A mechanistic individual-based model of microbial communities

  1. Lookup NU author(s)
  2. Dr Jayathilake Pahala Gedara
  3. Dr Prashant Gupta
  4. Dr Bowen Li
  5. Dr Curtis Madsen
  6. Dr Oluwole Oyebamiji
  7. Dr Rebeca Gonzalez-Cabaleiro
  8. Professor Stephen Rushton
  9. Dr Ben Bridgens
  10. Dr David Swailes
  11. Dr Ben Allen
  12. Dr Stephen McGough
  13. Dr Paolo Zuliani
  14. Dr Dana Ofiteru
  15. Professor Darren Wilkinson
  16. Dr Jinju Chen
  17. Professor Thomas Curtis
Author(s)Jayathilake PG, Gupta P, Li B, Madsen C, Oyebamiji O, Gonzalez-Cabaleiro R, Rushton S, Bridgens B, Swailes D, Allen B, McGough AS, Zuliani P, Ofiteru ID, Wilkinson DJ, Chen J, Curtis TP
Publication type Article
JournalPLoS One
Year2017
Volume12
Issue8
Pages
ISSN (electronic)1932-6203
Full text is available for this publication:
Accurate predictive modelling of the growth of microbial communities requires the credible representation of the interactions of biological, chemical and mechanical processes. However, although biological and chemical processes are represented in a number of Individual-based Models (IbMs) the interaction of growth and mechanics is limited. Conversely, there are mechanically sophisticated IbMs with only elementary biology and chemistry. This study focuses on addressing these limitations by developing a flexible IbM that can robustly combine the biological, chemical and physical processes that dictate the emergent properties of a wide range of bacterial communities. This IbM is developed by creating a microbiological adaptation of the open source Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). This innovation should provide the basis for "bottom up" prediction of the emergent behaviour of entire microbial systems. In the model presented here, bacterial growth, division, decay, mechanical contact among bacterial cells, and adhesion between the bacteria and extracellular polymeric substances are incorporated. In addition, fluid-bacteria interaction is implemented to simulate biofilm deformation and erosion. The model predicts that the surface morphology of biofilms becomes smoother with increased nutrient concentration, which agrees well with previous literature. In addition, the results show that increased shear rate results in smoother and more compact biofilms. The model can also predict shear rate dependent biofilm deformation, erosion, streamer formation and breakup.
PublisherPLOS
URLhttps://doi.org/10.1371/journal.pone.0181965
DOI10.1371/journal.pone.0181965
PubMed id28771505
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