Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow

Elizabeth Brunk; Kevin W George; Jorge Alonso-Gutierrez; Mitchell Thompson; Edward Baidoo; George Wang; Christopher J Petzold; Douglas McCloskey; Jonathan Monk; Laurence Yang; Edward J O'Brien; Tanveer S Batth; Hector Garcia Martin; Adam Feist; Paul D Adams; Jay D Keasling; Bernhard O Palsson; Taek Soon Lee

doi:10.1016/j.cels.2016.04.004

Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow

Elizabeth Brunk, Kevin W George, Jorge Alonso-Gutierrez, Mitchell Thompson, Edward Baidoo, George Wang, Christopher J Petzold, Douglas McCloskey, Jonathan Monk, Laurence Yang, Edward J O'Brien, Tanveer S Batth, Hector Garcia Martin, Adam Feist, Paul D Adams, Jay D Keasling, Bernhard O Palsson, Taek Soon Lee

50 Citations (Scopus)

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.

Original language	English
Journal	Cell Systems
Volume	2
Issue number	5
Pages (from-to)	335-46
Number of pages	12
ISSN	2405-4712
DOIs	https://doi.org/10.1016/j.cels.2016.04.004
Publication status	Published - 25 May 2016

Access to Document

10.1016/j.cels.2016.04.004

http://www.cell.com/article/S2405471216301120/pdf

Cite this

Brunk, E., George, K. W., Alonso-Gutierrez, J., Thompson, M., Baidoo, E., Wang, G., Petzold, C. J., McCloskey, D., Monk, J., Yang, L., O'Brien, E. J., Batth, T. S., Martin, H. G., Feist, A., Adams, P. D., Keasling, J. D., Palsson, B. O., & Lee, T. S. (2016). Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow. Cell Systems, 2(5), 335-46. https://doi.org/10.1016/j.cels.2016.04.004

Brunk, E, George, KW, Alonso-Gutierrez, J, Thompson, M, Baidoo, E, Wang, G, Petzold, CJ, McCloskey, D, Monk, J, Yang, L, O'Brien, EJ, Batth, TS, Martin, HG, Feist, A, Adams, PD, Keasling, JD, Palsson, BO & Lee, TS 2016, 'Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow', Cell Systems, vol. 2, no. 5, pp. 335-46. https://doi.org/10.1016/j.cels.2016.04.004

@article{453bf531f741458e897b804d51174ef1,

title = "Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow",

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.",

author = "Elizabeth Brunk and George, {Kevin W} and Jorge Alonso-Gutierrez and Mitchell Thompson and Edward Baidoo and George Wang and Petzold, {Christopher J} and Douglas McCloskey and Jonathan Monk and Laurence Yang and O'Brien, {Edward J} and Batth, {Tanveer S} and Martin, {Hector Garcia} and Adam Feist and Adams, {Paul D} and Keasling, {Jay D} and Palsson, {Bernhard O} and Lee, {Taek Soon}",

year = "2016",

month = may,

day = "25",

doi = "10.1016/j.cels.2016.04.004",

language = "English",

volume = "2",

pages = "335--46",

journal = "Cell Systems",

issn = "2405-4712",

publisher = "Cell Press",

number = "5",

}

TY - JOUR

T1 - Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow

AU - Brunk, Elizabeth

AU - George, Kevin W

AU - Alonso-Gutierrez, Jorge

AU - Thompson, Mitchell

AU - Baidoo, Edward

AU - Wang, George

AU - Petzold, Christopher J

AU - McCloskey, Douglas

AU - Monk, Jonathan

AU - Yang, Laurence

AU - O'Brien, Edward J

AU - Batth, Tanveer S

AU - Martin, Hector Garcia

AU - Feist, Adam

AU - Adams, Paul D

AU - Keasling, Jay D

AU - Palsson, Bernhard O

AU - Lee, Taek Soon

PY - 2016/5/25

Y1 - 2016/5/25

N2 - 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.

AB - 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.

U2 - 10.1016/j.cels.2016.04.004

DO - 10.1016/j.cels.2016.04.004

M3 - Journal article

C2 - 27211860

SN - 2405-4712

VL - 2

SP - 335

EP - 346

JO - Cell Systems

JF - Cell Systems

IS - 5

ER -

Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow

Abstract

Access to Document

Fingerprint

Cite this