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Modeling bioaffinity-based targeted delivery of antimicrobials to Escherichia coli biofilms using yeast microparticles. Part II: Parameter evaluation and validation.
Yi, Jiyoon; Huang, Kang; Nitin, Nitin.
  • Yi J; Department of Food Science and Technology, University of California-Davis, Davis, California, USA.
  • Huang K; School of Chemical Sciences, The University of Auckland, Auckland, New Zealand.
  • Nitin N; Department of Food Science and Technology, University of California-Davis, Davis, California, USA.
Biotechnol Bioeng ; 119(1): 247-256, 2022 01.
Article en En | MEDLINE | ID: mdl-34693998
ABSTRACT
The design of bioaffinity-based targeted delivery systems for biofilm inactivation may require a comprehensive understanding of physicochemical and biochemical properties of biobased antimicrobial particles and their interactions with biofilm. In this study, Escherichia coli biofilm inactivation by chlorine-charged yeast microparticles was numerically simulated, and the roles of chemical stability, binding affinity, and controlled release of this targeted delivery system were assessed using this numerical simulation. The simulation results were experimentally validated using two different types of yeast microparticles. The results of this study illustrate that chorine stability achieved by yeast microparticles was a key factor for improved biofilm inactivation in an organic-rich environment (>6 additional log reduction in 20 min compared to the free chlorine treatment). Moreover, the binding affinity of yeast microparticles to E. coli biofilms was another key factor for an enhanced inactivation of biofilm, as a 10-fold increase in binding rate resulted in a 4.2-fold faster inactivation. Overall, the mechanistic modeling framework developed in this study could guide the design and development of biobased particles for targeted inactivation of biofilms.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Saccharomyces cerevisiae / Biopelículas / Escherichia coli / Antiinfecciosos / Modelos Químicos Tipo de estudio: Prognostic_studies Idioma: En Año: 2022 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Saccharomyces cerevisiae / Biopelículas / Escherichia coli / Antiinfecciosos / Modelos Químicos Tipo de estudio: Prognostic_studies Idioma: En Año: 2022 Tipo del documento: Article