Inferring characteristics of bacterial swimming in biofilm matrix from time-lapse confocal laser scanning microscopy

  1. Guillaume Ravel
  2. Michel Bergmann
  3. Alain Trubuil
  4. Julien Deschamps
  5. Romain Briandet
  6. Simon Labarthe  Is a corresponding author
  1. INRAE, France
  2. Inria Bordeaux - Sud-Ouest Research Centre, France

Abstract

Biofilms are spatially organized communities of microorganisms embedded in a self-produced organic matrix, conferring to the population emerging properties such as an increased tolerance to the action of antimicrobials. It was shown that some bacilli were able to swim in the exogenous matrix of pathogenic biofilms and to counterbalance these properties. Swimming bacteria can deliver antimicrobial agents in situ, or potentiate the activity of antimicrobial by creating a transient vascularization network in the matrix. Hence, characterizing swimmer trajectories in the biofilm matrix is of particular interest to understand and optimize this new biocontrol strategy in particular, but also more generally to decipher ecological drivers of population spatial structure in natural biofilms ecosystems. In this study, a new methodology is developed to analyze time-lapse confocal laser scanning images to describe and compare the swimming trajectories of bacilli swimmers populations and their adaptations to the biofilm structure. The method is based on the inference of a kinetic model of swimmer populations including mechanistic interactions with the host biofilm. After validation on synthetic data, the methodology is implemented on images of three different species of motile bacillus species swimming in a Staphylococcus aureus biofilm. The fitted model allows to stratify the swimmer populations by their swimming behavior and provides insights into the mechanisms deployed by the micro-swimmers to adapt their swimming traits to the biofilm matrix.

Data availability

Data and codes have been deposited at https://forgemia.inra.fr/bioswimmers/swim-infer.Labarthe, Simon, Ravel, Guillaume, Deschamps, Julien, & Briandet, Romain. (2022). Inferring characteristics of bacterial swimming in biofilm matrix from time-lapse confocal laser scanning microscopy: compagnon code and data. Zenodo. https://doi.org/10.5281/zenodo.6560673

Article and author information

Author details

  1. Guillaume Ravel

    INRAE, Cestas, France
    Competing interests
    The authors declare that no competing interests exist.
  2. Michel Bergmann

    Inria Bordeaux - Sud-Ouest Research Centre, Talence, France
    Competing interests
    The authors declare that no competing interests exist.
  3. Alain Trubuil

    INRAE, Jouy-en-Josas, France
    Competing interests
    The authors declare that no competing interests exist.
  4. Julien Deschamps

    INRAE, Jouy-en-Josas, France
    Competing interests
    The authors declare that no competing interests exist.
  5. Romain Briandet

    INRAE, Jouy-en-Josas, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8123-3492
  6. Simon Labarthe

    INRAE, Cestas, France
    For correspondence
    simon.labarthe@inrae.fr
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5463-7256

Funding

Mathnum department - INRAe

  • Guillaume Ravel

Agence Nationale de la Recherche (ANR-12-ALID-0006)

  • Romain Briandet

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2022, Ravel et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Guillaume Ravel
  2. Michel Bergmann
  3. Alain Trubuil
  4. Julien Deschamps
  5. Romain Briandet
  6. Simon Labarthe
(2022)
Inferring characteristics of bacterial swimming in biofilm matrix from time-lapse confocal laser scanning microscopy
eLife 11:e76513.
https://doi.org/10.7554/eLife.76513

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https://doi.org/10.7554/eLife.76513