Evaluation of a micro/nanofluidic chip platform for the high-throughput detection of bacteria and their antibiotic resistance genes in post-neurosurgical meningitis

Abstract

Background: Post-neurosurgical meningitis (PNM) is one of the most severe hospital-acquired infections worldwide, and a large number of pathogens, especially those possessing multi-resistance genes, are related to these infections. Existing methods for detecting bacteria and measuring their response to antibiotics lack sensitivity and stability, and laboratory-based detection methods are inconvenient, requiring at least 24 h to complete. Rapid identification of bacteria and the determination of their susceptibility to antibiotics are urgently needed, in order to combat the emergence of multi-resistant bacterial strains. Methods: This study evaluated a novel, fast, and easy-to-use micro/nanofluidic chip platform (MNCP), which overcomes the difficulties of diagnosing bacterial infections in neurosurgery. This platform can identify 10 genus or species targets and 13 genetic resistance determinants within 1 h, and it is very simple to operate.A total of 108 bacterium-containing cerebrospinal fluid (CSF) cultures were tested using the MNCP for the identification of bacteria and determinants of genetic resistance. The results were compared to those obtained with conventional identification and antimicrobial susceptibility testing methods. Results: For the 108 CSF cultures, the concordance rate between the MNCP and the conventional identification method was 94.44%; six species attained 100% consistency. For the production of carbapenemase- and extended-spectrum beta-lactamase (ESBL)-related antibiotic resistance genes, both the sensitivity and specificity of the MNCP tests were high (>90.0%) and could fully meet the requirements of clinical diagnosis. Conclusions: The MNCP is fast, accurate, and easy to use, and has great clinical potential in the treatment of post-neurosurgical meningitis. Keywords: MNCP, PNM, Identification, Drug resistance gene