Interactions between Phenotypic Switching, Gene Network Dynamics and Evolutionary Dynamics in Growing Cell Populations

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dc.contributor.advisorBalazsi, Gabor
dc.contributor.advisorGunaratne, Gemunu H.
dc.contributor.committeeMemberBassler, Kevin E.
dc.contributor.committeeMemberDas, Mini
dc.contributor.committeeMemberCooper, Timothy F.
dc.creatorBelete, Merzu Kebede 1982-
dc.creator.orcid0000-0003-0183-3170
dc.date.accessioned2018-07-17T17:24:37Z
dc.date.available2018-07-17T17:24:37Z
dc.date.createdMay 2016
dc.date.issued2016-05
dc.date.submittedMay 2016
dc.date.updated2018-07-17T17:24:37Z
dc.description.abstractGene expression is a stochastic biological processes that controls the different phenotypes of an organism depending on the environment. High-resolution single cell measurements show that genetically identical cells can be different from each other even in a homogeneous environment, leading a spectrum of phenotypes with different cellular fitnesses that can reversibly switch between phenotypes. How population-level properties emerge from single cell behavior and how mutants emerge and spread in such populations is unclear. In this thesis, we developed mathematical models to study (i) the effect of time-delay needed for a mutation in a regulator gene influence an effector protein and the long term population fitness, (ii) how optimum population fitness behaves as a function of the growth rates of the various phenotypes for different durations in fluctuating environments. Our work shows a paradoxical outcome of evolution where mutations in a regulator gene interact with gene network dynamics and evolutionary dynamics, giving rise to permanent decrease in population fitness. In the other scenario of fluctuating environments, a previously predicted optimum exists for wider parameter regime if the environmental durations are long and narrow regime for short environmental durations. We also find that a mutant, which randomly evolved to match its phenotypic switching rates with environmental switching rates, can sweep the population if the predicted optimum matches with the assumed one, but not otherwise.
dc.description.departmentPhysics, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.citationPortions of this document have appeared in: Belete, Merzu Kebede, and Gábor Balázsi. "Optimality and adaptation of phenotypically switching cells in fluctuating environments." Physical Review E 92, no. 6 (2015): 062716. DOI: 10.1103/PhysRevE.92.062716.
dc.identifier.urihttp://hdl.handle.net/10657/3278
dc.language.isoeng
dc.rightsThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. UH Libraries has secured permission to reproduce any and all previously published materials contained in the work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectGene expression
dc.subjectEvolution
dc.subjectMonte-Carlo
dc.subjectPhenotypic-switching
dc.subjectCellular-fitness
dc.titleInteractions between Phenotypic Switching, Gene Network Dynamics and Evolutionary Dynamics in Growing Cell Populations
dc.type.dcmiText
dc.type.genreThesis
thesis.degree.collegeCollege of Natural Sciences and Mathematics
thesis.degree.departmentPhysics, Department of
thesis.degree.disciplinePhysics
thesis.degree.grantorUniversity of Houston
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

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