Cited by 172Microbial Metabolic Engineering and BioproductionBiofuel production and bioconversionGene Regulatory Network Analysis

Characterizing acetogenic metabolism using a genome-scale metabolic reconstruction of Clostridium ljungdahlii

Open access
Nagarajan, Harish, Sahin, Merve, Nogales, Juan, Latif, Haythem, Lovley, Derek R, Ebrahim, Ali, Zengler, Karsten·2013·Microbial Cell Factories

Abstract

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.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/1475-2859-12-118

Cites

52 of 52 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

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)
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
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

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review