2026-04-20T07:07:53Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/82692024-01-10T01:05:29Zcom_10259_6229com_10259_4534com_10259.4_106com_10259_2604col_10259_6230

Birnir, Bjorn Carpio, Ana Cebrián de Barrio, Elena Vidal, Perfecto 2024-01-09T12:56:13Z 2024-01-09T12:56:13Z 2018 1007-5704 http://hdl.handle.net/10259/8269 10.1016/j.cnsns.2017.05.016 1878-7274 Quantifying the action of antibiotics on biofilms is essential to devise therapies against chronic infections. Biofilms are bacterial communities attached to moist surfaces, sheltered from external aggressions by a polymeric matrix. Coupling a dynamic energy budget based description of cell metabolism to surrounding concentration fields, we are able to approximate survival curves measured for different antibiotics. We reproduce numerically stratified distributions of cell types within the biofilm and introduce ways to incorporate different resistance mechanisms. Qualitative predictions follow that are in agreement with experimental observations, such as higher survival rates of cells close to the substratum when employing antibiotics targeting active cells or enhanced polymer production when antibiotics are administered. The current computational model enables validation and hypothesis testing when developing therapies. Research partially supported by the NILS Mobility Program grant No. 001-ABELIM-2013 through the EEA financial mechanism and MINECO grant No. MTM2014-56948-C2-1-P. application/pdf eng Elsevier Communications in Nonlinear Science and Numerical Simulation. 2018, V. 54, p. 70-83 https://doi.org/10.1016/j.cnsns.2017.05.016 Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess Dynamic energy budget Bacterial biofilm Antibiotic Numerical simulation Microbiología Matemáticas Microbiology Mathematics Dynamic energy budget approach to evaluate antibiotic effects on biofilms info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Communications in Nonlinear Science and Numerical Simulation 54 70 83