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Metaproteomic and 16S rRNA Gene Sequencing Analysis of the Infant Fecal Microbiome

A metaproteomic analysis was conducted on the fecal microbiome of eight infants to characterize global protein and pathway expression. Although mass spectrometry-based proteomics is now a routine tool, analysis of the microbiome presents specific technical challenges, including the complexity and dy...

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Autores principales: Cortes, Laetitia, Wopereis, Harm, Tartiere, Aude, Piquenot, Julie, Gouw, Joost W., Tims, Sebastian, Knol, Jan, Chelsky, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6471839/
https://www.ncbi.nlm.nih.gov/pubmed/30901843
http://dx.doi.org/10.3390/ijms20061430
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author Cortes, Laetitia
Wopereis, Harm
Tartiere, Aude
Piquenot, Julie
Gouw, Joost W.
Tims, Sebastian
Knol, Jan
Chelsky, Daniel
author_facet Cortes, Laetitia
Wopereis, Harm
Tartiere, Aude
Piquenot, Julie
Gouw, Joost W.
Tims, Sebastian
Knol, Jan
Chelsky, Daniel
author_sort Cortes, Laetitia
collection PubMed
description A metaproteomic analysis was conducted on the fecal microbiome of eight infants to characterize global protein and pathway expression. Although mass spectrometry-based proteomics is now a routine tool, analysis of the microbiome presents specific technical challenges, including the complexity and dynamic range of member taxa, the need for well-annotated metagenomic databases, and high inter-protein sequence redundancy and similarity. In this study, an approach was developed for assessment of biological phenotype and metabolic status, as a functional complement to DNA sequence analysis. Fecal samples were prepared and analysed by tandem mass spectrometry and a homology-based meta-clustering strategy was used to combine peptides from multiple species into representative proteins. In total, 15,250 unique peptides were sequenced and assigned to 2154 metaclusters, which were then assigned to pathways and functional groups. Differences were noted in several pathways, consistent with the dominant genera observed in different subjects. Although this study was not powered to draw conclusions from the comparisons, the results obtained demonstrate the applicability of this approach and provide the methods needed for performing semi-quantitative comparisons of human fecal microbiome composition, physiology and metabolism, as well as a more detailed assessment of microbial composition in comparison to 16S rRNA gene sequencing.
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spelling pubmed-64718392019-04-26 Metaproteomic and 16S rRNA Gene Sequencing Analysis of the Infant Fecal Microbiome Cortes, Laetitia Wopereis, Harm Tartiere, Aude Piquenot, Julie Gouw, Joost W. Tims, Sebastian Knol, Jan Chelsky, Daniel Int J Mol Sci Article A metaproteomic analysis was conducted on the fecal microbiome of eight infants to characterize global protein and pathway expression. Although mass spectrometry-based proteomics is now a routine tool, analysis of the microbiome presents specific technical challenges, including the complexity and dynamic range of member taxa, the need for well-annotated metagenomic databases, and high inter-protein sequence redundancy and similarity. In this study, an approach was developed for assessment of biological phenotype and metabolic status, as a functional complement to DNA sequence analysis. Fecal samples were prepared and analysed by tandem mass spectrometry and a homology-based meta-clustering strategy was used to combine peptides from multiple species into representative proteins. In total, 15,250 unique peptides were sequenced and assigned to 2154 metaclusters, which were then assigned to pathways and functional groups. Differences were noted in several pathways, consistent with the dominant genera observed in different subjects. Although this study was not powered to draw conclusions from the comparisons, the results obtained demonstrate the applicability of this approach and provide the methods needed for performing semi-quantitative comparisons of human fecal microbiome composition, physiology and metabolism, as well as a more detailed assessment of microbial composition in comparison to 16S rRNA gene sequencing. MDPI 2019-03-21 /pmc/articles/PMC6471839/ /pubmed/30901843 http://dx.doi.org/10.3390/ijms20061430 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
Cortes, Laetitia
Wopereis, Harm
Tartiere, Aude
Piquenot, Julie
Gouw, Joost W.
Tims, Sebastian
Knol, Jan
Chelsky, Daniel
Metaproteomic and 16S rRNA Gene Sequencing Analysis of the Infant Fecal Microbiome
title Metaproteomic and 16S rRNA Gene Sequencing Analysis of the Infant Fecal Microbiome
title_full Metaproteomic and 16S rRNA Gene Sequencing Analysis of the Infant Fecal Microbiome
title_fullStr Metaproteomic and 16S rRNA Gene Sequencing Analysis of the Infant Fecal Microbiome
title_full_unstemmed Metaproteomic and 16S rRNA Gene Sequencing Analysis of the Infant Fecal Microbiome
title_short Metaproteomic and 16S rRNA Gene Sequencing Analysis of the Infant Fecal Microbiome
title_sort metaproteomic and 16s rrna gene sequencing analysis of the infant fecal microbiome
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6471839/
https://www.ncbi.nlm.nih.gov/pubmed/30901843
http://dx.doi.org/10.3390/ijms20061430
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