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

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 investiga...

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Autores principales: Xu, Wenyi, Chen, Tianda, Pei, Yuwei, Guo, Hao, Li, Zhuanyu, Yang, Yanan, Zhang, Fang, Yu, Jiaqi, Li, Xuesong, Yang, Yu, Zhao, Bowen, Wu, Chongming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8361837/
https://www.ncbi.nlm.nih.gov/pubmed/34394027
http://dx.doi.org/10.3389/fmicb.2021.678319
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author Xu, Wenyi
Chen, Tianda
Pei, Yuwei
Guo, Hao
Li, Zhuanyu
Yang, Yanan
Zhang, Fang
Yu, Jiaqi
Li, Xuesong
Yang, Yu
Zhao, Bowen
Wu, Chongming
author_facet Xu, Wenyi
Chen, Tianda
Pei, Yuwei
Guo, Hao
Li, Zhuanyu
Yang, Yanan
Zhang, Fang
Yu, Jiaqi
Li, Xuesong
Yang, Yu
Zhao, Bowen
Wu, Chongming
author_sort Xu, Wenyi
collection PubMed
description 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.
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spelling pubmed-83618372021-08-14 Characterization of Shallow Whole-Metagenome Shotgun Sequencing as a High-Accuracy and Low-Cost Method by Complicated Mock Microbiomes Xu, Wenyi Chen, Tianda Pei, Yuwei Guo, Hao Li, Zhuanyu Yang, Yanan Zhang, Fang Yu, Jiaqi Li, Xuesong Yang, Yu Zhao, Bowen Wu, Chongming Front Microbiol Microbiology 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. Frontiers Media S.A. 2021-07-30 /pmc/articles/PMC8361837/ /pubmed/34394027 http://dx.doi.org/10.3389/fmicb.2021.678319 Text en Copyright © 2021 Xu, Chen, Pei, Guo, Li, Yang, Zhang, Yu, Li, Yang, Zhao and Wu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Xu, Wenyi
Chen, Tianda
Pei, Yuwei
Guo, Hao
Li, Zhuanyu
Yang, Yanan
Zhang, Fang
Yu, Jiaqi
Li, Xuesong
Yang, Yu
Zhao, Bowen
Wu, Chongming
Characterization of Shallow Whole-Metagenome Shotgun Sequencing as a High-Accuracy and Low-Cost Method by Complicated Mock Microbiomes
title Characterization of Shallow Whole-Metagenome Shotgun Sequencing as a High-Accuracy and Low-Cost Method by Complicated Mock Microbiomes
title_full Characterization of Shallow Whole-Metagenome Shotgun Sequencing as a High-Accuracy and Low-Cost Method by Complicated Mock Microbiomes
title_fullStr Characterization of Shallow Whole-Metagenome Shotgun Sequencing as a High-Accuracy and Low-Cost Method by Complicated Mock Microbiomes
title_full_unstemmed Characterization of Shallow Whole-Metagenome Shotgun Sequencing as a High-Accuracy and Low-Cost Method by Complicated Mock Microbiomes
title_short Characterization of Shallow Whole-Metagenome Shotgun Sequencing as a High-Accuracy and Low-Cost Method by Complicated Mock Microbiomes
title_sort characterization of shallow whole-metagenome shotgun sequencing as a high-accuracy and low-cost method by complicated mock microbiomes
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8361837/
https://www.ncbi.nlm.nih.gov/pubmed/34394027
http://dx.doi.org/10.3389/fmicb.2021.678319
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