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Updated: May 12, 2025

Author Spotlight: Understanding and Detecting Environmental Antimicrobial Resistance by Combining Culture-Based Techniques and Genomics
Published on: July 19, 2024
From glacier forelands to human settlements: Patterns, environmental drivers, and risks of antibiotic resistance
Binglin Zhang1, Ruiqi Yang2, Yang Liu1
1Qilianshan Observation and Research Station of Cryosphere and Ecological Environment, Yulong Snow Station of Cryosphere and Sustainable Development, State Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco, Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China; Key Laboratory of Extreme Environmental Microbial Resources and Engineering, Gansu Province 730000, China.
Abstract:
Antibiotic resistance genes (ARGs) are biological pollutants widely present in glaciers, such as ice, snow, and melt water. However, it remains unclear whether ARGs in glaciers influence their distribution in human settlements within the glacier basins. Therefore, we investigated the distribution pattern and driving factors of ARGs in the Laohugou glacier basins on the Tibetan Plateau. Using high-throughput quantitative PCR, the total abundance of ARGs in the Laohugou glacier basins ranged from 7.53 × 10⁶ to 1.83 × 10⁹ copies/g, including 128 detected ARGs across 11 classes, with aminoglycoside resistance genes being the dominant group. The abundance of ARGs exhibited a U-shaped pattern along the elevational gradient, with higher levels in glacier regions and human settlements, and the lowest abundance at mid-elevations. While glacier melting and anthropogenic disturbance are likely major contributors to this pattern, other potential mechanisms may also be involved, such as elevation-dependent microbial community composition, atmospheric deposition and release of legacy ARGs from melting permafrost and glacial ice. Together, these processes likely interact to shape the observed ARG pattern in this alpine watershed. We further verified that the distribution of ARGs was strongly correlated with microbial community structure, especially bacterial communities (r > 0.50; p < 0.05). Network analysis showed that Nitrolancea negatively correlated with several core ARGs, suggesting its potential role in regulating the spread of ARGs. Random forest analysis and structural equation modeling (SEM) indicated that, after accounting for various driving factors, organic matter and bacterial biomass were the primary drivers of increased ARG abundance. This study provides a foundation for assessing the risks of ARGs in glacier basins under global climate change, offering insights into risk mitigation strategies and guiding future ecological and public health research.
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