Antibiotic resistance genes (ARGs) are important contaminants in water systems, and their detection depends strongly on methodological sensitivity. This study compared three molecular platforms, high-throughput quantitative polymerase chain reaction (HT-qPCR), hydrolysis probe-based qPCR, and droplet digital PCR (ddPCR), for detecting ARGs in wastewater, river water, and seawater in Thailand. HT-qPCR enabled broad resistome profiling, detecting 325-336 ARGs out of 373 targets (87.1-90.1%), with aminoglycoside, beta-lactam, macrolide-lincosamide-streptogramin B, sulfonamide, mobile genetic element, and integron genes most prevalent. qPCR quantified selected ARGs using standard curves constructed from plasmid standards whose absolute copy numbers were calibrated by ddPCR, yielding high efficiency and strong linearity. ddPCR detected the same target genes as qPCR with comparable concentration estimates and additionally identified blaIND, which was not observed by HT-qPCR or qPCR. Quantifications from qPCR and ddPCR showed high rank-based concordance across matrices. Combining HT-qPCR with qPCR improved coverage by about 1% relative to HT-qPCR alone, while HT-qPCR with ddPCR offered nearly identical values. In conclusion, HT-qPCR was most effective for comprehensive profiling, qPCR ensured reliable quantification, and ddPCR enabled detection of rare targets, supporting a tiered and cost-effective framework for smart ARG monitoring in tropical aquatic environments.
Srathongneam et al. (Wed,) studied this question.
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