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采用宏基因组学方法探索活性污泥中抗生素耐药基因在四年间的变化。

Exploring variation of antibiotic resistance genes in activated sludge over a four-year period through a metagenomic approach.

机构信息

Environmental Biotechnology Laboratory, Department of Civil Engineering, The University of Hong Kong , Hong Kong SAR, China.

出版信息

Environ Sci Technol. 2013 Sep 17;47(18):10197-205. doi: 10.1021/es4017365. Epub 2013 Aug 29.

Abstract

In this study, the profiles of ARGs in activated sludge from the Shatin WWTP of Hong Kong were investigated using metagenomic analysis over a four-year period. Forty giga base pairs of metagenomic data were generated from eight activated sludge samples collected biannually at two seasons (winter and summer) from July 2007 to January 2011. A structured database of ARGs was proposed and constructed to facilitate the classification of ARGs in the collected samples from metagenomic data using a customized script. Analysis of the data showed the existence of a broad-spectrum of different ARGs, some of which have never been reported in activated sludge before. The most abundant ARGs were aminoglycoside and tetracycline resistance genes, followed by resistance genes of sulfonamide, multidrug, and chloramphenicol. Seasonal fluctuations were observed for 3 types of ARGs, that is, resistance genes of tetracycline, sulfonamide, and vancomycin. The abundances of these resistance genes were generally higher in the samples collected in the winters than the samples collected in the contiguous summer. Further analyses were carried out for the presence of subtypes of ARGs for aminoglycoside, tetracycline, and beta-lactam. The abundances of some ARGs subtypes were inconsistent with those reported in previous studies of activated sludge using the PCR approach. Statistical analyses showed that the activated sludge data sets from this study can be distinguished from other types of samples based on their ARGs profiles. Furthermore, the results of this study demonstrate that a high throughput-based metagenomic approach combined with a structured database of ARGs provides a powerful tool for a comprehensive survey of the various ARGs not only in the activated sludge of a WWTP but in other environmental samples as well. Thus, the profiling of ARGs in other ecologically important environmental matrixes may help elucidate those environmental factors contributing to the spread of ARGs.

摘要

本研究通过四年的时间,利用宏基因组分析研究了香港沙田污水处理厂活性污泥中的 ARG 谱。从 2007 年 7 月至 2011 年 1 月,每隔半年从两个季节(冬季和夏季)采集 8 个活性污泥样本,共产生了 40 千兆碱基对的宏基因组数据。提出并构建了一个 ARG 结构化数据库,以便使用定制脚本从宏基因组数据中对收集的样本中的 ARG 进行分类。数据分析表明,存在广泛的不同 ARG,其中一些以前从未在活性污泥中报道过。最丰富的 ARG 是氨基糖苷类和四环素类抗性基因,其次是磺胺类、多药类和氯霉素类抗性基因。3 种 ARG(即四环素、磺胺类和万古霉素抗性基因)出现了季节性波动。这些抗性基因的丰度通常在冬季采集的样本中高于连续夏季采集的样本。进一步对氨基糖苷类、四环素类和β-内酰胺类的 ARG 亚类的存在情况进行了分析。一些 ARG 亚类的丰度与以前使用 PCR 方法对活性污泥进行的研究不一致。统计分析表明,基于高通量的宏基因组方法结合 ARG 结构化数据库,可以根据 ARG 谱区分本研究的活性污泥数据集与其他类型的样本。此外,本研究的结果表明,高通量的宏基因组方法结合 ARG 结构化数据库为全面调查不仅在 WWTP 的活性污泥中,而且在其他环境样本中各种 ARG 提供了有力的工具。因此,对其他生态重要环境基质中的 ARG 进行分析可能有助于阐明那些导致 ARG 传播的环境因素。

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