Evidence map›Paper›PMID 42875544›Full record

ReviewNature reviews. Urology2026

Bacterial strategies for surviving antibiotics during urinary tract infection: could uropathogenic Escherichia coli be persisters?

Ariana Costas, Bill Söderström, Molly A Ingersoll

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Urology, 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

3 authors.

Ariana CostasMucosal Inflammation and Immunity Team, Université Paris Cité, CNRS, INSERM, Institut Cochin, Paris, France.ORCID http://orcid.org/0009-0006-4370-507X
Bill SöderströmAustralian Institute for Microbiology and Infection, University of Technology Sydney, Ultimo, Sydney, New South Wales, Australia.ORCID http://orcid.org/0000-0001-9266-5322
Molly A IngersollMucosal Inflammation and Immunity Team, Université Paris Cité, CNRS, INSERM, Institut Cochin, Paris, France. molly.ingersoll@pasteur.fr.ORCID http://orcid.org/0000-0002-6388-7003

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Treating bacterial infections, such as urinary tract infection (UTI), with antibiotics does not always resolve the infection and often results in subsequent re-infection. Treatment failure can be driven by bacterial mechanisms of resistance, tolerance or persistence, collectively known as the antibiotic non-response. Antibiotic resistance is well characterized across various bacterial species and implicated in poor clinical outcomes in various infection settings. In the instance of resistance, bacteria harbour genetic determinants to evade antibiotics and continue to grow during treatment. Notably, bacteria can escape antibiotic killing in the absence of resistance genes. In response to the environment, an entire bacterial population can slow its growth rate, becoming tolerant to bactericidal antibiotic exposure. Alternatively, a subpopulation of bacteria, known as persister cells, survive whereas the remainder of the population is eliminated by bactericidal antibiotics. Both mechanisms enable bacteria to survive treatment, with the capacity to regrow following cessation of antibiotic treatment. However, our understanding of tolerance and persistence in the context of UTI is limited. Thus, two bacterial phenotypes that might contribute to poor outcomes are overlooked both in the clinic and in research, which could add to the challenges of treatment failure and recurrent UTI.

Identifiers

PMID42875544

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.