A computational model for microbial colonisation of an antifouling surface

Patrick Sinclair, Jennifer Longyear, Kevin Reynolds, Alistair A. Finnie, Chris Brackley, Martin Carballo Pacheco, Rosalind Allen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Biofouling of marine surfaces such as ship hulls is a major industrial problem. Antifouling (AF) paints delay the onset of biofouling by releasing biocidal chemicals. We present a computational model for microbial colonisation of a biocide-releasing AF surface. Our model accounts for random arrival from the ocean of microorganisms with different biocide resistance levels, biocide-dependent proliferation or killing, and a transition to a biofilm state. Our computer simulations support a picture in which biocide-resistant microorganisms initially form a loosely attached layer that eventually transitions to a growing biofilm. Once the growing biofilm is established, immigrating microorganisms are shielded from the biocide, allowing more biocide-susceptible strains to proliferate. In our model, colonisation of the AF surface is highly stochastic. The waiting time before the biofilm establishes is exponentially distributed, suggesting a Poisson process. The waiting time depends exponentially on both the concentration of biocide at the surface and the rate of arrival of resistant microorganisms from the ocean. Taken together our results suggest that biofouling of AF surfaces may be intrinsically stochastic and hence unpredictable, but immigration of more biocide-resistant species, as well as the biological transition to biofilm physiology, may be important factors controlling the time to biofilm establishment.
Original languageEnglish
Article number920014
JournalFrontiers in Microbiology
Volume13
DOIs
Publication statusPublished - 27 Sept 2022

Keywords / Materials (for Non-textual outputs)

  • antifouling paint
  • biofilm establishment
  • computational modeling
  • marine biofouling
  • stochastic model

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