JOURNAL ARTICLE

One Health compartment analysis of ESBL-producing Escherichia coli reveals multiple transmission events in a rural area of Madagascar.

  • Published In: Journal of Antimicrobial Chemotherapy (JAC), 2023, v. 78, n. 8. P. 1848 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Gay, Noellie; Rabenandrasana, Mamitina Alain Noah; Panandiniaina, Harielle Prisca; Rakotoninidrina, Marie Florence; Ramahatafandry, Ilo Tsimok'Haja; Enouf, Vincent; Roger, François; Collard, Jean-Marc; Cardinale, Eric; Rieux, Adrien; Loire, Etienne 3 of 3

Abstract

This article focuses on the genomic characterization and transmission dynamics of extended-spectrum β-lactamase-producing Escherichia coli (ESBL-Ec) across human, animal, and environmental compartments in a rural area of Madagascar. Whole-genome sequencing of 510 ESBL-Ec isolates from humans, various animals, and water revealed high genetic diversity without compartment-specific lineages, indicating frequent cross-compartment transmission. The study identified 104 transmission clusters involving multiple hosts and households, with the blaCTX-M-15 gene being the most prevalent ESBL gene across all compartments. These findings underscore the interconnectedness of antimicrobial resistance (AMR) reservoirs in low- and middle-income countries and highlight the importance of integrated 'One Health' surveillance to inform interventions targeting AMR transmission pathways.

Additional Information

  • Source:Journal of Antimicrobial Chemotherapy (JAC). 2023/08, Vol. 78, Issue 8, p1848
  • Document Type:Article
  • Subject Area:Geography and Cartography
  • Publication Date:2023
  • ISSN:0305-7453
  • DOI:10.1093/jac/dkad125
  • Accession Number:169828253
  • Copyright Statement:Copyright of Journal of Antimicrobial Chemotherapy (JAC) is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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