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Biological Functions and Biogenesis of Secreted Bacterial Outer Membrane Vesicles

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Kulp, Adam, Kuehn, Meta J.·2010·Annual Review of Microbiology

Abstract

Gram-negative bacteria produce outer membrane vesicles (OMVs) that contain biologically active proteins and perform diverse biological processes. Unlike other secretion mechanisms, OMVs enable bacteria to secrete insoluble molecules in addition to and in complex with soluble material. OMVs allow enzymes to reach distant targets in a concentrated, protected, and targeted form. OMVs also play roles in bacterial survival: Their production is a bacterial stress response and important for nutrient acquisition, biofilm development, and pathogenesis. Key characteristics of OMV biogenesis include outward bulging of areas lacking membrane-peptidoglycan bonds, the capacity to upregulate vesicle production without also losing outer membrane integrity, enrichment or exclusion of certain proteins and lipids, and membrane fission without direct energy from ATP/GTP hydrolysis. Comparisons of similar budding mechanisms from diverse biological domains have provided new insight into evaluating mechanisms for outer membrane vesiculation.

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Metadata

Authors
Kulp, A., & Kuehn, M. J.
Venue
Annual Review of Microbiology
Published
2010-10-13
Volume
64
Issue
1
Pages
163-184
ISSN
  • 0066-4227 (ISSN-L)
  • 1545-3251
OpenAlex
W2111951615
Cited by
1,533
References
0
FWCI
5.39
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Biological Functions and Biogenesis of Secreted Bacterial Outer Membrane Vesicles. https://app.cochat.ai/papers/10.1146/annurev.micro.091208.073413
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Kulp, A., & Kuehn, M. J. (2010). Biological Functions and Biogenesis of Secreted Bacterial Outer Membrane Vesicles. Annual Review of Microbiology. https://doi.org/10.1146/annurev.micro.091208.073413

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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.