Climate warming may aggravate the threat of antibiotic resistance genes (ARGs) to environmental and human health. However, whether temperature can predict ARGs and influence their assembly processes remains unknown. Here, we used metagenomic sequencing to explore how gradually elevated water temperature (23 °C, 26 °C, 29 °C, 32 °C, 35 °C) influences ARG and mobile genetic element (MGE) profiles in the Yellow River. In total, 30 ARG types including 679 subtypes were detected in our water samples. Gradually increased temperature remarkably reduced ARG diversity but increased ARG abundance. Approximately 37 % of ARGs and 42 % of MGEs were predicted by temperature, while most others were not sensitive to temperature. For each 1 °C increase in temperature, the ARG abundance rose by 2133 TPM (Transcripts Per kilobase of exon model per Million mapped reads) abundance, and multidrug, tetracycline and peptide resistance genes had the fastest increases. Proteobacteria and Actinobacteria were the primary ARG hosts, with 558 and 226 ARG subtypes, respectively. Although ARG profiles were mainly governed by stochastic process, elevated temperature increased the deterministic process of ARGs in the Yellow River. The abundance of five high-risk ARGs (tetM, mecA, bacA, vatE and tetW) significantly increased with elevated water temperature, and these ARGs co-occurred with several opportunistic pathogens (Delftia, Legionella and Pseudomonas), implying that antibiotic resistance risk may increase under climate warming. Our study explored the possibility of predicting resistomes and their health risks through temperature, providing a novel approach to predict and control ARGs in water environments under climate warming.
Keywords: Climate warming; Deterministic processes; Diversity; Metagenomics; Resistome; Temperature.
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