Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 350

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Bacterial evolution of antibiotic hypersensitivity

Open access
Lázár, Viktória, Pal Singh, Gajinder, Spohn, Réka, Nagy, István, Horváth, Balázs, Hrtyan, Mónika, Busa‐Fekete, Róbert, Bogos, Balázs, Méhi, Orsolya, Csörgő, Bálint, Pósfai, György, Fekete, Gergely, Szappanos, Balázs, Kégl, Balázs, Papp, Balázs, Pál, Csaba·2013·Molecular Systems Biology

Abstract

The evolution of resistance to a single antibiotic is frequently accompanied by increased resistance to multiple other antimicrobial agents. In sharp contrast, very little is known about the frequency and mechanisms underlying collateral sensitivity. In this case, genetic adaptation under antibiotic stress yields enhanced sensitivity to other antibiotics. Using large‐scale laboratory evolutionary experiments with Escherichia coli , we demonstrate that collateral sensitivity occurs frequently during the evolution of antibiotic resistance. Specifically, populations adapted to aminoglycosides have an especially low fitness in the presence of several other antibiotics. Whole‐genome sequencing of laboratory‐evolved strains revealed multiple mechanisms underlying aminoglycoside resistance, including a reduction in the proton‐motive force (PMF) across the inner membrane. We propose that as a side effect, these mutations diminish the activity of PMF‐dependent major efflux pumps (including the AcrAB transporter), leading to hypersensitivity to several other antibiotics. More generally, our work offers an insight into the mechanisms that drive the evolution of negative trade‐offs under antibiotic selection.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/msb.2013.57

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 4 references

Cited by

See all 350

Metadata

Authors
Lázár, V., Pal Singh, G., Spohn, R., Nagy, I., Horváth, B., Hrtyan, M., Busa‐Fekete, R., Bogos, B., Méhi, O., Csörgő, B., Pósfai, G., Fekete, G., Szappanos, B., Kégl, B., Papp, B., & Pál, C.
Venue
Molecular Systems Biology
Published
2013-01
Volume
9
Issue
1
Pages
700-700
ISSN
1744-4292 (ISSN-L)
OpenAlex
W2112833584
Cited by
350
References
4
FWCI
12.75
Type
journal article
Language
en
Open access
gold

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Bacterial evolution of antibiotic hypersensitivity. https://app.cochat.ai/papers/10.1038/msb.2013.57
The paper
Lázár, V., Pal Singh, G., Spohn, R., Nagy, I., Horváth, B., Hrtyan, M., Busa‐Fekete, R., Bogos, B., Méhi, O., Csörgő, B., Pósfai, G., Fekete, G., Szappanos, B., Kégl, B., Papp, B., & Pál, C. (2013). Bacterial evolution of antibiotic hypersensitivity. Molecular Systems Biology. https://doi.org/10.1038/msb.2013.57

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.