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Medientyp:
E-Artikel
Titel:
Discrimination between hypervirulent and non-hypervirulent ribotypes of Clostridioides difficile by MALDI-TOF mass spectrometry and machine learning
Beteiligte:
Abdrabou, Ahmed Mohamed Mostafa;
Sy, Issa;
Bischoff, Markus;
Arroyo, Manuel J.;
Becker, Sören L.;
Mellmann, Alexander;
von Müller, Lutz;
Gärtner, Barbara;
Berger, Fabian K.
Erschienen:
Springer Science and Business Media LLC, 2023
Erschienen in:
European Journal of Clinical Microbiology & Infectious Diseases, 42 (2023) 11, Seite 1373-1381
Sprache:
Englisch
DOI:
10.1007/s10096-023-04665-y
ISSN:
0934-9723;
1435-4373
Entstehung:
Anmerkungen:
Beschreibung:
AbstractHypervirulent ribotypes (HVRTs) of Clostridioides difficile such as ribotype (RT) 027 are epidemiologically important. This study evaluated whether MALDI-TOF can distinguish between strains of HVRTs and non-HVRTs commonly found in Europe. Obtained spectra of clinical C. difficile isolates (training set, 157 isolates) covering epidemiologically relevant HVRTs and non-HVRTs found in Europe were used as an input for different machine learning (ML) models. Another 83 isolates were used as a validation set. Direct comparison of MALDI-TOF spectra obtained from HVRTs and non-HVRTs did not allow to discriminate between these two groups, while using these spectra with certain ML models could differentiate HVRTs from non-HVRTs with an accuracy >95% and allowed for a sub-clustering of three HVRT subgroups (RT027/RT176, RT023, RT045/078/126/127). MALDI-TOF combined with ML represents a reliable tool for rapid identification of major European HVRTs.