Literature DB >> 28663049

Challenges and perspectives of metaproteomic data analysis.

Robert Heyer1, Kay Schallert2, Roman Zoun3, Beatrice Becher4, Gunter Saake5, Dirk Benndorf6.   

Abstract

In nature microorganisms live in complex microbial communities. Comprehensive taxonomic and functional knowledge about microbial communities supports medical and technical application such as fecal diagnostics as well as operation of biogas plants or waste water treatment plants. Furthermore, microbial communities are crucial for the global carbon and nitrogen cycle in soil and in the ocean. Among the methods available for investigation of microbial communities, metaproteomics can approximate the activity of microorganisms by investigating the protein content of a sample. Although metaproteomics is a very powerful method, issues within the bioinformatic evaluation impede its success. In particular, construction of databases for protein identification, grouping of redundant proteins as well as taxonomic and functional annotation pose big challenges. Furthermore, growing amounts of data within a metaproteomics study require dedicated algorithms and software. This review summarizes recent metaproteomics software and addresses the introduced issues in detail.
Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Big data; Bioinformatics; Environmental proteomics; Mass spectrometry; Microbial communities; Software

Mesh:

Year:  2017        PMID: 28663049     DOI: 10.1016/j.jbiotec.2017.06.1201

Source DB:  PubMed          Journal:  J Biotechnol        ISSN: 0168-1656            Impact factor:   3.307


  34 in total

1.  metaQuantome: An Integrated, Quantitative Metaproteomics Approach Reveals Connections Between Taxonomy and Protein Function in Complex Microbiomes.

Authors:  Caleb W Easterly; Ray Sajulga; Subina Mehta; James Johnson; Praveen Kumar; Shane Hubler; Bart Mesuere; Joel Rudney; Timothy J Griffin; Pratik D Jagtap
Journal:  Mol Cell Proteomics       Date:  2019-06-24       Impact factor: 5.911

2.  A Meta-proteogenomic Approach to Peptide Identification Incorporating Assembly Uncertainty and Genomic Variation.

Authors:  Sujun Li; Haixu Tang; Yuzhen Ye
Journal:  Mol Cell Proteomics       Date:  2019-05-29       Impact factor: 5.911

3.  Metaproteomics Analysis of Host-Microbiota Interfaces.

Authors:  Sjoerd van der Post; Liisa Arike
Journal:  Methods Mol Biol       Date:  2021

4.  A complete and flexible workflow for metaproteomics data analysis based on MetaProteomeAnalyzer and Prophane.

Authors:  Henning Schiebenhoefer; Kay Schallert; Bernhard Y Renard; Kathrin Trappe; Emanuel Schmid; Dirk Benndorf; Katharina Riedel; Thilo Muth; Stephan Fuchs
Journal:  Nat Protoc       Date:  2020-08-28       Impact factor: 13.491

5.  Novel Bioinformatics Strategies Driving Dynamic Metaproteomic Studies.

Authors:  Caitlin M A Simopoulos; Daniel Figeys; Mathieu Lavallée-Adam
Journal:  Methods Mol Biol       Date:  2022

Review 6.  Metaproteomics of the human gut microbiota: Challenges and contributions to other OMICS.

Authors:  Ngom Issa Isaac; Decloquement Philippe; Armstrong Nicholas; Didier Raoult; Chabrière Eric
Journal:  Clin Mass Spectrom       Date:  2019-06-04

Review 7.  Progress and Challenges in Ocean Metaproteomics and Proposed Best Practices for Data Sharing.

Authors:  Mak A Saito; Erin M Bertrand; Megan E Duffy; David A Gaylord; Noelle A Held; William Judson Hervey; Robert L Hettich; Pratik D Jagtap; Michael G Janech; Danie B Kinkade; Dagmar H Leary; Matthew R McIlvin; Eli K Moore; Robert M Morris; Benjamin A Neely; Brook L Nunn; Jaclyn K Saunders; Adam I Shepherd; Nicholas I Symmonds; David A Walsh
Journal:  J Proteome Res       Date:  2019-03-12       Impact factor: 4.466

8.  ProteaseGuru: A Tool for Protease Selection in Bottom-Up Proteomics.

Authors:  Rachel M Miller; Khairina Ibrahim; Lloyd M Smith
Journal:  J Proteome Res       Date:  2021-03-04       Impact factor: 4.466

9.  Deep learning for peptide identification from metaproteomics datasets.

Authors:  Shichao Feng; Ryan Sterzenbach; Xuan Guo
Journal:  J Proteomics       Date:  2021-07-08       Impact factor: 3.855

Review 10.  Metaproteomic analysis of human gut microbiome in digestive and metabolic diseases.

Authors:  Sheng Pan; Ru Chen
Journal:  Adv Clin Chem       Date:  2020-02-17       Impact factor: 6.303

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