Application of a microfluidic chip platform in rapid diagnosis of post-neurosurgical bacterial infection
10.13602/j.cnki.jcls.2019.04.02
- VernacularTitle:微流控芯片技术在神经外科术后细菌感染快速诊断中的应用
- Author:
Guanghui ZHENG
1
;
Ruimin MA
1
;
Fangqiang LI
1
;
Yan ZHANG
2
;
Mingzhong TANG
1
;
Yan ZHANG
1
;
Hong LYU
1
;
Guojun ZHANG
1
Author Information
1. Department of Clinical Laboratory, Beijing Tiantan Hospital Affiliated to Capital Medical University, Beijing Engineering Research Center of Immunological Reagents Clinical Research
2. China National Engineering Research Center for Beijing Biochip Technology
- Publication Type:Journal Article
- Keywords:
microfluidic chip;
post-neurosurgical bacterial infection;
drug resistance gene
- From:
Chinese Journal of Clinical Laboratory Science
2019;37(4):246-250
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To establish and evaluate a microfluidic chip platform for the rapid diagnosis of post-neurosurgical bacterial infection.
Methods:The pathogens isolated from patients with post-neurosurgical bacterial infection in Beijing Tiantan Hospital Affiliated to Capital Medical University during 2007 and 2016 and the epidemiological data from China drug resistance monitoring network CHINET were analyzed retrospectively. Based on the retrospective data and the molecular epidemiological information of drug-resistant bacteria reported in the literature, target pathogens and drug resistance gene parameters were selected. The microbial identification parameters from 10 different bacteria, including Klebsiella pneumoniae, Acinetobacter baumannii, Staphylococcus epidermidis, Enterobacter cloacae, Staphylococcus aureus, Escherichia coli, Enterococcus faecium, Enterococcus faecalis, Stenotrophomonas maltophilia and Pseudomonas aeruginosa, and the parameters of 15 drug resistance genes, including mecA, vanA, vanB, aacC1, aadA1, bla CTX-M-1 , bla CTX-M-9 , bla GES-1 , bla OXA-23 , bla OXA-24 , bla OXA-58 , bla OXA-66 , bla KPC-2 , bla IMP-4 and bla VIM-2 , were selected for designing a microfluidic chip platform. Using MAIDI-TOF MS for bacterial identification, multiplex PCR for the detection of drug resistance genes, micro-broth dilution method for the detection of drug resistance phenotypes and ESBLs screening test as reference methods, 13 known bacteria were used to evaluate the preliminary performance of the established microfluidic chip platform, and 108 cerebrospinal fluid bacterial culture positive specimens were used to evaluate the clinical application value of the microfluidic chip platform.
Results:The identification rates of 13 known strains and the coincidence rate of drug resistance genes were 100%. The coincidence rate of identification results for 108 cerebrospinal fluid bacterial culture positive specimens between the microfluidic chip platform and the MALDI-TOF MS method was as high as 94.44%. The coincidence rates of drug resistance phenotype of carbapenems, oxacillin, vancomycin, ESBLs and genotype between the microfluidic chip platform and the micro-broth dilution method or ESBLs screening test were above 90%.
Conclusion:The established microfluidic chip platform is fast and accurate, and has application value in microbial identification and the prediction of drug resistance, which may be used as an important supplementary method in the diagnosis of post-neurosurgical bacterial infection.
