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Biofilm Matrixome: Extracellular Components in Structured Microbial Communities

Open access
Karygianni, L., Ren, Z., Koo, H., Thurnheer, T.·2020·Trends in Microbiology

Abstract

Biofilms consist of microbial communities embedded in a 3D extracellular matrix. The matrix is composed of a complex array of extracellular polymeric substances (EPS) that contribute to the unique attributes of biofilm lifestyle and virulence. This ensemble of chemically and functionally diverse biomolecules is termed the 'matrixome'. The composition and mechanisms of EPS matrix formation, and its role in biofilm biology, function, and microenvironment are being revealed. This perspective article highlights recent advances about the multifaceted role of the 'matrixome' in the development, physical-chemical properties, and virulence of biofilms. We emphasize that targeting biofilm-specific conditions such as the matrixome could lead to precise and effective antibiofilm approaches. We also discuss the limited knowledge in the context of polymicrobial biofilms, and the need for more in-depth analyses of the EPS matrix in mixed communities that are associated with many human infectious diseases.

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Crossref · 10.1016/j.tim.2020.03.016

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Metadata

Authors
Karygianni, L., Ren, Z., Koo, H., & Thurnheer, T.
Venue
Trends in Microbiology
Publisher
Elsevier BV
Published
2020-08
Volume
28
Issue
8
Pages
668-681
ISSN
0966-842X (ISSN-L)
OpenAlex
W3019884735
Cited by
1,487
References
12
FWCI
12.43
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Biofilm Matrixome: Extracellular Components in Structured Microbial Communities. https://app.cochat.ai/papers/10.1016/j.tim.2020.03.016
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Karygianni, L., Ren, Z., Koo, H., & Thurnheer, T. (2020). Biofilm Matrixome: Extracellular Components in Structured Microbial Communities. Trends in Microbiology. https://doi.org/10.1016/j.tim.2020.03.016

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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.