aceQuorum-sensing, microbiome interactions, and emerging artificial intelligence-assisted anti-virulence strategies in Salmonella Typhi: a critical review of translational opportunities and challenges
Typhoid fever, caused by Salmonella enterica subsp. enterica serovar Typhi (Salmonella Typhi), remains a significant global health challenge that is increasingly complicated by the emergence and spread of multidrug-resistant (MDR) and extensively drug-resistant strains. Growing limitations of antibiotic-centered treatment strategies have stimulated interest in anti-virulence approaches targeting bacterial regulatory networks rather than viability alone. Among these, quorum-sensing (QS), particularly the LuxS-med…
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This critical review from July 30 2026 examines quorum-sensing, particularly LuxS-mediated AI-2 signaling, in Salmonella Typhi as a regulator of virulence, biofilm formation, and persistence amid rising multidrug-resistant and extensively drug-resistant typhoid. It surveys microbiome interactions and a range of anti-QS strategies and evaluates the role of AI, multi-omics integration, and systems-level frameworks in target identification and therapeutic prioritization.
The health relevance is that QS-targeted approaches could complement antibiotics and vaccines for typhoid control, but the review finds they remain investigational. Uncertainty remains about in vivo efficacy in S. Typhi specifically, clinically validated biomarkers, microbiome variability, ecological safety, and delivery and regulatory pathways, which limits near-term translation.
- Typhoid fever remains complicated by multidrug-resistant and extensively drug-resistant Salmonella Typhi strains.
- Review focuses on LuxS-mediated autoinducer-2 quorum-sensing regulation of virulence, biofilm formation, and persistence.
- Assessed interventions include microbiome-mediated quorum quenching, probiotics, phytochemicals, signal-degrading enzymes, and nucleic acid-based approaches.
- AI and multi-omics integration were examined for target identification and microbial network reconstruction.
AI with multi-omics and systems-level frameworks was used to support target identification, microbial network reconstruction, biomarker discovery, and therapeutic prioritization for anti-virulence strategies against Salmonella Typhi.
The rundown
The review distinguishes experimentally validated findings in S. Typhi from evidence extrapolated from non-typhoidal Salmonella and other enteric bacteria, and examines ecological interplay between QS, gut microbiome dynamics, and host responses affecting colonization resistance.
It comparatively assesses emerging anti-QS approaches including probiotics, postbiotics, phytochemicals, antimicrobial peptides, bacteriophage-associated approaches, and signal-degrading enzymes for mechanisms, evidence strength, and translational readiness as of July 30 2026.
Sources
- Peer-reviewedArchives of Microbiology2026-07-30
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