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High-resolution microbial community reconstruction by integrating short reads from multiple 16S rRNA regions

The emergence of massively parallel sequencing technology has revolutionized microbial profiling, allowing the unprecedented comparison of microbial diversity across time and space in a wide range of host-associated and environmental ecosystems. Although the high-throughput nature of such methods en...

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Autores principales: Amir, Amnon, Zeisel, Amit, Zuk, Or, Elgart, Michael, Stern, Shay, Shamir, Ohad, Turnbaugh, Peter J., Soen, Yoav, Shental, Noam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3905898/
https://www.ncbi.nlm.nih.gov/pubmed/24214960
http://dx.doi.org/10.1093/nar/gkt1070
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author Amir, Amnon
Zeisel, Amit
Zuk, Or
Elgart, Michael
Stern, Shay
Shamir, Ohad
Turnbaugh, Peter J.
Soen, Yoav
Shental, Noam
author_facet Amir, Amnon
Zeisel, Amit
Zuk, Or
Elgart, Michael
Stern, Shay
Shamir, Ohad
Turnbaugh, Peter J.
Soen, Yoav
Shental, Noam
author_sort Amir, Amnon
collection PubMed
description The emergence of massively parallel sequencing technology has revolutionized microbial profiling, allowing the unprecedented comparison of microbial diversity across time and space in a wide range of host-associated and environmental ecosystems. Although the high-throughput nature of such methods enables the detection of low-frequency bacteria, these advances come at the cost of sequencing read length, limiting the phylogenetic resolution possible by current methods. Here, we present a generic approach for integrating short reads from large genomic regions, thus enabling phylogenetic resolution far exceeding current methods. The approach is based on a mapping to a statistical model that is later solved as a constrained optimization problem. We demonstrate the utility of this method by analyzing human saliva and Drosophila samples, using Illumina single-end sequencing of a 750 bp amplicon of the 16S rRNA gene. Phylogenetic resolution is significantly extended while reducing the number of falsely detected bacteria, as compared with standard single-region Roche 454 Pyrosequencing. Our approach can be seamlessly applied to simultaneous sequencing of multiple genes providing a higher resolution view of the composition and activity of complex microbial communities.
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spelling pubmed-39058982014-01-29 High-resolution microbial community reconstruction by integrating short reads from multiple 16S rRNA regions Amir, Amnon Zeisel, Amit Zuk, Or Elgart, Michael Stern, Shay Shamir, Ohad Turnbaugh, Peter J. Soen, Yoav Shental, Noam Nucleic Acids Res Methods Online The emergence of massively parallel sequencing technology has revolutionized microbial profiling, allowing the unprecedented comparison of microbial diversity across time and space in a wide range of host-associated and environmental ecosystems. Although the high-throughput nature of such methods enables the detection of low-frequency bacteria, these advances come at the cost of sequencing read length, limiting the phylogenetic resolution possible by current methods. Here, we present a generic approach for integrating short reads from large genomic regions, thus enabling phylogenetic resolution far exceeding current methods. The approach is based on a mapping to a statistical model that is later solved as a constrained optimization problem. We demonstrate the utility of this method by analyzing human saliva and Drosophila samples, using Illumina single-end sequencing of a 750 bp amplicon of the 16S rRNA gene. Phylogenetic resolution is significantly extended while reducing the number of falsely detected bacteria, as compared with standard single-region Roche 454 Pyrosequencing. Our approach can be seamlessly applied to simultaneous sequencing of multiple genes providing a higher resolution view of the composition and activity of complex microbial communities. Oxford University Press 2013-12 2013-11-07 /pmc/articles/PMC3905898/ /pubmed/24214960 http://dx.doi.org/10.1093/nar/gkt1070 Text en © The Author(s) 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Methods Online
Amir, Amnon
Zeisel, Amit
Zuk, Or
Elgart, Michael
Stern, Shay
Shamir, Ohad
Turnbaugh, Peter J.
Soen, Yoav
Shental, Noam
High-resolution microbial community reconstruction by integrating short reads from multiple 16S rRNA regions
title High-resolution microbial community reconstruction by integrating short reads from multiple 16S rRNA regions
title_full High-resolution microbial community reconstruction by integrating short reads from multiple 16S rRNA regions
title_fullStr High-resolution microbial community reconstruction by integrating short reads from multiple 16S rRNA regions
title_full_unstemmed High-resolution microbial community reconstruction by integrating short reads from multiple 16S rRNA regions
title_short High-resolution microbial community reconstruction by integrating short reads from multiple 16S rRNA regions
title_sort high-resolution microbial community reconstruction by integrating short reads from multiple 16s rrna regions
topic Methods Online
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3905898/
https://www.ncbi.nlm.nih.gov/pubmed/24214960
http://dx.doi.org/10.1093/nar/gkt1070
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