Evidence map›Paper›PMID 42000255›Full record

ReviewTrends in genetics : TIG2026

Heterogeneity in microbial antibiotic responses: genetic basis and within-host evolution.

Qingyun Liu, Liang-Dong Lyu

Abstract readReview
In one paragraph

Review in Trends in genetics : TIG, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Qingyun LiuDepartment of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. Electronic address: qingyun_liu@med.unc.edu.
Liang-Dong LyuKey Laboratory of Medical Molecular Virology of the Ministry of Education/Ministry of Health, Department of Medical Microbiology and Parasitology, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China; Shanghai Clinical Research Center for Tuberculosis, Shanghai Key Laboratory of Tuberculosis, Shanghai Pulmonary Hospital, Shanghai 200433, China. Electronic address: ld.lyu@fudan.edu.cn.

Funding

Population Genomics-Guided Dissection of the Bacterial Genetic Basis of Tuberculosis TransmissibilityDP2AI192739 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Qingyun Liu · 2025 to 2026
$933k
NIAID NIH HHS DP2 AI192739
6 · The paper itself

Abstract

Antibiotic response phenotypes have traditionally been classified as either sensitive or resistant. However, accumulating evidence indicates that bacterial responses to antibiotics are far more heterogeneous than previously appreciated. A growing set of new descriptors-including antibiotic persistence, tolerance, heteroresistance, resilience, and perseverance-has been introduced to capture noncanonical antibiotic phenotypes, which are widespread in bacteria and recognized as a cause of treatment failure. Although defined by different criteria, these phenotypes all converge on the heterogeneous nature of bacterial antibiotic responses. In this review, we focus on the heterogeneity-causing mechanisms embedded in genome maintenance, transcription, and translation; discuss how within-host evolved mutations can modulate regulatory stochasticity and shift population dynamics in ways that favor bacterial propagation; and highlight key future directions.

Indexed as

Anti-Bacterial AgentsBacteriaDrug Resistance, BacterialAnimalsBiological EvolutionEvolution, MolecularHumansMutationPhenotypeAnti-Bacterial Agentsantibiotic resistanceantibiotic susceptibilityantibiotic tolerancemutagenesispopulation heterogeneitystochastic gene expressionwithin-host evolution

Identifiers

PMID42000255
PMCPMC13094712

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.