Title

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

Document Type

Article

Publication Date

11-10-2021

Publication Title

Cell Host Microbe

Keywords

washington; seattle; isb; Biological networks; Clostridioides difficile; Commensals; EGRIN; Host-pathogen interactions; In vivo adaptive response; Integrated Regulatory and Metabolic Network Model; PRIME; Web Portal

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.

Clinical Institute

Digestive Health

Department

Institute for Systems Biology

Department

Gastroenterology

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