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ATP-Dependent Persister Formation in Escherichia coli
Open accessAbstract
Persisters are dormant variants that form a subpopulation of cells tolerant to antibiotics. Persisters are largely responsible for the recalcitrance of chronic infections to therapy. In Escherichia coli , one widely accepted model of persister formation holds that stochastic accumulation of ppGpp causes activation of the Lon protease that degrades antitoxins; active toxins then inhibit translation, resulting in dormant, drug-tolerant persisters. We found that various stresses induce toxin-antitoxin (TA) expression but that induction of TAs does not necessarily increase persisters. The 16S rRNA promoter rrnB P1 was proposed to be a persister reporter and an indicator of toxin activation regulated by ppGpp. Using fluorescence-activated cell sorting (FACS), we confirmed the enrichment for persisters in the fraction of rrnB P1 -gfp dim cells; however, this is independent of toxin-antitoxins. rrnB P1 is coregulated by ppGpp and ATP. We show that rrnB P1 can report persisters in a relA / spoT deletion background, suggesting that rrnB P1 is a persister marker responding to ATP. Consistent with this finding, decreasing the level of ATP by arsenate treatment causes drug tolerance. Lowering ATP slows translation and prevents the formation of DNA double-strand breaks upon fluoroquinolone treatment. We conclude that variation in ATP levels leads to persister formation by decreasing the activity of antibiotic targets. IMPORTANCE Persisters are a subpopulation of antibiotic-tolerant cells responsible for the recalcitrance of chronic infections. Our current understanding of persister formation is primarily based on studies of E. coli . The activation of toxin-antitoxin systems by ppGpp has become a widely accepted model for persister formation. In this study, we found that stress-induced activation of mRNA interferase-type toxins does not necessarily cause persister formation. We also found that the persister marker rrnB P1 reports persister cells because it detects a drop in cellular ATP levels. Consistent with this, lowering the ATP level decreases antibiotic target activity and, thus, leads to persister formation. We conclude that stochastic variation in ATP is the main mechanism of persister formation. A decrease in ATP provides a satisfactory explanation for the drug tolerance of persisters, since bactericidal antibiotics act by corrupting energy-dependent targets.
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![FIG 1 Upregulation of TA modules plays a limited role in persister formation. (A to E) MG1655 (wild type [WT]) was grown under stress as described in Materials and Methods to approximately the same starting density as the control. Cultures were then challenged with ciprofloxacin (0.5 μg/ml) or ampicillin (100 μg/ml) for 4 h (A, C, D, E) or 5 h (B). (F, G) Strains with deletions of toxins showing increased expression under sodium stress or isoleucine starvation were tested for persister formation. MG1655 (WT) and isogenic mutant strains were grown to the same cell density under the indicated stress and then challenged with ampicillin (100 μg/ml) or ciprofloxacin (0.5 μg/ml) for 5 h (F) or 4 h (G). Results are expressed as percent survival by comparison to untreated culture prior to the addition of antibiotic. Data are the average results from at least two independent experiments performed with three biological replicates (n ≥ 6). An asterisk indicates a significant difference (P < 0.05) by two-tailed Student’s t test. Error bars represent standard deviations.](/paper-figures/e3258d9655454159af3502d09d615fcf/atp-dependent-persister-formation-in-i-escherichia-coli-i-figure-1.jpg)




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“It has been well studied that dormant state reduces the exposure of antibiotic targets and helps bacterial cells tolerate a variety of antibiotics, a process linked to the toxin-antitoxin system [18,54].”
From Antifungal persistence: Clinical relevance and mechanisms (2025) · cites this paper as [54]
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Metadata
- Authors
- Shan, Y., Brown Gandt, A., Rowe, S. E., Deisinger, J. P., Conlon, B. P., & Lewis, K.
- Affiliations
- Northeastern University (US)
- Department of Biology, Antimicrobial Discovery Center, Northeastern University, Boston, Massachusetts, USA
- Corresponding author
- Lewis, Kim
- Venue
- mBio
- Publisher
- American Society for Microbiology
- Published
- 2017-03-08
- Volume
- 8
- Issue
- 1
- ISSN
- 2150-7511 (ISSN-L)
- 2161-2129
- PMC
- PMC5296605
- OpenAlex
- W2586386056
- Cited by
- 508
- References
- 71
- Citations by year
- 2026: 55 · 2025: 61 · 2024: 47 · 2023: 42 · 2022: 54 · 2021: 61 · 2020: 56 · 2019: 69 · 2018: 37 · 2017: 26
- FWCI
- 34.04
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- mBio (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- UNC Libraries
- Funders
- DH | National Institute for Health Research (R01AI110578)
- Charles A. King Trust (Fellowship)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Bacterial Genetics and Biotechnology
- Health Sciences › Medicine › Infectious Diseases › Antimicrobial Resistance in Staphylococcus
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bacterial biofilms and quorum sensing
- Keywords
- persister cells, antibiotic tolerance, Escherichia coli, ATP levels, toxin-antitoxin systems, ppGpp, Lon protease, arsenate, protein synthesis inhibition, DNA double-strand breaks, fluoroquinolones, chronic infection
- MeSH terms
- Adenosine Triphosphate, Drug Tolerance, Escherichia coli, Gene Expression Regulation, Bacterial, Microbial Viability
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 ›
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