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Comparison of Bioinformatics Pipelines and Operating Systems for the Analyses of 16S rRNA Gene Amplicon Sequences in Human Fecal Samples
Amplicon high-throughput sequencing of 16S ribosomal RNA (rRNA) gene is currently the most widely used technique to investigate complex gut microbial communities. Microbial identification might be influenced by several factors, including the choice of bioinformatic pipelines, making comparisons acro...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7318847/ https://www.ncbi.nlm.nih.gov/pubmed/32636817 http://dx.doi.org/10.3389/fmicb.2020.01262 |
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author | Marizzoni, Moira Gurry, Thomas Provasi, Stefania Greub, Gilbert Lopizzo, Nicola Ribaldi, Federica Festari, Cristina Mazzelli, Monica Mombelli, Elisa Salvatore, Marco Mirabelli, Peppino Franzese, Monica Soricelli, Andrea Frisoni, Giovanni B. Cattaneo, Annamaria |
author_facet | Marizzoni, Moira Gurry, Thomas Provasi, Stefania Greub, Gilbert Lopizzo, Nicola Ribaldi, Federica Festari, Cristina Mazzelli, Monica Mombelli, Elisa Salvatore, Marco Mirabelli, Peppino Franzese, Monica Soricelli, Andrea Frisoni, Giovanni B. Cattaneo, Annamaria |
author_sort | Marizzoni, Moira |
collection | PubMed |
description | Amplicon high-throughput sequencing of 16S ribosomal RNA (rRNA) gene is currently the most widely used technique to investigate complex gut microbial communities. Microbial identification might be influenced by several factors, including the choice of bioinformatic pipelines, making comparisons across studies difficult. Here, we compared four commonly used pipelines (QIIME2, Bioconductor, UPARSE and mothur) run on two operating systems (OS) (Linux and Mac), to evaluate the impact of bioinformatic pipeline and OS on the taxonomic classification of 40 human stool samples. We applied the SILVA 132 reference database for all the pipelines. We compared phyla and genera identification and relative abundances across the four pipelines using the Friedman rank sum test. QIIME2 and Bioconductor provided identical outputs on Linux and Mac OS, while UPARSE and mothur reported only minimal differences between OS. Taxa assignments were consistent at both phylum and genus level across all the pipelines. However, a difference in terms of relative abundance was identified for all phyla (p < 0.013) and for the majority of the most abundant genera (p < 0.028), such as Bacteroides (QIIME2: 24.5%, Bioconductor: 24.6%, UPARSE-linux: 23.6%, UPARSE-mac: 20.6%, mothur-linux: 22.2%, mothur-mac: 21.6%, p < 0.001). The use of different bioinformatic pipelines affects the estimation of the relative abundance of gut microbial community, indicating that studies using different pipelines cannot be directly compared. A harmonization procedure is needed to move the field forward. |
format | Online Article Text |
id | pubmed-7318847 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73188472020-07-06 Comparison of Bioinformatics Pipelines and Operating Systems for the Analyses of 16S rRNA Gene Amplicon Sequences in Human Fecal Samples Marizzoni, Moira Gurry, Thomas Provasi, Stefania Greub, Gilbert Lopizzo, Nicola Ribaldi, Federica Festari, Cristina Mazzelli, Monica Mombelli, Elisa Salvatore, Marco Mirabelli, Peppino Franzese, Monica Soricelli, Andrea Frisoni, Giovanni B. Cattaneo, Annamaria Front Microbiol Microbiology Amplicon high-throughput sequencing of 16S ribosomal RNA (rRNA) gene is currently the most widely used technique to investigate complex gut microbial communities. Microbial identification might be influenced by several factors, including the choice of bioinformatic pipelines, making comparisons across studies difficult. Here, we compared four commonly used pipelines (QIIME2, Bioconductor, UPARSE and mothur) run on two operating systems (OS) (Linux and Mac), to evaluate the impact of bioinformatic pipeline and OS on the taxonomic classification of 40 human stool samples. We applied the SILVA 132 reference database for all the pipelines. We compared phyla and genera identification and relative abundances across the four pipelines using the Friedman rank sum test. QIIME2 and Bioconductor provided identical outputs on Linux and Mac OS, while UPARSE and mothur reported only minimal differences between OS. Taxa assignments were consistent at both phylum and genus level across all the pipelines. However, a difference in terms of relative abundance was identified for all phyla (p < 0.013) and for the majority of the most abundant genera (p < 0.028), such as Bacteroides (QIIME2: 24.5%, Bioconductor: 24.6%, UPARSE-linux: 23.6%, UPARSE-mac: 20.6%, mothur-linux: 22.2%, mothur-mac: 21.6%, p < 0.001). The use of different bioinformatic pipelines affects the estimation of the relative abundance of gut microbial community, indicating that studies using different pipelines cannot be directly compared. A harmonization procedure is needed to move the field forward. Frontiers Media S.A. 2020-06-17 /pmc/articles/PMC7318847/ /pubmed/32636817 http://dx.doi.org/10.3389/fmicb.2020.01262 Text en Copyright © 2020 Marizzoni, Gurry, Provasi, Greub, Lopizzo, Ribaldi, Festari, Mazzelli, Mombelli, Salvatore, Mirabelli, Franzese, Soricelli, Frisoni and Cattaneo. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Microbiology Marizzoni, Moira Gurry, Thomas Provasi, Stefania Greub, Gilbert Lopizzo, Nicola Ribaldi, Federica Festari, Cristina Mazzelli, Monica Mombelli, Elisa Salvatore, Marco Mirabelli, Peppino Franzese, Monica Soricelli, Andrea Frisoni, Giovanni B. Cattaneo, Annamaria Comparison of Bioinformatics Pipelines and Operating Systems for the Analyses of 16S rRNA Gene Amplicon Sequences in Human Fecal Samples |
title | Comparison of Bioinformatics Pipelines and Operating Systems for the Analyses of 16S rRNA Gene Amplicon Sequences in Human Fecal Samples |
title_full | Comparison of Bioinformatics Pipelines and Operating Systems for the Analyses of 16S rRNA Gene Amplicon Sequences in Human Fecal Samples |
title_fullStr | Comparison of Bioinformatics Pipelines and Operating Systems for the Analyses of 16S rRNA Gene Amplicon Sequences in Human Fecal Samples |
title_full_unstemmed | Comparison of Bioinformatics Pipelines and Operating Systems for the Analyses of 16S rRNA Gene Amplicon Sequences in Human Fecal Samples |
title_short | Comparison of Bioinformatics Pipelines and Operating Systems for the Analyses of 16S rRNA Gene Amplicon Sequences in Human Fecal Samples |
title_sort | comparison of bioinformatics pipelines and operating systems for the analyses of 16s rrna gene amplicon sequences in human fecal samples |
topic | Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7318847/ https://www.ncbi.nlm.nih.gov/pubmed/32636817 http://dx.doi.org/10.3389/fmicb.2020.01262 |
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