Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 549961
Title Metaproteomic and 16S rRNA Gene Sequencing Analysis of the Infant Fecal Microbiome
Author(s) Cortes, Laetitia; Wopereis, Harm; Tartiere, Aude; Piquenot, Julie; Gouw, Joost W.; Tims, Sebastian; Knol, Jan; Chelsky, Daniel
Source International Journal of Molecular Sciences 20 (2019)6. - ISSN 1661-6596
DOI https://doi.org/10.3390/ijms20061430
Department(s) Microbiology
MolEco
VLAG
Publication type Refereed Article in a scientific journal
Publication year 2019
Keyword(s) fecal - infants - intestinal - mass spectrometry - metabolism - metacluster - microbiome
Abstract

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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