Model-driven evaluation of the production potential for growth-coupled products of Escherichia coli
Open accessAbstract
Integrated approaches utilizing in silico analyses will be necessary to successfully advance the field of metabolic engineering. Here, we present an integrated approach through a systematic model-driven evaluation of the production potential for the bacterial production organism Escherichia coli to produce multiple native products from different representative feedstocks through coupling metabolite production to growth rate. Designs were examined for 11 unique central metabolism and amino acid targets from three different substrates under aerobic and anaerobic conditions. Optimal strain designs were reported for designs which possess maximum yield, substrate-specific productivity, and strength of growth-coupling for up to 10 reaction eliminations (knockouts). In total, growth-coupled designs could be identified for 36 out of the total 54 conditions tested, corresponding to eight out of the 11 targets. There were 17 different substrate/target pairs for which over 80% of the theoretical maximum potential could be achieved. The developed method introduces a new concept of objective function tilting for strain design. This study provides specific metabolic interventions (strain designs) for production strains that can be experimentally implemented, characterizes the potential for E. coli to produce native compounds, and outlines a strain design pipeline that can be utilized to design production strains for additional organisms.
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During aerobic glucose-limited chemostat growth in parallel E. coli cultures for 280 generations, mutations in the glycoporin lamB and the regulator malT were identified as the cause of long-term adaptation.
“In contrast to batch selected populations, during aerobic glucose-limited chemostat growth in parallel cultures for 280 generations, mutations in the glycoporin lamB and the regulator malT were identified as the cause of long-term adaptation.”
From Adaptive laboratory evolution—Principles and applications for biotechnology (2013) · cites this paper as [49]
Within a single chemostat culture, multiple stably co-existing malT mutations were observed.
“Moreover, within a single chemostat culture, the authors observed multiple stably co-existing malT mutations [49].”
From Adaptive laboratory evolution—Principles and applications for biotechnology (2013) · cites this paper as [49]
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References 53 · Cited by 238
Research works printed but not linked: 1
- Ma F Hanna MA 1999 Biodiesel production: a review Bioresource Technology 70 1 15
- Authors
- Feist, A. M., Zielinski, D. C., Orth, J. D., Schellenberger, J., Herrgard, M. J., & Palsson, B. Ø.
- Affiliations
- University of California San Diego (US)
- Corresponding author
- Palsson, Bernhard Ø.
- Venue
- Metabolic Engineering
- Publisher
- Elsevier BV
- Published
- 2010-05
- Volume
- 12
- Issue
- 3
- Pages
- 173-186
- ISSN
- 1096-7176 (ISSN-L)
- PMC
- PMC3125152
- OpenAlex
- W1975597731
- Cited by
- 238
- References
- 53
- Citations by year
- 2026: 4 · 2025: 8 · 2024: 10 · 2023: 9 · 2022: 11 · 2021: 21 · 2020: 9 · 2019: 22 · 2018: 20 · 2017: 18 · 2016: 18 · 2015: 20 · 2014: 21 · 2013: 8 · 2012: 11
- FWCI
- 4.96
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Metabolic Engineering (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- University of California, San Diego
- National Institute of General Medical Sciences (R01GM057089)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Bacterial Genetics and Biotechnology
- Keywords
- Escherichia coli, strain design, metabolic modeling, central carbon metabolism, amino acid production, aerobic and anaerobic conditions, production yield
- MeSH terms
- Bacteria, Biological Phenomena, Escherichia coli, Growth, Models, Biological, Risk Factors
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