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: 9354084
• 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/9354084
• 关键词: Accounting; Antifungal Therapy; Bacteria; Characteristics; Clinical; Clinical Microbiology; Conditioned Culture Media; Controlled Study; DNA Sequence; Databases; Detection; Diagnosis; Diagnostic; Goals; Growth; Individual; Institution; International; Laboratories; Liquid substance; MALDI-TOF Mass Spectrometry; Methods; Molds; Multicenter Studies; Mycoses; Performance; Procedures; Proteins; Solid; Technical Expertise; Technology; Time; United States National Institutes of Health; Yeasts; fungus; improved; 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, an eight-center national controlled study was undertaken to evaluate the clinical performance and accuracy of two fungal databases (the NIH Mold Database and the Bruker Fungi Database) against 80 clinical mold isolates. In addition, a collaborative project was undertaken with another US institution to investigate the effects of different culture conditions (media, time of incubation, solid vs. liquid media) against both fungal databases. Both studies are ongoing and it is envisaged that the findings will highlight important (previously undetermined) factors required for the uniform implementation of MALDI-TOF MS for the routine mold identification in clinical microbiology laboratories worldwide. This in turn will enable faster diagnosis and targeted therapeutic strategies for invasive fungal infections.

霉菌的传统识别是具有挑战性，繁琐且耗时的，依赖于培养或昂贵且专业的DNA测序方法的非特异性表型特征。 MALDI-TOF MS已彻底改变了全球临床微生物学实验室，从而可以快速鉴定细菌和酵母。但是，由于开发有效的蛋白质提取方法和临床全面数据库的有限可用性，这项技术并不容易应用于霉菌识别。 最近，我们为霉菌开发并优化了一个简单的蛋白质提取程序，并构建了一个高度严格的数据库，该数据库包括410个单独的分离株，代表90属和220种，用于通过MALDI-TOF MS快速识别模具。 NIH模具数据库是迄今为止开发的最全面的数据库，用于模具识别，并填补了临床微生物学领域的巨大诊断差距。 NIH模具数据库现已与全球范围内的> 100个临床微生物学实验室共享，以通过提供更快的鉴定（在生长检测后的30分钟内，而不是几周）来改善侵入性真菌感染的诊断，这反过来又可以指导最佳抗真菌治疗。 在这个财政年度，进行了一项八个中心的国家对照研究，以评估两个真菌数据库（NIH模具数据库和Bruker真菌数据库）的临床性能和准确性。此外，与另一家美国机构进行了一个协作项目，以调查不同文化条件（媒体，孵化时间，固体与液体媒体）对两个真菌数据库的影响。这两项研究都在进行中，并且可以预见，这些发现将突出统一实施MALDI-TOF MS所需的重要因素（以前尚不确定），用于全球临床微生物学实验室中常规霉菌识别。反过来，这将使诊断和针对性的侵入性真菌感染有针对性的治疗策略。