Global warming accelerates glacier melting, which releases antibiotic resistance genes (ARGs) into downstream ecosystems, poses a threat to ecological security and human health. Revealing the distribution and potential risks of ARGs in glaciers is crucial for assessing the impact of glacier melting caused by climate change on downstream ecosystems. Based on the above background, a research team of the Center for Pan-third Pole Environment of Lanzhou University published “Profiles and risk assessment of antibiotic resistome between Qinghai-Xizang Plateau and Polar Regions”.
The study delineated that despite a significant difference in abundance of ARGs in the Qinghai-Xizang Plateau and the Arctic and Antarctica glaciers, their types exhibited a high similarity, mainly consisting of bacitracin and multidrug-resistant ARGs. It further indicated that the resistance of microorganisms in the glacial environment is mainly driven by the natural evolutionary process. Further assessment of the risk of ARGs in glaciers was conducted based on their mobility and the pathogenicity of their hosts. Although most ARGs in glaciers fall into the low-risk category, high-risk ARGs were still detected, indicating the need for continuous monitoring of ARGs in glaciers.
Highlights:
ARGs released from glaciers posed a threat to the sustainable development of downstream ecosystem.
The relative abundance of ARGs were the highest in Qinghai-Xizang Plateau.
A consistent pattern in terms of antibiotic class and resistance mechanism across three regions.
The potential ARGs future risks under climate change require further research.

Core content:
This study focuses on the distribution characteristics and potential risks of ARGs in glaciers of the Qinghai-Xizang Plateau and Polar Regions, aiming to assess the impact of glacier melting under the background of climate change on downstream ecosystems and human health. By using 294 metagenomic sequences downloaded from public databases, the study conducted an in-depth analysis of the distribution characteristics and potential risks of ARGs in glaciers and their adjacent environments in the Qinghai-Xizang Plateau, Antarctica, and the Arctic. The main research results are as follows:
Abundance characteristics of ARGs: The abundance of ARGs in glaciers of the Qinghai-Xizang Plateau was the highest, while that in Antarctica glaciers was the lowest. This finding indicates that the Qinghai-Xizang Plateau, due to its geographical location and environmental conditions, may be more susceptible to the influence of antibiotic use in surrounding countries. In addition, significant differences in the abundance of ARGs were observed across different habitats, with the relative abundance of ARGs in snow being the highest and that in ice being the lowest. This may be related to the microbial community structure and activity in different habitats.
Types and distribution of ARGs: The types of ARGs in glaciers of the Qinghai-Xizang Plateau, Antarctica, and the Arctic were consistent. Bacitracin, multidrug resistance, and macrolides were the most common types of ARGs in glaciers. Particularly, the bacA gene was the most frequently detected ARG subtype in the microbial communities of glaciers. Such distribution characteristics may be related to the natural selection and adaptability of microorganisms.
Risk assessment: Based on the mobility of ARGs and the pathogenicity of their hosts, a risk assessment of glacier ARGs was conducted. The study showed that most ARGs belonged to the low-risk category, but a certain proportion of high-risk ARGs (Rank I) was also detected (approximately 8%). These high-risk ARGs may pose a threat to human health through horizontal gene transfer.

Outlook: Future research should focus on the spatiotemporal migration mechanism of ARGs in the glacier basin continuum (glacier–runoff–lake), strengthen the source analysis of glacier ARGs, based on the climate environment and age record function of deep ice cores, reveal the long-term interaction and evolution between ARGs and climate change, and establish a prediction model for the evolution of ARGs during the process of climate change.
DOI:10.1016/j.geosus.2025.100342