Characterization of Shallow Whole-Metagenome Shotgun Sequencing as a High-Accuracy and Low-Cost Method by Complicated Mock Microbiomes

被引:31
作者
Xu, Wenyi [1 ]
Chen, Tianda [1 ]
Pei, Yuwei [1 ]
Guo, Hao [1 ]
Li, Zhuanyu [1 ]
Yang, Yanan [2 ]
Zhang, Fang [2 ]
Yu, Jiaqi [2 ]
Li, Xuesong [3 ]
Yang, Yu [3 ]
Zhao, Bowen [1 ]
Wu, Chongming [2 ]
机构
[1] Beijing QuantiHlth Technol Co Ltd, Beijing, Peoples R China
[2] Chinese Acad Med Sci & Peking Union Med Coll, Pharmacol & Toxicol Res Ctr, Inst Med Plant Dev, Beijing, Peoples R China
[3] Qiqihar Med Univ, Affiliated Hosp 3, Qiqihar, Peoples R China
基金
中国国家自然科学基金;
关键词
shallow whole-metagenome shotgun sequencing; 16S rRNA gene amplicon sequencing; metagenomics; mock microbiomes; consistency; accuracy; 16S;
D O I
10.3389/fmicb.2021.678319
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Characterization of the bacterial composition and functional repertoires of microbiome samples is the most common application of metagenomics. Although deep whole-metagenome shotgun sequencing (WMS) provides high taxonomic resolution, it is generally cost-prohibitive for large longitudinal investigations. Until now, 16S rRNA gene amplicon sequencing (16S) has been the most widely used approach and usually cooperates with WMS to achieve cost-efficiency. However, the accuracy of 16S results and its consistency with WMS data have not been fully elaborated, especially by complicated microbiomes with defined compositional information. Here, we constructed two complex artificial microbiomes, which comprised more than 60 human gut bacterial species with even or varied abundance. Utilizing real fecal samples and mock communities, we provided solid evidence demonstrating that 16S results were of poor consistency with WMS data, and its accuracy was not satisfactory. In contrast, shallow whole-metagenome shotgun sequencing (shallow WMS, S-WMS) with a sequencing depth of 1 Gb provided outputs that highly resembled WMS data at both genus and species levels and presented much higher accuracy taxonomic assignments and functional predictions than 16S, thereby representing a better and cost-efficient alternative to 16S for large-scale microbiome studies.
引用
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页数:12
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