| 基于16S rDNA测序的巢湖流域水体粪便污染溯源 |
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| 引用本文： | 祁钊,赵相龙,桑金慧,何振杰,傅丹丹,岳振宇,宋祥军.基于16S rDNA测序的巢湖流域水体粪便污染溯源[J].农业环境科学学报,2023,42(5):1128-1138. |
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| 作者姓名： | 祁钊 赵相龙 桑金慧 何振杰 傅丹丹 岳振宇 宋祥军 |
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| 作者单位： | 安徽农业大学信息与计算机学院, 合肥 230036;安徽省动物性食品质量与生物安全工程实验室, 合肥 230036 |
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| 基金项目： | 国家自然科学基金青年科学基金项目（32202891）；安徽高校协同创新项目（GXXT-2019-035） |
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| 摘 要： | 排入地表水中的动物粪便会带来一系列生态与公共卫生问题，快速准确鉴别污染来源对于源头控制与污染治理具有重要意义。基于细菌群落的微生物溯源技术（Community-based microbial source tracking）以及高通量DNA测序技术（Next-generation sequencing，NGS），对污染源中微生物和环境样本中的微生物群落进行比较分析，进而对水体中粪便污染来源进行预测。本文利用16S rDNA测序，系统分析与比较了巢湖流域水体、沉积物样本与广泛的潜在污染源（包括村庄与养猪场污水，野生水鸟粪便，人类与家禽、家畜粪便）的细菌群落组成，同时，利用基于机器学习的溯源软件FEAST与Sourcetracker，对水体、沉积物样本的潜在污染源进行了预测。结果表明：水体与沉积物样本的微生物多样性显著高于粪便样本，其中巢湖水体与河流沉积物样本具有最高的物种多样性，同时样本中也存在大量未分类物种。变形菌门（Proteobacteria）、放线菌门（Actinobacteria），拟杆菌门（Bacteroidetes）广泛分布于所有样本中。溯源分析结果表明，村庄排污口与污水处理厂排污口样本是河水样本最主要的污染来源，沉积物与湖水样本则预测存在猪场排污水与野生水鸟粪便的污染，所有样本未检测到来自人粪与鸡粪的污染。
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| 关 键 词： | 16S rDNA测序 微生物群落 水体污染 微生物溯源 |
| 收稿时间： | 2022/6/22 0:00:00 |
Tracking fecal contamination in the Chaohu Lake basin based on 16S rDNA sequencing |
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| QI Zhao,ZHAO Xianglong,SANG Jinhui,HE Zhenjie,FU Dandan,YUE Zhenyu,SONG Xiangjun.Tracking fecal contamination in the Chaohu Lake basin based on 16S rDNA sequencing[J].Journal of Agro-Environment Science( J. Agro-Environ. Sci.),2023,42(5):1128-1138. |
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| Authors: | QI Zhao ZHAO Xianglong SANG Jinhui HE Zhenjie FU Dandan YUE Zhenyu SONG Xiangjun |
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| Affiliation: | School of Information and Computer, Anhui Agricultural University, Hefei 230036, China;Anhui Province Engineering Laboratory for Animal Food Quality and Bio-safety, College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China |
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| Abstract: | The discharge of animal waste into rivers can cause a series of ecological and public health problems, thus the rapid and accurate identification of pollution sources is of great importance for source control and pollution management. Combining next-generation sequencing(NGS) and community-based microbial source tracking(MST), we are able to compare the microbial community composition in contamination sources and environmental samples to predict the source of contamination. Using 16S rDNA sequencing, we analyzed the bacterial community composition of water bodies, sediments and potential pollution sources(including village sewage outlets, pig farm effluent, and wild bird, human, poultry, and livestock feces) in the Chaohu Lake basin and analyzed the potential pollution sources of water bodies and sediment samples using machine learning-based traceability software, FEAST and Sourcetracker. The results showed that the microbial diversity of water and sediment samples was significantly higher than that of fecal samples. Chaohu Lake water and river sediment samples exhibited the highest microbial diversity, as well as the presence of a large number of unclassified species. Proteobacteria, Actinobacteria, and Bacteroidetes were widely distributed in all samples. The results of source analysis showed that village sewage outlets and wastewater treatment plants were the most important sources of contamination in river water samples. While sediment and lake water samples were potentially contaminated by sewage and wild waterfowl feces, no contamination from human and chicken feces was detected in all samples. |
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| Keywords: | 16S rDNA sequencing microbial community water pollution microbial source tracking |
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