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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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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. |
format | Online Article Text |
id | pubmed-6471839 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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