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postgraduate thesis: Quantitative study of pattern formation on a density-dependent motility biological system

TitleQuantitative study of pattern formation on a density-dependent motility biological system
Authors
Advisors
Advisor(s):Zhang, FHuang, J
Issue Date2012
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Abstract
Quantitative biology is an emerging field that attracts intensive research interests. Pattern formation is a widely studied topic both in biology and physics. Scientists have been trying to figure out the basic principles behind the fascinating patterns in the nature. It’s still difficult to lift the complex veil on the underling mechanisms, especially in biology, although lots of the achievements have been achieved. The new developments in synthetic biology provide a different approach to study the natural systems, test the theories, and develop new ones. Biological systems have many unique features different from physics and chemistry, such as growth and active movement. In this project, a link between cell density and cell motility is established through cell-cell signaling. The genetic engineered Escherichia coli cell regulates its motility by sensing the local cell density. The regulation of cell motility by cell density leads to sequential and periodical stripe patterns when the cells grow and expand on a semi-solid agar plate. This synthetic stripe pattern formation system is quantitative studied by quantitative measurements, mathematical modeling and theoretical analysis. To characterize the stripe pattern, two novel methods have been developed to quantify the key parameters, including cell growth, spatiotemporal cell density profile and cell density-dependent motility, besides the standard molecular biological measurements. To better understand the underlying principle of the stripe pattern formation, a quantitative model is developed based on the experiments. The detailed dynamic process is studied by computer simulation. Besides, the model predicts that the number of stripes can be tuned by varying the parameters in the system. This has been tested by quantitatively modulation of the basal expression level of a single gene in the genetic circuit. Moreover, theoretical analysis of a simplified model provides us a clear picture of the stripe formation process. The steady state traveling wave solution is obtained, which leads to an analytic ansatz that can determine the phase boundary between the stripe and the no-stripe phases. This study does not only provide a quantitative understanding about the novel mechanism of stripe pattern formation, but also sets an good example of quantitative studies in biology. The techniques, methods and knowledge gleaned here may be applied in various interdisciplinary fields.
DegreeDoctor of Philosophy
SubjectPattern formation (Biology)
Cells - Motility.
Dept/ProgramPhysics

 

DC FieldValueLanguage
dc.contributor.advisorZhang, F-
dc.contributor.advisorHuang, J-
dc.contributor.authorFu, Xiongfei.-
dc.contributor.author傅雄飞.-
dc.date.issued2012-
dc.description.abstractQuantitative biology is an emerging field that attracts intensive research interests. Pattern formation is a widely studied topic both in biology and physics. Scientists have been trying to figure out the basic principles behind the fascinating patterns in the nature. It’s still difficult to lift the complex veil on the underling mechanisms, especially in biology, although lots of the achievements have been achieved. The new developments in synthetic biology provide a different approach to study the natural systems, test the theories, and develop new ones. Biological systems have many unique features different from physics and chemistry, such as growth and active movement. In this project, a link between cell density and cell motility is established through cell-cell signaling. The genetic engineered Escherichia coli cell regulates its motility by sensing the local cell density. The regulation of cell motility by cell density leads to sequential and periodical stripe patterns when the cells grow and expand on a semi-solid agar plate. This synthetic stripe pattern formation system is quantitative studied by quantitative measurements, mathematical modeling and theoretical analysis. To characterize the stripe pattern, two novel methods have been developed to quantify the key parameters, including cell growth, spatiotemporal cell density profile and cell density-dependent motility, besides the standard molecular biological measurements. To better understand the underlying principle of the stripe pattern formation, a quantitative model is developed based on the experiments. The detailed dynamic process is studied by computer simulation. Besides, the model predicts that the number of stripes can be tuned by varying the parameters in the system. This has been tested by quantitatively modulation of the basal expression level of a single gene in the genetic circuit. Moreover, theoretical analysis of a simplified model provides us a clear picture of the stripe formation process. The steady state traveling wave solution is obtained, which leads to an analytic ansatz that can determine the phase boundary between the stripe and the no-stripe phases. This study does not only provide a quantitative understanding about the novel mechanism of stripe pattern formation, but also sets an good example of quantitative studies in biology. The techniques, methods and knowledge gleaned here may be applied in various interdisciplinary fields.-
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.relation.ispartofHKU Theses Online (HKUTO)-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.source.urihttp://hub.hku.hk/bib/B48199424-
dc.subject.lcshPattern formation (Biology)-
dc.subject.lcshCells - Motility.-
dc.titleQuantitative study of pattern formation on a density-dependent motility biological system-
dc.typePG_Thesis-
dc.identifier.hkulb4819942-
dc.description.thesisnameDoctor of Philosophy-
dc.description.thesisleveldoctoral-
dc.description.thesisdisciplinePhysics-
dc.description.naturepublished_or_final_version-
dc.date.hkucongregation2012-

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