The effect of taxonomic classification by full-length 16S rRNA sequencing with a synthetic long-read technology

Abstract Characterizing the microbial communities inhabiting specimens is one of the primary objectives of microbiome studies. A short-read sequencing platform for reading partial regions of the 16S rRNA gene is most commonly used by reducing the cost burden of next-generation sequencing (NGS), but...

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Autores principales:	Jinuk Jeong, Kyeongeui Yun, Seyoung Mun, Won-Hyong Chung, Song-Yi Choi, Young-do Nam, Mi Young Lim, Chang Pyo Hong, ChanHyeok Park, Yong Ahn, Kyudong Han
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/6a8f477132134f5caa183f322c619ec0
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spelling	oai:doaj.org-article:6a8f477132134f5caa183f322c619ec02021-12-02T10:49:10ZThe effect of taxonomic classification by full-length 16S rRNA sequencing with a synthetic long-read technology10.1038/s41598-020-80826-92045-2322https://doaj.org/article/6a8f477132134f5caa183f322c619ec02021-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-80826-9https://doaj.org/toc/2045-2322Abstract Characterizing the microbial communities inhabiting specimens is one of the primary objectives of microbiome studies. A short-read sequencing platform for reading partial regions of the 16S rRNA gene is most commonly used by reducing the cost burden of next-generation sequencing (NGS), but misclassification at the species level due to its length being too short to consider sequence similarity remains a challenge. Loop Genomics recently proposed a new 16S full-length-based synthetic long-read sequencing technology (sFL16S). We compared a 16S full-length-based synthetic long-read (sFL16S) and V3-V4 short-read (V3V4) methods using 24 human GUT microbiota samples. Our comparison analyses of sFL16S and V3V4 sequencing data showed that they were highly similar at all classification resolutions except the species level. At the species level, we confirmed that sFL16S showed better resolutions than V3V4 in analyses of alpha-diversity, relative abundance frequency and identification accuracy. Furthermore, we demonstrated that sFL16S could overcome the microbial misidentification caused by different sequence similarity in each 16S variable region through comparison the identification accuracy of Bifidobacterium, Bacteroides, and Alistipes strains classified from both methods. Therefore, this study suggests that the new sFL16S method is a suitable tool to overcome the weakness of the V3V4 method.Jinuk JeongKyeongeui YunSeyoung MunWon-Hyong ChungSong-Yi ChoiYoung-do NamMi Young LimChang Pyo HongChanHyeok ParkYong AhnKyudong HanNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jinuk Jeong Kyeongeui Yun Seyoung Mun Won-Hyong Chung Song-Yi Choi Young-do Nam Mi Young Lim Chang Pyo Hong ChanHyeok Park Yong Ahn Kyudong Han The effect of taxonomic classification by full-length 16S rRNA sequencing with a synthetic long-read technology
description	Abstract Characterizing the microbial communities inhabiting specimens is one of the primary objectives of microbiome studies. A short-read sequencing platform for reading partial regions of the 16S rRNA gene is most commonly used by reducing the cost burden of next-generation sequencing (NGS), but misclassification at the species level due to its length being too short to consider sequence similarity remains a challenge. Loop Genomics recently proposed a new 16S full-length-based synthetic long-read sequencing technology (sFL16S). We compared a 16S full-length-based synthetic long-read (sFL16S) and V3-V4 short-read (V3V4) methods using 24 human GUT microbiota samples. Our comparison analyses of sFL16S and V3V4 sequencing data showed that they were highly similar at all classification resolutions except the species level. At the species level, we confirmed that sFL16S showed better resolutions than V3V4 in analyses of alpha-diversity, relative abundance frequency and identification accuracy. Furthermore, we demonstrated that sFL16S could overcome the microbial misidentification caused by different sequence similarity in each 16S variable region through comparison the identification accuracy of Bifidobacterium, Bacteroides, and Alistipes strains classified from both methods. Therefore, this study suggests that the new sFL16S method is a suitable tool to overcome the weakness of the V3V4 method.
format	article
author	Jinuk Jeong Kyeongeui Yun Seyoung Mun Won-Hyong Chung Song-Yi Choi Young-do Nam Mi Young Lim Chang Pyo Hong ChanHyeok Park Yong Ahn Kyudong Han
author_facet	Jinuk Jeong Kyeongeui Yun Seyoung Mun Won-Hyong Chung Song-Yi Choi Young-do Nam Mi Young Lim Chang Pyo Hong ChanHyeok Park Yong Ahn Kyudong Han
author_sort	Jinuk Jeong
title	The effect of taxonomic classification by full-length 16S rRNA sequencing with a synthetic long-read technology
title_short	The effect of taxonomic classification by full-length 16S rRNA sequencing with a synthetic long-read technology
title_full	The effect of taxonomic classification by full-length 16S rRNA sequencing with a synthetic long-read technology
title_fullStr	The effect of taxonomic classification by full-length 16S rRNA sequencing with a synthetic long-read technology
title_full_unstemmed	The effect of taxonomic classification by full-length 16S rRNA sequencing with a synthetic long-read technology
title_sort	effect of taxonomic classification by full-length 16s rrna sequencing with a synthetic long-read technology
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/6a8f477132134f5caa183f322c619ec0
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The effect of taxonomic classification by full-length 16S rRNA sequencing with a synthetic long-read technology

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