Flux Balance Analysis of Escherichia coli under Temperature and pH Stress Conditions

Handle URI:
http://hdl.handle.net/10754/552665
Title:
Flux Balance Analysis of Escherichia coli under Temperature and pH Stress Conditions
Authors:
Xu, Xiaopeng ( 0000-0003-2414-7851 )
Abstract:
An interesting discovery in biology is that most genes in an organism are dispensable. That means these genes have minor effects on survival of the organism in standard laboratory conditions. One explanation of this discovery is that some genes play important roles in specific conditions and are essential genes under those conditions. E. coli is a model organism, which is widely used. It can adapt to many stress conditions, including temperature, pH, osmotic, antibiotic, etc. Underlying mechanisms and associated genes of each stress condition responses are usually different. In our analysis, we combined protein abundance data and mutant conditional fitness data into E. coli constraint-based metabolic models to study conditionally essential metabolic genes under temperature and pH stress conditions. Flux Balance Analysis was employed as the modeling method to analysis these data. We discovered lists of metabolic genes, which are E. coli dispensable genes, but conditionally essential under some stress conditions. Among these conditionally essential genes, atpA in low pH stress and nhaA in high pH stress found experimental evidences from previous studies. Our study provides new conditionally essential gene candidates for biologists to explore stress condition mechanisms.
Advisors:
Gao, Xin ( 0000-0002-7108-3574 )
Committee Member:
Soloviev, Victor ( 0000-0001-8885-493X ) ; Bajic, Vladimir B. ( 0000-0001-5435-4750 )
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Program:
Computer Science
Issue Date:
12-May-2015
Type:
Thesis
Appears in Collections:
Theses; Computer Science Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.advisorGao, Xinen
dc.contributor.authorXu, Xiaopengen
dc.date.accessioned2015-05-12T13:37:56Zen
dc.date.available2015-05-12T13:37:56Zen
dc.date.issued2015-05-12en
dc.identifier.urihttp://hdl.handle.net/10754/552665en
dc.description.abstractAn interesting discovery in biology is that most genes in an organism are dispensable. That means these genes have minor effects on survival of the organism in standard laboratory conditions. One explanation of this discovery is that some genes play important roles in specific conditions and are essential genes under those conditions. E. coli is a model organism, which is widely used. It can adapt to many stress conditions, including temperature, pH, osmotic, antibiotic, etc. Underlying mechanisms and associated genes of each stress condition responses are usually different. In our analysis, we combined protein abundance data and mutant conditional fitness data into E. coli constraint-based metabolic models to study conditionally essential metabolic genes under temperature and pH stress conditions. Flux Balance Analysis was employed as the modeling method to analysis these data. We discovered lists of metabolic genes, which are E. coli dispensable genes, but conditionally essential under some stress conditions. Among these conditionally essential genes, atpA in low pH stress and nhaA in high pH stress found experimental evidences from previous studies. Our study provides new conditionally essential gene candidates for biologists to explore stress condition mechanisms.en
dc.language.isoenen
dc.subjectflux balance analysisen
dc.subjectstress conditionen
dc.subjectMetabolic modelingen
dc.subjectflux variability analysisen
dc.titleFlux Balance Analysis of Escherichia coli under Temperature and pH Stress Conditionsen
dc.typeThesisen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
thesis.degree.grantorKing Abdullah University of Science and Technologyen_GB
dc.contributor.committeememberSoloviev, Victoren
dc.contributor.committeememberBajic, Vladimir B.en
thesis.degree.disciplineComputer Scienceen
thesis.degree.nameMaster of Scienceen
dc.person.id129052en
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