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Identification of Antibiotic Resistance Gene Hosts in Treatment Wetlands Using a Single-Cell Based High-Throughput Approach

Knecht, Camila A.; Hinkel, Maja; Mäusezahl, Ines; Kaster, Anne-Kristin 1,2; Nivala, Jaime; Müller, Jochen A. ORCID iD icon 2
1 Institut für Angewandte Biowissenschaften (IAB), Karlsruher Institut für Technologie (KIT)
2 Institut für Biologische Grenzflächen (IBG), Karlsruher Institut für Technologie (KIT)

Abstract:

Determining the prevalence of antimicrobial resistance (AMR) in non-clinical settings is vital for better management of the global AMR crisis. Untreated and even treated wastewaters are important sources that release AMR into the environment. Methodologically, it is difficult to generate a comprehensive in situ profile of antibiotic resistance gene hosts. Here, we used epicPCR (emulsion, paired isolation, and concatenation PCR) as a cultivation-independent method to reveal the host profiles of the AMR indicator genes intI1, sul1, sul2, and dfrA1 in two constructed wetlands treating municipal wastewater. Overall, the epicPCR analysis revealed a profile of AMR indicator gene hosts that is consistent with literature data from cultivation-based approaches. Most carriers of antibiotic resistance (AR) genes and likely of class 1 integrons belonged to the Gammaproteobateria, particularly the Burkholderiaceae and Rhodocyclaceae families, followed by members of the Campylobacterota, Desulfobacterota, and Firmicutes. The analysis also identified several novel hosts for the indicator genes widely distributed in the wetlands, including the genera Legionella and Ralstonia. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000160090
Veröffentlicht am 03.07.2023
Originalveröffentlichung
DOI: 10.3390/w15132432
Scopus
Zitationen: 5
Web of Science
Zitationen: 5
Dimensions
Zitationen: 5
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte Biowissenschaften (IAB)
Institut für Biologische Grenzflächen (IBG)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2023
Sprache Englisch
Identifikator ISSN: 2073-4441
KITopen-ID: 1000160090
HGF-Programm 43.33.11 (POF IV, LK 01) Adaptive and Bioinstructive Materials Systems
Erschienen in Water
Verlag MDPI
Band 15
Heft 13
Seiten Art.-Nr.: 2432
Vorab online veröffentlicht am 30.06.2023
Schlagwörter antimicrobial resistance; wastewater; constructed wetland; single-cell analysis; epicPCR
Nachgewiesen in Scopus
Dimensions
Web of Science
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