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The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.

Targeting bacterial membrane function: an underexploited mechanism for treating persistent infections

Open access
Hurdle, Julian G., O'Neill, Alex J., Chopra, Ian, Lee, Richard E.·2011·Nature Reviews Microbiology

Abstract

Persistent infections involving slow-growing or non-growing bacteria are hard to treat with antibiotics that target biosynthetic processes in growing cells. Consequently, there is a need for antimicrobials that can treat infections containing dormant bacteria. In this Review, we discuss the emerging concept that disrupting the bacterial membrane bilayer or proteins that are integral to membrane function (including membrane potential and energy metabolism) in dormant bacteria is a strategy for treating persistent infections. The clinical applicability of these approaches is exemplified by the efficacy of lipoglycopeptides that damage bacterial membranes and of the diarylquinoline TMC207, which inhibits membrane-bound ATP synthase. Despite some drawbacks, membrane-active agents form an important new means of eradicating recalcitrant, non-growing bacteria.

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Crossref · 10.1038/nrmicro2474

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Metadata

Authors
Hurdle, J. G., O'Neill, A. J., Chopra, I., & Lee, R. E.
Venue
Nature Reviews Microbiology
Published
2010-12-16
Volume
9
Issue
1
Pages
62-75
ISSN
  • 1740-1526 (ISSN-L)
  • 1740-1534
OpenAlex
W1989761771
Cited by
871
References
14
FWCI
2.67
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Targeting bacterial membrane function: an underexploited mechanism for treating persistent infections. https://app.cochat.ai/papers/10.1038/nrmicro2474
The paper
Hurdle, J. G., O'Neill, A. J., Chopra, I., & Lee, R. E. (2011). Targeting bacterial membrane function: an underexploited mechanism for treating persistent infections. Nature Reviews Microbiology. https://doi.org/10.1038/nrmicro2474

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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.