| 石家庄城市和郊区河流沉积物可移动遗传元件时空差异与影响因素 |
| 摘要点击 483 全文点击 72 投稿时间：2024-03-05 修订日期：2024-05-27 |
| 查看HTML全文
查看全文 查看/发表评论 下载PDF阅读器 |
| 中文关键词 可移动遗传元件（MGEs） 时空分布 宏基因组 城市河流 郊区河流 社会经济因子 |
| 英文关键词 mobile genetic elements（MGEs） spatial and temporal distribution metagenome urban rivers rural rivers socio-economic factors |
| 作者 | 单位 | E-mail | | 陈昊达 | 河北科技大学环境科学与工程学院, 石家庄 050018 | chd971203@163.com | | 高赛 | 河北科技大学环境科学与工程学院, 石家庄 050018 | | | 王琳静 | 河北科技大学环境科学与工程学院, 石家庄 050018 | | | 赵波 | 河北科技大学环境科学与工程学院, 石家庄 050018 | | | 卢梦淇 | 河北科技大学环境科学与工程学院, 石家庄 050018 | | | 宋圆梦 | 河北科技大学环境科学与工程学院, 石家庄 050018 | | | 崔建升 | 河北科技大学环境科学与工程学院, 石家庄 050018
河北省污染防治生物技术实验室, 石家庄 050018 | | | 张璐璐 | 河北科技大学环境科学与工程学院, 石家庄 050018
河北省污染防治生物技术实验室, 石家庄 050018 | zhanglulu19850703@163.com |
|
| 中文摘要 |
| 随着抗生素在医疗和农业中的广泛使用,环境中抗生素抗性基因（ARGs）的扩散已严重威胁生态平衡和人类健康,特别是其在促进多重抗药性病原体的兴起中所起的作用. 河流环境作为ARGs和与之紧密相关的可移动遗传元件（MGEs）的主要传播途径,其研究意义重大. MGEs通过促进ARGs在细菌群体中的水平转移,加剧了抗性基因的扩散. 尽管已有研究探讨了MGEs与ARGs之间的相互作用,但关于河流中MGEs的时空分布差异及其驱动因素的研究仍相对不足. 因此,选取石家庄内2条郊区河流（共6个采样点）和3条城市河流（共9个采样点）作为研究对象,于2020年12月及2021年4月分别采集沉积物样本. 通过运用宏基因组测序技术,深入比较和分析了城市与郊区河流沉积物中MGEs的时空分布特征及其影响因素. 结果表明：①12月在城市和郊区河流中分别检出1 738种（60572 RPKM）和1 604种MGEs（26916 RPKM）；4月在城市和郊区河流中分别检出1 790种（74354 RPKM）和1 631种MGEs（32062 RPKM）；②城市河流MGEs种类和丰度>郊区河流MGEs种类和丰度,4月MGEs种类和丰度>12月MGEs种类和丰度；③在石家庄城市和郊区河流沉积物中ISPa38、IS26和tnpA是河流间差异最显著的典型MGEs；④PCoA和NMDS分析显示城市和郊区河流中MGEs均存在显著时空差异；⑤相关分析和共现结果表明,城市河流中MGEs丰度主要与抗生素浓度、工业企业、污水处理厂、总人口、畜牧业和水产养殖呈现显著正相关；郊区河流中MGEs丰度主要与抗生素浓度、畜牧业、水产养殖和总人口呈现显著正相关. 总体而言,通过比较城市和郊区河流中MGEs的时空异质性,识别城市和郊区河流中MGEs的主要驱动因素,可为后续不同河流中抗生素抗性风险管控提供数据支撑. |
| 英文摘要 |
| With the widespread use of antibiotics in medicine and agriculture, the spread of antibiotic resistance genes （ARGs） in the environment has become a serious threat to ecological balance and human health, particularly for its role in facilitating the emergence of multidrug-resistant pathogens. The study of riverine environments as a major transmission route for ARGs and closely related mobile genetic elements （MGEs） is of great importance. MGEs exacerbate the spread of resistance genes by facilitating the horizontal transfer of ARGs in bacterial populations. Although studies have been conducted to explore the interactions between MGEs and ARGs, there is still a relative lack of research on the spatial and temporal differences in the distribution of MGEs in rivers and their drivers. This study selected two rural rivers （with a total of six sampling points） and three urban rivers （with a total of nine sampling points） within Shijiazhuang as research subjects, and sediment samples were collected in December 2020 and April 2021. By employing metagenomic sequencing technology, this study comprehensively compared and analyzed the spatiotemporal distribution characteristics and influencing factors of MGEs in the sediment of urban and rural rivers. The results showed that： ① In December, 1 738 types of MGEs （60572 RPKM） and 1 604 types of MGEs （26916 RPKM） were detected in urban and rural rivers, respectively. In April, 1 790 types of MGEs （74354 RPKM） and 1 631 types of MGEs （32062 RPKM） were detected in urban and rural rivers, respectively. ② The types and abundance of MGEs in urban rivers were greater than those in rural rivers, and the types and abundance of MGEs in April were greater than those in December. ③ ISPa38, IS26, and tnpA were the most significantly different typical MGEs among the rivers in urban and suburban Shijiazhuang. ④ PCoA and NMDS analyses showed significant spatiotemporal differences in MGEs between urban and rural rivers. ⑤ Correlation analysis and co-occurrence results indicated that the abundance of MGEs in urban rivers was significantly positively correlated with antibiotic concentration, industrial enterprises, sewage treatment plants, total population, livestock farming, and aquaculture. In suburban rivers, the abundance of MGEs was mainly significantly positively correlated with antibiotic concentration, livestock farming, aquaculture, and total population. Overall, by comparing the spatiotemporal heterogeneity of MGEs in urban and rural rivers and identifying the main driving factors of MGEs in urban and suburban rivers, this study provides data support for subsequent risk management and control of antibiotic resistance in different rivers. |
|
|
|
