Literature DB >> 31555989

Soft sweep development of resistance in Escherichia coli under fluoroquinolone stress.

Xianxing Xie1, Ruichen Lv1,2, Chao Yang1, Yajun Song1, Yanfeng Yan1, Yujun Cui1, Ruifu Yang3.   

Abstract

We employed a stepwise selection model for investigating the dynamics of antibiotic-resistant variants in Escherichia coli K-12 treated with increasing concentrations of ciprofloxacin (CIP). Firstly, we used Sanger sequencing to screen the variations in the fluoquinolone target genes, then, employed Illumina NGS sequencing for amplicons targeted regions with variations. The results demonstrated that variations G81C in gyrA and K276N and K277L in parC are standing resistance variations (SRVs), while S83A and S83L in gyrA and G78C in parC were emerging resistance variations (ERVs). The variants containing SRVs and/or ERVs were selected successively based on their sensitivities to CIP. Variant strain 1, containing substitution G81C in gyrA, was immediately selected following ciprofloxacin exposure, with obvious increases in the parC SRV, and parC and gyrA ERV allele frequencies. Variant strain 2, containing the SRVs, then dominated the population following a 20× increase in ciprofloxacin concentration, with other associated allele frequencies also elevated. Variant strains 3 and 4, containing ERVs in gyrA and parC, respectively, were then selected at 40× and 160× antibiotic concentrations. Two variants, strains 5 and 6, generated in the selection procedure, were lost because of higher fitness costs or a lower level of resistance compared with variants 3 and 4. For the second induction, all variations/indels were already present as SRVs and selected out step by step at different passages. Whatever the first induction or second induction, our results confirmed the soft selective sweep hypothesis and provided critical information for guiding clinical treatment of pathogens containing SRVs.

Entities:  

Keywords:  Escherichia coli; ciprofloxacin; fitness cost; soft sweeps; stepwise selection

Mesh:

Substances:

Year:  2019        PMID: 31555989     DOI: 10.1007/s12275-019-9177-5

Source DB:  PubMed          Journal:  J Microbiol        ISSN: 1225-8873            Impact factor:   3.422


  52 in total

Review 1.  Antibiotic resistance and its cost: is it possible to reverse resistance?

Authors:  Dan I Andersson; Diarmaid Hughes
Journal:  Nat Rev Microbiol       Date:  2010-03-08       Impact factor: 60.633

2.  On the unfounded enthusiasm for soft selective sweeps.

Authors:  Jeffrey D Jensen
Journal:  Nat Commun       Date:  2014-10-27       Impact factor: 14.919

3.  Antibiotic-mediated recombination: ciprofloxacin stimulates SOS-independent recombination of divergent sequences in Escherichia coli.

Authors:  Elena López; Marina Elez; Ivan Matic; Jesús Blázquez
Journal:  Mol Microbiol       Date:  2007-04       Impact factor: 3.501

4.  Historical variations in mutation rate in an epidemic pathogen, Yersinia pestis.

Authors:  Yujun Cui; Chang Yu; Yanfeng Yan; Dongfang Li; Yanjun Li; Thibaut Jombart; Lucy A Weinert; Zuyun Wang; Zhaobiao Guo; Lizhi Xu; Yujiang Zhang; Hancheng Zheng; Nan Qin; Xiao Xiao; Mingshou Wu; Xiaoyi Wang; Dongsheng Zhou; Zhizhen Qi; Zongmin Du; Honglong Wu; Xianwei Yang; Hongzhi Cao; Hu Wang; Jing Wang; Shusen Yao; Alexander Rakin; Yingrui Li; Daniel Falush; Francois Balloux; Mark Achtman; Yajun Song; Jun Wang; Ruifu Yang
Journal:  Proc Natl Acad Sci U S A       Date:  2012-12-27       Impact factor: 11.205

5.  Interplay in the selection of fluoroquinolone resistance and bacterial fitness.

Authors:  Linda L Marcusson; Niels Frimodt-Møller; Diarmaid Hughes
Journal:  PLoS Pathog       Date:  2009-08-07       Impact factor: 6.823

6.  Versatile and open software for comparing large genomes.

Authors:  Stefan Kurtz; Adam Phillippy; Arthur L Delcher; Michael Smoot; Martin Shumway; Corina Antonescu; Steven L Salzberg
Journal:  Genome Biol       Date:  2004-01-30       Impact factor: 13.583

Review 7.  Fluoroquinolone resistance: mechanisms, impact on bacteria, and role in evolutionary success.

Authors:  Liam S Redgrave; Sam B Sutton; Mark A Webber; Laura J V Piddock
Journal:  Trends Microbiol       Date:  2014-05-16       Impact factor: 17.079

8.  A framework for variation discovery and genotyping using next-generation DNA sequencing data.

Authors:  Mark A DePristo; Eric Banks; Ryan Poplin; Kiran V Garimella; Jared R Maguire; Christopher Hartl; Anthony A Philippakis; Guillermo del Angel; Manuel A Rivas; Matt Hanna; Aaron McKenna; Tim J Fennell; Andrew M Kernytsky; Andrey Y Sivachenko; Kristian Cibulskis; Stacey B Gabriel; David Altshuler; Mark J Daly
Journal:  Nat Genet       Date:  2011-04-10       Impact factor: 38.330

9.  Quinolone resistance in absence of selective pressure: the experience of a very remote community in the Amazon forest.

Authors:  Lucia Pallecchi; Alessandro Bartoloni; Eleonora Riccobono; Connie Fernandez; Antonia Mantella; Donata Magnelli; Dario Mannini; Marianne Strohmeyer; Filippo Bartalesi; Hugo Rodriguez; Eduardo Gotuzzo; Gian Maria Rossolini
Journal:  PLoS Negl Trop Dis       Date:  2012-08-28

10.  Rates and mechanisms of bacterial mutagenesis from maximum-depth sequencing.

Authors:  Justin Jee; Aviram Rasouly; Ilya Shamovsky; Yonatan Akivis; Susan R Steinman; Bud Mishra; Evgeny Nudler
Journal:  Nature       Date:  2016-06-22       Impact factor: 49.962

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