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使用公开的 NEON 数据对全基因组鸟枪法和 16S 扩增子宏基因组测序进行微生物解析。

Microbial resolution of whole genome shotgun and 16S amplicon metagenomic sequencing using publicly available NEON data.

机构信息

Maryland Pathogen Research Institute, University of Maryland, College Park, Maryland, United States of America.

University of Maryland Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland, United States of America.

出版信息

PLoS One. 2020 Feb 13;15(2):e0228899. doi: 10.1371/journal.pone.0228899. eCollection 2020.

Abstract

Microorganisms are ubiquitous in the biosphere, playing a crucial role in both biogeochemistry of the planet and human health. However, identifying these microorganisms and defining their function are challenging. Widely used approaches in comparative metagenomics, 16S amplicon sequencing and whole genome shotgun sequencing (WGS), have provided access to DNA sequencing analysis to identify microorganisms and evaluate diversity and abundance in various environments. However, advances in parallel high-throughput DNA sequencing in the past decade have introduced major hurdles, namely standardization of methods, data storage, reproducible interoperability of results, and data sharing. The National Ecological Observatory Network (NEON), established by the National Science Foundation, enables all researchers to address queries on a regional to continental scale around a variety of environmental challenges and provide high-quality, integrated, and standardized data from field sites across the U.S. As the amount of metagenomic data continues to grow, standardized procedures that allow results across projects to be assessed and compared is becoming increasingly important in the field of metagenomics. We demonstrate the feasibility of using publicly available NEON soil metagenomic sequencing datasets in combination with open access Metagenomics Rapid Annotation using the Subsystem Technology (MG-RAST) server to illustrate advantages of WGS compared to 16S amplicon sequencing. Four WGS and four 16S amplicon sequence datasets, from surface soil samples prepared by NEON investigators, were selected for comparison, using standardized protocols collected at the same locations in Colorado between April-July 2014. The dominant bacterial phyla detected across samples agreed between sequencing methodologies. However, WGS yielded greater microbial resolution, increased accuracy, and allowed identification of more genera of bacteria, archaea, viruses, and eukaryota, and putative functional genes that would have gone undetected using 16S amplicon sequencing. NEON open data will be useful for future studies characterizing and quantifying complex ecological processes associated with changing aquatic and terrestrial ecosystems.

摘要

微生物在生物圈中无处不在,在地球的生物地球化学和人类健康中发挥着关键作用。然而,识别这些微生物并定义其功能具有挑战性。比较宏基因组学、16S 扩增子测序和全基因组鸟枪法测序(WGS)等广泛使用的方法,已经可以进行 DNA 测序分析,以识别微生物并评估各种环境中的多样性和丰度。然而,过去十年中平行高通量 DNA 测序的进步带来了重大障碍,即方法标准化、数据存储、结果的可重复互操作性和数据共享。由美国国家科学基金会建立的国家生态观测站网络(NEON)使所有研究人员都能够针对各种环境挑战,在区域到大陆范围内解决查询问题,并提供来自美国各地实地站点的高质量、综合和标准化数据。随着宏基因组数据量的不断增加,在宏基因组学领域,允许评估和比较跨项目结果的标准化程序变得越来越重要。我们展示了使用公开可用的 NEON 土壤宏基因组测序数据集与开放获取的使用子系统技术(MG-RAST)服务器的宏基因组快速注释相结合的可行性,以说明 WGS 与 16S 扩增子测序相比的优势。选择了来自 NEON 研究人员准备的表层土壤样本的四个 WGS 和四个 16S 扩增子序列数据集,用于比较,使用在 2014 年 4 月至 7 月在科罗拉多州同一地点收集的标准化协议。两种测序方法检测到的优势细菌门在样本之间是一致的。然而,WGS 产生了更高的微生物分辨率、更高的准确性,并允许鉴定更多的细菌、古菌、病毒和真核生物属,以及使用 16S 扩增子测序可能无法检测到的假定功能基因。NEON 开放数据将有助于未来研究描述和量化与水生态系统和陆地生态系统变化相关的复杂生态过程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6987/7018008/12abf5b573ec/pone.0228899.g001.jpg

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