Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemistry, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 123-134). / Humans are exposed to a variety of infectious pathogens, such as virus, bacteria, etc. But we survive thanks to our immune systems. One of the important immune systems is the adaptive immune system, which mounts pathogen specific immune responses. The orchestrators are lymphocytes, including B cells and T cells. When lymphocytes are stimulated strongly enough by infected or antigen-presenting cells, the signal will be transmitted through a complex network of biochemical reactions underlying the cellular functions. Such a complex network is fundamentally regulated by stochastic principles with intriguing behaviors. This thesis aims to understand the signaling network in lymphocytes and the stochastic regulation behind. In lymphocytes, mitogen-activated protein (MAP) kinases can be triggered by various stimuli (growth factors, cytokines, etc.) with significant cellular responses (proliferation, inflammation, etc.). We first investigate the roles of upstream proteins, Son of Sevenless (SOS) and Ras guanyl-releasing protein (RasGRP), in MAP kinases, Erk and P38, activation. The signaling pathways of P38 activation are still elusive. In Chapter 3, we study two signaling pathways for P38 activation, the classical pathway through the linker for activation of T cells (LAT) complex and the alternative pathway directly via ZAP-70 molecules. In both of studies, we bring together computational tools, stochastic theories and cell biology by collaborating with biologists, Professor Jeroen Roose and Dr. Jesse Jun, in University of California, San Francisco. In biochemical systems, like lymphocytes, fluctuations are ubiquitous. Such noise may drive biochemical systems from one stable state to the other with biological significance. In this part of the work, we investigate fluctuation-driven transitions in two biochemical models: genetic toggle switches (GTS) and self/non-self peptide-major histocompatibility complex (MHC) discrimination models. In the GTS model, we introduce dynamical disorder in rate coefficients and study its influences in optimal transition paths, transition rates, and the stationary probability distribution of the system. In peptide-MHC discrimination part, we investigate the effects of a conformational change step of ZAP-70 molecules on the sensitivity and robustness of the discrimination. / by Hang Chen. / Ph. D.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/105020 |
| Date | January 2016 |
| Creators | Chen, Hang, Ph. D. Massachusetts Institute of Technology |
| Contributors | Arup K. Chakraborty., Massachusetts Institute of Technology. Department of Chemistry., Massachusetts Institute of Technology. Department of Chemistry. |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 134 pages, application/pdf |
| 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., http://dspace.mit.edu/handle/1721.1/7582 |
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