Quantifying the pattern of microbial cell dispersion, density and clustering on surfaces of differing chemistries and topographies using multifractal analysis

• Multifractal analysis was used to quantify cell dispersion, density and clustering.
• S. aureus displayed a more heterogeneous cell dispersion.
• S. epidermidis dispersion was more symmetric and homogeneous.
• S. aureus was influenced more by surface chemistry.
• S. epidermidis cells was influenced marginally more by surface topography.

The effects of surface topography on bacterial distribution across a surface are of extreme importance when designing novel, hygienic or antimicrobial surface coatings. The majority of methods that are deployed to describe the pattern of cell dispersion, density and clustering across surfaces are currently qualitative. This paper presents a novel application of multifractal analysis to quantitatively measure these factors using medically relevant microorganisms (Staphylococcus aureus or Staphylococcus epidermidis). Surfaces (medical grade 316 stainless steel) and coatings (Ti–ZrN, Ti–ZrN/6.0%Ag, Ti–ZrN/15.6%Ag, TiZrN/24.7%Ag) were used in microbiological retention assays. Results demonstrated that S. aureus displayed a more heterogeneous cell dispersion (∆αAS < 1) whilst the dispersion of S. epidermidis was more symmetric and homogeneous (∆αAS ≥ 1). Further, although the surface topography and chemistry had an effect on cell dispersion, density and clustering, the type of bonding that occurred at the surface interface was also important. Both types of cells were influenced by both surface topographical and chemical effects; however, S. aureus was influenced marginally more by surface chemistry whilst S. epidermidis cells was influenced marginally more by surface topography. Thus, this effect was bacterially species specific. The results demonstrate that multifractal analysis is a method that can be used to quantitatively analyse the cell dispersion, density and clustering of retained microorganisms on surfaces. Using quantitative descriptors has the potential to aid the understanding the effect of surface properties on the production of hygienic and antimicrobial coatings.