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Updated: Oct 15, 2026

Time-Lapse Epifluorescence Microscopy Imaging of Pseudomonas aeruginosa and Staphylococcus aureus Heterogeneous Phenotypes
Published on: February 14, 2025
Heteroresistance tolerance and persistence in antibiotic treatment failure
Aida Ombašić1, Farah Assala Messaoudi2
1Sarajevo Medical School, University Sarajevo School of Science and Technology, Sarajevo, Bosnia and Herzegovina. aida.ombasic@ssst.edu.ba.
Abstract:
Antibiotic susceptibility testing measures growth inhibition but incompletely describes the population heterogeneity and time-dependent survival that can compromise bacterial eradication. This narrative review integrates foundational experiments with recent mechanistic, diagnostic and clinical studies of heteroresistance, tolerance and persistence. Four complementary dimensions organize interpretation: growth during exposure, population fraction, minimum inhibitory concentration behaviour and killing kinetics. These dimensions distinguish phenotypes without making them mutually exclusive. Heteroresistance can arise through resistance-gene amplification, plasmid copy-number changes or regulatory and mutational variation; recent studies demonstrate alternative routes to increased gene dosage and limitations of targeting amplification alone. Tolerance and persistence involve context-dependent changes in growth, energy allocation, damage avoidance and repair, but neither dormancy nor toxin-antitoxin activation provides a universal explanation. Experimental evolution and longitudinal clinical isolates support links to resistance evolution, whereas patient-level outcome associations remain inconsistent. Positive findings in Escherichia coli bloodstream infections and selected cefiderocol-treated cohorts must be interpreted alongside negative studies and methodological limitations. An integrated workflow combines routine susceptibility testing, population analysis, time-kill measurements and survivor retesting, with single-cell approaches used to resolve ambiguous results. Evidence tables separate mechanistic and animal findings from clinical associations. The principal translational challenge is to establish whether phenotype-informed management improves outcomes beyond conventional susceptibility-guided care, rather than assuming that detection alone establishes clinical causality or dictates treatment.
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