Shunsuke Segawa: Department of Molecular Diagnosis, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo Ward, Chiba City, Chiba Prefecture Japan ; Division of Laboratory Medicine and Clinical Genetics, Chiba University Hospital, 1-8-1 Inohana, Chuo Ward, Chiba City, Chiba Prefecture Japan.
Motoi Nishimura: Department of Molecular Diagnosis, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo Ward, Chiba City, Chiba Prefecture Japan ; Division of Laboratory Medicine and Clinical Genetics, Chiba University Hospital, 1-8-1 Inohana, Chuo Ward, Chiba City, Chiba Prefecture Japan ; Clinical Proteomics Research Center, Chiba University Hospital, 1-8-1 Inohana, Chuo Ward, Chiba City, Chiba Prefecture Japan.
Kazuyuki Sogawa: Clinical Proteomics Research Center, Chiba University Hospital, 1-8-1 Inohana, Chuo Ward, Chiba City, Chiba Prefecture Japan ; Department of Food Biochemistry, School of Life and Environmental Science, Azabu University, 1-17-71 Fuchinobe, Chuo Ward, Sagamihara City, Kanagawa Prefecture Japan.
Sachio Tsuchida: Department of Molecular Diagnosis, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo Ward, Chiba City, Chiba Prefecture Japan ; Division of Laboratory Medicine and Clinical Genetics, Chiba University Hospital, 1-8-1 Inohana, Chuo Ward, Chiba City, Chiba Prefecture Japan ; Clinical Proteomics Research Center, Chiba University Hospital, 1-8-1 Inohana, Chuo Ward, Chiba City, Chiba Prefecture Japan.
Shota Murata: Division of Laboratory Medicine and Clinical Genetics, Chiba University Hospital, 1-8-1 Inohana, Chuo Ward, Chiba City, Chiba Prefecture Japan.
Masaharu Watanabe: Division of Laboratory Medicine and Clinical Genetics, Chiba University Hospital, 1-8-1 Inohana, Chuo Ward, Chiba City, Chiba Prefecture Japan.
Kazuyuki Matsushita: Department of Molecular Diagnosis, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo Ward, Chiba City, Chiba Prefecture Japan.
Katsuhiko Kamei: Medical Mycology Research Center, Chiba University, 1-8-1 Inohana, Chuo Ward, Chiba City, Chiba Prefecture Japan.
Fumio Nomura: Department of Molecular Diagnosis, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo Ward, Chiba City, Chiba Prefecture Japan ; Division of Laboratory Medicine and Clinical Genetics, Chiba University Hospital, 1-8-1 Inohana, Chuo Ward, Chiba City, Chiba Prefecture Japan ; Clinical Proteomics Research Center, Chiba University Hospital, 1-8-1 Inohana, Chuo Ward, Chiba City, Chiba Prefecture Japan.
BACKGROUND: The MALDI (matrix-assisted laser desorption/ionization) Biotyper system for bacterial identification has already been utilized in clinical microbiology laboratories as a successful clinical application of protoemics. However, in cases of Nocardia, mass spectra suitable for MALDI Biotyper identification are often not obtained if such specimens are processed like general bacteria. This problem is related to the insufficiencies in bacterial spectrum databases that preclude accurate specimen identification. Here, we developed a bacterial processing method to improve mass spectra from specimens of the genus Nocardia. In addition, with the new processing method, we constructed a novel in-house bacterial database that combines a commercial database and mass spectra of Nocardia strains from the Department of Clinical Laboratory at Chiba University Hospital (DCLC) and the Medical Mycology Research Center at Chiba University (MMRC). RESULTS: The newly developed method (Nocardia Extraction Method at DCLC [NECLC]) based on ethanol-formic acid extraction (EFAE) improved mass spectra obtained from Nocardia specimens. The Nocardia in-house database at Chiba University Hospital (NDCUH) was then successfully validated. In brief, prior to introduction of the NECLC and NDCUH, 10 of 64 (15.6%) clinical isolates were identified at the species level and 16 isolates (25.0%) could only be identified at the genus level. In contrast, after the introduction, 58 isolates (90.6%) were identified at the species level and 6 isolates (9.4%) were identified at the genus level. CONCLUSIONS: The results of this study suggest that MALDI-TOF (time-of-flight) Biotyper system can identify Nocardia accurately in a short time in combination with a simple processing method and an in-house database.
