MALDI-TOF MS Using a Custom-Made Database, Biomarker Assignment, or Mathematical Classifiers Does Not Differentiate Shigella spp. and Escherichia coli

Abstract

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 and evaluated using spectra of 456 Shigella spp., 42 E. coli, and 61 EIEC isolates. 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 the distinction of S. dysenteriae, S. boydii, and E. coli was poor. With biomarker assignment, 98% S. sonnei isolates were correctly identified, although specificity was low. Discriminating markers for S. dysenteriae, S. boydii, and E. coli were not assigned at all. Classification models using machine learning correctly identified Shigella in 96% of isolates, but most E. coli isolates were also assigned to Shigella. None of the proposed alternative approaches were suitable for clinical diagnostics for identifying Shigella spp., E. coli, and EIEC, reflecting their relatedness and 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.

Keywords: EIEC; Escherichia coli; MALDI-TOF MS; Shigella spp.; biomarker assignment; custom-made database; machine-learning classifiers.

Figure 1

The classes in the different discrimination levels to which isolates were assigned.

Figure 2

Dendrogram of MSPs of training isolates. Blue = cluster 1; green = cluster 2; red = cluster 3. Yellow/blue vertical band = manual cluster distinction at distance level 50–100 relative units with species designation using the culture-based identification algorithm.

Figure 3

Number of different species in the first 10 matches per spot with the direct smear method. Identity (x-axis) was assigned using the culture-based identification algorithm. Black horizontal bars represent the median number of species; the 25–75% interquartile ranges are indicated by the blue vertical bars, and 5–95% intervals by the black vertical lines. Outliers are indicated with blue dots.

Figure 4

PCA of isolates in the training set. (a) Colored at genus level: beige = Shigella, teal = Escherichia; (b) Colored at pathotype level: black = Shigella/EIEC, green = E. coli (other than EIEC); (c) Colored at group level: orange = Shigella spp., yellow = EIEC, purple = E. coli (other than EIEC); (d) Colored at species level: light blue = S. dysenteriae, red = S. flexneri, green = S. boydii, pink = S. sonnei, blue = EIEC, light grey = Other E. coli.