TY - JOUR
T1 - Aminoglycoside-resistance gene signatures are predictive of aminoglycoside MICs for carbapenem-resistant Klebsiella pneumoniae
AU - Huang, Yanqin
AU - Rana, Amisha P.
AU - Wenzler, Eric
AU - Ozer, Egon A.
AU - Krapp, Fiorella
AU - Bulitta, Jürgen B.
AU - Hauser, Alan R.
AU - Bulman, Zackery P.
N1 - Publisher Copyright:
© 2021 The Author(s) 2021. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For permissions, please email: [email protected].
PY - 2022/2/1
Y1 - 2022/2/1
N2 - Background: Aminoglycoside-containing regimens may be an effective treatment option for infections caused by carbapenem-resistant Klebsiella pneumoniae (CR-Kp), but aminoglycoside-resistance genes are common in these strains. The relationship between the aminoglycoside-resistance genes and aminoglycoside MICs remains poorly defined. Objectives: To identify genotypic signatures capable of predicting aminoglycoside MICs for CR-Kp. Methods: Clinical CR-Kp isolates (n = 158) underwent WGS to detect aminoglycoside-resistance genes. MICs of amikacin, gentamicin, plazomicin and tobramycin were determined by broth microdilution (BMD). Principal component analysis was used to initially separate isolates based on genotype. Multiple linear regression was then used to generate models that predict aminoglycoside MICs based on the aminoglycoside-resistance genes. Last, the performance of the predictive models was tested against a validation cohort of 29 CR-Kp isolates. Results: Among the original 158 CR-Kp isolates, 91.77% (145/158) had at least one clinically relevant aminoglycoside-resistance gene. As a group, 99.37%, 84.81%, 82.28% and 10.76% of the CR-Kp isolates were susceptible to plazomicin, amikacin, gentamicin and tobramycin, respectively. The first two principal components explained 72.23% of the total variance in aminoglycoside MICs and separated isolates into four groups with aac(6′)-Ib, aac(6′)-Ib′, aac(6′)-Ib+aac(6′)-Ib′ or no clinically relevant aminoglycoside-resistance genes. Regression models predicted aminoglycoside MICs with adjusted R2 values of 56%-99%. Within the validation cohort, the categorical agreement when comparing the observed BMD MICs with the predicated MICs was 96.55%, 89.66%, 86.21% and 82.76% for plazomicin, gentamicin, amikacin and tobramycin, respectively. Conclusions: Susceptibility to each aminoglycoside varies in CR-Kp. Detection of aminoglycoside-resistance genes may be useful to predict aminoglycoside MICs for CR-Kp.
AB - Background: Aminoglycoside-containing regimens may be an effective treatment option for infections caused by carbapenem-resistant Klebsiella pneumoniae (CR-Kp), but aminoglycoside-resistance genes are common in these strains. The relationship between the aminoglycoside-resistance genes and aminoglycoside MICs remains poorly defined. Objectives: To identify genotypic signatures capable of predicting aminoglycoside MICs for CR-Kp. Methods: Clinical CR-Kp isolates (n = 158) underwent WGS to detect aminoglycoside-resistance genes. MICs of amikacin, gentamicin, plazomicin and tobramycin were determined by broth microdilution (BMD). Principal component analysis was used to initially separate isolates based on genotype. Multiple linear regression was then used to generate models that predict aminoglycoside MICs based on the aminoglycoside-resistance genes. Last, the performance of the predictive models was tested against a validation cohort of 29 CR-Kp isolates. Results: Among the original 158 CR-Kp isolates, 91.77% (145/158) had at least one clinically relevant aminoglycoside-resistance gene. As a group, 99.37%, 84.81%, 82.28% and 10.76% of the CR-Kp isolates were susceptible to plazomicin, amikacin, gentamicin and tobramycin, respectively. The first two principal components explained 72.23% of the total variance in aminoglycoside MICs and separated isolates into four groups with aac(6′)-Ib, aac(6′)-Ib′, aac(6′)-Ib+aac(6′)-Ib′ or no clinically relevant aminoglycoside-resistance genes. Regression models predicted aminoglycoside MICs with adjusted R2 values of 56%-99%. Within the validation cohort, the categorical agreement when comparing the observed BMD MICs with the predicated MICs was 96.55%, 89.66%, 86.21% and 82.76% for plazomicin, gentamicin, amikacin and tobramycin, respectively. Conclusions: Susceptibility to each aminoglycoside varies in CR-Kp. Detection of aminoglycoside-resistance genes may be useful to predict aminoglycoside MICs for CR-Kp.
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U2 - 10.1093/jac/dkab381
DO - 10.1093/jac/dkab381
M3 - Article
C2 - 34668007
AN - SCOPUS:85123969787
SN - 0305-7453
VL - 77
SP - 356
EP - 363
JO - Journal of antimicrobial chemotherapy
JF - Journal of antimicrobial chemotherapy
IS - 2
ER -
