The distinction between resistance and tolerance is central to the argument. Resistant bacteria grow even in the presence of an antibiotic, and the mutations that confer resistance are readily detected because they allow measurable growth under drug pressure. Tolerant bacteria, by contrast, survive antibiotic exposure without necessarily growing, and they do so in ways that can be temporary and hard to distinguish from ordinary physiological stasis. That has historically made tolerance difficult to study: if a phenotype is transient and non-heritable, it leaves little trace in the kinds of experiments that classical microbiology was built to perform. The result has been a research landscape in which resistance mechanisms are well catalogued while tolerance mechanisms remain comparatively obscure.

Kobras’s review contends that this obscurity is no longer tenable, because the tools now exist to interrogate tolerance at the level of the genome. Genome-wide analyses, combined with laboratory evolution experiments and functional genetic screens, have begun to reveal the pathways that allow bacteria to survive antibiotic exposure beyond the familiar model of dormant, metabolically quiescent cells. Laboratory evolution, in which bacterial populations are propagated under antibiotic stress over many generations, allows tolerance-associated variants to accumulate and be identified through whole-genome sequencing of the evolved lineages. Functional screens, including genome-scale knockout and overexpression libraries, allow researchers to ask systematically which genes, when disrupted or amplified, change how long cells survive a drug.

The technical power of these approaches lies in their convergence. Sequencing an evolved population identifies candidate mutations, but it cannot by itself distinguish causal changes from hitchhikers. Functional screens provide the complementary evidence: if a mutation identified by evolution also produces a tolerance phenotype when introduced deliberately, the case for causality strengthens. Combining the two, alongside precise reconstruction of variants in clean genetic backgrounds, allows the genetic architecture of tolerance to be resolved, including cases where multiple loci interact. This is where the concept of epistasis becomes important. The review highlights that the effects of tolerance variants may depend on the presence of other variants, meaning that the same mutation can produce different survival outcomes in different genetic backgrounds. Untangling these interactions is essential if tolerance is to be predicted from sequence data alone.

One of the most consequential shifts described in the review is conceptual. The dominant model of antibiotic tolerance has centred on persisters, a subpopulation of cells that enter a dormant or slow-growing state and thereby evade antibiotics that kill actively growing bacteria. Dormancy remains an important part of the picture, but the genomics-driven work summarised by Kobras reveals survival pathways that operate independently of the dormant-cell model. Bacteria can survive antibiotic exposure through active physiological responses, stress-response programmes and metabolic adjustments that are encoded in the genome and subject to evolutionary modification. Recognising this breadth matters because it expands the set of potential intervention points: if tolerance is not solely a property of dormant cells, then strategies aimed solely at waking persisters up may address only part of the problem.

The clinical stakes are considerable. Treatment failure in bacterial infections is usually attributed to resistance, but tolerance can plausibly explain cases in which patients fail therapy despite isolates that test as susceptible in the laboratory. Standard susceptibility testing measures growth inhibition at fixed drug concentrations, a framework that can miss survival phenotypes expressed over longer time scales or under the fluctuating drug concentrations that occur in treated patients. Tolerant populations also buy time for resistance to emerge, because cells that survive initial exposure constitute the population in which resistance mutations can subsequently arise. The review therefore frames tolerance not only as a direct cause of treatment failure but as a factor that shapes the evolution of resistance itself, an influence that genomic approaches are now positioned to quantify.

That connection between tolerance and resistance evolution is one of the areas the review identifies as ripe for further work. If particular tolerance genotypes accelerate the emergence of resistance, then detecting those genotypes in patient-derived isolates could inform treatment choices before resistance becomes detectable by conventional means. Genome-wide analyses of tolerance offer a route to identifying candidate genes and variants in clinical isolates, extending the insights of laboratory systems to the strains that actually cause disease. Population genomics of clinical collections could, in principle, reveal whether tolerance-associated variants recur in specific lineages, correlate with treatment outcomes, or precede the acquisition of classical resistance determinants.

Kobras is careful, however, about the limits of the current evidence base. Most of what is known about the genetics of tolerance comes from laboratory systems: reference strains, defined media, controlled drug exposures and evolution experiments designed to make phenotypes measurable. Whether the pathways identified under those conditions operate to the same extent, or in the same combinations, in the environments of actual infections is unresolved. Infection sites present bacteria with nutrient limitation, host immune pressures, biofilm structures and antibiotic concentrations that vary over space and time, and any of these factors could modify the contribution of a given tolerance variant. The review presents the translation of laboratory insights into patient-derived isolates as the key outstanding challenge, and as the step that will determine whether genomic tolerance research changes clinical practice.

The potential payoffs of meeting that challenge are spelled out in diagnostic and therapeutic terms. On the diagnostic side, a better understanding of tolerance genetics could support assays that flag tolerant genotypes in isolates, complementing conventional susceptibility testing and giving clinicians a more complete picture of how a pathogen is likely to behave during therapy. On the therapeutic side, the pathways revealed by genome-wide analyses define candidate targets for drugs that would sensitize tolerant bacteria to existing antibiotics, an attractive strategy because it would extend the useful life of drugs already in the clinic rather than requiring entirely new classes of antimicrobials. Combination therapy designed to eliminate tolerant subpopulations could also reduce the reservoir from which resistance emerges, addressing both problems simultaneously.

The review, which is open access and was published on 2 October 2026 after being received on 28 May and accepted on 24 August, arrives at a moment when antimicrobial resistance remains one of the most pressing threats to global health, and when the research community is increasingly aware that resistance alone does not explain every therapeutic failure. By consolidating the genomics-driven transformation of tolerance research, Kobras provides a roadmap for a field moving from phenomenology toward mechanism. The core message is that antibiotic tolerance has a genetics, that this genetics is now tractable with modern tools, and that resolving it, first in the laboratory and then in patient-derived isolates, offers a realistic path toward diagnostics and therapies that account for the full range of bacterial survival strategies. If that programme succeeds, the stubborn gap between a susceptible laboratory test and a failed course of treatment may finally begin to close.

Subject of Research: Genomic analysis of antibiotic tolerance and its genetic basis in bacteria

Article Title: Transforming antibiotic tolerance research through genomics

Article References: Kobras, C. M. (2026). Transforming antibiotic tolerance research through genomics. Genome Biology. https://doi.org/10.1186/s13059-026-04257-x

Image Credits: AI Generated

DOI: 10.1186/s13059-026-04257-x

Keywords: antibiotic tolerance, antimicrobial resistance, bacterial genomics, persistence, epistasis, laboratory evolution, functional genomics, treatment failure, population genomics, bacterial survival, Genome Biology, microbial genetics