Toward a whole-cell model of Escherichia coli

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Abstract/Contents

Abstract
Whole-cell computational models comprehensively simulate the growth and division of single cells, explicitly accounting for the functions of all known gene products and their interactions. Such models have the potential to revolutionize biology by serving as a platform to interpret complex behaviors, prioritize experiments, and enable design. In 2012, our lab completed the first whole-cell model of the simplest culturable organism, Mycoplasma genitalium. Since then we have focused our efforts on modeling Escherichia coli, one of the foundational model organisms in biology. In addition to having 10 times more genes and 50 times more molecules than M. genitalium, E. coli exhibits sophisticated regulation in response to environmental stimuli and perturbations. Currently, we have an E. coli model that incorporates the function of over 1200 genes and synthesizes tens of thousands of data points collected from both high- and low-throughput experiments performed over the last six decades. In building this model, we have incorporated many of E. coli's feedback control mechanisms, included hundreds of kinetic constraints in a model of metabolism, decreased simulation runtime more than ten-fold, and demonstrated the ability of our simulated cells to reliably reproduce over multiple generations. Furthermore, we have used the model to explore behaviors that arise from the interactions of multiple biological processes. In doing so, we have uncovered and quantified the prevalence of sub-generational gene expression. As the model continues to expand in size and scope, we hope that it will further our understanding of cell physiology and find practical applications in synthetic biology and medicine.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2017
Issuance monographic
Language English

Creators/Contributors

Associated with Macklin, Derek Nathaniel
Associated with Stanford University, Department of Bioengineering.
Primary advisor Covert, Markus
Thesis advisor Covert, Markus
Thesis advisor Altman, Russ
Thesis advisor Bryant, Zev David
Advisor Altman, Russ
Advisor Bryant, Zev David

Subjects

Genre Theses

Bibliographic information

Statement of responsibility Derek Nathaniel Macklin.
Note Submitted to the Department of Bioengineering.
Thesis Thesis (Ph.D.)--Stanford University, 2017.
Location electronic resource

Access conditions

Copyright
© 2017 by Derek Nathaniel Macklin
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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