Characterizing acetogenic metabolism using a genome-scale metabolic reconstruction of Clostridium ljungdahlii
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BACKGROUND: The metabolic capabilities of acetogens to ferment a wide range of sugars, to grow autotrophically on H2/CO2, and more importantly on synthesis gas (H2/CO/CO2) make them very attractive candidates as production hosts for biofuels and biocommodities. Acetogenic metabolism is considered one of the earliest modes of bacterial metabolism. A thorough understanding of various factors governing the metabolism, in particular energy conservation mechanisms, is critical for metabolic engineering of acetogens for targeted production of desired chemicals. RESULTS: Here, we present the genome-scale metabolic network of Clostridium ljungdahlii, the first such model for an acetogen. This genome-scale model (iHN637) consisting of 637 genes, 785 reactions, and 698 metabolites captures all the major central metabolic and biosynthetic pathways, in particular pathways involved in carbon fixation and energy conservation. A combination of metabolic modeling, with physiological and transcriptomic data provided insights into autotrophic metabolism as well as aided the characterization of a nitrate reduction pathway in C. ljungdahlii. Analysis of the iHN637 metabolic model revealed that flavin based electron bifurcation played a key role in energy conservation during autotrophic growth and helped identify genes for some of the critical steps in this mechanism. CONCLUSIONS: iHN637 represents a predictive model that recapitulates experimental data, and provides valuable insights into the metabolic response of C. ljungdahlii to genetic perturbations under various growth conditions. Thus, the model will be instrumental in guiding metabolic engineering of C. ljungdahlii for the industrial production of biocommodities and biofuels.
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Similar genome-scale models also exist for C. ljungdahlii and M. thermoacetica.
“Similar models also exist for C. ljungdahlii (Nagarajan et al., 2013) and M. thermoacetica (Islam et al., 2015).”
From Gas Fermentation—A Flexible Platform for Commercial Scale Production of Low-Carbon-Fuels and Chemicals from Waste and Renewable Feedstocks (2016) · cites this paper as Nagarajan et al., 2013
Transcriptomics analyses have been performed for C. autoethanogenum and C. ljungdahlii.
“and transcriptomics analyses of C. autoethanogenum (Mock et al., 2015; Marcellin et al., 2016) and C. ljungdahlii (Nagarajan et al., 2013; Tan et al., 2013; Whitham et al., 2015).”
From Gas Fermentation—A Flexible Platform for Commercial Scale Production of Low-Carbon-Fuels and Chemicals from Waste and Renewable Feedstocks (2016) · cites this paper as Nagarajan et al., 2013
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- Authors
- Nagarajan, H., Sahin, M., Nogales, J., Latif, H., Lovley, D. R., Ebrahim, A., & Zengler, K.
- Affiliations
- University of California San Diego (US)
- University of Massachusetts Amherst (US)
- Corresponding author
- Zengler, Karsten
- Venue
- Microbial Cell Factories
- Published
- 2013-11-25
- Volume
- 12
- Issue
- 1
- Pages
- 118-118
- ISSN
- 1475-2859 (ISSN-L)
- PMC
- PMC4222884
- OpenAlex
- W2038304602
- Cited by
- 170
- References
- 52
- Citations by year
- 2026: 8 · 2025: 8 · 2024: 10 · 2023: 9 · 2022: 23 · 2021: 11 · 2020: 13 · 2019: 13 · 2018: 19 · 2017: 19 · 2016: 11 · 2015: 13 · 2014: 13
- FWCI
- 5.52
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Microbial Cell Factories (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Science Foundation (1144086)
- U.S. Department of Energy (DEAR0000159, DEAR0000087, DESC0004917)
- Advanced Research Projects Agency - Energy (DE-AR0000159)
- Office of Science
- University of California, San Diego
- Advanced Research Projects Agency
- National Institute of General Medical Sciences (U01GM102098)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Physical Sciences › Engineering › Biomedical Engineering › Biofuel production and bioconversion
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- Clostridium ljungdahlii, genome-scale metabolic models, autotrophic growth, energy conservation, CO2 fixation, metabolic engineering, biofuels
- MeSH terms
- Acetates, Clostridium, Genome, Metabolic Networks and Pathways, Biofuels, Metabolic Engineering
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