Expanding the Capabilities of Constraint-based Metabolic Models for Biotechnology Purposes

Over the past decade, the constraint-based approach to metabolic modeling has become an important tool for understanding and controlling biology. Unfortunately, the application of this novel approach to systems biology in biotechnology has been limited by three significant technical issues: existing...

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Main Author: Zhuang, Kai
Other Authors: Mahadevan, Radhakrishnan
Language:en_ca
Published: 2012
Subjects:
Online Access:http://hdl.handle.net/1807/35079
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spelling ndltd-TORONTO-oai-tspace.library.utoronto.ca-1807-350792013-04-19T19:58:37ZExpanding the Capabilities of Constraint-based Metabolic Models for Biotechnology PurposesZhuang, Kaimetabolismmodelingoptimization0542Over the past decade, the constraint-based approach to metabolic modeling has become an important tool for understanding and controlling biology. Unfortunately, the application of this novel approach to systems biology in biotechnology has been limited by three significant technical issues: existing metabolic modeling methods cannot completely model the overflow metabolism, cannot model the metabolism of microbial communities, and cannot design strains optimized for productivity and titer. Three computational methods – the Flux Balance Analysis with Membrane Economics (FBAME) method, the Dynamic Multi-species Metabolic Modeling (DyMMM) framework, and the Dynamic Strain Scanning Optimization (DySScO) strategy – have been developed to resolve these issues respectively. First, the FBAME method, which adopts the membrane occupancy limitation hypothesis, was used to explain and predict the phenomenon of overflow metabolism, an important metabolic phenomenon in industrial fermentation, in Escherichia coli. Then, the DyMMM framework was used to investigate the community metabolism during uranium bioremediation, and demonstrated that the simultaneous addition of acetate and Fe(III) may be a theoretically viable uranium bioremediation strategy. Lastly, the DySScO strategy, which combines the DyMMM framework with existing strain design algorithms, was used to design commodity-chemical producing E. coli optimized for a balanced product yield, titer, and volumetric productivity. These novel computational methods allow for broader applications of constraint-based metabolic models in biotechnology settings.Mahadevan, Radhakrishnan2012-112013-03-04T15:28:34ZNO_RESTRICTION2013-03-04T15:28:34Z2013-03-04Thesishttp://hdl.handle.net/1807/35079en_ca
collection NDLTD
language en_ca
sources NDLTD
topic metabolism
modeling
optimization
0542
spellingShingle metabolism
modeling
optimization
0542
Zhuang, Kai
Expanding the Capabilities of Constraint-based Metabolic Models for Biotechnology Purposes
description Over the past decade, the constraint-based approach to metabolic modeling has become an important tool for understanding and controlling biology. Unfortunately, the application of this novel approach to systems biology in biotechnology has been limited by three significant technical issues: existing metabolic modeling methods cannot completely model the overflow metabolism, cannot model the metabolism of microbial communities, and cannot design strains optimized for productivity and titer. Three computational methods – the Flux Balance Analysis with Membrane Economics (FBAME) method, the Dynamic Multi-species Metabolic Modeling (DyMMM) framework, and the Dynamic Strain Scanning Optimization (DySScO) strategy – have been developed to resolve these issues respectively. First, the FBAME method, which adopts the membrane occupancy limitation hypothesis, was used to explain and predict the phenomenon of overflow metabolism, an important metabolic phenomenon in industrial fermentation, in Escherichia coli. Then, the DyMMM framework was used to investigate the community metabolism during uranium bioremediation, and demonstrated that the simultaneous addition of acetate and Fe(III) may be a theoretically viable uranium bioremediation strategy. Lastly, the DySScO strategy, which combines the DyMMM framework with existing strain design algorithms, was used to design commodity-chemical producing E. coli optimized for a balanced product yield, titer, and volumetric productivity. These novel computational methods allow for broader applications of constraint-based metabolic models in biotechnology settings.
author2 Mahadevan, Radhakrishnan
author_facet Mahadevan, Radhakrishnan
Zhuang, Kai
author Zhuang, Kai
author_sort Zhuang, Kai
title Expanding the Capabilities of Constraint-based Metabolic Models for Biotechnology Purposes
title_short Expanding the Capabilities of Constraint-based Metabolic Models for Biotechnology Purposes
title_full Expanding the Capabilities of Constraint-based Metabolic Models for Biotechnology Purposes
title_fullStr Expanding the Capabilities of Constraint-based Metabolic Models for Biotechnology Purposes
title_full_unstemmed Expanding the Capabilities of Constraint-based Metabolic Models for Biotechnology Purposes
title_sort expanding the capabilities of constraint-based metabolic models for biotechnology purposes
publishDate 2012
url http://hdl.handle.net/1807/35079
work_keys_str_mv AT zhuangkai expandingthecapabilitiesofconstraintbasedmetabolicmodelsforbiotechnologypurposes
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