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Analysis of the Cystic Fibrosis Lung Microbiota via Serial Illumina Sequencing of Bacterial 16S rRNA Hypervariable Regions

The characterization of bacterial communities using DNA sequencing has revolutionized our ability to study microbes in nature and discover the ways in which microbial communities affect ecosystem functioning and human health. Here we describe Serial Illumina Sequencing (SI-Seq): a method for deep se...

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Detalles Bibliográficos
Autores principales: Maughan, Heather, Wang, Pauline W., Diaz Caballero, Julio, Fung, Pauline, Gong, Yunchen, Donaldson, Sylva L., Yuan, Lijie, Keshavjee, Shaf, Zhang, Yu, Yau, Yvonne C. W., Waters, Valerie J., Tullis, D. Elizabeth, Hwang, David M., Guttman, David S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3462755/
https://www.ncbi.nlm.nih.gov/pubmed/23056217
http://dx.doi.org/10.1371/journal.pone.0045791
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author Maughan, Heather
Wang, Pauline W.
Diaz Caballero, Julio
Fung, Pauline
Gong, Yunchen
Donaldson, Sylva L.
Yuan, Lijie
Keshavjee, Shaf
Zhang, Yu
Yau, Yvonne C. W.
Waters, Valerie J.
Tullis, D. Elizabeth
Hwang, David M.
Guttman, David S.
author_facet Maughan, Heather
Wang, Pauline W.
Diaz Caballero, Julio
Fung, Pauline
Gong, Yunchen
Donaldson, Sylva L.
Yuan, Lijie
Keshavjee, Shaf
Zhang, Yu
Yau, Yvonne C. W.
Waters, Valerie J.
Tullis, D. Elizabeth
Hwang, David M.
Guttman, David S.
author_sort Maughan, Heather
collection PubMed
description The characterization of bacterial communities using DNA sequencing has revolutionized our ability to study microbes in nature and discover the ways in which microbial communities affect ecosystem functioning and human health. Here we describe Serial Illumina Sequencing (SI-Seq): a method for deep sequencing of the bacterial 16S rRNA gene using next-generation sequencing technology. SI-Seq serially sequences portions of the V5, V6 and V7 hypervariable regions from barcoded 16S rRNA amplicons using an Illumina short-read genome analyzer. SI-Seq obtains taxonomic resolution similar to 454 pyrosequencing for a fraction of the cost, and can produce hundreds of thousands of reads per sample even with very high multiplexing. We validated SI-Seq using single species and mock community controls, and via a comparison to cystic fibrosis lung microbiota sequenced using 454 FLX Titanium. Our control runs show that SI-Seq has a dynamic range of at least five orders of magnitude, can classify >96% of sequences to the genus level, and performs just as well as 454 and paired-end Illumina methods in estimation of standard microbial ecology diversity measurements. We illustrate the utility of SI-Seq in a pilot sample of central airway secretion samples from cystic fibrosis patients.
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spelling pubmed-34627552012-10-10 Analysis of the Cystic Fibrosis Lung Microbiota via Serial Illumina Sequencing of Bacterial 16S rRNA Hypervariable Regions Maughan, Heather Wang, Pauline W. Diaz Caballero, Julio Fung, Pauline Gong, Yunchen Donaldson, Sylva L. Yuan, Lijie Keshavjee, Shaf Zhang, Yu Yau, Yvonne C. W. Waters, Valerie J. Tullis, D. Elizabeth Hwang, David M. Guttman, David S. PLoS One Research Article The characterization of bacterial communities using DNA sequencing has revolutionized our ability to study microbes in nature and discover the ways in which microbial communities affect ecosystem functioning and human health. Here we describe Serial Illumina Sequencing (SI-Seq): a method for deep sequencing of the bacterial 16S rRNA gene using next-generation sequencing technology. SI-Seq serially sequences portions of the V5, V6 and V7 hypervariable regions from barcoded 16S rRNA amplicons using an Illumina short-read genome analyzer. SI-Seq obtains taxonomic resolution similar to 454 pyrosequencing for a fraction of the cost, and can produce hundreds of thousands of reads per sample even with very high multiplexing. We validated SI-Seq using single species and mock community controls, and via a comparison to cystic fibrosis lung microbiota sequenced using 454 FLX Titanium. Our control runs show that SI-Seq has a dynamic range of at least five orders of magnitude, can classify >96% of sequences to the genus level, and performs just as well as 454 and paired-end Illumina methods in estimation of standard microbial ecology diversity measurements. We illustrate the utility of SI-Seq in a pilot sample of central airway secretion samples from cystic fibrosis patients. Public Library of Science 2012-10-02 /pmc/articles/PMC3462755/ /pubmed/23056217 http://dx.doi.org/10.1371/journal.pone.0045791 Text en © 2012 Maughan 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Maughan, Heather
Wang, Pauline W.
Diaz Caballero, Julio
Fung, Pauline
Gong, Yunchen
Donaldson, Sylva L.
Yuan, Lijie
Keshavjee, Shaf
Zhang, Yu
Yau, Yvonne C. W.
Waters, Valerie J.
Tullis, D. Elizabeth
Hwang, David M.
Guttman, David S.
Analysis of the Cystic Fibrosis Lung Microbiota via Serial Illumina Sequencing of Bacterial 16S rRNA Hypervariable Regions
title Analysis of the Cystic Fibrosis Lung Microbiota via Serial Illumina Sequencing of Bacterial 16S rRNA Hypervariable Regions
title_full Analysis of the Cystic Fibrosis Lung Microbiota via Serial Illumina Sequencing of Bacterial 16S rRNA Hypervariable Regions
title_fullStr Analysis of the Cystic Fibrosis Lung Microbiota via Serial Illumina Sequencing of Bacterial 16S rRNA Hypervariable Regions
title_full_unstemmed Analysis of the Cystic Fibrosis Lung Microbiota via Serial Illumina Sequencing of Bacterial 16S rRNA Hypervariable Regions
title_short Analysis of the Cystic Fibrosis Lung Microbiota via Serial Illumina Sequencing of Bacterial 16S rRNA Hypervariable Regions
title_sort analysis of the cystic fibrosis lung microbiota via serial illumina sequencing of bacterial 16s rrna hypervariable regions
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3462755/
https://www.ncbi.nlm.nih.gov/pubmed/23056217
http://dx.doi.org/10.1371/journal.pone.0045791
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