ArticleJournal of clinical microbiology2013
Novel approach for differentiating Shigella species and Escherichia coli by matrix-assisted laser desorption ionization-time of flight mass spectrometry.
Article in Journal of clinical microbiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
52 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of machine learning on clinical MALDI-TOF MS.Briefings in bioinformatics · 2026Pooled it
- An ode to the 16S rRNA gene: its history, importance, caveats and future in microbiome research.Microbial genomics · 2026Review
- Phenotypic and genotypic relationships between Shigella species and Escherichia coli O37:H10 isolates in Addis Ababa, Ethiopia.BMC research notes · 2025Article
- Leveraging innovative diagnostics as a tool to contain superbugs.Antonie van Leeuwenhoek · 2025Review
- Effect of feeding a gestation diet to sows for 5 days post-farrowing and feeding a liquid mixture of milk replacer and starter diet to suckling piglets on growth, selected health parameters and faecal microbiota of suckling pigs on two research farms.Translational animal science · 2025Article
- Differentiation ofPathogens (Basel, Switzerland) · 2024Article
- Molecular identification and antimicrobial resistance patterns of enterobacterales in community urinary tract infections among indigenous women in Ecuador: addressing microbiological misidentification.BMC infectious diseases · 2024Article
- Distinguishing methicillin-resistant Staphylococcus aureus from methicillin-sensitive strains by combining FeMikrochimica acta · 2024Article
- Comparison of automatic methods MALDI-TOF, VITEK2 and manual methods for the identification of intestinal microbial communities on the example of samples from alpacas (Journal of veterinary research · 2023Article
- Using Protein Fingerprinting for Identifying and Discriminating Methicillin ResistantDiagnostics (Basel, Switzerland) · 2023Article
- Escherichia Coli: What Is and Which Are?Molecular biology and evolution · 2023Article
- Article
- How MALDI-TOF Mass Spectrometry Technology Contributes to Microbial Infection Control in Healthcare Settings.Vaccines · 2022Review
- Discrimination of Escherichia coli, Shigella flexneri, and Shigella sonnei using lipid profiling by MALDI-TOF mass spectrometry paired with machine learning.MicrobiologyOpen · 2022Article
- MALDI-TOF MS Using a Custom-Made Database, Biomarker Assignment, or Mathematical Classifiers Does Not DifferentiateMicroorganisms · 2022Article
- Shigella Outer Membrane Vesicles as Promising Targets for Vaccination.International journal of molecular sciences · 2022Review
- Microbial Identification in the Clinical Microbiology Laboratory Using MALDI-TOF-MS.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Relationship Between Antibiotic Resistance, Biofilm Formation, and Biofilm-Specific Resistance inInfection and drug resistance · 2022Article
- Pseudotargeted Metabolomic Fingerprinting and Deep Learning for Identification and Visualization of Common Pathogens.Frontiers in microbiology · 2022Article
- Historical, current, and emerging tools for identification and serotyping of Shigella.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2021Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Shigella species are so closely related to Escherichia coli that routine matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) cannot reliably differentiate them. Biochemical and serological methods are typically used to distinguish these species; however, "inactive" isolates of E. coli are biochemically very similar to Shigella species and thus pose a greater diagnostic challenge. We used ClinProTools (Bruker Daltonics) software to discover MALDI-TOF MS biomarker peaks and to generate classification models based on the genetic algorithm to differentiate between Shigella species and E. coli. Sixty-six Shigella spp. and 72 E. coli isolates were used to generate and test classification models, and the optimal models contained 15 biomarker peaks for genus-level classification and 12 peaks for species-level classification. We were able to identify 90% of E. coli and Shigella clinical isolates correctly to the species level. Only 3% of tested isolates were misidentified. This novel MALDI-TOF MS approach allows laboratories to streamline the identification of E. coli and Shigella species.
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