Signal processing and decision making in single cells

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 2008.

Bibliographic Details
Main Author: Mettetal, Jerome Thomas, II
Other Authors: Alexander van Oudenaarden.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2009
Subjects:
Online Access:http://hdl.handle.net/1721.1/45445
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author Mettetal, Jerome Thomas, II
author2 Alexander van Oudenaarden.
author_facet Alexander van Oudenaarden.
Mettetal, Jerome Thomas, II
author_sort Mettetal, Jerome Thomas, II
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description Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 2008.
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spelling mit-1721.1/454452019-04-12T21:30:09Z Signal processing and decision making in single cells Mettetal, Jerome Thomas, II Alexander van Oudenaarden. Massachusetts Institute of Technology. Dept. of Physics. Massachusetts Institute of Technology. Dept. of Physics. Physics. Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 2008. Includes bibliographical references (p. 199-206). Cells are not simple passive observers oblivious to their environment, but sense and adapt to environmental changes in order to thrive. In addition to sensing the presence of signals in the environment, cells can extract information relating to the dynamics and spatial location of these signals and implement a response to these extracellular perturbations. This work examines a variety of signal-processing and decision-making processes across several different organisms. To explore the connection between biological network topology and temporal signal processing, we study how periodic signals are propagated in the Hog1 osmotic response pathway of the budding yeast Saccharomyces cerevisiae. Utilizing systems identification tools from control engineering, we study how the cells rapidly and robustly maintain osmotic homeostasis. By measuring the expression level of key proteins we begin to understand how fluctuating environments regulate gene expression. The lac operon in Escherichia coli has the ability to display a bistable, "all-ornothing" response to sugar. To understand how noise drives transitions between these two stable states, we measure switching dynamics in a population of cells. A simple model is constructed that can make predictions about system behavior unavailable from a deterministic model. Further, by measuring individual switching events in a similar bistable system implemented in the Galactose utilization pathway of Saccharomyces cerevisiae, we find that correlations in switching times of related individuals can be explained in terms of correlations in levels of key regulatory proteins. Many single celled organisms, such as the slime mold Dictyostelium discoideum, can sense and respond to concentration gradients of extracellular signaling molecules. We find that the cells' ability to detect an extracellular signal is influenced by an asymmetric intracellular signal, which varies in direction and magnitude from cell-to-cell. Further, a model that accounts for both signals predicts the observed population response to directed stimuli. (cont.) Finally, we explore a "bet-hedging" strategy for fluctuating environments with an engineered population of Saccharomyces cerevisiae cells that randomly switch between two phenotypes. Each phenotype is fit to one of two alternating environments. We find that to optimize fitness, cells must tune the phenotypic transition rates in accordance with the rate of environmental transitions. by Jerome Thomas Mettetal, II. Ph.D. 2009-04-29T17:43:41Z 2009-04-29T17:43:41Z 2008 2008 Thesis http://hdl.handle.net/1721.1/45445 318116978 eng 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 206 p. application/pdf Massachusetts Institute of Technology
spellingShingle Physics.
Mettetal, Jerome Thomas, II
Signal processing and decision making in single cells
title Signal processing and decision making in single cells
title_full Signal processing and decision making in single cells
title_fullStr Signal processing and decision making in single cells
title_full_unstemmed Signal processing and decision making in single cells
title_short Signal processing and decision making in single cells
title_sort signal processing and decision making in single cells
topic Physics.
url http://hdl.handle.net/1721.1/45445
work_keys_str_mv AT mettetaljeromethomasii signalprocessinganddecisionmakinginsinglecells