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ANCHOR: a 16S rRNA gene amplicon pipeline for microbial analysis of multiple environmental samples
Analysis of 16S ribosomal RNA (rRNA) gene amplification data for microbial barcoding can be inaccurate across complex environmental samples. A method, ANCHOR, is presented and designed for improved species‐level microbial identification using paired‐end sequences directly, multiple high‐complexity s...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6851558/ https://www.ncbi.nlm.nih.gov/pubmed/30990927 http://dx.doi.org/10.1111/1462-2920.14632 |
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author | Gonzalez, Emmanuel Pitre, Frederic E. Brereton, Nicholas J. B. |
author_facet | Gonzalez, Emmanuel Pitre, Frederic E. Brereton, Nicholas J. B. |
author_sort | Gonzalez, Emmanuel |
collection | PubMed |
description | Analysis of 16S ribosomal RNA (rRNA) gene amplification data for microbial barcoding can be inaccurate across complex environmental samples. A method, ANCHOR, is presented and designed for improved species‐level microbial identification using paired‐end sequences directly, multiple high‐complexity samples and multiple reference databases. A standard operating procedure (SOP) is reported alongside benchmarking against artificial, single sample and replicated mock data sets. The method is then directly tested using a real‐world data set from surface swabs of the International Space Station (ISS). Simple mock community analysis identified 100% of the expected species and 99% of expected gene copy variants (100% identical). A replicated mock community revealed similar or better numbers of expected species than MetaAmp, DADA2, Mothur and QIIME1. Analysis of the ISS microbiome identified 714 putative unique species/strains and differential abundance analysis distinguished significant differences between the Destiny module (U.S. laboratory) and Harmony module (sleeping quarters). Harmony was remarkably dominated by human gastrointestinal tract bacteria, similar to enclosed environments on earth; however, Destiny module bacteria also derived from nonhuman microbiome carriers present on the ISS, the laboratory's research animals. ANCHOR can help substantially improve sequence resolution of 16S rRNA gene amplification data within biologically replicated environmental experiments and integrated multidatabase annotation enhances interpretation of complex, nonreference microbiomes. |
format | Online Article Text |
id | pubmed-6851558 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-68515582019-11-18 ANCHOR: a 16S rRNA gene amplicon pipeline for microbial analysis of multiple environmental samples Gonzalez, Emmanuel Pitre, Frederic E. Brereton, Nicholas J. B. Environ Microbiol Research Articles Analysis of 16S ribosomal RNA (rRNA) gene amplification data for microbial barcoding can be inaccurate across complex environmental samples. A method, ANCHOR, is presented and designed for improved species‐level microbial identification using paired‐end sequences directly, multiple high‐complexity samples and multiple reference databases. A standard operating procedure (SOP) is reported alongside benchmarking against artificial, single sample and replicated mock data sets. The method is then directly tested using a real‐world data set from surface swabs of the International Space Station (ISS). Simple mock community analysis identified 100% of the expected species and 99% of expected gene copy variants (100% identical). A replicated mock community revealed similar or better numbers of expected species than MetaAmp, DADA2, Mothur and QIIME1. Analysis of the ISS microbiome identified 714 putative unique species/strains and differential abundance analysis distinguished significant differences between the Destiny module (U.S. laboratory) and Harmony module (sleeping quarters). Harmony was remarkably dominated by human gastrointestinal tract bacteria, similar to enclosed environments on earth; however, Destiny module bacteria also derived from nonhuman microbiome carriers present on the ISS, the laboratory's research animals. ANCHOR can help substantially improve sequence resolution of 16S rRNA gene amplification data within biologically replicated environmental experiments and integrated multidatabase annotation enhances interpretation of complex, nonreference microbiomes. John Wiley & Sons, Inc. 2019-05-21 2019-07 /pmc/articles/PMC6851558/ /pubmed/30990927 http://dx.doi.org/10.1111/1462-2920.14632 Text en © 2019 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Research Articles Gonzalez, Emmanuel Pitre, Frederic E. Brereton, Nicholas J. B. ANCHOR: a 16S rRNA gene amplicon pipeline for microbial analysis of multiple environmental samples |
title | ANCHOR: a 16S rRNA gene amplicon pipeline for microbial analysis of multiple environmental samples |
title_full | ANCHOR: a 16S rRNA gene amplicon pipeline for microbial analysis of multiple environmental samples |
title_fullStr | ANCHOR: a 16S rRNA gene amplicon pipeline for microbial analysis of multiple environmental samples |
title_full_unstemmed | ANCHOR: a 16S rRNA gene amplicon pipeline for microbial analysis of multiple environmental samples |
title_short | ANCHOR: a 16S rRNA gene amplicon pipeline for microbial analysis of multiple environmental samples |
title_sort | anchor: a 16s rrna gene amplicon pipeline for microbial analysis of multiple environmental samples |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6851558/ https://www.ncbi.nlm.nih.gov/pubmed/30990927 http://dx.doi.org/10.1111/1462-2920.14632 |
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