| Title | Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow. |
| Year of Publication | 2016 |
| Authors | E. Brunk; K.W. George; J. Alonso-Gutierrez; M. Thompson; E. Baidoo; G. Wang; C.J. Petzold; D. McCloskey; J. Monk; L. Yang; E.J. O'Brien; T.S. Batth; H.Garcia Martin; A. Feist; P.D. Adams; J.D. Keasling; B.O. Palsson; T.Soon Lee |
| Journal | PLoS Comput Biol |
| 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. |
| PubMed ID | 27211860 |
