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Modeling the response of a biofilm to silver-based antimicrobial.

Authors :
Stine AE
Nassar D
Miller JK
Clemons CB
Wilber JP
Young GW
Yun YH
Cannon CL
Leid JG
Youngs WJ
Milsted A
Source :
Mathematical biosciences [Math Biosci] 2013 Jul; Vol. 244 (1), pp. 29-39. Date of Electronic Publication: 2013 Apr 27.
Publication Year :
2013

Abstract

Biofilms are found within the lungs of patients with chronic pulmonary infections, in particular patients with cystic fibrosis, and are the major cause of morbidity and mortality for these patients. The work presented here is part of a large interdisciplinary effort to develop an effective drug delivery system and treatment strategy to kill biofilms growing in the lung. The treatment strategy exploits silver-based antimicrobials, in particular, silver carbene complexes (SCC). This manuscript presents a mathematical model describing the growth of a biofilm and predicts the response of a biofilm to several basic treatment strategies. The continuum model is composed of a set of reaction-diffusion equations for the transport of soluble components (nutrient and antimicrobial), coupled to a set of reaction-advection equations for the particulate components (living, inert, and persister bacteria, extracellular polymeric substance, and void). We explore the efficacy of delivering SCC both in an aqueous solution and in biodegradable polymer nanoparticles. Minimum bactericidal concentration (MBC) levels of antimicrobial in both free and nanoparticle-encapsulated forms are estimated. Antimicrobial treatment demonstrates a biphasic killing phenomenon, where the active bacterial population is killed quickly followed by a slower killing rate, which indicates the presence of a persister population. Finally, our results suggest that a biofilm with a ready supply of nutrient throughout its depth has fewer persister bacteria and hence may be easier to treat than one with less nutrient.<br /> (Copyright © 2013 Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1879-3134
Volume :
244
Issue :
1
Database :
MEDLINE
Journal :
Mathematical biosciences
Publication Type :
Academic Journal
Accession number :
23628237
Full Text :
https://doi.org/10.1016/j.mbs.2013.04.006