JOURNAL ARTICLE
Aeromonas isolation reveals this genus's contribution to antimicrobial resistance fluxes across the wastewater–treated water–river interface.
Published In: Journal of Applied Microbiology, 2025, v. 136, n. 1. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Xu, Jianxin; Jensen, Mia Kristine Staal; Lassen, Simon Bo; Brandt, Kristian Koefoed; Dechesne, Arnaud; Smets, Barth F 3 of 3
Abstract
This article focuses on assessing the isolation methods, distribution, and antimicrobial resistance (AMR) profiles of Aeromonas species in wastewater and receiving aquatic environments at five municipal wastewater treatment plants (WWTPs) in Denmark. The study found that Aeromonas spp. are prevalent and phylogenetically diverse in these environments, with ampicillin sheep blood agar (ASBA) medium recovering the most diverse isolates. Wastewater treatment reduced Aeromonas abundance by 2–3 orders of magnitude, but treated effluents still contributed resistant Aeromonas, particularly those resistant to beta-lactams and tetracyclines, to downstream waters. Although Aeromonas isolates showed moderate resistance levels, their resistance profiles did not consistently reflect the broader community resistance gene patterns detected by high-throughput qPCR, indicating limitations in using Aeromonas alone as an AMR indicator. The findings support the use of ASBA for monitoring Aeromonas in environmental waters and highlight the role of treated wastewater in disseminating AMR Aeromonas into surface waters.
Additional Information
- Source:Journal of Applied Microbiology. 2025/01, Vol. 136, Issue 1, p1
- Document Type:Article
- Subject Area:Engineering
- Publication Date:2025
- ISSN:1364-5072
- DOI:10.1093/jambio/lxae302
- Accession Number:182905270
- Copyright Statement:Copyright of Journal of Applied Microbiology 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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