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The Impact of Bioinformatics Pipelines on Microbiota Studies: Does the Analytical “Microscope” Affect the Biological Interpretation?

Targeted metagenomics is the solution of choice to reveal differential microbial profiles (defined by richness, diversity and composition) as part of case-control studies. It is well documented that each data processing step may have the potential to introduce bias in the results. However, selecting...

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Autores principales: Siegwald, Léa, Caboche, Ségolène, Even, Gaël, Viscogliosi, Eric, Audebert, Christophe, Chabé, Magali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6843237/
https://www.ncbi.nlm.nih.gov/pubmed/31561435
http://dx.doi.org/10.3390/microorganisms7100393
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author Siegwald, Léa
Caboche, Ségolène
Even, Gaël
Viscogliosi, Eric
Audebert, Christophe
Chabé, Magali
author_facet Siegwald, Léa
Caboche, Ségolène
Even, Gaël
Viscogliosi, Eric
Audebert, Christophe
Chabé, Magali
author_sort Siegwald, Léa
collection PubMed
description Targeted metagenomics is the solution of choice to reveal differential microbial profiles (defined by richness, diversity and composition) as part of case-control studies. It is well documented that each data processing step may have the potential to introduce bias in the results. However, selecting a bioinformatics pipeline to analyze high-throughput sequencing data from A to Z remains one of the critical considerations in a case-control microbiota study design. Consequently, the aim of this study was to assess whether the same biological conclusions regarding human gut microbiota composition and diversity could be reached using different bioinformatics pipelines. In this work, we considered four pipelines (mothur, QIIME, kraken and CLARK) with different versions and databases, and examined their impact on the outcome of metagenetic analysis of Ion Torrent 16S sequencing data. We re-analyzed a case-control study evaluating the impact of the colonization of the intestinal protozoa Blastocystis sp. on the human gut microbial profile. Although most pipelines reported the same trends in this case-control study, we demonstrated how the use of different pipelines affects the biological conclusions that can be drawn. Targeted metagenomics must therefore rather be considered as a profiling tool to obtain a broad sense of the variations of the microbiota, rather than an accurate identification tool.
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spelling pubmed-68432372019-11-25 The Impact of Bioinformatics Pipelines on Microbiota Studies: Does the Analytical “Microscope” Affect the Biological Interpretation? Siegwald, Léa Caboche, Ségolène Even, Gaël Viscogliosi, Eric Audebert, Christophe Chabé, Magali Microorganisms Article Targeted metagenomics is the solution of choice to reveal differential microbial profiles (defined by richness, diversity and composition) as part of case-control studies. It is well documented that each data processing step may have the potential to introduce bias in the results. However, selecting a bioinformatics pipeline to analyze high-throughput sequencing data from A to Z remains one of the critical considerations in a case-control microbiota study design. Consequently, the aim of this study was to assess whether the same biological conclusions regarding human gut microbiota composition and diversity could be reached using different bioinformatics pipelines. In this work, we considered four pipelines (mothur, QIIME, kraken and CLARK) with different versions and databases, and examined their impact on the outcome of metagenetic analysis of Ion Torrent 16S sequencing data. We re-analyzed a case-control study evaluating the impact of the colonization of the intestinal protozoa Blastocystis sp. on the human gut microbial profile. Although most pipelines reported the same trends in this case-control study, we demonstrated how the use of different pipelines affects the biological conclusions that can be drawn. Targeted metagenomics must therefore rather be considered as a profiling tool to obtain a broad sense of the variations of the microbiota, rather than an accurate identification tool. MDPI 2019-09-26 /pmc/articles/PMC6843237/ /pubmed/31561435 http://dx.doi.org/10.3390/microorganisms7100393 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Siegwald, Léa
Caboche, Ségolène
Even, Gaël
Viscogliosi, Eric
Audebert, Christophe
Chabé, Magali
The Impact of Bioinformatics Pipelines on Microbiota Studies: Does the Analytical “Microscope” Affect the Biological Interpretation?
title The Impact of Bioinformatics Pipelines on Microbiota Studies: Does the Analytical “Microscope” Affect the Biological Interpretation?
title_full The Impact of Bioinformatics Pipelines on Microbiota Studies: Does the Analytical “Microscope” Affect the Biological Interpretation?
title_fullStr The Impact of Bioinformatics Pipelines on Microbiota Studies: Does the Analytical “Microscope” Affect the Biological Interpretation?
title_full_unstemmed The Impact of Bioinformatics Pipelines on Microbiota Studies: Does the Analytical “Microscope” Affect the Biological Interpretation?
title_short The Impact of Bioinformatics Pipelines on Microbiota Studies: Does the Analytical “Microscope” Affect the Biological Interpretation?
title_sort impact of bioinformatics pipelines on microbiota studies: does the analytical “microscope” affect the biological interpretation?
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6843237/
https://www.ncbi.nlm.nih.gov/pubmed/31561435
http://dx.doi.org/10.3390/microorganisms7100393
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