Abstract：
Acid mine drainage (AMD) caused environmental risks from heavy metal pollution, requiring treatment methods such as chemical precipitation and biological treatment. Monitoring and adapting treatment processes was crucial for success, but cost-effective pollution monitoring methods were lacking. Using bioindicators measured through 16S rRNA was a promising method to assess environmental pollution. This study evaluated the effects of AMD on ecological health using the ecological risk index (RI) and the Risk Assessment Code (RAC) indices. Additionally, we also examined how acidic metal stress affected the diversity of bacteria and fungi, as well as their networks. Bioindicators were identified using linear discriminant analysis effect size (LEfSe), Partial least squares regression (PLS-R), and Spearman analyses. The study found that Cd, Cu, Pb, and As pose potential ecological risks in that order. Fungal diversity decreased by 44.88% in AMD-affected areas, more than the 33.61% decrease in bacterial diversity. Microbial diversity was positively correlated with pH (r = 0.88, p = 0.04) and negatively correlated with bioavailable metal concentrations (r = -0.59, p = 0.05). Similarly, microbial diversity was negatively correlated with bioavailable metal concentrations (bio_Cu, bio_Pb, bio_Cd) (r = 0.79, p = 0.03). Acidiferrobacter and Thermoplasmataceae were prevalent in acidic metal environments, while Puia and Chitinophagaceae were identified as biomarker species in the control area (LDA>4). Acidiferrobacter and Thermoplasmataceae were found to be pH-tolerant bioindicators with high reliability (r = 1, P < 0.05, BW > 0.1) through PLS-R and Spearman analysis. Conversely, Puia and Chitinophagaceae were pH-sensitive bioindicators, while Teratosphaeriaceae was a potential bioindicator for Cu-Zn-Cd metal pollution. This study identified bioindicator species for acid and metal pollution in AMD habitats. This study outlined the focus of biological monitoring in AMD acidic stress environments, including extreme pH, heavy metal pollutants, and indicator species. It also provided essential information for heavy metal bioremediation, such as the role of omics and the effects of organic matter on metal bioavailability.
摘要：
酸性矿山排水（AMD）造成重金属污染的环境风险，需要化学沉淀和生物处理等处理方法。监测和调整治疗过程对于成功至关重要，但是缺乏具有成本效益的污染监测方法。使用通过16SrRNA测量的生物指示剂是评估环境污染的一种有前途的方法。本研究使用生态风险指数（RI）和风险评估代码（RAC）指数评估了AMD对生态健康的影响。此外,我们还研究了酸性金属胁迫如何影响细菌和真菌的多样性，以及他们的网络。使用线性判别分析效应大小(LEfSe)鉴定生物指标，偏最小二乘回归(PLS-R)，和斯皮尔曼分析。研究发现Cd,Cu,Pb,并以此顺序构成潜在的生态风险。在受AMD影响的地区，真菌多样性下降了44.88%，细菌多样性下降33.61%以上。微生物多样性与pH呈正相关（r=0.88，p=0.04），与生物可利用金属浓度呈负相关（r=-0.59，p=0.05）。同样，微生物多样性与生物可利用金属浓度呈负相关(bio_Cu，bio_Pb,bio_Cd)(r=0.79,p=0.03)。在酸性金属环境中普遍存在酸性亚铁杆菌和热生杆菌科，而Puia和Chitinophagaceae被鉴定为对照区的生物标志物（LDA>4）。通过PLS-R和Spearman分析，发现酸性亚铁杆菌和热质杆菌科是具有高可靠性（r=1，P<0.05，BW>0.1）的pH耐受生物指标。相反，Puia和Chitinophagaceae是pH敏感的生物指标，而Teratosphaeriaceae是Cu-Zn-Cd金属污染的潜在生物指示剂。这项研究确定了AMD栖息地中酸和金属污染的生物指示物种。本研究概述了AMD酸性应激环境中生物监测的重点，包括极端的pH值,重金属污染物,和指示物种。它还为重金属生物修复提供了必要的信息，例如组学的作用和有机物对金属生物利用度的影响。
