Metaproteomic analysis using the Galaxy framework
Metaproteomic analysis using the Galaxy framework
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DOI：
10.1002/pmic.201500074
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发表时间：
2015-10-01
期刊：
影响因子：
3.4
通讯作者：
Griffin, Timothy J.
中科院分区：
文献类型：
--
作者：
Jagtap, Pratik D.;Blakely, Alan;Griffin, Timothy J.
元蛋白质组学研究环境样品或宿主生物体(如人类)中微生物群落(微生物组)表达的蛋白质，揭示这些群落所赋予的分子功能。与传统的蛋白质组学相比，元蛋白质组学提出了独特的数据分析挑战，包括使用来自数百或数千个生物的大型蛋白质数据库，以及确保高数据质量的众多处理步骤。这些挑战限制了许多研究人员使用代谢蛋白质组学。作为回应，我们在银河生物信息学框架内开发了一个可访问和灵活的元蛋白质组学工作流程。通过对人类口腔组织渗出液样本的分析，我们建立了一个基于Galaxy的模块化工作流程，该工作流程自动化了用于搜索大型序列数据库的约简方法，从而能够全面识别宿主蛋白(人)以及来自非宿主生物的Meta蛋白。在下游，自动化处理步骤使基本的局部比对搜索工具能够分析和评估/可视化多肽序列匹配质量，从而最大限度地提高结果的可信度。输出的结果与分类和功能表征工具(如Unipept、MEGAN5)兼容。Galaxy还允许与其他人共享完整的工作流程，促进再现性，并为进一步修改和改进提供模板。我们的结果为建立Galaxy作为元蛋白质组数据分析解决方案提供了蓝图。所有MS数据都存放在ProteomeXchange中，标识符为PXD001655()。
Metaproteomics characterizes proteins expressed by microorganism communities (microbiome) present in environmental samples or a host organism (e.g. human), revealing insights into the molecular functions conferred by these communities. Compared to conventional proteomics, metaproteomics presents unique data analysis challenges, including the use of large protein databases derived from hundreds or thousands of organisms, as well as numerous processing steps to ensure high data quality. These challenges limit the use of metaproteomics for many researchers. In response, we have developed an accessible and flexible metaproteomics workflow within the Galaxy bioinformatics framework. Via analysis of human oral tissue exudate samples, we have established a modular Galaxy-based workflow that automates a reduction method for searching large sequence databases, enabling comprehensive identification of host proteins (human) as well as meta-proteins from the nonhost organisms. Downstream, automated processing steps enable basic local alignment search tool analysis and evaluation/visualization of peptide sequence match quality, maximizing confidence in results. Outputted results are compatible with tools for taxonomic and functional characterization (e.g. Unipept, MEGAN5). Galaxy also allows for the sharing of complete workflows with others, promoting reproducibility and also providing a template for further modification and enhancement. Our results provide a blueprint for establishing Galaxy as a solution for metaproteomic data analysis. All MS data have been deposited in the ProteomeXchange with identifier PXD001655 ().