A novel biochemistry approach combined with MALDI-TOF MS to discriminate Escherichia coli and Shigella species.


Journal

Analytica chimica acta
ISSN: 1873-4324
Titre abrégé: Anal Chim Acta
Pays: Netherlands
ID NLM: 0370534

Informations de publication

Date de publication:
15 Dec 2023
Historique:
received: 14 07 2023
revised: 04 10 2023
accepted: 26 10 2023
medline: 27 11 2023
pubmed: 24 11 2023
entrez: 23 11 2023
Statut: ppublish

Résumé

Escherichia coli and Shigella spp. are closely related, making it crucial to accurately identify them for disease control and prevention. In this study, we utilized MALDI-TOF MS to identify characteristic peaks of decarboxylation products of lysine and ornithine to distinguish between E. coli and Shigella spp. Our findings indicate that the peak at m/z 103.12 ± 0.1 of the product cadaverine from lysine decarboxylase is unique to E. coli, while all Shigella species lack the m/z 103.12 ± 0.1 peak. However, S. sonnei and S. boydii serotype C13 exhibit a specific peak at m/z 89.10 ± 0.1, which is the product of putrescine from ornithine decarboxylase. We were able to correctly identify 97.06% (132 of 136) of E. coli and Shigella isolates and 100% (8 of 8) of S. sonnei isolates using this biochemical-based MALDI-TOF MS detection system. This technology is advantageous for its high-throughput, high quality, and ease of operation, and is of significant value for the diagnosis of E. coli and Shigella-related diseases.

Identifiants

pubmed: 37996154
pii: S0003-2670(23)01188-1
doi: 10.1016/j.aca.2023.341967
pii:
doi:

Substances chimiques

Cadaverine L90BEN6OLL
Putrescine V10TVZ52E4

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

341967

Informations de copyright

Copyright © 2023 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Tianyi Li (T)

National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.

Qinghua Zou (Q)

Department of Microbiology and Infectious Disease Center, School of Basic Medical Sciences, Peking University, Beijing, 100191, China.

Binghua Zhang (B)

National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.

Di Xiao (D)

National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China. Electronic address: xiaodi@icdc.cn.

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Classifications MeSH