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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Quantitative analysis of biological decision switches

Joh, In-Ho 01 April 2011 (has links)
Cells switch phenotypes or behaviors to adapt to various environmental stimuli. Often there are multiple alternative phenotypes, hence a cell chooses one phenotype among them, a process which we term a ``decision switch'. At the cellular level, decision switches are governed by gene regulation, hence they are intrinsically stochastic. Here we investigate two aspects of decision switches: how copy number of genetic components facilitates multiple phenotypes and how temporal dynamics of gene regulation with stochastic fluctuations affect switching a cell fate. First, we demonstrate that gene expression can be sensitive to changes in the copy number of genes and promoters, and alternative phenotypes may arise due to bistability within gene regulatory networks. Our analysis in phage-lambda-infected E. coli cells exhibit drastic change in gene expression by changing the copy number of viral genes, suggesting phages can determine their fates collectively via sharing gene products. Second, we examine decision switches mediated by temporal dynamics of gene regulation. We consider a case when temporal gene expression triggers a corresponding cell fate, and apply it to the lysis-lysogeny decision switch by phage lambda. Our analysis recapitulates the systematic bias between lysis and lysogeny by the viral gene copy number. We also present a quantitative measure of cell fate predictability based on temporal gene expression. Analyses using our framework suggest that the future fate of a cell can be highly correlated with temporal gene expression, and predicted if the current gene expression is known.

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