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从大型数据库中进行迭代搜索以解释大型人类肠道宏蛋白质组数据集的优势。

Benefits of Iterative Searches of Large Databases to Interpret Large Human Gut Metaproteomic Data Sets.

机构信息

Université Paris-Saclay, INRAE, MGP, 78350, Jouy-en-Josas, France.

Université Paris-Saclay, INRAE, AgroParisTech, Micalis Institute, 78350, Jouy-en-Josas, France.

出版信息

J Proteome Res. 2021 Mar 5;20(3):1522-1534. doi: 10.1021/acs.jproteome.0c00669. Epub 2021 Feb 2.

Abstract

The gut microbiota are increasingly considered as a main partner of human health. Metaproteomics enables us to move from the functional potential revealed by metagenomics to the functions actually operating in the microbiome. However, metaproteome deciphering remains challenging. In particular, confident interpretation of a myriad of MS/MS spectra can only be pursued with smart database searches. Here, we compare the interpretation of MS/MS data sets from 48 individual human gut microbiomes using three interrogation strategies of the dedicated Integrated nonredundant Gene Catalog (IGC 9.9 million genes from 1267 individual fecal samples) together with the database: the classical single-step interrogation strategy and two iterative strategies (in either two or three steps) aimed at preselecting a reduced-sized, more targeted search space for the final peptide spectrum matching. Both iterative searches outperformed the single-step classical search in terms of the number of peptides and protein clusters identified and the depth of taxonomic and functional knowledge, and this was the most convincing with the three-step approach. However, iterative searches do not help in reducing variability of repeated analyses, which is inherent to the traditional data-dependent acquisition mode, but this variability did not affect the hierarchical relationship between replicates and all other samples.

摘要

肠道微生物群越来越被认为是人类健康的主要伙伴。代谢蛋白质组学使我们能够从宏基因组学揭示的功能潜力转向微生物组中实际运作的功能。然而,代谢蛋白质组的破译仍然具有挑战性。特别是,只有通过智能数据库搜索才能对大量 MS/MS 光谱进行可靠的解释。在这里,我们使用三种针对专用的整合非冗余基因目录(来自 1267 个粪便样本的 990 万个基因)和数据库的检索策略来比较 48 个人类肠道微生物组的 MS/MS 数据集的解释:经典的单步检索策略和两种迭代策略(两步或三步),旨在为最终的肽谱匹配预先选择更小的、更有针对性的搜索空间。就鉴定的肽和蛋白质簇的数量以及分类和功能知识的深度而言,两种迭代搜索均优于单步经典搜索,三步搜索方法的效果最为明显。然而,迭代搜索并不能帮助减少传统数据依赖采集模式固有的重复分析的可变性,但这种可变性不会影响重复样本与所有其他样本之间的层次关系。

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