Optimization of the Quantification of Antibiotic Resistance Genes in Multimedia from the Yangtze River Estuary

Antibiotic resistance gene (ARG) monitoring in environmental systems increasingly relies on DNA-based molecular approaches; however, the extent to which DNA extraction strategies bias downstream resistome interpretation remains insufficiently understood. This study systematically evaluated the effects of single versus successive DNA extraction on DNA recovery, microbial community composition, and the abundance and diversity of 385 genes related to antibiotic resistance including ARGs, mobile genetic elements (MGEs) across three contrasting matrices: water, sediment, and fish intestinal tissue. Successive extraction markedly increased DNA yield and detection of functional genes in water and sediment, particularly for low-abundance and particle-associated taxa. Enhanced recovery resulted in higher richness and abundance of ARGs and MGEs and strengthened correlations between intI1, ARGs, and bacterial taxa, indicating that single-cycle extraction may underestimate resistome magnitude and potential host associations in complex matrices. Conversely, biological tissue showed limited benefit or even reduced gene abundance with repeated extraction, likely due to rapid depletion of extractable nucleic acids and DNA degradation. While successive extraction improves recovery efficiency, the potential inclusion of extracellular or relic DNA suggests caution in interpreting inflated ARG abundance. Overall, our findings demonstrate that DNA extraction is a matrix-dependent methodological driver that can reshape both quantitative outcomes and ecological inference. Matrix-specific optimization and careful protocol selection are therefore essential for improving data comparability and minimizing methodological underestimation in environmental resistome assessments.