High-risk ARGs (HRA) Chip: A high-throughput qPCR-based array for assessment of high-risk ARGs from the environment.

ABSTRACT

The global surge in antibiotic resistance genes (ARGs) presents a serious public health challenge. While methods like metagenomic analysis and qPCR arrays have been instrumental in investigating ARG distributions and dynamics, the vast diversity of ARGs often complicates effective monitoring and risk assessment. Here, we developed a High-Risk ARGs (HRA) chip based on high-capacity quantitative PCR array targeting previously identified high-risk ARGs. These ARGs are known to be prevalent in human-related environments, exhibit gene mobility, and are present in ESKAPE pathogens. The HRA chip include 101 primer sets and the 16S rRNA gene as a reference. These primer sets consist of 34 obtained from previous studies, and 67 newly designed primer sets which were validated in silico and experimentally. Absolute quantification of targeted ARGs is accomplished by generating standard curves for all ARGs with serially ten-fold diluted mixed plasmids containing targeted ARG sequences. The amplification efficiencies of all ARGs exceed 99% via plasmid template dilution tests, suggesting high reliability in quantification. The performance of HRA chip is further evaluated by practical applications in environmental samples from wastewater treatment plants (WWTPs) and soils with various land use types and fertilization regimes. The results indicate the dynamics of high-risk ARGs during wastewater treatment process, and reveal the profiles of soil high-risk ARGs which is distinct from those derived via metagenomic approaches. These findings highlight the potentials of HRA Chip in the evaluation of anthropogenic impacts on the environmental resistome with a more focused spectrum of high-risk ARGs. Overall, the HRA Chip emerges as a powerful and efficient high-throughput tool for rapid detection and quantification of high-risk ARGs, facilitating comprehensive profiling of high-risk resistomes in environmental samples which is essential for human health risk assessment of ARGs.