Literature DB >> 12805267

The mutant selection window and antimicrobial resistance.

Karl Drlica1.   

Abstract

The mutant selection window is an antimicrobial concentration range extending from the minimal concentration required to block the growth of wild-type bacteria up to that required to inhibit the growth of the least susceptible, single-step mutant. The upper boundary is also called the mutant prevention concentration (MPC). Placing antimicrobial concentrations inside the window is expected to enrich resistant mutant subpopulations selectively, whereas placing concentrations above the window is expected to restrict selective enrichment. Since window dimensions are characteristic of each pathogen-antimicrobial combination, they can be linked with antimicrobial pharmacokinetics to rank compounds and dosing regimens in terms of their propensity to enrich mutant fractions of bacterial populations. For situations in which antimicrobial concentrations cannot be kept above the window, restricting the enrichment of mutants requires combination therapy.

Mesh:

Substances:

Year:  2003        PMID: 12805267     DOI: 10.1093/jac/dkg269

Source DB:  PubMed          Journal:  J Antimicrob Chemother        ISSN: 0305-7453            Impact factor:   5.790


  124 in total

Review 1.  The population genetics of antibiotic resistance: integrating molecular mechanisms and treatment contexts.

Authors:  R Craig MacLean; Alex R Hall; Gabriel G Perron; Angus Buckling
Journal:  Nat Rev Genet       Date:  2010-06       Impact factor: 53.242

2.  Selective advantage of resistant strains at trace levels of antibiotics: a simple and ultrasensitive color test for detection of antibiotics and genotoxic agents.

Authors:  Anne Liu; Amie Fong; Elinne Becket; Jessica Yuan; Cindy Tamae; Leah Medrano; Maria Maiz; Christine Wahba; Catherine Lee; Kim Lee; Katherine P Tran; Hanjing Yang; Robert M Hoffman; Anya Salih; Jeffrey H Miller
Journal:  Antimicrob Agents Chemother       Date:  2011-01-03       Impact factor: 5.191

Review 3.  Mechanisms of resistance and clinical relevance of resistance to β-lactams, glycopeptides, and fluoroquinolones.

Authors:  Louis B Rice
Journal:  Mayo Clin Proc       Date:  2012-02       Impact factor: 7.616

4.  Fate of a mutation in a fluctuating environment.

Authors:  Ivana Cvijović; Benjamin H Good; Elizabeth R Jerison; Michael M Desai
Journal:  Proc Natl Acad Sci U S A       Date:  2015-08-24       Impact factor: 11.205

5.  The anti-methicillin-resistant Staphylococcus aureus quinolone WCK 771 has potent activity against sequentially selected mutants, has a narrow mutant selection window against quinolone-resistant Staphylococcus aureus, and preferentially targets DNA gyrase.

Authors:  Sachin S Bhagwat; Lakshmi A Mundkur; Shrikant V Gupte; Mahesh V Patel; Habil F Khorakiwala
Journal:  Antimicrob Agents Chemother       Date:  2006-08-28       Impact factor: 5.191

6.  Mutant Prevention Concentration and Mutant Selection Window of Micafungin and Anidulafungin in Clinical Candida glabrata Isolates.

Authors:  Pilar Escribano; Jesús Guinea; María Ángeles Bordallo-Cardona; Laura Judith Marcos-Zambrano; Carlos Sánchez-Carrillo; Elia Gómez G de la Pedrosa; Rafael Cantón; Emilio Bouza
Journal:  Antimicrob Agents Chemother       Date:  2018-02-23       Impact factor: 5.191

7.  Fitness costs of fluoroquinolone resistance in Streptococcus pneumoniae.

Authors:  Daniel E Rozen; Lesley McGee; Bruce R Levin; Keith P Klugman
Journal:  Antimicrob Agents Chemother       Date:  2006-11-20       Impact factor: 5.191

Review 8.  Optimising dosing strategies of antibacterials utilising pharmacodynamic principles: impact on the development of resistance.

Authors:  C Andrew DeRyke; Su Young Lee; Joseph L Kuti; David P Nicolau
Journal:  Drugs       Date:  2006       Impact factor: 9.546

9.  Prevalence of Quinolone Resistance in Enterobacteriaceae from Sierra Leone and the Detection of qnrB Pseudogenes and Modified LexA Binding Sites.

Authors:  Tomasz A Leski; Michael G Stockelman; Umaru Bangura; Daniel Chae; Rashid Ansumana; David A Stenger; Gary J Vora; Chris R Taitt
Journal:  Antimicrob Agents Chemother       Date:  2016-10-21       Impact factor: 5.191

10.  Novel concentration-killing curve method for estimation of bactericidal potency of antibiotics in an in vitro dynamic model.

Authors:  Y Q Liu; Y Z Zhang; P J Gao
Journal:  Antimicrob Agents Chemother       Date:  2004-10       Impact factor: 5.191

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.