Identification of Fusobacterium Species Using Matrix-Assisted Laser Desorption/Ionization-Timeof- Flight Mass Spectrometry by Updating ASTA CoreDB
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Purpose: Fusobacterium species can cause infections, and associations with cancer are being increasingly reported. As their clinical significance differs, accurate identification of individual species is important. However, matrix-assisted laser desorption/ion-ization-time of flight mass spectrometry has not been found to be effective in identifying Fusobacterium species in previous studies. In this study, we aimed to improve the accuracy and efficacy of identifying Fusobacterium species in clinical laboratories. Materials and Methods: In total, 229 Fusobacterium isolates were included in this study. All isolates were identified at the species level based on nucleotide sequences of the 16S ribosomal RNA gene and/or DNA-dependent RNA polymerase β-subunit gene (rpoB). Where necessary, isolates were identified based on whole genome sequences. Among them, 47 isolates were used for updating the ASTA database, and 182 isolates were used for the validation of Fusobacterium spp. identification. Results: Fusobacterium isolates used for validation (182/182) were correctly identified at the genus level, and most (180/182) were correctly identified at the species level using the ASTA MicroIDSys system. Most of the F. nucleatum isolates (74/75) were correctly identified at the subspecies level. Conclusion: The updated ASTA MicroIDSys system can identify nine species of Fusobacterium and four subspecies of F. nucleatum in good agreement. This tool can be routinely used in clinical microbiology laboratories to identify Fusobacterium species and serve as a springboard for future research.
Abstract
Purpose: Fusobacterium species can cause infections, and associations with cancer are being increasingly reported. As their clinical significance differs, accurate identification of individual species is important. However, matrix-assisted laser desorption/ion-ization-time of flight mass spectrometry has not been found to be effective in identifying Fusobacterium species in previous studies. In this study, we aimed to improve the accuracy and efficacy of identifying Fusobacterium species in clinical laboratories. Materials and Methods: In total, 229 Fusobacterium isolates were included in this study. All isolates were identified at the species level based on nucleotide sequences of the 16S ribosomal RNA gene and/or DNA-dependent RNA polymerase β-subunit gene (rpoB). Where necessary, isolates were identified based on whole genome sequences. Among them, 47 isolates were used for updating the ASTA database, and 182 isolates were used for the validation of Fusobacterium spp. identification. Results: Fusobacterium isolates used for validation (182/182) were correctly identified at the genus level, and most (180/182) were correctly identified at the species level using the ASTA MicroIDSys system. Most of the F. nucleatum isolates (74/75) were correctly identified at the subspecies level. Conclusion: The updated ASTA MicroIDSys system can identify nine species of Fusobacterium and four subspecies of F. nucleatum in good agreement. This tool can be routinely used in clinical microbiology laboratories to identify Fusobacterium species and serve as a springboard for future research.
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