| 大同铅锌尾矿不同污染程度土壤细菌群落分析及生态功能特征 |
| 摘要点击 1304 全文点击 452 投稿时间：2022-09-17 修订日期：2022-10-01 |
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| 中文关键词 尾矿 土壤理化因子 高通量测序 细菌群落结构 生态功能预测 |
| 英文关键词 tail mining area soil physical and chemical factors high-throughput sequencing bacterial community structure ecological function prediction |
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| 中文摘要 |
| 随着工业化飞速发展，矿山开采滞留大量废弃物严重破坏了生态环境，造成的污染亟待解决.以不同污染区为对象，利用Illumina高通量测序技术分析土壤细菌群落的变化，结合土壤理化因子探究土壤细菌群落主要影响因素，并对其潜在生态学功能进行预测.结果表明，受尾矿污染加剧影响，土壤养分流失严重.土壤样品共获得细菌操作分类单元（OTU）14253个，重度污染区（W1）、中度污染区（W2）、轻度污染区（W3）和清洁区（CK）的OTU数分别为3240、3330、3813和3870个，随着污染加剧，土壤OTU值下降.在土壤细菌群落α多样性分析中，与CK相比，W1显著降低了Chao1、ACE和Shannon指数（P<0.05），W3无显著差异.土壤细菌群落的优势菌门是放线菌门（β-Actinobacteria）、变形菌门（β-Proteobacteria）和绿弯菌门（β-Chloroflexi），污染区（W1~W3）提高了放线菌门和变形菌门的相对丰度，降低了绿弯菌门的相对丰度，W1优势菌门的相对丰度与CK差异性显著（P<0.05）.RDA分析表明土壤理化性质与土壤细菌群落的总变异数为93.35%；Spearman分析表明，放线菌门与氮源和有机质呈显著负相关，与pH呈显著正相关；变形菌门与氮源、磷源、有效钾和有机质呈显著负相关，与全钾和pH呈显著正相关；绿弯菌门与氮源、磷源、有效钾和有机质呈极显著正相关，与pH呈极显著负相关.利用Tax4 Fun进行了生物代谢通路分析，土壤重金属污染影响土壤细菌群落，改变了其参与的主要生物代谢类型.FAPROTAX预测结果表明，W1显著增加了塑性降解、尿素分解和木质素分解代谢相关的基因丰度（P<0.05），CK参与的代谢模式的基因丰度要高于污染区，不仅参与降解代谢还与氧化代谢有关，表明尾矿污染影响改变了土壤细菌群落能量代谢和功能潜力.研究结果揭示了尾矿不同污染区土壤细菌分类和功能多样性的变化及驱动机制，为矿区植物恢复和生态修复提供了理论依据. |
| 英文摘要 |
| A rapid rise in industrialization has led to the accumulation of copious mining waste, which has caused serious destruction of the ecological environment, resulting in severe pollution problems that need to be addressed urgently. In this study, altered soil bacterial communities in different polluted areas were analyzed using the Illumina high-throughput sequencing technique. The primary factors along with physical and chemical factors influencing the soil bacterial communities were also investigated, and the associated potential ecological functions were predicted. The results of these analyses indicated that aggravated pollution caused severe loss of tailing soil nutrients. A total of 14253 bacterial OTU was obtained from the soil samples. The total numbers of OTU in the heavily polluted area (W1), moderately polluted area (W2), lightly polluted area (W3), and clean area (CK) were 3240, 3330, 3813, and 3870, respectively. However, the soil OTUs decreased gradually with increasing pollution. In the α-diversity index analysis, the richness and evenness of the soil bacterial community were significantly decreased in the W1 group. A significant decrease in the Chao1, ACE, and Shannon indexes was also observed in the W1 group, whereas no significant difference was observed in the W3 group compared to the control. The dominant bacterial phyla identified in the soil wereβ-Actinobacteria, β-Proteobacteria, and β-Chloroflexi. Further, the relative abundance of β-Actinobacteria and β-Proteobacteria was high, whereas relative abundance of β-Chloroflexi in the W1-W3 groups was low compared to that in the control. The relative abundance of the dominant phylum in the W1 group was significantly different than that in the CK group (P<0.05). RDA showed that the soil physical and chemical properties selected in this study explained the total variation in soil bacterial community by 93.35%. Spearman analysis showed that β-Actinobacteria was negatively correlated with nitrogen source and organic matter and positively correlated with pH; β-Proteobacteria was negatively correlated with nitrogen source, phosphorus source, available potassium, and organic matter and positively correlated with total potassium and pH; and β-Chloroflexi was positively correlated with nitrogen source, phosphorus source, available potassium, and organic matter and negatively correlated with pH. Tax4 Fun was used to analyze the biological metabolic pathway. Heavy metal pollution in the soil affected the soil bacterial community and changed the main types of biological metabolism. The ecological functions of soil bacteria groups in different polluted areas were predicted by FAPROTAX. The results showed that the dominant metabolic patterns were affected by the pollution degree, and the metabolic patterns of soil bacteria in polluted areas were relatively single. The functional abundance of metabolic patterns of soil bacteria communities in CK was higher than that in polluted areas, which not only participated in degradation metabolism but also related to oxidation metabolism. |
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