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Equations To Predict Antimicrobial MICs in Neisseria gonorrhoeae Using Molecular Antimicrobial Resistance Determinants
Author(s) -
Walter Demczuk,
Irene Martín,
Pam Sawatzky,
Vanessa Allen,
Brigitte Lefebvre,
Linda Hoang,
Prenilla Naidu,
Jessica Minion,
Paul VanCaeseele,
David Haldane,
David W Eyre,
Michael R. Mulvey
Publication year - 2020
Publication title -
antimicrobial agents and chemotherapy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.07
H-Index - 259
eISSN - 1070-6283
pISSN - 0066-4804
DOI - 10.1128/aac.02005-19
Subject(s) - cefixime , neisseria gonorrhoeae , azithromycin , gonorrhea , microbiology and biotechnology , antimicrobial , ciprofloxacin , penicillin , ceftriaxone , antibiotic resistance , cephalosporin , biology , tetracycline , medicine , antibiotics , virology , human immunodeficiency virus (hiv)
The emergence of Neisseria gonorrhoeae strains that are resistant to azithromycin and extended-spectrum cephalosporins represents a public health threat, that of untreatable gonorrhea infections. Multivariate regression modeling was used to determine the contributions of molecular antimicrobial resistance determinants to the overall antimicrobial MICs for ceftriaxone, cefixime, azithromycin, tetracycline, ciprofloxacin, and penicillin. A training data set consisting of 1,280 N. gonorrhoeae strains was used to generate regression equations which were then applied to validation data sets of Canadian ( n  = 1,095) and international ( n  = 431) strains. The predicted MICs for extended-spectrum cephalosporins (ceftriaxone and cefixime) were fully explained by 5 amino acid substitutions in PenA, A311V, A501P/T/V, N513Y, A517G, and G543S; the presence of a disrupted mtrR promoter; and the PorB G120 and PonA L421P mutations. The correlation of predicted MICs within one doubling dilution to phenotypically determined MICs of the Canadian validation data set was 95.0% for ceftriaxone, 95.6% for cefixime, 91.4% for azithromycin, 98.2% for tetracycline, 90.4% for ciprofloxacin, and 92.3% for penicillin, with an overall sensitivity of 99.9% and specificity of 97.1%. The correlations of predicted MIC values to the phenotypically determined MICs were similar to those from phenotype MIC-only comparison studies. The ability to acquire detailed antimicrobial resistance information directly from molecular data will facilitate the transition to whole-genome sequencing analysis from phenotypic testing and can fill the surveillance gap in an era of increased reliance on nucleic acid assay testing (NAAT) diagnostics to better monitor the dynamics of N. gonorrhoeae .

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