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生物信息学在宏蛋白质组学中的进展和应用,有助于弥合微生物群落中基因组序列和代谢功能之间的差距。

Bioinformatic progress and applications in metaproteogenomics for bridging the gap between genomic sequences and metabolic functions in microbial communities.

机构信息

Department of Proteomics, UFZ-Helmholtz Centre for Environmental Research, Leipzig, Germany; Institute of Animal Nutrition, University of Hohenheim, Stuttgart, Germany.

出版信息

Proteomics. 2013 Oct;13(18-19):2786-804. doi: 10.1002/pmic.201200566. Epub 2013 Aug 7.

Abstract

Metaproteomics of microbial communities promises to add functional information to the blueprint of genes derived from metagenomics. Right from its beginning, the achievements and developments in metaproteomics were closely interlinked with metagenomics. In addition, the evaluation, visualization, and interpretation of metaproteome data demanded for the developments in bioinformatics. This review will give an overview about recent strategies to use genomic data either from public databases or organismal specific genomes/metagenomes to increase the number of identified proteins obtained by mass spectrometric measurements. We will review different published metaproteogenomic approaches in respect to the used MS pipeline and to the used protein identification workflow. Furthermore, different approaches of data visualization and strategies for phylogenetic interpretation of metaproteome data are discussed as well as approaches for functional mapping of the results to the investigated biological systems. This information will in the end allow a comprehensive analysis of interactions and interdependencies within microbial communities.

摘要

微生物群落的宏蛋白质组学有望为基于宏基因组学的基因蓝图添加功能信息。从一开始,宏蛋白质组学的成就和发展就与宏基因组学紧密相连。此外,生物信息学的发展需要对宏蛋白质组数据进行评估、可视化和解释。这篇综述将概述最近的策略,即利用来自公共数据库或特定于生物体的基因组/宏基因组的基因组数据来增加通过质谱测量获得的鉴定蛋白的数量。我们将回顾不同的已发表的宏蛋白质组学方法,包括所使用的 MS 分析流程和蛋白鉴定工作流程。此外,还讨论了不同的数据可视化方法和用于宏蛋白质组数据分析的系统发育解释策略,以及将结果映射到所研究的生物系统的功能方法。这些信息最终将允许对微生物群落内部的相互作用和相互依存关系进行全面分析。

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