项目名称: 基于微流控LAMP技术的血液中假丝酵母菌和曲霉菌同步快速检测
项目编号: No.81472032
项目类型: 面上项目
立项/批准年度: 2015
项目学科: 医药、卫生
项目作者: 吴文娟
作者单位: 同济大学
项目金额: 65万元
中文摘要: 侵袭性真菌感染的准确、早期诊断是治疗疾病和抢救生命的关键。作为重要的侵袭性真菌感染病原体,血液中假丝酵母和曲霉菌的同步快速检测具有非常重要的意义。然而, 目前真菌的诊断技术远不能满足临床需求。本研究拟在已完成的国家十一五重大专项课题建立的病原细菌微流体芯片技术基础上,以血流感染常见的5种假丝酵母菌和3种曲霉菌为研究对象,采用微流控LAMP技术,以真菌ITS、rDNA、IGS基因保守区为靶标筛选菌种特异性LAMP引物, 结合芯片病原微生物富集技术和多通道芯片同步检测技术,实现快速直接检测血液中假丝酵母菌和曲霉菌的种特异性分析,进而以LAMP微流控芯片为核心设计制作进样、分析、报告一体化检测系统,发展真菌血症的快速诊断新技术,为建立有效的侵袭性真菌感染早期预警、早期诊断与治疗监测技术平台奠定基础。
中文关键词: 微流控芯片;环介导等温扩增;假丝酵母菌;曲霉菌;快速检测
英文摘要: Invasive fungal infections are associated with high morbidity and mortality in critically ill patients due, in part, to diagnostic difficulties in the early stages. Up to now, there is no optimal assay to detect invasive fungi such as candida and aspergillus simultaneously in blood. New techniques are required for invasive mycoses earlier diagnosis, prognostic information and monitoring outcome. Based on the microfluidic chip for mycobacteria identification which developed in our completed national mega research project, in this study, we focus on the target molecules including C.albicans , C. glabrata,C. krusei,C. tropicalis,C. parapsilosisand A. fumigatus,A. flavus,A. niger. LAMP primers that bind to specific target molecules with high specificity and affinity selected based on ITS, rDNA, IGS fungi conserved DNA fragments. Combined with pathogenic microorganism enrichment microfluidic chip and multi-channel detect microfluidic chip to rapid detect different target pathogens in blood at one assay.And taking LAMP microfluidic chip as the core, develop the automated microfluidic systems integration of sample priming, analysis, report, for a new rapid diagnostic technology of fungemia. The LAMP-based compact microfluidic system for diagnosis may even lead to a point-of-care device. The use of LAMP-Microfluidic systems screening and diagnosis invasive fungal infection is expected to continue growing in the near future and may make a substantial impact on biomedical applications.
英文关键词: microfluidic chip;LAMP;Candida;Aspergillus;rapid detection