Discrimination between hypervirulent and non-hypervirulent ribotypes of Clostridioides difficile by MALDI-TOF mass spectrometry and machine learning
Ahmed Mohamed Mostafa Abdrabou, Issa Sy, Markus Bischoff, Manuel J. Arroyo, Sören L. Becker, Alexander Mellmann, Lutz von Müller, Barbara C. Gärtner, Fabian K. Berger
Abstract
Hypervirulent 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.