Literature DB >> 29216342

Comparison of phenotypic and WGS-derived antimicrobial resistance profiles of Salmonella enterica serovars Typhi and Paratyphi.

Martin R Day1, Michel Doumith1, Vivienne Do Nascimento1, Satheesh Nair1, Philip M Ashton1, Claire Jenkins1, Timothy J Dallman1, Flora J Stevens2, Joanne Freedman2, Katie L Hopkins1, Neil Woodford1, Elizabeth M De Pinna1, Gauri Godbole1.   

Abstract

Objectives: Surveillance of antimicrobial resistance (AMR) in Salmonella enterica serovars Typhi and Paratyphi is essential to provide an evidence base for empirical treatment protocols and to monitor emerging AMR. We sought to compare phenotypic and WGS-based genotypic methods for the detection of AMR in Salmonella Typhi and Salmonella Paratyphi.
Methods: WGS data from 603 isolates of Salmonella Typhi (n = 332) and Salmonella Paratyphi (n = 271) were mapped to genes or chromosomal mutations known to be associated with phenotypic AMR and compared with phenotypic susceptibility data interpreted using breakpoints recommended by EUCAST.
Results: There were two (0.03%) discordant interpretations out of a possible 6030 isolate/antimicrobial class combinations. MDR (resistant to three or more classes of antimicrobial) was detected in 83/332 (25.0%) Salmonella Typhi isolates, but was not detected in Salmonella Paratyphi. Thirty-six (10.8%) isolates of Salmonella Typhi were resistant to ciprofloxacin (MIC >0.5 mg/L), with 33 (9.9%) of 332 exhibiting mutations in gyrA and parC, and 244 (73.5%) isolates had reduced susceptibility to ciprofloxacin (MIC 0.06-0.25 mg/L). In comparison, 209/227 (92.1%) isolates of Salmonella Paratyphi A exhibited resistance to ciprofloxacin (MIC >0.5 mg/L). No resistance to azithromycin or the third-generation cephalosporins was detected. Conclusions: WGS data provided a robust and informative approach for monitoring MDR and emerging resistance to ciprofloxacin in Salmonella Typhi and Salmonella Paratyphi. Phenotypic antimicrobial susceptibility testing continues to be performed to guide targeted individual patient treatment, but inferred AMR profiles from WGS data may be used for surveillance and to guide empirical therapy. © Crown copyright 2017.

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Year:  2018        PMID: 29216342     DOI: 10.1093/jac/dkx379

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


  15 in total

1.  Validating the AMRFinder Tool and Resistance Gene Database by Using Antimicrobial Resistance Genotype-Phenotype Correlations in a Collection of Isolates.

Authors:  Michael Feldgarden; Vyacheslav Brover; Daniel H Haft; Arjun B Prasad; Douglas J Slotta; Igor Tolstoy; Gregory H Tyson; Shaohua Zhao; Chih-Hao Hsu; Patrick F McDermott; Daniel A Tadesse; Cesar Morales; Mustafa Simmons; Glenn Tillman; Jamie Wasilenko; Jason P Folster; William Klimke
Journal:  Antimicrob Agents Chemother       Date:  2019-10-22       Impact factor: 5.191

2.  Setup, Validation, and Quality Control of a Centralized Whole-Genome-Sequencing Laboratory: Lessons Learned.

Authors:  Cath Arnold; Kirstin Edwards; Meeta Desai; Steve Platt; Jonathan Green; David Conway
Journal:  J Clin Microbiol       Date:  2018-07-26       Impact factor: 5.948

3.  Salmonella enterica Serovar Typhi in Bangladesh: Exploration of Genomic Diversity and Antimicrobial Resistance.

Authors:  Arif M Tanmoy; Emilie Westeel; Katrien De Bruyne; Johan Goris; Alain Rajoharison; Mohammad S I Sajib; Alex van Belkum; Samir K Saha; Florence Komurian-Pradel; Hubert P Endtz
Journal:  mBio       Date:  2018-11-13       Impact factor: 7.867

4.  MinION nanopore sequencing identifies the position and structure of bacterial antibiotic resistance determinants in a multidrug-resistant strain of enteroaggregative Escherichia coli.

Authors:  David R Greig; Timothy J Dallman; Katie L Hopkins; Claire Jenkins
Journal:  Microb Genom       Date:  2018-09-20

5.  Informal genomic surveillance of regional distribution of Salmonella Typhi genotypes and antimicrobial resistance via returning travellers.

Authors:  Danielle J Ingle; Satheesh Nair; Hassan Hartman; Philip M Ashton; Zoe A Dyson; Martin Day; Joanne Freedman; Marie A Chattaway; Kathryn E Holt; Timothy J Dallman
Journal:  PLoS Negl Trop Dis       Date:  2019-09-12

6.  Genomic surveillance detects Salmonella enterica serovar Paratyphi A harbouring blaCTX-M-15 from a traveller returning from Bangladesh.

Authors:  Satheesh Nair; Martin Day; Gauri Godbole; Tranprit Saluja; Gemma C Langridge; Timothy J Dallman; Marie Chattaway
Journal:  PLoS One       Date:  2020-01-30       Impact factor: 3.240

Review 7.  Whole-genome sequencing as part of national and international surveillance programmes for antimicrobial resistance: a roadmap.

Authors: 
Journal:  BMJ Glob Health       Date:  2020-11

8.  Prediction of Phenotypic Antimicrobial Resistance Profiles From Whole Genome Sequences of Non-typhoidal Salmonella enterica.

Authors:  Saskia Neuert; Satheesh Nair; Martin R Day; Michel Doumith; Philip M Ashton; Kate C Mellor; Claire Jenkins; Katie L Hopkins; Neil Woodford; Elizabeth de Pinna; Gauri Godbole; Timothy J Dallman
Journal:  Front Microbiol       Date:  2018-03-27       Impact factor: 5.640

Review 9.  Genome-Based Prediction of Bacterial Antibiotic Resistance.

Authors:  Michelle Su; Sarah W Satola; Timothy D Read
Journal:  J Clin Microbiol       Date:  2019-02-27       Impact factor: 5.948

10.  AMRFinderPlus and the Reference Gene Catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence.

Authors:  Michael Feldgarden; Vyacheslav Brover; Narjol Gonzalez-Escalona; Jonathan G Frye; Julie Haendiges; Daniel H Haft; Maria Hoffmann; James B Pettengill; Arjun B Prasad; Glenn E Tillman; Gregory H Tyson; William Klimke
Journal:  Sci Rep       Date:  2021-06-16       Impact factor: 4.996

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