Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 629

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Persisters: a distinct physiological state of E. coli

Open access
Shah, Devang, Zhang, Zhigang, Khodursky, Arkady B, Kaldalu, Niilo, Kurg, Kristi, Lewis, Kim·2006·BMC Microbiology

Abstract

Background: Bacterial populations contain persisters, phenotypic variants that constitute approximately 1% of cells in stationary phase and biofilm cultures. Multidrug tolerance of persisters is largely responsible for the inability of antibiotics to completely eradicate infections. Recent progress in understanding persisters is encouraging, but the main obstacle in understanding their nature was our inability to isolate these elusive cells from a wild-type population since their discovery in 1944. Results: We hypothesized that persisters are dormant cells with a low level of translation, and used this to physically sort dim E. coli cells which do not contain sufficient amounts of unstable GFP expressed from a promoter whose activity depends on the growth rate. The dim cells were tolerant to antibiotics and exhibited a gene expression profile distinctly different from those observed for cells in exponential or stationary phases. Genes coding for toxin-antitoxin module proteins were expressed in persisters and are likely contributors to this condition. Conclusion: We report a method for persister isolation and conclude that these cells represent a distinct state of bacterial physiology.

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 · 10.1186/1471-2180-6-53

Cites

3 of 3 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 3 references

Cited by

See all 629

Metadata

Authors
Shah, D., Zhang, Z., Khodursky, A. B., Kaldalu, N., Kurg, K., & Lewis, K.
Venue
BMC Microbiology
Published
2006-06-12
Volume
6
Issue
1
ISSN
1471-2180
OpenAlex
W2145676608
Cited by
629
References
3
FWCI
10.43
Type
journal article
Language
en
Open access
green

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: Persisters: a distinct physiological state of E. coli. https://app.cochat.ai/papers/10.1186/1471-2180-6-53
The paper
Shah, D., Zhang, Z., Khodursky, A. B., Kaldalu, N., Kurg, K., & Lewis, K. (2006). Persisters: a distinct physiological state of E. coli. BMC Microbiology. https://doi.org/10.1186/1471-2180-6-53

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.