Multiple linear regression analysis of bacterial deposition to polyurethane coatings after conditioning film formation in the marine environment
van Zanten, J.
de Vries, J.
van der Mei, H.C.
Many studies have shown relationships of substratum hydrophobicity, charge or roughness with bacterial adhesion, although bacterial adhesion is governed by interplay of different physico-chemical properties and multiple regression analysis would be more suitable to reveal mechanisms of bacterial adhesion. The formation of a conditioning film of organic compounds adsorbed from seawater affects the properties of substratum surfaces prior to bacterial adhesion, which is a complicating factor in studying the mechanism of bacterial adhesion. In this paper, the impact of conditioning films adsorbed from natural seawater to four polyurethane coatings with different hydrophobicity, elasticity and roughness was studied for three different marine bacterial strains in a multiple linear regression analysis. The water contact angle on hydrophobic coatings decreased on average by 8 degrees and increased on average by the same amount on hydrophilic coatings. These changes were accompanied by increased concentrations of oxygen and nitrogen on the surface as determined by X-ray photoelectron spectroscopy, indicative of adsorption of proteinaceous material. Furthermore, the mean surface roughness increased on average by 4 nm after conditioning film formation. Multiple linear regression analysis revealed that changes in deposition due to conditioning film formation of Marinobacter hydrocarbonoclasticus, Psychrobacter sp. SW5H and Halomonas pacifica in a stagnation-point flow chamber could be explained in a model comprising hydrophobicity and the prevalence of nitrogen-rich components on the surface for the most hydrophobic strain. For the two more hydrophilic strains, deposition was governed by a combination of surface roughness and hydrophobicity. Elasticity was not a factor in bacterial adhesion to conditioning films. © 2004 SGM.
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Multivariate logistic regression analysis
X-ray photoelectron spectroscopy
Society for General Microbiology
Microbiology, 150 (6), 111-123