Application of colloidal gold immunochromatography in rapid determination of carbapene-mase in CRE
Objective To evaluate clinical application value of colloidal gold immunochromatogra-phy(GICA)for rapid detection of carbapenemase in carbapenem-resistant Enterobacteriaceae(CRE)isolates.Methods Totally,54 non-reduplicative isolates of CRE were collected from March 2016 to November 2021 in L iuzhou.The expression of carbapenemase gene was preliminary screening by the carbapenemase phenotype test and the review determination of carbapenemase by multiple real-time quantitative PCR.For the strains whose drug resistance genes could not be identified by the above methods,the whole genome sequencing(WGS)was used for detection.The type of carbapenemase in CRE was rapidly detected by GICA.Multiple real-time quantita-tive PCR was used as reference method to evaluate the accuracy of GICA in the rapid determination of carbapen-emase.Results The CRE collected in this study were 54 isolates,mainly including Escherichia coli(27 iso-lates,50.0%)and Klebsiella pneumoniae(14 isolates,25.9%).The results of carbapenemase phenotype test showed that there were 50 metal enzymes isolates(92.6%),2 serine enzymes isolates(3.7%),and 2 both metal enzymes and serine enzymes isolates(3.7%).Consistent with the detection results of multiple real-time quantita-tive PCR,the results of colloidal gold immunochromatography,showed that there were 50 NDM positive isolates(92.6%),2 KPC positive isolates(3.7%),1 NDM+KPC positive isolate(1.9%)and 1 NDM+OXA-48 positive isolate(1.9%).The consistency of colloidal gold immunochromatography and multiplex fluorescent quantitative PCR in rapid detection of carbapenemase types of CRE isolates was 100%.The accuracy of GICA for the deter-mination of the carbapenemase types of NDM,KPC and OXA-48 positive isolates was 100%.Conclusion GICA has the advantages of rapid,simple and high accuracy in rapid determination of carbapenemase in CRE,which has important application value in clinical precise treatment of CRE infection.
NETL
NSTL
万方数据
