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<p><i>Vibrio cholerae</i> thrives at the interface between the aquatic environment and the human host dynamically through integration of environmental signals to highly coordinated virulence programs. This review examines how environmental sensing systems, regulatory networks, biofilm formation, and secretory systems have been integrated to maintain stability, transmission, and pathogenesis. By incorporating these advances in genomics, transcriptomics, proteomics, metabolomics, and predictive models, we demonstrate how multi-omics approaches have changed our understanding of condition-related virulence regulation at the system-level view. In addition, we extend this framework via comparative analysis among pathogenic <i>Vibrio</i> species and also reveal conserved regulatory architectures alongside species-specific adaptations that affect ecological fitness and pathological potential. Finally, discussing how multi-omics and machine learning integration can enable outbreak prediction, inform One Health approaches, and identify environmental regulating anti-virulence targets. This integrated insight positions environmental regulation as a central organizing agent of Vibrio pathogenicity and provides a roadmap for translating complex biological datasets to practical insights in the public health and treatment field.</p>

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Environmental regulation of virulence in Vibrio cholerae: integrating multi-omics, predictive models, and comparative insights across emerging Vibrio species

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月7日

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  • Seyed Soheil Tabibian,
  • Shayan Yaghmayee,
  • Aryan Rahbar,
  • Ava Khalili Dehkordi,
  • Samira Sanami,
  • Omid Pajand

摘要

Vibrio cholerae thrives at the interface between the aquatic environment and the human host dynamically through integration of environmental signals to highly coordinated virulence programs. This review examines how environmental sensing systems, regulatory networks, biofilm formation, and secretory systems have been integrated to maintain stability, transmission, and pathogenesis. By incorporating these advances in genomics, transcriptomics, proteomics, metabolomics, and predictive models, we demonstrate how multi-omics approaches have changed our understanding of condition-related virulence regulation at the system-level view. In addition, we extend this framework via comparative analysis among pathogenic Vibrio species and also reveal conserved regulatory architectures alongside species-specific adaptations that affect ecological fitness and pathological potential. Finally, discussing how multi-omics and machine learning integration can enable outbreak prediction, inform One Health approaches, and identify environmental regulating anti-virulence targets. This integrated insight positions environmental regulation as a central organizing agent of Vibrio pathogenicity and provides a roadmap for translating complex biological datasets to practical insights in the public health and treatment field.