Toggle Main Menu Toggle Search

Open Access padlockePrints

A mechanistic individual-based model of microbial communities

Lookup NU author(s): Dr Jayathilake Pahala Gedara, Dr Prashant Gupta, Dr Bowen LiORCiD, Dr Curtis Madsen, Dr Oluwole Oyebamiji, Dr Rebeca Gonzalez-Cabaleiro, Professor Stephen Rushton, Professor Ben BridgensORCiD, Dr David Swailes, Dr Ben Allen, Dr Stephen McGough, Dr Paolo Zuliani, Dr Dana OfiteruORCiD, Professor Darren Wilkinson, Dr Jinju Chen, Professor Thomas CurtisORCiD



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


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.

Publication metadata

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

Publication status: Published

Journal: PLoS One

Year: 2017

Volume: 12

Issue: 8

Online publication date: 03/08/2017

Acceptance date: 10/07/2017

Date deposited: 10/08/2017

ISSN (electronic): 1932-6203

Publisher: PLOS


DOI: 10.1371/journal.pone.0181965

PubMed id: 28771505


Altmetrics provided by Altmetric


Funder referenceFunder name