Literature DB >> 34905165

Sample Processing for Metaproteomic Analysis of Human Gut Microbiota.

Carmen García-Durán1, Raquel Martínez-López1, Lucía Monteoliva1, Concha Gil2,3.   

Abstract

Human gut microbiota can be studied through the characterization of microorganisms present in feces. Metaproteomics has arisen as a good approach to investigate this vast community. However, the processing of fecal samples in order to obtain the largest number of proteins from gut microbiota to be subsequently analyzed by means of metaproteomics is a challenge. Here we describe a protocol to approach this task. It includes two main steps: the first step of humectation and dispersion of the feces, followed by the separation of microorganisms from other fecal components such as roughage and food debris, and the second step in which microbial cells are broken up and microbiota proteins recovered for MS analysis. Detailed procedures for sample preparation, protein extraction, trypsin digestion, and mass spectrometry analysis for gut microbiota samples are provided.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Bead-beating; Fecal samples; Gut microbiota; Mass spectrometry; Metaproteomics; Sonication

Mesh:

Substances:

Year:  2022        PMID: 34905165     DOI: 10.1007/978-1-0716-1936-0_5

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  8 in total

1.  Unipept web services for metaproteomics analysis.

Authors:  Bart Mesuere; Toon Willems; Felix Van der Jeugt; Bart Devreese; Peter Vandamme; Peter Dawyndt
Journal:  Bioinformatics       Date:  2016-01-27       Impact factor: 6.937

2.  The MetaProteomeAnalyzer: a powerful open-source software suite for metaproteomics data analysis and interpretation.

Authors:  Thilo Muth; Alexander Behne; Robert Heyer; Fabian Kohrs; Dirk Benndorf; Marcus Hoffmann; Miro Lehtevä; Udo Reichl; Lennart Martens; Erdmann Rapp
Journal:  J Proteome Res       Date:  2015-02-23       Impact factor: 4.466

Review 3.  Gut microbiota and IBD: causation or correlation?

Authors:  Josephine Ni; Gary D Wu; Lindsey Albenberg; Vesselin T Tomov
Journal:  Nat Rev Gastroenterol Hepatol       Date:  2017-07-19       Impact factor: 46.802

4.  Gut microbiota associations with common diseases and prescription medications in a population-based cohort.

Authors:  Matthew A Jackson; Serena Verdi; Maria-Emanuela Maxan; Cheol Min Shin; Jonas Zierer; Ruth C E Bowyer; Tiphaine Martin; Frances M K Williams; Cristina Menni; Jordana T Bell; Tim D Spector; Claire J Steves
Journal:  Nat Commun       Date:  2018-07-09       Impact factor: 14.919

5.  Altered diversity and composition of the gut microbiome in patients with cervical cancer.

Authors:  Zhongqiu Wang; Qingxin Wang; Jing Zhao; Linlin Gong; Yan Zhang; Xia Wang; Zhiyong Yuan
Journal:  AMB Express       Date:  2019-03-23       Impact factor: 3.298

6.  MetaLab: an automated pipeline for metaproteomic data analysis.

Authors:  Kai Cheng; Zhibin Ning; Xu Zhang; Leyuan Li; Bo Liao; Janice Mayne; Alain Stintzi; Daniel Figeys
Journal:  Microbiome       Date:  2017-12-02       Impact factor: 14.650

Review 7.  Brain-Gut-Microbiota Axis in Alzheimer's Disease.

Authors:  Karol Kowalski; Agata Mulak
Journal:  J Neurogastroenterol Motil       Date:  2019-01-31       Impact factor: 4.924

8.  Survey of metaproteomics software tools for functional microbiome analysis.

Authors:  Ray Sajulga; Caleb Easterly; Michael Riffle; Bart Mesuere; Thilo Muth; Subina Mehta; Praveen Kumar; James Johnson; Bjoern Andreas Gruening; Henning Schiebenhoefer; Carolin A Kolmeder; Stephan Fuchs; Brook L Nunn; Joel Rudney; Timothy J Griffin; Pratik D Jagtap
Journal:  PLoS One       Date:  2020-11-10       Impact factor: 3.240

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.