UK NEQAS in antibiotic assays

Accuracy of Different Bioinformatics Methods in Detecting Antibiotic Resistance and Virulence Factors from Staphylococcus aureus Whole-Genome Sequences

In principle, whole-genome sequencing (WGS) can predict phenotypic resistance directly from a genotype, replacing laboratory-based tests. However, the contribution of different bioinformatics methods to genotype-phenotype discrepancies has not been systematically explored to date. We compared three WGS-based bioinformatics methods (Genefinder [read based], Mykrobe [de Bruijn graph based], and Typewriter [BLAST based]) for predicting the presence/absence of 83 different resistance determinants and virulence genes and overall antimicrobial susceptibility in 1,379 Staphylococcus aureus isolates previously characterized by standard laboratory methods (disc diffusion, broth and/or agar dilution, and PCR). In total, 99.5% (113,830/114,457) of individual resistance-determinant/virulence gene predictions were identical between all three methods, with only 627 (0.5%) discordant predictions, demonstrating high overall agreement (Fleiss' kappa = 0.98, P < 0.0001). Discrepancies when identified were in only one of the three methods for all genes except the cassette recombinase, ccrC(b). The genotypic antimicrobial susceptibility prediction matched the laboratory phenotype in 98.3% (14,224/14,464) of cases (2,720 [18.8%] resistant, 11,504 [79.5%] susceptible). There was greater disagreement between the laboratory phenotypes and the combined genotypic predictions (97 [0.7%] phenotypically susceptible, but all bioinformatic methods reported resistance; 89 [0.6%] phenotypically resistant, but all bioinformatics methods reported susceptible) than within the three bioinformatics methods (54 [0.4%] cases, 16 phenotypically resistant, 38 phenotypically susceptible). However, in 36/54 (67%) cases, the consensus genotype matched the laboratory phenotype. In this study, the choice between these three specific bioinformatic methods to identify resistance determinants or other genes in S. aureus did not prove critical, with all demonstrating high concordance with each other and phenotypic/molecular methods. However, each has some limitations; therefore, consensus methods provide some assurance.

Development and validation of a new ultra-performance liquid chromatographic method for vancomycin assay in serum and its application to therapeutic drug monitoring

OBJECTIVE

The aim of this study was to develop and validate an ultra-performance liquid chromatographic (UPLC) method with photodiode array detector for the measurement of vancomycin in human serum samples for therapeutic drug monitoring or other applications.

METHODS

The method included the extraction of vancomycin in serum by deproteinization with acetonitrile. The analyses were carried out using an ACQUITY UPLC BEH C(18) column (2.1 × 50 mm, 1.7 μm) using acetonitrile and 0.005 M KH(2)PO(4) buffer (pH 2.5) as the mobile phase at a flow rate of 0.3 mL/min, with photodiode array detection at 230 nm. The method was validated for extraction recovery, inter- and intraday precision (relative standard deviation, RSD%), and accuracy and stability of vancomycin in serum. Both the established UPLC method and fluorescence polarization immunoassay (FPIA) were used to measure the prepared quality control (QC) samples (1.0, 7.0, 35.0, 75.0 mg/L) to validate the accuracy of UPLC. Furthermore, both methods were subsequently used to assay the vancomycin concentration in 172 clinical serum samples collected from patients receiving vancomycin in the hospitals localized in Shanghai (China) and 32 control samples from United Kingdom National External Quality Assessment Service (UK NEQAS).

RESULTS

The retention time of vancomycin was 2.6 minutes. The calibration curve for UPLC was linear over the range 1.0-100.0 mg/L (R(2) > 0.999). The method was fully validated in terms of recovery, selectivity, accuracy, precision, and various conditions. The absolute difference% and RSD% of the prepared QC samples assayed by UPLC were all better than the results by FPIA. A paired t test of the results of the prepared QC samples indicated that the results of all the QC samples had significant difference (P < 0.05), except for the 7.0 mg/L QC samples, which suggested that UPLC was more accurate for the samples containing low or high concentration of vancomycin. A correlation with the Deming model provided a good linear relation between the results of the 2 methods applied to 172 samples, with equation of UPLC = 0.99 × FPIA - 0.19 (R(2)= 0.923), and the agreement of the 2 methods was illustrated using Bland-Altman plot with a mean difference (UPLC - FPIA) of -0.428 mg/L and 95% confidence interval of -8.33 to 7.47 mg/L, respectively. A Student t test comparing results obtained by the UPLC method and group mean results of control samples from UK NEQAS were not significant (P = 0.057).

CONCLUSIONS

A short analysis time, small amount of serum needed, high specificity, and accuracy make the UPLC method developed in this study appropriate and practical for vancomycin therapeutic drug monitoring and could be applied to other nonserum applications or where requiring superior validation parameters such as for pharmacokinetic/pharmacodynamic studies.