Evidence map›Paper›PMID 42353650›Full record

ReviewAntibiotics (Basel, Switzerland)2026

Bacterial Persister Cells as Evolutionary Catalysts of Antibiotic Resistance: Mechanisms, Clinical Implications, and Therapeutic Strategies.

Tae-Jong Kim

Abstract readReview
In one paragraph

Review in Antibiotics (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Tae-Jong KimDepartment of Forest Products and Biotechnology, Kookmin University, Seoul 02707, Republic of Korea.ORCID 0000-0002-7483-0432

Funding

Korea Forest Service RS-2024-00404816
6 · The paper itself

Abstract

Antibiotic resistance is a growing global health threat. However, its evolution cannot be fully understood without considering antibiotic tolerance and persistence. Persister cells are phenotypic variants that survive lethal antibiotic exposure without heritable resistance, primarily through growth arrest, metabolic slowdown, and stress-adaptive states. Although persistence has been viewed as a transient survival phenomenon, increasing evidence suggests that it may also have a genetic basis by preserving populations during antibiotic-induced bottlenecks and enabling regrowth, mutation, and selection under certain conditions. This review examines the molecular mechanisms underlying persister formation, including toxin-antitoxin systems, stringent-response signaling, ATP depletion, translational arrest, and stress-response networks. We discuss how persistence contributes to antibiotic tolerance in biofilms, host environments, and recurrent infections, and how repeated antibiotic exposure may promote stepwise evolution from phenotypic survival to stable resistance in specific contexts. Evidence from experimental evolution, clinical observations, and system-level analyses supports a potential but context-dependent link between persistence and resistance. We also highlight therapeutic strategies targeting persister cells, including antipersister compounds, metabolic activation, combination therapies, bacteriophages, and alternative approaches. Finally, we outline future research directions, emphasizing single-cell technologies, systems biology, longitudinal clinical studies, and evolution-informed treatment design. A comprehensive understanding of persistence and its evolutionary implications is essential for improving treatment efficacy and limiting the emergence of long-term antibiotic resistance.

Indexed as

antibiotic resistance evolutionantibiotic toleranceantipersister strategiesbacterial persister cellsbiofilmsphenotypic heterogeneitystress response networks

Identifiers

PMID42353650
PMCPMC13295575

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.