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Data-driven modelling makes quantitative predictions regarding bacteria surface motility.

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  • Additional Information
    • Source:
      Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE
    • Publication Information:
      Original Publication: San Francisco, CA : Public Library of Science, [2005]-
    • Subject Terms:
      Pseudomonas aeruginosa*/physiology ; Fimbriae, Bacterial*/physiology ; Models, Biological* ; Computer Simulation* ; Computational Biology*; Movement/physiology ; Bayes Theorem
    • Abstract:
      In this work, we quantitatively compare computer simulations and existing cell tracking data of P. aeruginosa surface motility in order to analyse the underlying motility mechanism. We present a three dimensional twitching motility model, that simulates the extension, retraction and surface association of individual Type IV Pili (TFP), and is informed by recent experimental observations of TFP. Sensitivity analysis is implemented to minimise the number of model parameters, and quantitative estimates for the remaining parameters are inferred from tracking data by approximate Bayesian computation. We argue that the motility mechanism is highly sensitive to experimental conditions. We predict a TFP retraction speed for the tracking data we study that is in a good agreement with experimental results obtained under very similar conditions. Furthermore, we examine whether estimates for biologically important parameters, whose direct experimental determination is challenging, can be inferred directly from tracking data. One example is the width of the distribution of TFP on the bacteria body. We predict that the TFP are broadly distributed over the bacteria pole in both walking and crawling motility types. Moreover, we identified specific configurations of TFP that lead to transitions between walking and crawling states.
      (Copyright: © 2024 Barton et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
    • Abstract:
      The authors have declared that no competing interests exist.
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    • Publication Date:
      Date Created: 20240514 Date Completed: 20240524 Latest Revision: 20240526
    • Publication Date:
      20260130
    • Accession Number:
      PMC11125545
    • Accession Number:
      10.1371/journal.pcbi.1012063
    • Accession Number:
      38743804