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A Bayesian approach to modelling the impact of hydrodynamic shear stress on biofilm deformation

Lookup NU author(s): Dr Oluwole Oyebamiji, Professor Darren Wilkinson, Dr Jayathilake Pahala Gedara, Professor Stephen Rushton, Dr Bowen Li, Dr Ben Bridgens, Dr Paolo Zuliani

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


Abstract

We investigate the feasibility of using a surrogate-based method to emulate thedeformation and detachment behaviour of a biofilm in response to hydrodynamic shearstress. The influence of shear force, growth rate and viscoelastic parameters on thepatterns of growth, structure and resulting shape of microbial biofilms was examined.We develop a statistical modelling approach to this problem, using combination ofBayesian Poisson regression and dynamic linear models for the emulation. Weobserve that the hydrodynamic shear force affects biofilm deformation in line with someliterature. Sensitivity results also showed that the expected number of shear events,shear flow, yield coefficient for heterotrophic bacteria and extracellular polymericsubstance (EPS) stiffness per unit EPS mass are the four principal mechanismsgoverning the bacteria detachment in this study. The sensitivity of the modelparameters is temporally dynamic, emphasising the significance of conducting thesensitivity analysis across multiple time points. The surrogate models are shown toperform well, and produced ~480 fold increase in computational efficiency. Weconclude that a surrogate-based approach is effective, and resulting biofilm structure isdetermined primarily by a balance between bacteria growth, viscoelastic parametersand applied shear stress.


Publication metadata

Author(s): Oyebamiji OK, Wilkinson DJ, Pahala-Gedara J, Rushton SP, Li B, Bridgens B, Zuliani P

Publication type: Article

Publication status: Published

Journal: PLOS ONE

Year: 2018

Volume: 13

Issue: 4

Online publication date: 12/04/2018

Acceptance date: 24/03/2018

ISSN (electronic): 1932-6203

Publisher: Public Library of Science

URL: https://doi.org/10.1371/journal.pone.0195484

DOI: 10.1371/journal.pone.0195484

Data Source Location: http://dx.doi.org/10.17634/123172-3


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