Determining antimicrobial susceptibility in Salmonella enterica serovar Typhimurium through whole genome sequencing: a comparison against multiple phenotypic susceptibility testing methods

Mensah, Nana, Tang, Yue, Cawthraw, Shaun, Abuoun, Manal, Fenner, Jackie, Thomson, Nicholas R., Mather, Alison E. and Petrovska-Holmes, Liljana (2019) Determining antimicrobial susceptibility in Salmonella enterica serovar Typhimurium through whole genome sequencing: a comparison against multiple phenotypic susceptibility testing methods. BMC Microbiology, 19. ISSN 1471-2180

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Abstract

Background : UK public health organisations perform routine antimicrobial susceptibility tests (ASTs) to characterise the potential for antimicrobial resistance in Salmonella enterica serovars. Genetic determinants of these resistance mechanisms are detectable by whole genome sequencing (WGS), however the viability of WGS-based genotyping as an alternative resistance screening tool remains uncertain. We compared WGS-based genotyping, disk diffusion and agar dilution to the broth microdilution reference AST for 102 Salmonella enterica serovar Typhimurium (S. Typhimurium) isolates across 11 antimicrobial compounds. Results : Genotyping concordance, interpreted using epidemiological cut-offs (ECOFFs), was 89.8% (1007/1122) with 0.83 sensitivity and 0.96 specificity. For seven antimicrobials interpreted using Salmonella clinical breakpoints, genotyping produced 0.84 sensitivity and 0.88 specificity. Although less accurate than disk diffusion (0.94 sensitivity, 0.93 specificity) and agar dilution (0.83 sensitivity, 0.98 specificity), genotyping performance improved to 0.89 sensitivity and 0.97 specificity when two antimicrobials with relatively high very major error rates were excluded (streptomycin and sulfamethoxazole). Conclusions : An 89.8% concordance from WGS-based AST predictions using ECOFF interpretations suggest that WGS would serve as an effective screening tool for the tracking of antimicrobial resistance mechanisms in S. Typhimurium. For use as a standalone clinical diagnostic screen, further work is required to reduce the error rates for specific antimicrobials.

Item Type: Article
Uncontrolled Keywords: sdg 3 - good health and well-being ,/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being
Faculty \ School:
UEA Research Groups: Faculty of Medicine and Health Sciences > Research Centres > Metabolic Health
Depositing User: LivePure Connector
Date Deposited: 09 Jul 2019 08:30
Last Modified: 06 Jun 2024 15:07
URI: https://ueaeprints.uea.ac.uk/id/eprint/71682
DOI: 10.1186/s12866-019-1520-9

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