Understanding the complex interactions that occur between heterologous and native biochemical pathways represents a major challenge in metabolic engineering and synthetic biology. We present a workflow that integrates metabolomics, proteomics, and genome-scale models of Escherichia coli metabolism to study the effects of introducing a heterologous pathway into a microbial host. This workflow incorporates complementary approaches from computational systems biology, metabolic engineering, and synthetic biology; provides molecular insight into how the host organism microenvironment changes due to pathway engineering; and demonstrates how biological mechanisms underlying strain variation can be exploited as an engineering strategy to increase product yield. As a proof of concept, we present the analysis of eight engineered strains producing three biofuels: isopentenol, limonene, and bisabolene. Application of this workflow identified the roles of candidate genes, pathways, and biochemical reactions in observed experimental phenomena and facilitated the construction of a mutant strain with improved productivity. The contributed workflow is available as an open-source tool in the form of iPython notebooks. Copyright \copyright 2016 Elsevier Inc. All rights reserved.
%0 Journal Article
%1 Brunk2016Characterizing
%A Brunk, Elizabeth
%A George, Kevin W.
%A Alonso-Gutierrez, Jorge
%A Thompson, Mitchell
%A Baidoo, Edward
%A Wang, George
%A Petzold, Christopher J.
%A McCloskey, Douglas
%A Monk, Jonathan
%A Yang, Laurence
%A O'Brien, Edward J.
%A Batth, Tanveer S.
%A Martin, Hector Garcia G.
%A Feist, Adam
%A Adams, Paul D.
%A Keasling, Jay D.
%A Palsson, Bernhard O.
%A Lee, Taek Soon S.
%D 2016
%J Cell systems
%K ecoli flux-analysis omics
%N 5
%P 335--346
%T Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow.
%U http://view.ncbi.nlm.nih.gov/pubmed/27211860
%V 2
%X Understanding the complex interactions that occur between heterologous and native biochemical pathways represents a major challenge in metabolic engineering and synthetic biology. We present a workflow that integrates metabolomics, proteomics, and genome-scale models of Escherichia coli metabolism to study the effects of introducing a heterologous pathway into a microbial host. This workflow incorporates complementary approaches from computational systems biology, metabolic engineering, and synthetic biology; provides molecular insight into how the host organism microenvironment changes due to pathway engineering; and demonstrates how biological mechanisms underlying strain variation can be exploited as an engineering strategy to increase product yield. As a proof of concept, we present the analysis of eight engineered strains producing three biofuels: isopentenol, limonene, and bisabolene. Application of this workflow identified the roles of candidate genes, pathways, and biochemical reactions in observed experimental phenomena and facilitated the construction of a mutant strain with improved productivity. The contributed workflow is available as an open-source tool in the form of iPython notebooks. Copyright \copyright 2016 Elsevier Inc. All rights reserved.
@article{Brunk2016Characterizing,
abstract = {Understanding the complex interactions that occur between heterologous and native biochemical pathways represents a major challenge in metabolic engineering and synthetic biology. We present a workflow that integrates metabolomics, proteomics, and genome-scale models of Escherichia coli metabolism to study the effects of introducing a heterologous pathway into a microbial host. This workflow incorporates complementary approaches from computational systems biology, metabolic engineering, and synthetic biology; provides molecular insight into how the host organism microenvironment changes due to pathway engineering; and demonstrates how biological mechanisms underlying strain variation can be exploited as an engineering strategy to increase product yield. As a proof of concept, we present the analysis of eight engineered strains producing three biofuels: isopentenol, limonene, and bisabolene. Application of this workflow identified the roles of candidate genes, pathways, and biochemical reactions in observed experimental phenomena and facilitated the construction of a mutant strain with improved productivity. The contributed workflow is available as an open-source tool in the form of {iPython} notebooks. Copyright {\copyright} 2016 Elsevier Inc. All rights reserved.},
added-at = {2018-12-02T16:09:07.000+0100},
author = {Brunk, Elizabeth and George, Kevin W. and Alonso-Gutierrez, Jorge and Thompson, Mitchell and Baidoo, Edward and Wang, George and Petzold, Christopher J. and McCloskey, Douglas and Monk, Jonathan and Yang, Laurence and O'Brien, Edward J. and Batth, Tanveer S. and Martin, Hector Garcia G. and Feist, Adam and Adams, Paul D. and Keasling, Jay D. and Palsson, Bernhard O. and Lee, Taek Soon S.},
biburl = {https://www.bibsonomy.org/bibtex/2226bffbc8141ac14f6adc02f5020dd28/karthikraman},
citeulike-article-id = {14379935},
citeulike-linkout-0 = {http://view.ncbi.nlm.nih.gov/pubmed/27211860},
citeulike-linkout-1 = {http://www.hubmed.org/display.cgi?uids=27211860},
day = 25,
interhash = {0fbcdcfb87b0badd38f2e2ea1d96ae70},
intrahash = {226bffbc8141ac14f6adc02f5020dd28},
issn = {2405-4712},
journal = {Cell systems},
keywords = {ecoli flux-analysis omics},
month = may,
number = 5,
pages = {335--346},
pmid = {27211860},
posted-at = {2017-06-21 07:56:19},
priority = {2},
timestamp = {2018-12-02T16:09:07.000+0100},
title = {Characterizing Strain Variation in Engineered E. coli Using a {Multi-Omics}-Based Workflow.},
url = {http://view.ncbi.nlm.nih.gov/pubmed/27211860},
volume = 2,
year = 2016
}