Riffle Michael, May Damon H, Timmins-Schiffman Emma, Mikan Molly P, Jaschob Daniel, Noble William Stafford, Nunn Brook L
Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.
Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.
Proteomes. 2017 Dec 27;6(1):2. doi: 10.3390/proteomes6010002.
Metaproteomics is the characterization of all proteins being expressed by a community of organisms in a complex biological sample at a single point in time. Applications of metaproteomics range from the comparative analysis of environmental samples (such as ocean water and soil) to microbiome data from multicellular organisms (such as the human gut). Metaproteomics research is often focused on the quantitative functional makeup of the metaproteome and which organisms are making those proteins. That is: What are the functions of the currently expressed proteins? How much of the metaproteome is associated with those functions? And, which microorganisms are expressing the proteins that perform those functions? However, traditional protein-centric functional analysis is greatly complicated by the large size, redundancy, and lack of biological annotations for the protein sequences in the database used to search the data. To help address these issues, we have developed an algorithm and web application (dubbed "MetaGOmics") that automates the quantitative functional (using Gene Ontology) and taxonomic analysis of metaproteomics data and subsequent visualization of the results. MetaGOmics is designed to overcome the shortcomings of traditional proteomics analysis when used with metaproteomics data. It is easy to use, requires minimal input, and fully automates most steps of the analysis-including comparing the functional makeup between samples. MetaGOmics is freely available at https://www.yeastrc.org/metagomics/.
元蛋白质组学是对复杂生物样品中一个生物群落在某一时刻所表达的所有蛋白质进行表征。元蛋白质组学的应用范围从环境样品(如海水和土壤)的比较分析到多细胞生物(如人类肠道)的微生物组数据。元蛋白质组学研究通常聚焦于元蛋白质组的定量功能组成以及产生这些蛋白质的生物体。也就是说:当前表达的蛋白质有哪些功能?元蛋白质组中有多少与这些功能相关?以及,哪些微生物在表达执行这些功能的蛋白质?然而,传统的以蛋白质为中心的功能分析因用于搜索数据的数据库中蛋白质序列的庞大、冗余以及缺乏生物学注释而变得极为复杂。为帮助解决这些问题,我们开发了一种算法和网络应用程序(称为“MetaGOmics”),它能自动对元蛋白质组学数据进行定量功能(使用基因本体论)和分类分析,并随后对结果进行可视化。MetaGOmics旨在克服传统蛋白质组学分析在与元蛋白质组学数据结合使用时的缺点。它易于使用,所需输入最少,并且能完全自动化分析的大多数步骤,包括比较样品之间的功能组成。可在https://www.yeastrc.org/metagomics/免费获取MetaGOmics。