The dynamics of genetic networks

Living cells are made up of networks of interacting genes, proteins and biochemicals. Simple interactions between network components can lead to complex collective dynamics. Cells use these emergent dynamical properties to propagate signals and perform computations, to probe their surroundings and generate appropriate responses. These phenomena can only be understood at the network level, not at the level of individual components. We have explored the behavior of a variety of biological networks, using quantitative experimental measurements to validate the predictions of detailed network models. Signal and noise in genetic networks. Biochemical reactions often involve small numbers of molecules, and are therefore dominated by stochastic fluctuations. We theoretically analyzed the origin of fluctuations in linearized genetic networks, and showed that these fluctuations could be suppressed by certain network architectures. We then experimentally measured the expression of a reporter protein in single cells of an isogenic bacterial population, and found that stochastic mechanisms caused expression levels to vary from cell to cell. We demonstrated that this variability arose due to number fluctuations in transcription and translation processes, and showed that it could be regulated using genetic parameters. Computational properties of genetic networks. Regulatory networks implement intricate computations which determine the response of a cell to external stimuli. The phosphotransferase system of Escherichia coli regulates the metabolism of several sugars. We used a biochemical model of the system to investigate the range of possible metabolic responses it could generate.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Physics.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2004

Author dc:creator

• Thattai, Mukund, 1976-

Advisor dc:contributor.advisor

• Alexander van Oudenaarden and Sebastian Seung.

• Physics.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/29458

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/29458