Evidence map›Paper›PMID 42687645›Full record

ArticleJournal of microbiology (Seoul, Korea)2026

Fluctuating environmental adaptation shapes antibiotic survival in Mycobacterium tuberculosis.

Eun Seon Chung

Abstract read
In one paragraph

Article in Journal of microbiology (Seoul, Korea), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Eun Seon ChungDepartment of Molecular Biology and Microbiology, Tufts University School of Medicine, Boston, MA 02111, USA.

Funding

Tufts University School of Medicine
6 · The paper itself

Abstract

Mycobacterium tuberculosis (Mtb) encounters diverse and fluctuating microenvironments during infection, including changes in nutrient availability and pH. While adaptation to individual host-associated conditions has been extensively studied, the impact of repeated environmental fluctuations on bacterial physiology and antibiotic survival remains unclear. In this study, we investigated how long-term adaptation to stable or fluctuating environments influences Mtb growth and drug responses. Mtb populations were serially passaged for six consecutive passages under combinations of different carbon sources and pH conditions that were either maintained consistently or altered across passages. Environmental history significantly affected bacterial growth dynamics and antibiotic survival. Notably, under identical final condition with cholesterol as a sole carbon source, populations adapted to a stable environment exhibited higher survival following bedaquiline and rifampicin treatment than populations exposed to fluctuating environments. These findings suggest that stable environments promote the optimization of growth and stress-response programs, whereas environmental fluctuations limit such optimization despite potentially increasing phenotypic heterogeneity and a possibility of survival. Together, our results identify environmental history as an important determinant of antibiotic survival in Mtb and highlight the need to consider dynamic host-like environments when investigating tuberculosis physiology and drug responses.

Indexed as

Adaptation, PhysiologicalAntitubercular AgentsMycobacterium tuberculosisCarbonCholesterolDiarylquinolinesEnvironmentHydrogen-Ion ConcentrationMicrobial Sensitivity TestsMicrobial ViabilityRifampinAntitubercular AgentsbedaquilineCarbonCholesterolDiarylquinolinesRifampinantibiotic tolerancefluctuating environmentsMycobacterium tuberculosis

Identifiers

PMID42687645
PMCPMC13688124

What OpenQuestion holds

Textmetadata
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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.