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Article

Correlation between Phenotypic and In Silico Detection of Antimicrobial Resistance in Salmonella enterica in Canada Using Staramr

1
National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB R3E 3R2, Canada
2
Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, MB R3E 0J9, Canada
3
Centre for Food-Borne, Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, ON K1A 0K9, Canada
4
United States Centers for Disease Control and Prevention, Atlanta, GA 30333, USA
5
Cadham Provincial Laboratory, Winnipeg, MB R3E 3J7, Canada
6
Public Health Ontario Laboratories, Toronto, ON M5G 1M1, Canada
7
Horizon Health Network, Saint John, NB E2L 4L2, Canada
8
Laboratoire de Santé Publique du Québec, Sainte-Anne-de-Bellevue, QC H9X 3R5, Canada
9
Queen Elizabeth Hospital, Charlottetown, PE C1A 8T5, Canada
10
Queen Elizabeth II Health Sciences Centre, Halifax, NS B3H 2Y9, Canada
11
British Columbia Center for Disease Control, Vancouver, BC V5Z 4R4, Canada
12
Alberta Precision Laboratories: Public Health Laboratory (ProvLab), Edmonton, AB T6G 2J2, Canada
13
Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB T6G 2B7, Canada
14
Roy Romanow Provincial Laboratory, Regina, SK S4S 5W6, Canada
15
Newfoundland and Labrador Public Health and Microbiology Laboratory, St. John’s, NL A1A 3Z9, Canada
*
Author to whom correspondence should be addressed.
Academic Editor: David Bermudes
Microorganisms 2022, 10(2), 292; https://doi.org/10.3390/microorganisms10020292
Received: 14 December 2021 / Revised: 18 January 2022 / Accepted: 21 January 2022 / Published: 26 January 2022
Whole genome sequencing (WGS) of Salmonella supports both molecular typing and detection of antimicrobial resistance (AMR). Here, we evaluated the correlation between phenotypic antimicrobial susceptibility testing (AST) and in silico prediction of AMR from WGS in Salmonella enterica (n = 1321) isolated from human infections in Canada. Phenotypic AMR results from broth microdilution testing were used as the gold standard. To facilitate high-throughput prediction of AMR from genome assemblies, we created a tool called Staramr, which incorporates the ResFinder and PointFinder databases and a custom gene-drug key for antibiogram prediction. Overall, there was 99% concordance between phenotypic and genotypic detection of categorical resistance for 14 antimicrobials in 1321 isolates (18,305 of 18,494 results in agreement). We observed an average sensitivity of 91.2% (range 80.5–100%), a specificity of 99.7% (98.6–100%), a positive predictive value of 95.4% (68.2–100%), and a negative predictive value of 99.1% (95.6–100%). The positive predictive value of gentamicin was 68%, due to seven isolates that carried aac(3)-IVa, which conferred MICs just below the breakpoint of resistance. Genetic mechanisms of resistance in these 1321 isolates included 64 unique acquired alleles and mutations in three chromosomal genes. In general, in silico prediction of AMR in Salmonella was reliable compared to the gold standard of broth microdilution. WGS can provide higher-resolution data on the epidemiology of resistance mechanisms and the emergence of new resistance alleles. View Full-Text
Keywords: antimicrobial resistance; whole-genome sequencing; molecular epidemiology; AMR prediction; Salmonella antimicrobial resistance; whole-genome sequencing; molecular epidemiology; AMR prediction; Salmonella
MDPI and ACS Style

Bharat, A.; Petkau, A.; Avery, B.P.; Chen, J.C.; Folster, J.P.; Carson, C.A.; Kearney, A.; Nadon, C.; Mabon, P.; Thiessen, J.; Alexander, D.C.; Allen, V.; El Bailey, S.; Bekal, S.; German, G.J.; Haldane, D.; Hoang, L.; Chui, L.; Minion, J.; Zahariadis, G.; Domselaar, G.V.; Reid-Smith, R.J.; Mulvey, M.R. Correlation between Phenotypic and In Silico Detection of Antimicrobial Resistance in Salmonella enterica in Canada Using Staramr. Microorganisms 2022, 10, 292. https://doi.org/10.3390/microorganisms10020292

AMA Style

Bharat A, Petkau A, Avery BP, Chen JC, Folster JP, Carson CA, Kearney A, Nadon C, Mabon P, Thiessen J, Alexander DC, Allen V, El Bailey S, Bekal S, German GJ, Haldane D, Hoang L, Chui L, Minion J, Zahariadis G, Domselaar GV, Reid-Smith RJ, Mulvey MR. Correlation between Phenotypic and In Silico Detection of Antimicrobial Resistance in Salmonella enterica in Canada Using Staramr. Microorganisms. 2022; 10(2):292. https://doi.org/10.3390/microorganisms10020292

Chicago/Turabian Style

Bharat, Amrita, Aaron Petkau, Brent P. Avery, Jessica C. Chen, Jason P. Folster, Carolee A. Carson, Ashley Kearney, Celine Nadon, Philip Mabon, Jeffrey Thiessen, David C. Alexander, Vanessa Allen, Sameh El Bailey, Sadjia Bekal, Greg J. German, David Haldane, Linda Hoang, Linda Chui, Jessica Minion, George Zahariadis, Gary V. Domselaar, Richard J. Reid-Smith, and Michael R. Mulvey. 2022. "Correlation between Phenotypic and In Silico Detection of Antimicrobial Resistance in Salmonella enterica in Canada Using Staramr" Microorganisms 10, no. 2: 292. https://doi.org/10.3390/microorganisms10020292

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