Development and Application of Rapid Clinical Visualization Molecular Diagnostic Technology for Cryptococcus neoformans/C. gattii Based on Recombinase Polymerase Amplification Combined With a Lateral Flow Strip

基于重组酶聚合酶扩增结合侧向层析试纸的新型隐球菌/格特隐球菌快速临床可视化分子诊断技术的开发与应用

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Abstract

Cryptococcus neoformans (C. neoformans)/C. gattii can easily invade the human central nervous system and cause cryptococcal meningitis (CM). The clinical fatality rate of these fungi is extremely high and causes more than 180,000 deaths worldwide every year. At present, the common clinical identification methods of these fungi are traditional culture methods and Indian ink staining. In addition, enzyme-linked immunosorbent assay (ELISAs), polymerase chain reaction (PCR), real-time quantitative PCR detecting system (qPCR), mass spectrometry, and metagenomic next-generation sequencing (mNGS) have also been applied to detect these fungus. Due to the rapid progress of meningitis caused by C. neoformans/C. gattii infection, there is a desperate need for fast, sensitive, and on-site detection methods to meet the clinical diagnosis. Recombinase polymerase amplification (RPA) is a promising isothermal amplification technique that can compensate for the shortcomings of the above techniques, featuring short reaction time, high specificity, and high sensitivity, thus meeting the demand for in-field detection of C.neoformans/C. gattii. In our study, RPA- lateral flow strip (LFS) was used to amplify the capsule-associated gene, CAP64, of C. neoformans/C. gattii, and the primer-probe design was optimized by introducing base mismatches to obtain a specific and sensitive primer-probe combination for clinical testing, and specificity of the detection system was determined for 26 common clinical pathogens. This system was developed to obtain results in 20 min at an isothermal temperature of 37°C with a lower limit of detection as low as 10 CFU/μL or 1 fg/μL. A total of 487 clinical samples collected from multicenter multiplexes were tested to evaluate the detection performance of the RPA-LFS system, which revealed that the system could specifically detect C. neoformans/C. gattii, meeting the need for rapid, specific, and sensitive detection.

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