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.
Highlights
Microbiome research has offered promising insights into microbial contributions to human health [1] and environmental dynamics [2]
Algorithms and strategies for matching MS/MS to peptide sequences by database searching have been modified to address this challenge—in particular, addressing the decreased sensitivity of peptide matches due to increased false discovery rates in large databases [18], and challenges of protein identity inference due to sharing of proteins across multiple organisms in the database. Another significant challenge presented by metaproteomic informatics is that many disparate, specialized software tools must be used within each of the core areas required for successful data analysis and interpretation
We introduce new resources aimed at increasing access to advanced metaproteomic informatics tools and facilitating training in their use, thereby breaking down the barriers that hold back many researchers seeking to utilize metaproteomics in their work
Summary
Microbiome research has offered promising insights into microbial contributions to human health [1] and environmental dynamics [2]. Algorithms and strategies for matching MS/MS to peptide sequences by database searching have been modified to address this challenge—in particular, addressing the decreased sensitivity of peptide matches due to increased false discovery rates in large databases [18], and challenges of protein identity inference due to sharing of proteins across multiple organisms in the database (e.g., the meta-protein concept in [22]) Another significant challenge presented by metaproteomic informatics is that many disparate, specialized software tools must be used within each of the core areas required for successful data analysis and interpretation. The accessible resources should help to increase wider adoption of metaproteomic informatics tools, as well as provide a framework for future collaborative efforts to make cutting-edge metaproteomic informatics tools available to the greater research community
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