Are all antibiotic persisters created equal?
Open accessAbstract
Antibiotic persisters are a sub-population of bacteria able to survive in the presence of bactericidal antibiotic despite the lack of heritable drug resistance mechanisms. This phenomenon exists across many bacterial species and is observed for many different antibiotics. Though these bacteria are often described as “multidrug persisters” very few experiments have been carried out to determine the homogeneity of a persister population to different drugs. Further, there is much debate in the field as to the origins of a persister cell. Is it formed spontaneously? Does it form in response to stress? These questions are particularly pressing in the field of Mycobacterium tuberculosis, where persisters may play a crucial role in the required length of treatment and the development of multidrug resistant organisms. Here we aim to interpret the known mechanisms of antibiotic persistence and how they may relate to improving treatments for M. tuberculosis, exposing the gaps in knowledge that prevent us from answering the question: Are all antibiotic persisters created equal?
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Fungal persisters are often recalcitrant to multiple antibiotics, as has been observed in antibiotic persistence.
“In antibiotic persistence, persisters are often recalcitrant to multiple antibiotics [49,50], which has been observed with fungal persisters as well.”
From Antifungal persistence: Clinical relevance and mechanisms (2025) · cites this paper as [50]
The “Multidrug persistence” section reports bacterial persister populations that tolerate some antibiotic combinations and show cross-tolerance to certain other drugs. It also says cross-tolerance varies by drug and cautions that finding persisters after separate drug treatments does not establish that the same persisters tolerate multiple antibiotics. The source therefore supports the possibility, but not the unqualified frequency implied by “often.” The citation is attached to the antibiotic-persistence clause, not the statement about fungal persisters. (LLM, conf=0.82)
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Prach, L. M., Pascopella, L., Barry, P. M., Flood, J., Porco, T. C., Hopewell, P. C., & Metcalfe, J. Z. (2013) · AIDS · doi:10.1097/01.aids.0000432445.07437.07 · Cited by 16 · see citing works
Saravanan, P., Dusthackeer, A., Rajmani, R. S., Mahizhaveni, B., Nirmal, C. R., Rajadas, S. E., Bhardwaj, N., Ponnuraja, C., Bhaskar, A., Hemanthkumar, A. K., et al. (2021) · Scientific Reports · doi:10.1038/s41598-020-80439-2 · Cited by 14 · see citing works
Determinants of serum concentration of first-line anti-tuberculosis drugs from China
Lei, Q., Wang, H., Zhao, Y., Dang, L., Zhu, C., Lv, X., Wang, H., & Zhou, J. (2019) · Medicine · doi:10.1097/md.0000000000017523 · Cited by 10 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Antibiotic tolerance: targeting bacterial survival
Boeck, L. (2023) · Current Opinion in Microbiology · doi:10.1016/j.mib.2023.102328 · Cited by 31 · see citing works
Proton motive force and antibiotic tolerance in bacteria
Wan, Y., Zheng, J., Chan, E. W., & Chen, S. (2024) · Microbial Biotechnology · doi:10.1111/1751-7915.70042 · Cited by 16 · see citing works
Association Between Diabetes Mellitus–Tuberculosis and the Generation of Drug Resistance
Cornejo-Báez, A. A., Zenteno‐Cuevas, R., & Luna‐Herrera, J. (2024) · Microorganisms · doi:10.3390/microorganisms12122649 · Cited by 16 · see citing works
Bacterial survivors: evaluating the mechanisms of antibiotic persistence
Shi, X., & Zarkan, A. (2022) · Microbiology · doi:10.1099/mic.0.001266 · Cited by 15 · see citing works
Nontuberculous Mycobacteria, Mucociliary Clearance, and Bronchiectasis
Retuerto-Guerrero, M., López-Medrano, R., de Freitas-González, E., & Rivero-Lezcano, O. M. (2024) · Microorganisms · doi:10.3390/microorganisms12040665 · Cited by 13 · see citing works
Liu, T., Wang, Y., Hou, Z., Shi, Z., Wang, R., Shi, Y., Hua, L., Wu, L., Xu, M., Ding, X., et al. (2024) · BMC Microbiology · doi:10.1186/s12866-024-03424-z · Cited by 12 · see citing works
Choi, V., Carugo, D., & Stride, E. (2025) · npj Antimicrobials and Resistance · doi:10.1038/s44259-025-00086-3 · Cited by 12 · see citing works
Antifungal persistence: Clinical relevance and mechanisms
Wang, R., Lv, J., Chen, L., Zhao, Y., & Du, H. (2025) · PLoS pathogens · doi:10.1371/journal.ppat.1013456 · Cited by 12 · see citing works
“In antibiotic persistence, persisters are often recalcitrant to multiple antibiotics [49,50], which has been observed with fungal persisters as well.”
