Matrix-Assisted Laser Desorption-Ionization Time-of-Flight mass spectrometry using a custom-made database, biomarker assignment, or mathematical classifiers does not differentiate Shigella spp. and Escherichia coli

Purpose Shigella spp . and E. coli are closely related and cannot be distinguished using Matrix-Assisted Laser Desorption-Ionization Time-of-Flight mass spectrometry (MALDI-TOF MS) with commercially available databases. Here, three alternative approaches using MALDI-TOF MS to identify and distinguish Shigella spp ., E. coli , and its pathotype EIEC were explored. Methods A custom-made database was developed, biomarkers were assigned, and classification models using machine learning were designed and evaluated using spectra of 456 Shigella spp ., 42 E. coli , and 61 EIEC isolates, obtained by the direct smear method and the ethanol-formic acid extraction method. The isolates were identified using ipaH PCR and phenotypic and serological typing. Results Identification with a custom-made database resulted in >94% Shigella identified at the genus level and >91% S. sonnei and S. flexneri at the species level, but distinction of S. dysenteriae, S. boydii , and E. coli was poor. Moreover, 10-15% of duplicates rendered discrepant results. With biomarker assignment, 98% S. sonnei isolates were correctly identified, although the S. sonnei biomarkers were not specific as other species, for instance S. boydii and E. coli were also identified as S. sonnei . Discriminating markers for S. dysenteriae, S. boydii , and E. coli were not assigned at all. Classifiers identified Shigella in 96% of isolates correctly, but most E. coli isolates were also assigned to Shigella . Conclusion None of the proposed alternative approaches is suitable for use in clinical diagnostics for the identification of Shigella spp ., E. coli , and EIEC, reflecting their relatedness and problematic taxonomical classification. We suggest the use of MALDI-TOF MS for the identification of the Shigella spp ./ E. coli complex, but other tests should be used for distinction.