bioRxivSystems Biology
A curated C. difficile strain 630 metabolic network: prediction of essential targets and inhibitors
Abstract
Clostridium difficile is the leading cause of hospital-borne infections occurring when the natural intestinal flora is depleted following antibiotic treatment. We present iMLTC804cdf, an extensively curated reconstructed metabolic network for the C. difficile pathogenic strain 630. iMLTC804cdf contains 804 genes, 705 metabolites and 766 metabolic, 145 exchange and 118 transport reactions. iMLTC804cdf is the most complete and accurate metabolic reconstruction of a gram-positive anaerobic bacteria to date. We validate the model with simulated growth assays in different media and carbon sources and use it to predict essential genes. We obtain 88.8% accuracy in the prediction of gene essentiality when compared to experimental data for B. subtilis homologs. We predict the existence of 83 essential genes and 68 essential gene pairs, a number of which are unique to C. difficile and have non-existing or predicted non-essential human homologs. For 19 of these potential therapeutic targets, we find 72 inhibitors of homologous proteins that could serve as starting points in the development of new antibiotics, including approved drugs with the potential for drug repositioning.\n\nSystems & Synthetic Biology Subject Category: Genome Scale & Integrative Biology\n\nMolecular & Cell Biology Subject Category: Pharmacology & Drug Discovery
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Novel drivers of virulence in Clostridioides difficile identified via context-specific metabolic network analysis
M. L. Jenior, J. L. Leslie, … J. A. Papin·bioRxiv·Nov 9, 2020
- Clostridium difficile colonizes alternative nutrient niches during infection across distinct murine gut microbiomes
M. L. Jenior, J. L. Leslie, … P. D. Schloss·mSystemsPeer-reviewed·Aug 29, 2017
- Computational Modeling of the Gut Microbiota Predicts Metabolic Mechanisms of Recurrent Clostridioides difficile Infection
M. A. Henson·bioRxiv·Apr 10, 2020
- Genome sequence and characterization of a hypervirulent BI/NAP1/027 Clostridioides difficile (CDC20121308)
Laureano Ángel Español, Miranda Clara Palumbo, … Virginia Pasquinelli·bioRxiv·Apr 25, 2024
- Analysis of Essential Genes in Clostridioides difficile by CRISPRi and Tn-seq
Maia E. Alberts, Micaila P. Kurtz, … David S. Weiss·Journal of BacteriologyPeer-reviewed·Sep 8, 2025
- Blocking toxin function and modulating the gut microbiota: caffeic acid phenethyl ester as a potential treatment for Clostridioides difficile infection
Yan Guo, Yong Zhang, … Jiazhang Qiu·bioRxiv·Aug 19, 2024