Data supporting the publication: Quality Assurance Strategies for Reliable HT-qPCR-Based Antibiotic-Resistant Genes Monitoring in the Aquatic Environment

Accurate assessment of antibiotic resistance genes (ARGs) in the environment is vital for addressing antimicrobial resistance (AMR). High-throughput quantitative PCR (HT-qPCR) enables rapid, multi-gene analysis but poses quality assurance challenges due to many endpoints. We evaluated key quality indicators – primer performance, detection limits, melting temperatures, quality warnings, and addition of calibration curves and DNA background – using HT-qPCR data from 250 samples targeting 24 genes in a river catchment. Triplicate agreement within and between high-throughput chips was high. Calibration curves consisting of synthetic DNA allowed gene-specific PCR range determination and revealed inadequate efficiency for qepA (61.1). In silico primer analysis indicated low efficacy for blaCTX-M (0.55) and qacF/H (0.63), and low specificity for blaCMY, ermX, mcr-2, and qepA (0.02–0.67). Melting temperature analysis confirmed non-specific products for these four genes, and inconsistencies in nine others (blaNDM, blaOXA-48, ermX, floR, qepA, strB, tetG, vanA, vanTC), indicating possible false positives. Omitting calibration curves and assuming uniform efficiency overestimated relative abundances by 0.25–1.3 log10 units. Applying optimized quality control to catchment samples showed expected trends – ARG concentrations declined from wastewater influent to effluent and general catchment – with some sensitivity loss for low-abundance genes (vanTG, vanTC, vanA). It was concluded that HT-qPCR requires robust quality control in order to enable high-throughput ARG surveillance in aquatic environments. Incorporating primer validation, melting temperature checks, and gene-specific Ct cut-offs from calibration curves significantly improves HT-qPCR accuracy.