2023
DOI: 10.1016/j.diagmicrobio.2023.116045
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Improved identification of Streptococcus bovis-Streptococcus equinus-complex species and subspecies by MALDI-TOF MS using a novel library

Jonas Öberg,
Malin Inghammar,
Bo Nilson
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“…Matrix-Assisted Laser Desorption/Ionization Time-of Flight Mass Spectrometry (MALDI-TOF MS) has been widely applied for the fast and accurate clinical identification of microbial species in recent years. MALDI-TOF MS could identify different subspecies ( Wang et al, 2022 ; Liu et al, 2023 ; Oberg et al, 2023 ), like automated, fast and accurate prediction of methicillin-resistant Staphylococcus aureus (MRSA) clonal complexes (CCs) ( Camoez et al, 2016 ) and GBS subspecies-level typing based on the mass variation of ribosomal subunit proteins (rsp profile) ( Rothen et al, 2019 ). The previous reported GBS subtyping strategies based on MALDI-TOF MS all require manual assessment of the acquired spectra and highly trained personnel with professional tools like ClinProTool software or online GBS serotyper, including peak biomarkers of different GBS sequence types (STs) and serotypes ( Lartigue et al, 2011 ; Lanotte et al, 2013 ; Lin et al, 2019 ), the statistical models generated based on MALDI-TOF MS spectrometry for the rapid classification of major GBS serotypes (Ia, Ib, III, V, VI) ( Wang et al, 2019 ) and STs (ST10, ST12, ST17, ST19) ( Huang et al, 2020 ), or the facile machine learning GBS CCs multi-classification model generated through XGBoost algorithm based on the antibiotic susceptibility, serotypes and virulence genes of GBS strains ( Liu et al, 2022 ), making them not suitable for routine clinical application.…”
Section: Introductionmentioning
confidence: 99%
“…Matrix-Assisted Laser Desorption/Ionization Time-of Flight Mass Spectrometry (MALDI-TOF MS) has been widely applied for the fast and accurate clinical identification of microbial species in recent years. MALDI-TOF MS could identify different subspecies ( Wang et al, 2022 ; Liu et al, 2023 ; Oberg et al, 2023 ), like automated, fast and accurate prediction of methicillin-resistant Staphylococcus aureus (MRSA) clonal complexes (CCs) ( Camoez et al, 2016 ) and GBS subspecies-level typing based on the mass variation of ribosomal subunit proteins (rsp profile) ( Rothen et al, 2019 ). The previous reported GBS subtyping strategies based on MALDI-TOF MS all require manual assessment of the acquired spectra and highly trained personnel with professional tools like ClinProTool software or online GBS serotyper, including peak biomarkers of different GBS sequence types (STs) and serotypes ( Lartigue et al, 2011 ; Lanotte et al, 2013 ; Lin et al, 2019 ), the statistical models generated based on MALDI-TOF MS spectrometry for the rapid classification of major GBS serotypes (Ia, Ib, III, V, VI) ( Wang et al, 2019 ) and STs (ST10, ST12, ST17, ST19) ( Huang et al, 2020 ), or the facile machine learning GBS CCs multi-classification model generated through XGBoost algorithm based on the antibiotic susceptibility, serotypes and virulence genes of GBS strains ( Liu et al, 2022 ), making them not suitable for routine clinical application.…”
Section: Introductionmentioning
confidence: 99%