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通过整体方法量化和预测水体中的抗菌药物和抗微生物药物耐药基因:来自美国明尼苏达州的一项研究。

Quantifying and predicting antimicrobials and antimicrobial resistance genes in waterbodies through a holistic approach: a study in Minnesota, United States.

机构信息

Department of Veterinary and Biomedical Sciences, College of Veterinary Medicine, University of Minnesota, 1971 Commonwealth Ave., St. Paul, MN, 55108, USA.

Minnesota Department of Health, P.O. Box 64975, St. Paul, MN, 55164-0975, USA.

出版信息

Sci Rep. 2021 Sep 21;11(1):18747. doi: 10.1038/s41598-021-98300-5.

Abstract

The environment plays a key role in the spread and persistence of antimicrobial resistance (AMR). Antimicrobials and antimicrobial resistance genes (ARG) are released into the environment from sources such as wastewater treatment plants, and animal farms. This study describes an approach guided by spatial mapping to quantify and predict antimicrobials and ARG in Minnesota's waterbodies in water and sediment at two spatial scales: macro, throughout the state, and micro, in specific waterbodies. At the macroscale, the highest concentrations across all antimicrobial classes were found near populated areas. Kernel interpolation provided an approximation of antimicrobial concentrations and ARG abundance at unsampled locations. However, there was high uncertainty in these predictions, due in part to low study power and large distances between sites. At the microscale, wastewater treatment plants had an effect on ARG abundance (sul1 and sul2 in water; bla, intl1, mexB, and sul2 in sediment), but not on antimicrobial concentrations. Results from sediment reflected a long-term history, while water reflected a more transient record of antimicrobials and ARG. This study highlights the value of using spatial analyses, different spatial scales, and sampling matrices, to design an environmental monitoring approach to advance our understanding of AMR persistence and dissemination.

摘要

环境在抗生素耐药性(AMR)的传播和持续存在中起着关键作用。抗生素和抗生素耐药基因(ARG)从废水处理厂和养殖场等来源释放到环境中。本研究描述了一种基于空间制图的方法,以量化和预测明尼苏达州水体中的抗生素和 ARG 在水和沉积物中的含量,包括宏观(全州范围)和微观(特定水体)两个空间尺度。在宏观尺度上,所有抗生素类别中浓度最高的地方都靠近人口密集区。核插值提供了未采样点处抗生素浓度和 ARG 丰度的近似值。然而,由于研究能力低和站点之间距离大,这些预测存在高度不确定性。在微观尺度上,废水处理厂对抗生素耐药基因(ARG)丰度(水中的 sul1 和 sul2;沉积物中的 bla、intl1、mexB 和 sul2)有影响,但对抗生素浓度没有影响。沉积物的结果反映了长期的历史,而水则反映了抗生素和 ARG 的更短暂的记录。本研究强调了使用空间分析、不同的空间尺度和采样矩阵来设计环境监测方法的价值,以提高对抗生素耐药性持续存在和传播的理解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87b2/8455696/8f54e6ed3265/41598_2021_98300_Fig1_HTML.jpg

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