鉱山影響を受けた河川堆積物における重金属勾配に対する微生物の分類学的および機能的応答

Legacy heavy metal pollution from historical mining restructures sediment microbial composition and function directly impacting contaminant fate and ecosystem health. The Dongdagou stream (Baiyin, China) possesses a pronounced geochemical gradient caused by long-term discharge of potentially toxic metals including Cd, Cu, Pb, and Zn. We employed this natural gradient to characterize microbial taxonomic and functional responses to metal stress. Sediment samples from four zones along the contamination gradient were analyzed for geochemistry, metal concentrations, and microbial composition (bacteria, archaea, and fungi) via high-throughput amplicon sequencing, with functional potential inferred using PICRUSt2. We found that microbial community structure and function were primarily shaped by metal concentration, with db-RDA explaining 18.1%, 12.4%, and 12.9% of the variance for bacteria, archaea, and fungi, respectively. Cadmium was identified as the strongest individual predictor for both bacterial (r² = 0.50, p = 0.001) and fungal (r² = 0.38, p = 0.001) communities. Bacterial diversity increased significantly downstream as contamination declined, with Shannon diversity increasing from 5.17 in the Source Zone to 6.28 in the Distal Zone (Tukey's multiple comparison test, p < 0.05). Upstream sediments were dominated by metal-tolerant taxa such as Sulfurifustis (17.4%) and Acidithiobacillus (5.0%), while downstream taxa shifted to heterotrophic genera like Gallionella (4.8%) with diverse metabolic capabilities. Despite cadmium being a key predictor, archaeal and fungal communities demonstrated greater compositional stability than bacteria, as shown by their lower beta-dispersion (ANOSIM R = 0.3152 and 0.5762, respectively, compared to 0.7222 for bacteria), indicating potential functional redundancy. Metagenomic predictions revealed a significant enrichment of genes for metal detoxification, anaerobic respiration, and oxidative stress response in polluted zones. These findings establish that microbial communities are both sensitive bioindicators and key mediators of contaminant dynamics, providing a framework for using microbial signatures to assess sediment health and monitor remediation efficacy.