Literature DB >> 23628237

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

A E Stine1, D Nassar, J K Miller, C B Clemons, J P Wilber, G W Young, Y H Yun, C L Cannon, J G Leid, W J Youngs, A Milsted.   

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.
Copyright © 2013 Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Substances:

Year:  2013        PMID: 23628237      PMCID: PMC3697101          DOI: 10.1016/j.mbs.2013.04.006

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  51 in total

1.  The dependence of quorum sensing on the depth of a growing biofilm.

Authors:  D L Chopp; M J Kirisits; B Moran; M R Parsek
Journal:  Bull Math Biol       Date:  2003-11       Impact factor: 1.758

2.  Particle-based multidimensional multispecies biofilm model.

Authors:  Cristian Picioreanu; Jan-Ulrich Kreft; Mark C M Van Loosdrecht
Journal:  Appl Environ Microbiol       Date:  2004-05       Impact factor: 4.792

3.  Adaptive responses to antimicrobial agents in biofilms.

Authors:  Barbara Szomolay; Isaac Klapper; Jack Dockery; Phil S Stewart
Journal:  Environ Microbiol       Date:  2005-08       Impact factor: 5.491

4.  Non-degradable microparticles containing a hydrophilic and/or a lipophilic drug: preparation, characterization and drug release modeling.

Authors:  M Hombreiro-Pérez; J Siepmann; C Zinutti; A Lamprecht; N Ubrich; M Hoffman; R Bodmeier; P Maincent
Journal:  J Control Release       Date:  2003-03-26       Impact factor: 9.776

5.  A multispecies biofilm model.

Authors:  O Wanner; W Gujer
Journal:  Biotechnol Bioeng       Date:  1986-03       Impact factor: 4.530

Review 6.  Anti-inflammatory medications for cystic fibrosis lung disease: selecting the most appropriate agent.

Authors:  James F Chmiel; Michael W Konstan
Journal:  Treat Respir Med       Date:  2005

7.  Biofilm accumulation model that predicts antibiotic resistance of Pseudomonas aeruginosa biofilms.

Authors:  P S Stewart
Journal:  Antimicrob Agents Chemother       Date:  1994-05       Impact factor: 5.191

8.  Persister cells and tolerance to antimicrobials.

Authors:  Iris Keren; Niilo Kaldalu; Amy Spoering; Yipeng Wang; Kim Lewis
Journal:  FEMS Microbiol Lett       Date:  2004-01-15       Impact factor: 2.742

Review 9.  New concepts of the pathogenesis of cystic fibrosis lung disease.

Authors:  R C Boucher
Journal:  Eur Respir J       Date:  2004-01       Impact factor: 16.671

10.  The role of the biofilm matrix in structural development.

Authors:  N G Cogan; James P Keener
Journal:  Math Med Biol       Date:  2004-06       Impact factor: 1.854

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.