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Amyloid fibers provide structural integrity to Bacillus subtilis biofilms

Open access
Romero, Diego, Aguilar, Claudio, Losick, Richard, Kolter, Roberto·2010·Proceedings of the National Academy of Sciences

Abstract

Bacillus subtilis forms biofilms whose constituent cells are held together by an extracellular matrix. Previous studies have shown that the protein TasA and an exopolysaccharide are the main components of the matrix. Given the importance of TasA in biofilm formation, we characterized the physicochemical properties of this protein. We report that purified TasA forms fibers of variable length and 10–15 nm in width. Biochemical analyses, in combination with the use of specific dyes and microscopic analyses, indicate that TasA forms amyloid fibers. Consistent with this hypothesis, TasA fibers required harsh treatments (e.g., formic acid) to be depolymerized. When added to a culture of a tasA mutant, purified TasA restored wild-type biofilm morphology, indicating that the purified protein retained biological activity. We propose that TasA forms amyloid fibers that bind cells together in the biofilm.

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Metadata

Authors
Romero, D., Aguilar, C., Losick, R., & Kolter, R.
Venue
Proceedings of the National Academy of Sciences
Published
2010-01-13
Volume
107
Issue
5
Pages
2230-2234
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2086603752
Cited by
792
References
5
FWCI
15.01
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Amyloid fibers provide structural integrity to Bacillus subtilis biofilms. https://app.cochat.ai/papers/10.1073/pnas.0910560107
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Romero, D., Aguilar, C., Losick, R., & Kolter, R. (2010). Amyloid fibers provide structural integrity to Bacillus subtilis biofilms. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0910560107

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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.