Literature DB >> 18815368

Drug interactions modulate the potential for evolution of resistance.

Jean-Baptiste Michel1, Pamela J Yeh, Remy Chait, Robert C Moellering, Roy Kishony.   

Abstract

Antimicrobial treatments increasingly rely on multidrug combinations, in part because of the emergence and spread of antibiotic resistance. The continued effectiveness of combination treatments depends crucially on the frequency with which multidrug resistance arises. Yet, it is unknown how this propensity for resistance depends on cross-resistance and on epistatic interactions-ranging from synergy to antagonism-between the drugs. Here, we analyzed how interactions between pairs of drugs affect the spontaneous emergence of resistance in the medically important pathogen Staphylococcus aureus. Resistance is selected for within a window of drug concentrations high enough to inhibit wild-type growth but low enough for some resistant mutants to grow. Introducing an experimental method for high-throughput colony imaging, we counted resistant colonies arising across a two-dimensional matrix of drug concentrations for each of three drug pairs. Our data show that these different drug combinations have significantly different impacts on the size of the window of drug concentrations where resistance is selected for. We framed these results in a mathematical model in which the frequencies of resistance to single drugs, cross-resistance, and epistasis combine to determine the propensity for multidrug resistance. The theory suggests that drug pairs which interact synergistically, preferred for their immediate efficacy, may in fact favor the future evolution of resistance. This framework reveals the central role of drug epistasis in the evolution of resistance and points to new strategies for combating the emergence of drug-resistant bacteria.

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Year:  2008        PMID: 18815368      PMCID: PMC2567468          DOI: 10.1073/pnas.0800944105

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  34 in total

1.  Mutant prevention concentrations of fluoroquinolones for clinical isolates of Streptococcus pneumoniae.

Authors:  J M Blondeau; X Zhao; G Hansen; K Drlica
Journal:  Antimicrob Agents Chemother       Date:  2001-02       Impact factor: 5.191

Review 2.  Principles for the buffering of genetic variation.

Authors:  J L Hartman; B Garvik; L Hartwell
Journal:  Science       Date:  2001-02-09       Impact factor: 47.728

Review 3.  Persistence of antibiotic resistant bacteria.

Authors:  Dan I Andersson
Journal:  Curr Opin Microbiol       Date:  2003-10       Impact factor: 7.934

Review 4.  The mutant selection window and antimicrobial resistance.

Authors:  Karl Drlica
Journal:  J Antimicrob Chemother       Date:  2003-06-12       Impact factor: 5.790

5.  HIV and AIDS: 20 years of science.

Authors:  Anthony S Fauci
Journal:  Nat Med       Date:  2003-07       Impact factor: 53.440

6.  Functional classification of drugs by properties of their pairwise interactions.

Authors:  Pamela Yeh; Ariane I Tschumi; Roy Kishony
Journal:  Nat Genet       Date:  2006-03-19       Impact factor: 38.330

Review 7.  Predicting antibiotic resistance.

Authors:  José L Martínez; Fernando Baquero; Dan I Andersson
Journal:  Nat Rev Microbiol       Date:  2007-12       Impact factor: 60.633

8.  Restricting the selection of antibiotic-resistant mutant bacteria: measurement and potential use of the mutant selection window.

Authors:  Xilin Zhao; Karl Drlica
Journal:  J Infect Dis       Date:  2002-01-31       Impact factor: 5.226

9.  Mutant prevention concentration as a measure of fluoroquinolone potency against mycobacteria.

Authors:  G Sindelar; X Zhao; A Liew; Y Dong; T Lu; J Zhou; J Domagala; K Drlica
Journal:  Antimicrob Agents Chemother       Date:  2000-12       Impact factor: 5.191

10.  Phase II trial of sorafenib plus interferon alfa-2b as first- or second-line therapy in patients with metastatic renal cell cancer.

Authors:  Jared A Gollob; W Kimryn Rathmell; Tina M Richmond; Christine B Marino; Elizabeth K Miller; Gayle Grigson; Catharine Watkins; Lin Gu; Bercedis L Peterson; John J Wright
Journal:  J Clin Oncol       Date:  2007-08-01       Impact factor: 44.544

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  93 in total

1.  Prediction of resistance development against drug combinations by collateral responses to component drugs.

Authors:  Christian Munck; Heidi K Gumpert; Annika I Nilsson Wallin; Harris H Wang; Morten O A Sommer
Journal:  Sci Transl Med       Date:  2014-11-12       Impact factor: 17.956

Review 2.  Viral quasispecies evolution.

Authors:  Esteban Domingo; Julie Sheldon; Celia Perales
Journal:  Microbiol Mol Biol Rev       Date:  2012-06       Impact factor: 11.056

3.  Automated imaging with ScanLag reveals previously undetectable bacterial growth phenotypes.

Authors:  Irit Levin-Reisman; Orit Gefen; Ofer Fridman; Irine Ronin; David Shwa; Hila Sheftel; Nathalie Q Balaban
Journal:  Nat Methods       Date:  2010-08-01       Impact factor: 28.547

Review 4.  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

5.  Regulation of phenotypic variability by a threshold-based mechanism underlies bacterial persistence.

Authors:  Eitan Rotem; Adiel Loinger; Irine Ronin; Irit Levin-Reisman; Chana Gabay; Noam Shoresh; Ofer Biham; Nathalie Q Balaban
Journal:  Proc Natl Acad Sci U S A       Date:  2010-06-28       Impact factor: 11.205

6.  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 7.  Multidrug evolutionary strategies to reverse antibiotic resistance.

Authors:  Michael Baym; Laura K Stone; Roy Kishony
Journal:  Science       Date:  2016-01-01       Impact factor: 47.728

8.  A Hybrid Drug Limits Resistance by Evading the Action of the Multiple Antibiotic Resistance Pathway.

Authors:  Kathy K Wang; Laura K Stone; Tami D Lieberman; Michal Shavit; Timor Baasov; Roy Kishony
Journal:  Mol Biol Evol       Date:  2015-11-03       Impact factor: 16.240

Review 9.  Malaria biology and disease pathogenesis: insights for new treatments.

Authors:  Louis H Miller; Hans C Ackerman; Xin-zhuan Su; Thomas E Wellems
Journal:  Nat Med       Date:  2013-02-06       Impact factor: 53.440

10.  The innate growth bistability and fitness landscapes of antibiotic-resistant bacteria.

Authors:  J Barrett Deris; Minsu Kim; Zhongge Zhang; Hiroyuki Okano; Rutger Hermsen; Alexander Groisman; Terence Hwa
Journal:  Science       Date:  2013-11-29       Impact factor: 47.728

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