Cargando…
The effect of taxonomic classification by full-length 16S rRNA sequencing with a synthetic long-read technology
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 misclassi...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7814050/ https://www.ncbi.nlm.nih.gov/pubmed/33462291 http://dx.doi.org/10.1038/s41598-020-80826-9 |
_version_ | 1783637978581565440 |
---|---|
author | Jeong, Jinuk Yun, Kyeongeui Mun, Seyoung Chung, Won-Hyong Choi, Song-Yi Nam, Young-do Lim, Mi Young Hong, Chang Pyo Park, ChanHyeok Ahn, Yong Ju Han, Kyudong |
author_facet | Jeong, Jinuk Yun, Kyeongeui Mun, Seyoung Chung, Won-Hyong Choi, Song-Yi Nam, Young-do Lim, Mi Young Hong, Chang Pyo Park, ChanHyeok Ahn, Yong Ju Han, Kyudong |
author_sort | Jeong, Jinuk |
collection | PubMed |
description | 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 | Online Article Text |
id | pubmed-7814050 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78140502021-01-21 The effect of taxonomic classification by full-length 16S rRNA sequencing with a synthetic long-read technology Jeong, Jinuk Yun, Kyeongeui Mun, Seyoung Chung, Won-Hyong Choi, Song-Yi Nam, Young-do Lim, Mi Young Hong, Chang Pyo Park, ChanHyeok Ahn, Yong Ju Han, Kyudong Sci Rep Article 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. Nature Publishing Group UK 2021-01-18 /pmc/articles/PMC7814050/ /pubmed/33462291 http://dx.doi.org/10.1038/s41598-020-80826-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Jeong, Jinuk Yun, Kyeongeui Mun, Seyoung Chung, Won-Hyong Choi, Song-Yi Nam, Young-do Lim, Mi Young Hong, Chang Pyo Park, ChanHyeok Ahn, Yong Ju Han, Kyudong The effect of taxonomic classification by full-length 16S rRNA sequencing with a synthetic long-read technology |
title | 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_short | 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 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7814050/ https://www.ncbi.nlm.nih.gov/pubmed/33462291 http://dx.doi.org/10.1038/s41598-020-80826-9 |
work_keys_str_mv | AT jeongjinuk theeffectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT yunkyeongeui theeffectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT munseyoung theeffectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT chungwonhyong theeffectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT choisongyi theeffectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT namyoungdo theeffectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT limmiyoung theeffectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT hongchangpyo theeffectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT parkchanhyeok theeffectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT ahnyongju theeffectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT hankyudong theeffectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT jeongjinuk effectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT yunkyeongeui effectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT munseyoung effectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT chungwonhyong effectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT choisongyi effectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT namyoungdo effectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT limmiyoung effectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT hongchangpyo effectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT parkchanhyeok effectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT ahnyongju effectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology AT hankyudong effectoftaxonomicclassificationbyfulllength16srrnasequencingwithasyntheticlongreadtechnology |