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Uncovering the Dynamic Mechanisms of the Pseudomonas Aeruginosa Quorum Sensing and Virulence Networks Using Boolean Modelling

Lookup NU author(s): Manuel Banzhaf

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Abstract

© 2002-2011 IEEE. Pseudomonas aeruginosa is an opportunistic pathogen with a large repertoire of virulence factors that allow it to cause acute and chronic infections. Treatment of P. aeruginosa infections often fail due to its antibiotic resistance mechanisms, thus novel strategies aim at targeting virulence factors instead of growth-related features. Although the elements of the virulence networks of P. aeruginosa have been identified, how they interact and influence the overall virulence regulation is unclear. In this study, we reconstructed the signaling and transcriptional regulatory networks of 12 acute and 8 chronic virulence factors, and the 4 quorum sensing systems of P. aeruginosa. Using Boolean modelling, we showed that the static interactions and the time when they take place are important features in the quorum sensing network. We also found that the virulence factors of the acute networks are under strict repression or non-strict activation, while those of most of the chronic networks are under repression. In conclusion, Boolean modelling provides a system-level view of the P. aeruginosa virulence and quorum sensing networks to gain new insights into the various mechanisms that support its pathogenicity. Thus, we suggest that Boolean modelling could be used to guide the design of new treatments against P. aeruginosa.


Publication metadata

Author(s): Banzhaf M, Resendis-Antonio O, Lisandra Zepeda-Mendoza M

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Nanobioscience

Year: 2020

Volume: 19

Issue: 3

Pages: 394-402

Print publication date: 01/07/2020

Online publication date: 02/03/2020

Acceptance date: 23/02/2020

ISSN (print): 1536-1241

ISSN (electronic): 1558-2639

Publisher: IEEE

URL: https://doi.org/10.1109/TNB.2020.2977820

DOI: 10.1109/TNB.2020.2977820

PubMed id: 32142451


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Funding

Funder referenceFunder name
836384
European Union Horizon 2020

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