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Updated: Sep 2, 2025

Bioprospecting of Extremophilic Microorganisms to Address Environmental Pollution
Published on: December 30, 2021
Ecological risk assessment and identification of the distinct microbial groups in heavy metal-polluted river
Cheng Yang1, Zhuo Zeng1, Yuanyuan Wang1
1Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 610031, China.
Abstract:
To assess the health of river ecosystems, it is essential to quantify the ecological risk of heavy metals in river sediments and the structure of microbial communities. As important tributaries of the Tuo River in the upper reaches of the Yangtze River, the Mianyuan River and the Shiting River, are closely related to the economic development and human daily life in the region. This study assessed the ecological risks of heavy-metal-polluted river sediments, the heavy-metal-driven bacterial communities were revealed, and the relationships between the ecological risks and the identical bacterial communities were discussed. The Cd content was significantly greater than the environmental background value, leading to a serious pollution and very high ecological risk at the confluence of the two rivers and the upper reaches of the Mianyuan River. Microbial community analysis showed that Rhodobacter, Nocardioides, Sphingomonas, and Pseudarthrobacter were the dominant bacterial genera in the sediments of the Shiting River. However, the dominant bacterial genera in the Mianyuan River were Kouleothrix, Dechloromonas, Gaiella, Pedomicrobium, and Hyphomicrobium. Mantel test results showed (r = 0.5977, P = 0.005) that the Cd, As, Zn, Pb, Cr, and Cu were important factors that influenced differences in the distribution of sediment bacterial communities Mianyuan and Shiting rivers. A correlation heatmap showed that heavy metals were negatively correlated for most bacterial communities, but some bacterial communities were tolerant and showed a positive correlation. Overall, the microbial structure of the river sediments showed a diverse spatial distribution due to the influence of heavy metals. The results will improve the understanding of rivers contaminated by heavy metals and provide theoretical support for conservation and in situ ecological restoration of river ecosystems.

