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Mathematical modelling of bacterial quorum sensing: A review.
Bull. Math. Biol. 78, 1585-1639 (2016)
Bacterial quorum sensing (QS) refers to the process of cell-to-cell bacterial communication enabled through the production and sensing of the local concentration of small molecules called autoinducers to regulate the production of gene products (e.g. enzymes or virulence factors). Through autoinducers, bacteria interact with individuals of the same species, other bacterial species, and with their host. Among QS-regulated processes mediated through autoinducers are aggregation, biofilm formation, bioluminescence, and sporulation. Autoinducers are therefore “master” regulators of bacterial lifestyles. For over 10 years, mathematical modelling of QS has sought, in parallel to experimental discoveries, to elucidate the mechanisms regulating this process. In this review, we present the progress in mathematical modelling of QS, highlighting the various theoretical approaches that have been used and discussing some of the insights that have emerged. Modelling of QS has benefited almost from the onset of the involvement of experimentalists, with many of the papers which we review, published in non-mathematical journals. This review therefore attempts to give a broad overview of the topic to the mathematical biology community, as well as the current modelling efforts and future challenges.
Impact Factor
Scopus SNIP
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Times Cited
Times Cited
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1.326
0.704
38
46
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Publication type
Article: Journal article
Document type
Review
Keywords
Antibacterial ; Autoinducers ; Bacteria ; Communication ; Mathematical Modelling ; Quorum Sensing ; Simulations; Cell-cell Communication; Gram-negative Bacteria; Pseudomonas-aeruginosa; Vibrio-fischeri; Staphylococcus-aureus; Gene-expression; Regulation Systems; Social Evolution; Biofilm Growth; Feedback Loops
Language
english
Publication Year
2016
HGF-reported in Year
2016
ISSN (print) / ISBN
0092-8240
e-ISSN
1522-9602
Journal
Bulletin of Mathematical Biology
Quellenangaben
Volume: 78,
Issue: 8,
Pages: 1585-1639
Publisher
Springer
Publishing Place
New York
Reviewing status
Peer reviewed
Institute(s)
Institute of Computational Biology (ICB)
POF-Topic(s)
30205 - Bioengineering and Digital Health
Research field(s)
Enabling and Novel Technologies
PSP Element(s)
G-503800-001
WOS ID
WOS:000384817400001
Scopus ID
84983444966
Erfassungsdatum
2016-09-05