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MAPLE:一种微生物组分析管道,可实现最佳肽搜索以及分类和功能比较分析。

MAPLE: A Microbiome Analysis Pipeline Enabling Optimal Peptide Search and Comparative Taxonomic and Functional Analysis.

机构信息

Department of Pharmaceutical Sciences, University of Maryland, School of Pharmacy, Baltimore, Maryland 21201, United States.

出版信息

J Proteome Res. 2021 May 7;20(5):2882-2894. doi: 10.1021/acs.jproteome.1c00114. Epub 2021 Apr 13.

Abstract

Metaproteomics by mass spectrometry (MS) is a powerful approach to profile a large number of proteins expressed by all organisms in a highly complex biological or ecological sample, which is able to provide a direct and quantitative assessment of the functional makeup of a microbiota. The human gastrointestinal microbiota has been found playing important roles in human physiology and health, and metaproteomics has been shown to shed light on multiple novel associations between microbiota and diseases. MS-powered proteomics generally relies on genome data to define search space. However, metaproteomics, which simultaneously analyzes all proteins from hundreds to thousands of species, faces significant challenges regarding database search and interpretation of results. To overcome these obstacles, we have developed a user-friendly microbiome analysis pipeline (MAPLE, freely downloadable at http://maple.rx.umaryland.edu/), which is able to define an optimal search space by inferring proteomes specific to samples following the principle of parsimony. MAPLE facilitates highly comparable or better peptide identification compared to a sample-specific metagenome-guided search. In addition, we implemented an automated peptide-centric enrichment analysis function in MAPLE to address issues of traditional protein-centric comparison, enabling straightforward and comprehensive comparison of taxonomic and functional makeup between microbiota.

摘要

基于质谱的宏蛋白质组学(MS)是一种强大的方法,可以对高度复杂的生物或生态样本中所有生物体表达的大量蛋白质进行分析,能够直接和定量评估微生物组的功能组成。人类胃肠道微生物组在人类生理学和健康中发挥着重要作用,宏蛋白质组学已经揭示了微生物组与疾病之间的多种新关联。基于 MS 的蛋白质组学通常依赖于基因组数据来定义搜索空间。然而,宏蛋白质组学同时分析来自数百到数千个物种的所有蛋白质,在数据库搜索和结果解释方面面临重大挑战。为了克服这些障碍,我们开发了一个用户友好的微生物组分析管道(MAPLE,可在 http://maple.rx.umaryland.edu/ 免费下载),它能够通过推断样本特异性蛋白质组来定义最佳搜索空间,遵循简约原则。MAPLE 能够实现比基于样本特异性宏基因组指导搜索更高的肽鉴定可比性或更好的肽鉴定。此外,我们在 MAPLE 中实现了自动化的基于肽的富集分析功能,以解决传统基于蛋白质的比较问题,能够在微生物组之间进行分类学和功能组成的直接和全面比较。

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