Multicenter Studies to Evaluate the Performance of MALDI-TOF MS for Fungal Identification

评估 MALDI-TOF MS 真菌鉴定性能的多中心研究

• 批准号: 10019272
• 负责人: Anna Lau
• 金额: --
• 依托单位: CLINICAL CENTER
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10019272
• 关键词: Antifungal Therapy; Bacteria; Characteristics; Clinical; Clinical Microbiology; Computer software; Consumption; Controlled Study; DNA sequencing; Data; Databases; Detection; Diagnosis; Diagnostic; Evaluation; Geographic Locations; Growth; Individual; International; Laboratories; MALDI-TOF Mass Spectrometry; Manufacturer Name; Methods; Microbiology; Molds; Multicenter Studies; Mycoses; Performance; Phenotype; Procedures; Proteins; Publications; Reproducibility; Technology; Time; United States National Institutes of Health; Update; Yeasts; frontier; fungus; improved; instrument; mass spectrometer; targeted treatment

Traditional identification of molds is challenging, cumbersome, and time-consuming, relying on non-specific phenotypic characteristics from culture or expensive and specialized DNA sequencing methods. MALDI-TOF MS has revolutionized clinical microbiology laboratories worldwide, enabling rapid identification of bacteria and yeast. This technology, however, has not been readily applied to mold identification due to technical challenges in developing an efficient protein extraction method and the limited availability of clinically comprehensive databases. Recently, we developed and optimized a simple protein extraction procedure for molds and constructed a highly stringent database comprising 410 individual isolates representing 90 genera and 220 species for the rapid identification of molds by MALDI-TOF MS. The NIH Mold Database is the most comprehensive database developed to date for mold identification and has filled a huge diagnostic gap in the field of clinical microbiology. The NIH Mold Database has now been shared with >100 clinical microbiology laboratories worldwide in an effort to improve the diagnosis of invasive fungal infections by providing faster identification (within 30 minutes of growth detection as opposed to weeks) that in turn can guide optimal antifungal therapy. During this fiscal year, we completed a ten-center national controlled study that evaluated the clinical performance and accuracy of two fungal databases (the NIH Mold Database and the Bruker Fungi Database) against 80 clinical mold isolates has come to a close. This study has highlighted important (previously undetermined) factors such as spectral acquisition settings required to improve and achieve successful/uniform implementation of MALDI-TOF MS for routine mold identification in clinical microbiology laboratories. In fact, in August 2019, the manufacturer of the mass spectrometer (Bruker Daltonics) released updated software with specific changes to acquisition parameters to improve mold identification. Data regarding poor inter-instrument reproducibility is supported by two recent publications from different groups. This phenomenon has not been demonstrated previously for large-scale bacterial and yeast studies, and results are surprising and warrant further evaluation. The results from this study have been accepted for publication in Frontiers Microbiology (in press, Sep 2019).

传统的霉菌鉴定是具有挑战性的，繁琐的，耗时的，依赖于非特异性表型特征的培养或昂贵的和专门的DNA测序方法。MALDI-TOF MS已经彻底改变了全球的临床微生物实验室，使细菌和酵母的快速鉴定成为可能。然而，由于在开发有效的蛋白质提取方法和临床综合数据库的有限可用性方面的技术挑战，该技术尚未轻易应用于霉菌鉴定。