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A Method for Comprehensive Proteomic Analysis of Human Faecal Samples to Investigate Gut Dysbiosis in Patients with Cystic Fibrosis

  • Griet Debyser
  • Maarten Aerts
  • Pieter Van Hecke
  • Bart Mesuere
  • Gwen Duytschaever
  • Peter Dawyndt
  • Kris De Boeck
  • Peter Vandamme
  • Bart DevreeseEmail author
Chapter
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 1073)

Abstract

Background: This chapter reports the evaluation of two shotgun metaproteomic workflows. The methods were developed to investigate gut dysbiosis via analysis of the faecal microbiota from patients with cystic fibrosis (CF). We aimed to set up an unbiased and effective method to extract the entire proteome, i.e. to extract sufficient bacterial proteins from the faecal samples in combination with a maximum of host proteins giving information on the disease state.

Methods: Two protocols were compared; the first method involves an enrichment of the bacterial proteins while the second method is a more direct method to generate a whole faecal proteome extract. The different extracts were analysed using denaturing polyacrylamide gel electrophoresis followed by liquid chromatography-tandem mass spectrometry aiming a maximal coverage of the bacterial protein content in faecal samples.

Results and conclusions: In all extracts, microbial proteins are detected, and in addition, nonbacterial proteins are detected in all samples providing information about the host status. Our study demonstrates the huge influence of the used protein extraction method on the obtained result and shows the need for a standardised and appropriate sample preparation for metaproteomic analysis. To address questions on the health status of the patients, a whole protein extract is preferred over a method to enrich the bacterial fraction. In addition, the method of the whole protein fraction is faster, which gives the possibility to analyse more biological replicates.

Notes

Acknowledgements

This research was supported by grant G.0638.10 from Research Foundation Flanders (FWO). PD acknowledges the support of Ghent University (MRP Bioinformatics: from nucleotides to networks). The authors thank Dr. Kris Moreel for the generous help with the LC-MS/MS analyses on the FT-ICR-MS.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Griet Debyser
    • 1
  • Maarten Aerts
    • 1
  • Pieter Van Hecke
    • 1
  • Bart Mesuere
    • 2
  • Gwen Duytschaever
    • 1
  • Peter Dawyndt
    • 2
  • Kris De Boeck
    • 3
  • Peter Vandamme
    • 1
  • Bart Devreese
    • 1
    Email author
  1. 1.Department of Biochemistry and MicrobiologyGhent UniversityGhentBelgium
  2. 2.Department of Applied Mathematics, Computer Science and StatisticsGhent UniversityGhentBelgium
  3. 3.Department of PediatricsUniversity Hospital of LeuvenLeuvenBelgium

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