Evaluation of MALDI-TOF MS, sequencing of D2 LSU rRNA and internal transcribed spacer regions (ITS) for the identification of filamentous fungi isolated from a pharmaceutical facility.

The identification of filamentous fungi through culture characterization may be hampered by phenotypic variability. Information obtained from the identification of microorganisms are important for investigation of sources of contamination of a product or process. The aim of this study was to identify filamentous fungal strains (n = 50) isolated from a pharmaceutical facility by using Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS), as well as D2 domain of the large-subunit (LSU) ribosomal RNA gene and internal transcribed spacer regions (ITS) sequencing. MALDI-TOF MS system only identified five strains at the species level, while 45 were not identified. The analysis through GenBank allowed the identification of up to 19 strains at the species level, while MycoBank allowed the identification of up to nine strains at the species level. The databases identified up to 11 genera: Penicillium, Aspergillus, Cladosporium, Chaetomium, Coniochaeta, Curvularia, Diaporthe, Fusarium, Trichoderma, Rhizopus and Microdochium. MALDI-TOF MS showed an insufficient database to identify the species of fungi. DNA sequencing was the best methodology to identify to the genus level but was unable to differentiate between closely related species. Therefore further methods for the identification of filamentous fungi from pharmaceutical areas at species level need to be developed.

MALDI-TOF MS database expansion for identification of Bacillus and related genera isolated from a pharmaceutical facility.

Bacillus and related genera are among the main bacterial groups isolated from pharmaceutical production areas. The identification of Bacillus species and related genera by classical methods is particularly difficult, due to similarities between closely related species. The Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) is one of the most promising techniques for chemotaxonomic characterization of microorganisms, being an alternative to genotypic methods. This study aimed to identify Bacillus strains and related genera isolated from immunobiological production areas by phylogenetic analysis of housekeeping genes and expand the database associated with MALDI-TOF MS to improve their identification. In a previous study, 97 aerobic endospore-forming bacteria isolated from a pharmaceutical facility were analyzed by MALDI-TOF MS and 16S rRNA gene full-length sequencing. All strains were identified as Bacillus and related genera by the latest methodology. Among the 97 strains, 22 were unidentified and 2 strains were misidentified by MALDI-TOF MS. In the present study, these 24 strains were subjected to 16S rRNA gene phylogenetic analysis. Strains not identified at species level by this methodology were submitted to rpoB gene phylogenetic analysis. After identifying the strains, 19 of the 24 strains were incubated for 24, 48, and 72 h on Tryptic Soy Agar and Sheep Blood Agar and subjected to analysis by MALDI-TOF MS. A SuperSpectrum for each strain was created and entered into the equipment database. Finally, the 24 strains were again submitted to proteomic analysis by MALDI-TOF MS, and, at this time, all were correctly identified. The genotypic identification of in-house isolated strains and the introduction of these spectra in MALDI-TOF MS, in order to obtain a customized database, proved to be an extremely effective tool in the identification of Bacillus and related genera from pharmaceutical industry origin.

Assessment of VITEK® 2, MALDI-TOF MS and full gene 16S rRNA sequencing for aerobic endospore-forming bacteria isolated from a pharmaceutical facility.

VITEK®2, MALDI-TOF MS and 16S rRNA sequencing were evaluated for the identification of aerobic endospore-forming bacteria (AEB) from a pharmaceutical facility. MALDI-TOF MS demonstrated higher accuracy compared to VITEK®2, although both databases were insufficient to identify AEB species. Sequencing was the best methodology, but unable to identify closely related species.