Performance of the MSI-2 Database for Fungal Identification by Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry from Cleanroom Environments

MSI-2数据库在洁净室环境下利用基质辅助激光解吸电离飞行时间质谱法进行真菌鉴定的性能

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Abstract

Accurate mold identification by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is dependent on robust organism representation in available databases. The Mass Spectrometry Identification (MSI) platform has proven successful for mold identification in clinical and veterinary settings but has yet to be studied with a large set of environmental isolates. Here, we performed a retrospective study using spectra collected by the Bruker MALDI Biotyper (MBT) v4.1 microflex LT instrument to evaluate the MSI-2 database alongside the combined use of the Bruker MBT (including the MBT Filamentous Fungi Library) and the National Institutes of Health (NIH) mold database (MBT/NIH databases). Analysis was performed for 462 environmental fungal isolates (representing 73 different fungi) cultured from the hospital pharmacy and cellular therapy suites as part of the current good manufacturing practices (cGMP) environmental monitoring program at the NIH. When used alone, MSI-2 identified 237 spectra (51.3%) at its higher score threshold (index A), while the MBT/NIH databases identified only 183 spectra (39.6%; P < 0.001) at the equivalent threshold of ≥2.0. The combination of all three databases at the respective high thresholds improved identification sensitivity to 327 spectra (70.8%). The combination of MSI-2 with the MBT/NIH databases at a lowered threshold (index B or ≥1.7, respectively) identified 400/462 environmental spectra (86.6%). Our results show that the MSI-2 database, in combination with existing databases, may be useful for environmental surveillance, particularly by clinical or industry laboratories involved in cGMP or current good tissue practices (cGTP) applications, such as cellular therapy manufacturing facilities and sterile compounding pharmacies.

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