even seemingly identical cells (belonging to isogenic populations, and living under macroscopically similar conditions), will experience variations in their local microenvironments and in the numbers of gene copies, messenger RNAs, proteins, and other macromolecules that constitute their make up, and importantly, dictate their behavior. In this thesis I will employ the methods of systems biology, stochastic simulation, and mathematical analysis to investigate some of the causes and outcomes of this type of biological variability in the microbial world. This document is divided into four main chapters. The first focuses on how the stochastic expression of metabolic enzymes affects the growth and metabolic pathway usage of individual Escherichia coli cells. The second chapter deals with how E. coli cells in colonies diverge behaviorally as a function of their location, and how they naturally tend to cooperate in a previously unknown form of crossfeeding. Finally, the third and fourth chapters deal with details of how gene expression stochasticity itself arises, with an eye toward the effects that DNA replication have on mRNA and protein statistics (and what that means for interpreting single molecule experiments).

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Physics

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2018

Author dc:creator

• Cole, Jr., John Andrew

Contributors dc:contributor

• Luthey-Schulten, Zaida
• Goldenfeld, Nigel
• Chemla, Yann
• Kuehn, Seppe

• Stochastic gene expression, metabolism

Statement dc:rights

• Copyright 2017 John A. Cole Jr.

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/99301

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/99301