Decoding the spatiotemporal heterogeneity of bacterial virulence gene expression using single-cell approaches.

Bacterial pathogenicity arises from dynamic interactions between microbial virulence determinants and host conditions, in which infection outcomes are shaped by both host immunity and phenotypic heterogeneity within clonal bacterial populations. Rather than behaving as uniform entities, bacterial populations diversify into distinct physiological states across space and time during infection. This heterogeneity stems from stochastic gene expression, environmental fluctuations, genetic variation, and cellular aging, generating subpopulations with distinct physiological states. Mechanisms such as bistability, phase variation, persistence, quorum sensing, and history-dependent behavior enable bacteria to diversify phenotypes across space and time, promoting survival under fluctuating and hostile conditions. These strategies underpin cooperative behaviors including division of labor and bet-hedging, which enhance population fitness, virulence potential and resilience during infection. Pathogens exploit heterogeneity to balance acute virulence with long-term persistence, evade host immunity, establish biofilms, and tolerate antibiotic treatment. Recent advances in single-cell technologies, including bacterial single-cell transcriptomics, fluorescent reporter systems integrated with microfluidics, and stable isotope probing, now enable direct measurement of bacterial heterogeneity at unprecedented resolution and within structured environments. Here, we review the molecular mechanisms generating bacterial heterogeneity, the regulatory architectures underlying these processes, and the single-cell technologies that enable their study. Understanding how rare but critical bacterial subpopulations drive infection dynamics will be essential for developing anti-virulence and precision antimicrobial strategies targeting pathogenic subpopulations rather than average population behavior.