The DOI matches its Crossref record; 163 of the 163 references it cites were found in a registry or an index.
Quorum sensing and social networking in the microbial world
Open accessAbstract
For many years, bacterial cells were considered primarily as selfish individuals, but, in recent years, it has become evident that, far from operating in isolation, they coordinate collective behaviour in response to environmental challenges using sophisticated intercellular communication networks. Cell-to-cell communication between bacteria is mediated by small diffusible signal molecules that trigger changes in gene expression in response to fluctuations in population density. This process, generally referred to as quorum sensing (QS), controls diverse phenotypes in numerous Gram-positive and Gram-negative bacteria. Recent advances have revealed that bacteria are not limited to communication within their own species but are capable of ‘listening in’ and ‘broadcasting to’ unrelated species to intercept messages and coerce cohabitants into behavioural modifications, either for the good of the population or for the benefit of one species over another. It is also evident that QS is not limited to the bacterial kingdom. The study of two-way intercellular signalling networks between bacteria and both uni- and multicellular eukaryotes as well as between eukaryotes is just beginning to unveil a rich diversity of communication pathways.
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Metadata
- Authors
- Atkinson, S., & Williams, P.
- Venue
- Journal of The Royal Society Interface
- Publisher
- The Royal Society
- Published
- 2009-08-12
- Volume
- 6
- Issue
- 40
- Pages
- 959-978
- ISSN
- 1742-5662 (ISSN-L)
- 1742-5689
- OpenAlex
- W2029205241
- Cited by
- 422
- References
- 163
- FWCI
- 9.24
- Type
- journal article
- Language
- en
- Open access
- green
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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.
