Integrated Metabolic Modeling, Culturing, and Transcriptomics Explain Enhanced Virulence of Vibrio cholerae during Coinfection with Enterotoxigenic Escherichia coli

Author:

Abdel-Haleem Alyaa M.12ORCID,Ravikumar Vaishnavi3,Ji Boyang4,Mineta Katsuhiko1,Gao Xin1,Nielsen Jens34ORCID,Gojobori Takashi12,Mijakovic Ivan34

Affiliation:

1. King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Centre (CBRC), Thuwal, Saudi Arabia

2. King Abdullah University of Science and Technology (KAUST), Biological and Environmental Sciences and Engineering (BESE) Division, Thuwal, Saudi Arabia

3. Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kongens Lyngby, Denmark

4. Systems and Synthetic Biology, Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden

Abstract

Most studies proposing new strategies to manage and treat infections have been largely focused on identifying druggable targets that can inhibit a pathogen's growth when it is the single cause of infection. In vivo , however, infections can be caused by multiple species. This is important to take into account when attempting to develop or use current antibacterials since their efficacy can change significantly between single infections and coinfections. In this study, we used genome-scale metabolic models (GEMs) to interrogate the growth capabilities of Vibrio cholerae in single infections and coinfections with enterotoxigenic E. coli (ETEC), which cooccur in a large fraction of diarrheagenic patients. Coinfection model predictions showed that V. cholerae growth capabilities are enhanced in the presence of ETEC relative to V. cholerae single infection, through cross-fed metabolites made available to V. cholerae by ETEC. In vitro , cocultures of the two enteric pathogens further confirmed model predictions showing an increased growth of V. cholerae in coculture relative to V. cholerae single cultures while ETEC growth was suppressed. Dual RNAseq analysis of the cocultures also confirmed that the transcriptome of V. cholerae was distinct during coinfection compared to single-infection scenarios where processes related to metabolism were significantly perturbed. Further, in silico gene-knockout simulations uncovered discrepancies in gene essentiality for V. cholerae growth between single infections and coinfections. Integrative model-guided analysis thus identified druggable targets that would be critical for V. cholerae growth in both single infections and coinfections; thus, designing inhibitors against those targets would provide a broader spectrum of coverage against cholera infections.

Funder

Chalmers University of Technology

King Abdullah University of Science and Technology

Publisher

American Society for Microbiology

Subject

Computer Science Applications,Genetics,Molecular Biology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics,Biochemistry,Physiology,Microbiology

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