Mangroves are prone to receive pollutants and act as a sink for antibiotic resistance genes (ARGs). However, knowledge of the human health risk of ARGs and its influencing factors in mangrove ecosystems is limited, particularly at large scales. Here, we applied a high-throughput sequencing technique combined with an ARG risk assessment framework to investigate the profiles of ARGs and their public health risks from mangrove wetlands across South China. We detected 456 ARG subtypes, and found 71 of them were identified as high-risk ARGs, accounting for 0.25 % of the total ARG abundance. Both ARGs and bacterial communities showed a distance-decay biogeography, but ARGs had a steeper slope. Linear regression analysis between features of co-occurrence network and high-risk ARG abundance implies that greater connections in the network would result in higher health risk. Structural equation models showed that geographic distance and MGEs were the most influential factors that affected ARG patterns, ARGs and MGEs contributed the most to the health risk profiles in mangrove ecosystems. This work provides a novel understanding of biogeographic patterns and health risk assessment of ARGs in mangrove ecosystems and can have profound significance for mangrove environment management with regard to ARG risk control.
Keywords: Antibiotic resistance genes; Biogeographic pattern; Human health risk; Mangrove ecosystem; Mobile genetic elements.
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