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Biophysical methods bridging signal pathway architecture and dynamics in multigenerational bacterial processes

Cells sense their environment and process changes through intracellular signaling networks to coordinate behavioral changes, such as cell fate decisions. In bacterial systems, these changes often occur over time periods longer than a single cell cycle. While we are now able to experimentally track and monitor these behavioral changes over multiple generations, we have a limited conceptual understanding of how these decisions are mediated by signaling pathways. Here, I present two projects that build predictive frameworks for understanding signaling pathway dynamics over multiple generations informed by the signal network architectures. In the first section, I use computational simulations to understand how signaling pathway architecture controls the duration over which related cells maintain similar concentrations of signaling pathway components following division from a common mother cell. I find that signal amplification is a requirement for similarity between related cells. In the second section, I take a joint theory-experiment approach to analyze the accumulation timescale of the signaling molecule cyclic di-GMP during biofilm initiation in the soil bacterium B. subtilis. Here I predict that the accumulation occurs over many generations, suggesting the possibility cyclic di-GMP is used as a cellular timer mechanism during biofilm initiation. These results both explain previous experimental findings as well as generate new predictions for how signaling pathways mediate single-cell behaviors in bacterial populations. Together, my work demonstrates the power of a joint theory-experiment approach to understand the long-term, dynamical behavior of intracellular signaling pathways by linking their architecture to their dynamical function.

Identiferoai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/46262
Date24 May 2023
CreatorsAronson, Mark Samuel
ContributorsSgro, Allyson E.
Source SetsBoston University
Languageen_US
Detected LanguageEnglish
TypeThesis/Dissertation
RightsAttribution-NonCommercial-NoDerivatives 4.0 International, http://creativecommons.org/licenses/by-nc-nd/4.0/

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