Objectives: Phenotypic and genotypic methods for the detection of antimicrobial resistance (AMR) in Shigella sonnei in England and Wales were compared and evaluated. Methods: WGS data from 341 isolates of S. sonnei isolated between June 2015 and January 2016 were mapped to genes known to be associated with phenotypic AMR. Antimicrobial susceptibility testing was performed on all viable isolates (n = 335). Results: Fifteen of 335 isolates had a discrepancy between phenotypic and genotypic testing for 1 of the 10 antimicrobial classes tested, equating to 15 (0.45%) discordant results out of a possible 3350 isolate/antimicrobial combinations. All 15 mismatched results were genotypically resistant but phenotypically susceptible. Eleven of the 15 discrepancies were observed in streptomycin resistance profiles. The most common resistance profile was trimethoprim, sulphonamides, tetracyclines and streptomycin, occurring in 97 (28.4%) isolates. Resistances to ciprofloxacin and the third-generation cephalosporins, not detected in England and Wales prior to 2002, were identified in 18.2% and 12% of isolates, respectively. Three hundred and four (89.1%) isolates were MDR. There was no significant association between any of the AMR determinants tested and recent foreign travel in male or female cases. The number of isolates of S. sonnei harbouring blaTEM-1 and ermB/mphA was significantly higher in men who reported no recent travel outside the UK. Conclusions: The use of WGS for routine public health surveillance is a reliable method for rapid detection of emerging AMR in isolates of S. sonnei.
Objectives: Phenotypic and genotypic methods for the detection of antimicrobial resistance (AMR) in Shigella sonnei in England and Wales were compared and evaluated. Methods: WGS data from 341 isolates of S. sonnei isolated between June 2015 and January 2016 were mapped to genes known to be associated with phenotypic AMR. Antimicrobial susceptibility testing was performed on all viable isolates (n = 335). Results: Fifteen of 335 isolates had a discrepancy between phenotypic and genotypic testing for 1 of the 10 antimicrobial classes tested, equating to 15 (0.45%) discordant results out of a possible 3350 isolate/antimicrobial combinations. All 15 mismatched results were genotypically resistant but phenotypically susceptible. Eleven of the 15 discrepancies were observed in streptomycin resistance profiles. The most common resistance profile was trimethoprim, sulphonamides, tetracyclines and streptomycin, occurring in 97 (28.4%) isolates. Resistances to ciprofloxacin and the third-generation cephalosporins, not detected in England and Wales prior to 2002, were identified in 18.2% and 12% of isolates, respectively. Three hundred and four (89.1%) isolates were MDR. There was no significant association between any of the AMR determinants tested and recent foreign travel in male or female cases. The number of isolates of S. sonnei harbouring blaTEM-1 and ermB/mphA was significantly higher in men who reported no recent travel outside the UK. Conclusions: The use of WGS for routine public health surveillance is a reliable method for rapid detection of emerging AMR in isolates of S. sonnei.
Authors: Alex van Belkum; Carey-Ann D Burnham; John W A Rossen; Frederic Mallard; Olivier Rochas; William Michael Dunne Journal: Nat Rev Microbiol Date: 2020-02-13 Impact factor: 60.633
Authors: Jane Hawkey; Kalani Paranagama; Kate S Baker; Rebecca J Bengtsson; François-Xavier Weill; Nicholas R Thomson; Stephen Baker; Louise Cerdeira; Zamin Iqbal; Martin Hunt; Danielle J Ingle; Timothy J Dallman; Claire Jenkins; Deborah A Williamson; Kathryn E Holt Journal: Nat Commun Date: 2021-05-11 Impact factor: 14.919
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