MODELING BIOLOGICAL SYSTEMS WITH CYBERNETIC CONTROL LAWS AND STEADY STATE FLUX DISTRIBUTIONS
Loading...
No Access Until
Permanent Link(s)
Collections
Other Titles
Authors
Abstract
Metabolism is a process by which organisms extract energy from its environment to power itself. The interplay between cellular environment, nutrients present and the chemical reactions occurring within the organisms dictate the execution of metabolism. Single cell microbes, such as E. coli, P. putida and yeast, can be redesigned to be miniature chemical reactors that transform sugars and other carbon sources into biofuels. Enhancing bio-process conditions can stimulate the production of therapeutic proteins in mammalian cells. Hence, understanding the strategy of metabolism in organisms would help us build better technologies for controlling formation of end products like cell mass, biofuels,therapeutic proteins etc. Steady state flux analysis techniques have gained a lot of popularity in the field of systems biology due to successful qualitative analysis of large scale metabolic networks. This technique has been used to improve production of ethanol in Saccharomyces cerevisiae and lactic acid in Escherichia coli (E. coli), to name a few examples. Despite this success, its major shortcoming re-mains in providing quantitative measurements of metabolite profiles that can be further validated with experiments. Previous cybernetic models have accurately validated experimental results and described molecular processes governing metabolism, but their application is limited to small scale metabolic net-works. We have built a mathematical framework that combines solutions from steady state flux analysis with cybernetic principles to overcome the challenge of describing metabolic data for large scale metabolic networks. We have established computational models that can capture dynamic metabolic regulation in bacterial and mammalian cells. These models integrate chemical kinetics, mass balances, enzyme catalysis and stoichiometric laws to predict biology that can help us optimize cellular machinery towards bioproduct formation.
Journal / Series
Volume & Issue
Description
78 pages
Sponsorship
Date Issued
2019-12
Publisher
Keywords
Cybernetic Modeling; Flux Balance Analysis; Markov Chain Monte Carlo; Metabolic Engineering; Modeling Cell Growth for E. coli and CHO cells; Steady State Flux Analysis
Location
Effective Date
Expiration Date
Sector
Employer
Union
Union Local
NAICS
Number of Workers
Committee Chair
Varner, Jeffrey D.
DeLisa, Matthew
DeLisa, Matthew
Committee Co-Chair
Committee Member
Degree Discipline
Chemical Engineering
Degree Name
M.S., Chemical Engineering
Degree Level
Master of Science
Related Version
Related DOI
Related To
Related Part
Based on Related Item
Has Other Format(s)
Part of Related Item
Related To
Related Publication(s)
Link(s) to Related Publication(s)
References
Link(s) to Reference(s)
Previously Published As
Government Document
ISBN
ISMN
ISSN
Other Identifiers
Rights
Attribution-ShareAlike 4.0 International
Types
dissertation or thesis