HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Journal articles

Predictive regulatory and metabolic network models for systems analysis of Clostridioides difficile

Abstract : We present predictive models for comprehensive systems analysis of Clostridioides difficile, the etiology of pseudomembranous colitis. By leveraging 151 published transcriptomes, we generated an EGRIN model that organizes 90% of C. difficile genes into a transcriptional regulatory network of 297 co-regulated modules, implicating genes in sporulation, carbohydrate transport, and metabolism. By advancing a metabolic model through addition and curation of metabolic reactions including nutrient uptake, we discovered 14 amino acids, diverse carbohydrates, and 10 metabolic genes as essential for C. difficile growth in the intestinal environment. Finally, we developed a PRIME model to uncover how EGRIN-inferred combinatorial gene regulation by transcription factors, such as CcpA and CodY, modulates essential metabolic processes to enable C. difficile growth relative to commensal colonization. The C. difficile interactive web portal provides access to these model resources to support collaborative systems-level studies of context-specific virulence mechanisms in C. difficile.
Complete list of metadata

Contributor : Nadine Delarue Connect in order to contact the contributor
Submitted on : Friday, February 18, 2022 - 2:02:13 PM
Last modification on : Friday, April 15, 2022 - 3:03:32 AM

Links full text



Mario Arrieta-Ortiz, Selva Rupa Christinal Immanuel, Serdar Turkarslan, Wei-Ju Wu, Brintha Girinathan, et al.. Predictive regulatory and metabolic network models for systems analysis of Clostridioides difficile. Cell Host & Microbe, 2021, 29 (11), pp.1709-1723.e5. ⟨10.1016/j.chom.2021.09.008⟩. ⟨pasteur-03580007⟩



Record views