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Proteomes 2018, 6(1), 7; doi:10.3390/proteomes6010007

Disseminating Metaproteomic Informatics Capabilities and Knowledge Using the Galaxy-P Framework

1
Bioinformatics Group, Department of Computer Science, University of Freiburg, 79110 Freiburg im Breisgau, Germany
2
Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN 55455, USA
3
Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55455, USA
4
Institute of Biotechnology, University of Helsinki, 00014 Helsinki, Finland
5
Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
6
Computational Biology Group, Ghent University, Krijgslaan 281, B-9000 Ghent, Belgium
7
Department of Chemical & Systems Biology, Stanford University, Stanford, CA 94305, USA
8
Center for Bio/Molecular Science & Engineering, Naval Research Laboratory, Washington, DC 20375, USA
9
Bioinformatics Unit (MF1), Department for Methods Development and Research Infrastructure, Robert Koch Institute, 13353 Berlin, Germany
10
Department of Diagnostic and Biological Sciences, University of Minnesota, Minneapolis, MN 55455, USA
11
Porto Conte Ricerche Science and Technology Park of Sardinia, 07041 Alghero, Italy
*
Author to whom correspondence should be addressed.
Received: 11 December 2017 / Revised: 26 January 2018 / Accepted: 26 January 2018 / Published: 31 January 2018
(This article belongs to the Special Issue Metaproteomics)
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Abstract

The impact of microbial communities, also known as the microbiome, on human health and the environment is receiving increased attention. Studying translated gene products (proteins) and comparing metaproteomic profiles may elucidate how microbiomes respond to specific environmental stimuli, and interact with host organisms. Characterizing proteins expressed by a complex microbiome and interpreting their functional signature requires sophisticated informatics tools and workflows tailored to metaproteomics. Additionally, there is a need to disseminate these informatics resources to researchers undertaking metaproteomic studies, who could use them to make new and important discoveries in microbiome research. The Galaxy for proteomics platform (Galaxy-P) offers an open source, web-based bioinformatics platform for disseminating metaproteomics software and workflows. Within this platform, we have developed easily-accessible and documented metaproteomic software tools and workflows aimed at training researchers in their operation and disseminating the tools for more widespread use. The modular workflows encompass the core requirements of metaproteomic informatics: (a) database generation; (b) peptide spectral matching; (c) taxonomic analysis and (d) functional analysis. Much of the software available via the Galaxy-P platform was selected, packaged and deployed through an online metaproteomics “Contribution Fest“ undertaken by a unique consortium of expert software developers and users from the metaproteomics research community, who have co-authored this manuscript. These resources are documented on GitHub and freely available through the Galaxy Toolshed, as well as a publicly accessible metaproteomics gateway Galaxy instance. These documented workflows are well suited for the training of novice metaproteomics researchers, through online resources such as the Galaxy Training Network, as well as hands-on training workshops. Here, we describe the metaproteomics tools available within these Galaxy-based resources, as well as the process by which they were selected and implemented in our community-based work. We hope this description will increase access to and utilization of metaproteomics tools, as well as offer a framework for continued community-based development and dissemination of cutting edge metaproteomics software.
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Keywords: metaproteomics; functional microbiome; bioinformatics; software workflow development; Galaxy platform; mass spectrometry; community development metaproteomics; functional microbiome; bioinformatics; software workflow development; Galaxy platform; mass spectrometry; community development
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary materials

  • Supplementary File 1:

    Supplementary (PDF, 2252 KB)

  • Externally hosted supplementary file 1
    Link: https://z.umn.edu/supps1
    Description: Step-by-step training instructions for usage of the metaproteomics gateway and the tools and workflow.

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MDPI and ACS Style

Blank, C.; Easterly, C.; Gruening, B.; Johnson, J.; Kolmeder, C.A.; Kumar, P.; May, D.; Mehta, S.; Mesuere, B.; Brown, Z.; Elias, J.E.; Hervey, W.J.; McGowan, T.; Muth, T.; Nunn, B.L.; Rudney, J.; Tanca, A.; Griffin, T.J.; Jagtap, P.D. Disseminating Metaproteomic Informatics Capabilities and Knowledge Using the Galaxy-P Framework. Proteomes 2018, 6, 7.

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