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MetaSort untangles metagenome assembly by reducing microbial community complexity

Most current approaches to analyse metagenomic data rely on reference genomes. Novel microbial communities extend far beyond the coverage of reference databases and de novo metagenome assembly from complex microbial communities remains a great challenge. Here we present a novel experimental and bioi...

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Detalles Bibliográficos
Autores principales: Ji, Peifeng, Zhang, Yanming, Wang, Jinfeng, Zhao, Fangqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5264255/
https://www.ncbi.nlm.nih.gov/pubmed/28112173
http://dx.doi.org/10.1038/ncomms14306
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author Ji, Peifeng
Zhang, Yanming
Wang, Jinfeng
Zhao, Fangqing
author_facet Ji, Peifeng
Zhang, Yanming
Wang, Jinfeng
Zhao, Fangqing
author_sort Ji, Peifeng
collection PubMed
description Most current approaches to analyse metagenomic data rely on reference genomes. Novel microbial communities extend far beyond the coverage of reference databases and de novo metagenome assembly from complex microbial communities remains a great challenge. Here we present a novel experimental and bioinformatic framework, metaSort, for effective construction of bacterial genomes from metagenomic samples. MetaSort provides a sorted mini-metagenome approach based on flow cytometry and single-cell sequencing methodologies, and employs new computational algorithms to efficiently recover high-quality genomes from the sorted mini-metagenome by the complementary of the original metagenome. Through extensive evaluations, we demonstrated that metaSort has an excellent and unbiased performance on genome recovery and assembly. Furthermore, we applied metaSort to an unexplored microflora colonized on the surface of marine kelp and successfully recovered 75 high-quality genomes at one time. This approach will greatly improve access to microbial genomes from complex or novel communities.
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spelling pubmed-52642552017-02-03 MetaSort untangles metagenome assembly by reducing microbial community complexity Ji, Peifeng Zhang, Yanming Wang, Jinfeng Zhao, Fangqing Nat Commun Article Most current approaches to analyse metagenomic data rely on reference genomes. Novel microbial communities extend far beyond the coverage of reference databases and de novo metagenome assembly from complex microbial communities remains a great challenge. Here we present a novel experimental and bioinformatic framework, metaSort, for effective construction of bacterial genomes from metagenomic samples. MetaSort provides a sorted mini-metagenome approach based on flow cytometry and single-cell sequencing methodologies, and employs new computational algorithms to efficiently recover high-quality genomes from the sorted mini-metagenome by the complementary of the original metagenome. Through extensive evaluations, we demonstrated that metaSort has an excellent and unbiased performance on genome recovery and assembly. Furthermore, we applied metaSort to an unexplored microflora colonized on the surface of marine kelp and successfully recovered 75 high-quality genomes at one time. This approach will greatly improve access to microbial genomes from complex or novel communities. Nature Publishing Group 2017-01-23 /pmc/articles/PMC5264255/ /pubmed/28112173 http://dx.doi.org/10.1038/ncomms14306 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Ji, Peifeng
Zhang, Yanming
Wang, Jinfeng
Zhao, Fangqing
MetaSort untangles metagenome assembly by reducing microbial community complexity
title MetaSort untangles metagenome assembly by reducing microbial community complexity
title_full MetaSort untangles metagenome assembly by reducing microbial community complexity
title_fullStr MetaSort untangles metagenome assembly by reducing microbial community complexity
title_full_unstemmed MetaSort untangles metagenome assembly by reducing microbial community complexity
title_short MetaSort untangles metagenome assembly by reducing microbial community complexity
title_sort metasort untangles metagenome assembly by reducing microbial community complexity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5264255/
https://www.ncbi.nlm.nih.gov/pubmed/28112173
http://dx.doi.org/10.1038/ncomms14306
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