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Obtaining long 16S rDNA sequences using multiple primers and its application on dioxin-containing samples
BACKGROUND: Next-generation sequencing (NGS) technology has transformed metagenomics because the high-throughput data allow an in-depth exploration of a complex microbial community. However, accurate species identification with NGS data is challenging because NGS sequences are relatively short. Asse...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4682383/ https://www.ncbi.nlm.nih.gov/pubmed/26681335 http://dx.doi.org/10.1186/1471-2105-16-S18-S13 |
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author | Chen, Yi-Lin Lee, Chuan-Chun Lin, Ya-Lan Yin, Kai-Min Ho, Chung-Liang Liu, Tsunglin |
author_facet | Chen, Yi-Lin Lee, Chuan-Chun Lin, Ya-Lan Yin, Kai-Min Ho, Chung-Liang Liu, Tsunglin |
author_sort | Chen, Yi-Lin |
collection | PubMed |
description | BACKGROUND: Next-generation sequencing (NGS) technology has transformed metagenomics because the high-throughput data allow an in-depth exploration of a complex microbial community. However, accurate species identification with NGS data is challenging because NGS sequences are relatively short. Assembling 16S rDNA segments into longer sequences has been proposed for improving species identification. Current approaches, however, either suffer from amplification bias due to one single primer or insufficient 16S rDNA reads in whole genome sequencing data. RESULTS: Multiple primers were used to amplify different 16S rDNA segments for 454 sequencing, followed by 454 read classification and assembly. This permitted targeted sequencing while reducing primer bias. For test samples containing four known bacteria, accurate and near full-length 16S rDNAs of three known bacteria were obtained. For real soil and sediment samples containing dioxins in various concentrations, 16S rDNA sequences were lengthened by 50% for about half of the non-rare microbes, and 16S rDNAs of several microbes reached more than 1000 bp. In addition, reduced primer bias using multiple primers was illustrated. CONCLUSIONS: A new experimental and computational pipeline for obtaining long 16S rDNA sequences was proposed. The capability of the pipeline was validated on test samples and illustrated on real samples. For dioxin-containing samples, the pipeline revealed several microbes suitable for future studies of dioxin chemistry. |
format | Online Article Text |
id | pubmed-4682383 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-46823832015-12-21 Obtaining long 16S rDNA sequences using multiple primers and its application on dioxin-containing samples Chen, Yi-Lin Lee, Chuan-Chun Lin, Ya-Lan Yin, Kai-Min Ho, Chung-Liang Liu, Tsunglin BMC Bioinformatics Research BACKGROUND: Next-generation sequencing (NGS) technology has transformed metagenomics because the high-throughput data allow an in-depth exploration of a complex microbial community. However, accurate species identification with NGS data is challenging because NGS sequences are relatively short. Assembling 16S rDNA segments into longer sequences has been proposed for improving species identification. Current approaches, however, either suffer from amplification bias due to one single primer or insufficient 16S rDNA reads in whole genome sequencing data. RESULTS: Multiple primers were used to amplify different 16S rDNA segments for 454 sequencing, followed by 454 read classification and assembly. This permitted targeted sequencing while reducing primer bias. For test samples containing four known bacteria, accurate and near full-length 16S rDNAs of three known bacteria were obtained. For real soil and sediment samples containing dioxins in various concentrations, 16S rDNA sequences were lengthened by 50% for about half of the non-rare microbes, and 16S rDNAs of several microbes reached more than 1000 bp. In addition, reduced primer bias using multiple primers was illustrated. CONCLUSIONS: A new experimental and computational pipeline for obtaining long 16S rDNA sequences was proposed. The capability of the pipeline was validated on test samples and illustrated on real samples. For dioxin-containing samples, the pipeline revealed several microbes suitable for future studies of dioxin chemistry. BioMed Central 2015-12-09 /pmc/articles/PMC4682383/ /pubmed/26681335 http://dx.doi.org/10.1186/1471-2105-16-S18-S13 Text en Copyright © 2015 Chen et al. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Chen, Yi-Lin Lee, Chuan-Chun Lin, Ya-Lan Yin, Kai-Min Ho, Chung-Liang Liu, Tsunglin Obtaining long 16S rDNA sequences using multiple primers and its application on dioxin-containing samples |
title | Obtaining long 16S rDNA sequences using multiple primers and its application on dioxin-containing samples |
title_full | Obtaining long 16S rDNA sequences using multiple primers and its application on dioxin-containing samples |
title_fullStr | Obtaining long 16S rDNA sequences using multiple primers and its application on dioxin-containing samples |
title_full_unstemmed | Obtaining long 16S rDNA sequences using multiple primers and its application on dioxin-containing samples |
title_short | Obtaining long 16S rDNA sequences using multiple primers and its application on dioxin-containing samples |
title_sort | obtaining long 16s rdna sequences using multiple primers and its application on dioxin-containing samples |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4682383/ https://www.ncbi.nlm.nih.gov/pubmed/26681335 http://dx.doi.org/10.1186/1471-2105-16-S18-S13 |
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