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Cited by 262

The DOI matches its Crossref record; 69 of the 69 references it cites were found in a registry or an index.

Identification of Proteins Associated with the Pseudomonas aeruginosa Biofilm Extracellular Matrix

Toyofuku, Masanori, Roschitzki, Bernd, Riedel, Katharina, Eberl, Leo·2012·Journal of Proteome Research
DOI 10.1021/pr300395j
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Abstract

Biofilms are surface-associated bacteria that are embedded in a matrix of self-produced polymeric substances (EPSs). The EPS is composed of nucleic acids, polysaccharides, lipids, and proteins. While polysaccharide components have been well studied, the protein content of the matrix is largely unknown. Here we conducted a comprehensive proteomic study to identify proteins associated with the biofilm matrix of Pseudomonas aeruginosa PAO1 (the matrix proteome). This analysis revealed that approximately 30% of the identified matrix proteins were outer membrane proteins, which are also typically found in outer membrane vesicles (OMVs). Electron microscopic inspection confirmed the presence of large amounts of OMVs within the biofilm matrix, supporting previous notions that OMVs are abundant constituents of P. aeruginosa biofilms. Our results demonstrate that while some proteins associated with the P. aeruginosa matrix are derived from secreted proteins and lysed cells, the large majority of the matrix proteins originate from OMVs. Furthermore, we demonstrate that the protein content of planktonic and biofilm OMVs is surprisingly different and may reflect the different physiological states of planktonic and sessile cells.

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Metadata

Authors
Toyofuku, M., Roschitzki, B., Riedel, K., & Eberl, L.
Venue
Journal of Proteome Research
Publisher
American Chemical Society (ACS)
Published
2012-09-26
Volume
11
Issue
10
Pages
4906-4915
ISSN
  • 1535-3893 (ISSN-L)
  • 1535-3907
DOI
10.1021/pr300395j
OpenAlex
W2094149145
Cited by
262
References
69
FWCI
4.88
Type
journal article
Language
en
Open access
closed

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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.