Abstract

Given the threat to public health posed by antibiotic resistance transmission, environmental monitoring is essential for tracking antibiotic resistance genes (ARGs). Houseflies, being ubiquitous organisms capable of carrying and disseminating ARGs, serve as suitable indicators for environmental monitoring. In this study, we employ metagenomic approaches to investigate housefly body surface samples from five typical sites associated with human activities. The investigation reveals microbiome diversity among the samples, along with variations in the occurrence and mobility potential of ARGs. Metagenomic analysis indicates that the composition of ARGs on housefly body surfaces is influenced by environmental ARGs, which may be enriched on the housefly body surface. The resistance genes related to multidrug, β-lactam, bacitracin, and tetracycline were the predominant ARGs detected, with multidrug-related ARGs consistently exhibiting dominance. Furthermore, the abundance of ARGs in the different housefly body surface samples was found to correlate with the population density and mobility of the sampling site. Natural environments exhibited the lowest ARG abundance, while areas with higher population density and limited population mobility displayed higher ARG abundance. This study emphasizes the effectiveness of houseflies as monitors for environmental ARGs and underscores their potential for assessing and controlling antibiotic resistance risks in urban environments.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.