Huang, Y., Zong, Y., Jiang, Y., Lu, J., Yang, G., Li, H., Wang, Z., Zhou, Y., Liao, G., Cheng, L., et al. (2025) · Journal of Materials Chemistry B · doi:10.1039/d5tb00450k · Cited by 5 · see citing works
Pal, P., Khan, M. Y., Sharma, S., Kumar, Y., Mangla, N., Kaushal, P. S., & Agarwal, N. (2023) · Communications Biology · doi:10.1038/s42003-023-05059-8 · Cited by 4 · see citing works
Ikeda, H., & Maeda, S. (2024) · Microorganisms · doi:10.3390/microorganisms12091888 · Cited by 3 · see citing works
Persister Intestinal Bacteria, Epigenetics and Major Depression
Vitetta, L., Bambling, M., & Strodl, E. S. (2025) · Frontiers in Bioscience-Landmark · doi:10.31083/fbl26837 · Cited by 2 · see citing works
Persister cells and antibiotic resistance: an overview
Glory, A. Z. K. (2023) · doi:10.61577/jmi.2023.100002
Liu, T., Wang, Y., Hou, Z., Shi, Z., Wang, R., Shi, Y., Hua, L., Wu, L., Xu, M., Ding, X., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26420328
Deng, Y., Beahm, D. R., Maurais, H. E., Etheridge, K., Schultz, D., & Sarpeshkar, R. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.30.702957
Tavares, M. R. S., Andreo, N., Lôbo, T. D. L. G. F., de França, C. A., Félix, W. P., Moreira, M. A. S., Azevedo, V. A. D. C., Brenig, B., Broetto, L., & da Costa, M. M. (2026) · Network Modeling Analysis in Health Informatics and Bioinformatics · doi:10.1007/s13721-026-00767-7
Sarpeshkar, R., Deng, Y., Beahm, D. R., Maurais, H. E., Etheridge, K., & Schultz, D. (2026) · Research Square · doi:10.21203/rs.3.rs-9022969/v1
Shultis, M. W., Mulholland, C. V., Cui, J., Chen, M., Johnson, S., Hiner, C. R., & Berney, M. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.05.28.728405
Self-citationMihnev, A., Luong, D., Porat, J., & Chang, R. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.10.23.761362
- Authors
- Shultis, M. W., Mulholland, C. V., & Berney, M.
- Affiliations
- Albert Einstein College of Medicine (US)
- Corresponding author
- Berney, Michael
- Venue
- Frontiers in Cellular and Infection Microbiology
- Publisher
- Frontiers Media SA
- Published
- 2022-08-17
- Volume
- 12
- Pages
- 933458-933458
- ISSN
- 2235-2988 (ISSN-L)
- PMC
- PMC9428696
- OpenAlex
- W4292317564
- Cited by
- 19
- References
- 95
- Citations by year
- 2026: 4 · 2025: 4 · 2024: 7 · 2023: 3 · 2022: 1
- FWCI
- 0.58
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Cellular and Infection Microbiology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Potts Memorial Foundation
- National Institute of Allergy and Infectious Diseases
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Bacterial Genetics and Biotechnology
- Health Sciences › Medicine › Infectious Diseases › Tuberculosis Research and Epidemiology
- Health Sciences › Medicine › Infectious Diseases › Antimicrobial Resistance in Staphylococcus
- Keywords
- Mycobacterium tuberculosis, antibiotic tolerance, multidrug resistance, stress response, tuberculosis treatment duration
- MeSH terms
- Anti-Bacterial Agents, Mycobacterium tuberculosis
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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