Article ; Online: Novel approach for differentiating Shigella species and Escherichia coli by matrix-assisted laser desorption ionization-time of flight mass spectrometry.
Journal of clinical microbiology
2013 Volume 51, Issue 11, Page(s) 3711–3716
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 ... ...
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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MeSH term(s) | Bacteriological Techniques/methods ; Biomarkers/analysis ; Escherichia coli/chemistry ; Escherichia coli/classification ; Humans ; Shigella/chemistry ; Shigella/classification ; Software ; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization/methods |
Chemical Substances | Biomarkers |
Language | English |
Publishing date | 2013-08-28 |
Publishing country | United States |
Document type | Evaluation Study ; Journal Article |
ZDB-ID | 390499-4 |
ISSN | 1098-660X ; 0095-1137 |
ISSN (online) | 1098-660X |
ISSN | 0095-1137 |
DOI | 10.1128/JCM.01526-13 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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