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Title:Quantifying transcriptional regulation in Escherichia coli and phage lambda at single-cell, single-molecule resolution
Author(s):Sepulveda Duran, Leonardo
Director of Research:Golding, Ido
Doctoral Committee Chair(s):Golding, Ido
Doctoral Committee Member(s):Slauch, James M.; Kuhlman, Thomas E.; Aksimentiev, Aleksei
Department / Program:School of Molecular & Cell Bio
Discipline:Biophysics & Computnl Biology
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):single-cell
single-molecule
transcription regulation
gene expression
systems biology
stochasticity
gene regulation function
single molecule fluorescent in situ hybridization (smFISH)
immunofluorescence
E. coli
Phage lambda
transcription factors
Abstract:The information that instructs cells on how to create the molecules that perform cellular functions resides within the DNA. The basic unit of genetic information is called a gene, which is a region of the DNA that contains the instructions to produce messenger RNAs (mRNAs). An enzyme called RNA polymerase generates mRNAs through a process called transcription. In transcription, mRNAs are used as templates to produce proteins, in a subsequent process called translation. Proteins constitute the main molecular workers in the cell, whose roles include sensing signals from the environment, carrying out enzymatic reactions, and performing transcription and translation. A particular class of proteins, called transcription factors, regulates the expression of genes, and therefore control cell behavior. Transcription factors bind to DNA sites close to the promoter of the gene, which is the DNA sequence that is recognized by the RNA polymerase to start transcription. By interacting with RNA polymerase, transcription factors are able to either activate or repress the expression of genes. Cellular processes are coordinated by multiple transcription factors, which regulate themselves as well as each other, creating gene regulatory networks. In these networks, each node represents a transcription factor, and each link is a regulatory interaction. These interactions can be described by a gene regulatory function, which is a mathematical relationship that describes how the change in the cellular concentration of a transcription factor affects the transcriptional activity of the gene it regulates. These relationships, in turn, determine the expression levels of all proteins within cells, and thereby govern cell behavior at any given time. Despite their relevance, few studies have measured gene regulatory functions in a quantitative manner. Although these studies constitute an important step in elucidating the behavior of gene regulatory networks, they have limitations. First, most of these studies have been performed in bulk. By averaging over cell populations, they obscure the inherent stochasticity of transcription, which depends on a series of single-molecule events. Second, most of these studies have measured protein concentrations and transcriptional activities indirectly, possibly adding confounding factors to the measurements. In this thesis, I present work aimed at bridging the gaps in knowledge outlined above. To achieve this goal, we have developed a novel methodology that allows us to characterize the gene regulatory function of a promoter of interest in individual bacterial cells at the single-molecule level. I will demonstrate the development of a novel method to detect both individual mRNAs and protein molecules and to measure their copy-number in individual Escherichia coli cells. I also will show how we use the mRNA copy-number statistics to obtain information about the underlying stochastic kinetics of transcription. I will then use this technique to quantify the gene regulatory function of a promoter in one of the simplest and most well studied biological systems: the one comprised by the bacterium Escherichia coli and its virus, phage lambda.
Issue Date:2014-09-16
URI:http://hdl.handle.net/2142/50377
Rights Information:Copyright 2014 Leonardo A. Sepúlveda
Date Available in IDEALS:2014-09-16
2016-09-22
Date Deposited:2014-08


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