PurposeShigella 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 for identification and distinction of Shigella spp., E. coli and its pathotype EIEC were explored.MethodsA 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.ResultsIdentification 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 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.ConclusionNone of the proposed alternative approaches is suitable for use in clinical diagnostics for the identification of Shigella spp., E. coli and EIEC because of their poor distinctive properties. We suggest the use of MALDI-TOF MS for identification of the Shigella spp./E. coli complex, but other tests should be used for distinction.