Surface conditioning with escherichia coli cell wall components can reduce biofilm formation by decreasing initial adhesion

• Autor(a) principal: Luciana Gomes
• Data de Publicação: 2017
• Outros Autores: Joana Moreira, Araujo, JDP, Filipe Mergulhão
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://hdl.handle.net/10216/116052

Bacterial adhesion and biofilm formation on food processing surfaces pose major risks to human health. Non-efficient cleaning of equipment surfaces and piping can act as a conditioning layer that affects the development of a new biofilm post-disinfection. We have previously shown that surface conditioning with cell extracts could reduce biofilm formation. In the present work, we hypothesized that E. coli cell wall components could be implicated in this phenomena and therefore mannose, myristic acid and palmitic acid were tested as conditioning agents. To evaluate the effect of surface conditioning and flow topology on biofilm formation, assays were performed in agitated 96-well microtiter plates and in a parallel plate flow chamber (PPFC), both operated at the same average wall shear stress (0.07 Pa) as determined by computational fluid dynamics (CFD). It was observed that when the 96-well microtiter plate and the PPFC were used to form biofilms at the same shear stress, similar results were obtained. This shows that the referred hydrodynamic feature may be a good scale-up parameter from high-throughput platforms to larger scale flow cell systems as the PPFC used in this study. Mannose did not have any effect on E. coli biofilm formation, but myristic and palmitic acid inhibited biofilm development by decreasing cell adhesion (in about 50%). These results support the idea that in food processing equipment where biofilm formation is not critical below a certain threshold, bacterial lysis and adsorption of cell components to the surface may reduce biofilm buildup and extend the operational time. (c) 2017 Filipe J. Mergulhão, et al., licensee AIMS Press.