{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/99301"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/99301","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Modeling heterogeneity in the microbial world","abstract":"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).","abstract_html":"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).","abstract_has_math":false,"creators":["Cole, Jr., John Andrew"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Physics","degree_department":null,"school":null,"contributors":["Luthey-Schulten, Zaida","Goldenfeld, Nigel","Chemla, Yann","Kuehn, Seppe"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-03-13T15:45:06Z","date_published":"2018-03-13T15:45:06Z","updated_at":"2026-07-22T22:24:37Z","subjects":["Stochastic gene expression, metabolism"],"languages":["en"],"rights":["Copyright 2017 John A. Cole Jr."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/99301","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Luthey-Schulten, Zaida","Goldenfeld, Nigel","Chemla, Yann","Kuehn, Seppe"]},{"key":"dc:creator","label":"Author","values":["Cole, Jr., John Andrew"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2018-03-13T15:45:06Z","2017-10-10","2017-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Physics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Stochastic gene expression, metabolism"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2017 John A. Cole Jr."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/99301"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["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).","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2018-03-13 without embargo terms","The student, John Cole, Jr., accepted the attached license on 2017-10-09 at 14:31.","The student, John Cole, Jr., submitted this Dissertation for approval on 2017-10-09 at 14:43.","This Dissertation was approved for publication on 2017-10-10 at 13:45.","DSpace SAF Submission Ingestion Package generated from Vireo submission #11673 on 2018-03-13 at 10:07:51","Made available in DSpace on 2018-03-13T15:45:06Z (GMT). No. of bitstreams: 2 COLEJR-DISSERTATION-2017.pdf: 13584842 bytes, checksum: 0e5a96087634612898a4cf763e12bb32 (MD5) LICENSE.txt: 4206 bytes, checksum: 0c02340c78b3c2f13fa20ed0205c172f (MD5) Previous issue date: 2017-10-10"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Modeling heterogeneity in the microbial world"]}]}],"canonical_facts":{"dc:contributor":["Luthey-Schulten, Zaida","Goldenfeld, Nigel","Chemla, Yann","Kuehn, Seppe"],"dc:creator":["Cole, Jr., John Andrew"],"dc:date":["2018-03-13T15:45:06Z","2017-10-10","2017-12"],"dc:description":["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).","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2018-03-13 without embargo terms","The student, John Cole, Jr., accepted the attached license on 2017-10-09 at 14:31.","The student, John Cole, Jr., submitted this Dissertation for approval on 2017-10-09 at 14:43.","This Dissertation was approved for publication on 2017-10-10 at 13:45.","DSpace SAF Submission Ingestion Package generated from Vireo submission #11673 on 2018-03-13 at 10:07:51","Made available in DSpace on 2018-03-13T15:45:06Z (GMT). No. of bitstreams: 2 COLEJR-DISSERTATION-2017.pdf: 13584842 bytes, checksum: 0e5a96087634612898a4cf763e12bb32 (MD5) LICENSE.txt: 4206 bytes, checksum: 0c02340c78b3c2f13fa20ed0205c172f (MD5) Previous issue date: 2017-10-10"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/99301"],"dc:language":["en"],"dc:rights":["Copyright 2017 John A. Cole Jr."],"dc:subject":["Stochastic gene expression, metabolism"],"dc:title":["Modeling heterogeneity in the microbial world"],"dc:type":["text"],"thesis:degree_discipline":["Physics"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:37Z"}