Bacterial heteroresistance mechanisms, dynamics, and emerging diagnostic approaches.

Antibiotic heteroresistance is a form of within-isolate susceptibility heterogeneity in which an apparently susceptible bacterial population contains rare subpopulations capable of growth at substantially higher antibiotic concentrations. It is commonly defined as resistant minorities occurring at frequencies ≥10-7 and growing at concentrations at least eight-fold above those that inhibit the dominant population, as demonstrated by population analysis profiling or related assays. This phenomenon has been described in diverse Gram-negative and Gram-positive pathogens and across multiple drug classes and is frequently characterized by instability, with resistant subpopulations expanding under treatment and contracting once drug pressure is relieved. This dynamic behavior contributes to systematic under-detection by routine antimicrobial susceptibility testing, which is optimized for population-average endpoints and may miss clinically relevant resistant tails, helping explain treatment failure despite 'susceptible' results. Mechanistically, heteroresistance spans a continuum from genotypic processes, including gene amplification, plasmid copy-number variation, transposition, and point mutations, to phenotypic mechanisms driven by reversible regulatory and physiological states such as transcriptional reprogramming, stochastic expression variability, and intergenerational phenotypic memory. These mechanisms can coexist and shift under antibiotic selection, supporting the view that heteroresistance may act as an evolutionary intermediate linking susceptibility and stable resistance. Recent advances in single-cell phenotyping, copy-number-aware genomics, transcriptomics, pharmacodynamic and population modeling, and machine-learning-assisted diagnostics offer new opportunities to detect and interpret susceptibility distributions. Integrating these approaches into clinical microbiology and stewardship will be essential to improve risk stratification, guide therapy, and predict resistance evolution.