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Data-Independent Acquisition Mass Spectrometry in Metaproteomics of Gut Microbiota-Implementation and Computational Analysis

机译:肠道微生物肿瘤的数组中的数据无关的采集质谱和计算分析

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Metagenomic approaches focus on taxonomy or gene annotation but lack power in defining functionality of gut microbiota. Therefore, metaproteomics approaches have been introduced to overcome this limitation. However, the common metaproteomics approach uses data-dependent acquisition mass spectrometry, which is known to have limited reproducibility when analyzing samples with complex microbial composition. In this work, we provide a proof of concept for data-independent acquisition (DIA) metaproteomics. To this end, we analyze metaproteomes using DIA mass spectrometry and introduce an open-source data analysis software package, diatools, which enables accurate and consistent quantification of DIA metaproteomics data. We demonstrate the feasibility of our approach in gut microbiota metaproteomics using laboratory-assembled microbial mixtures as well as human fecal samples.
机译:Metagenomic方法专注于分类学或基因注释,但缺乏肠道微生物肿瘤功能的力量。 因此,已经引入了标准族方法来克服这种限制。 然而,常见的元标术方法使用数据依赖性采集质谱法,该质谱法在分析具有复杂微生物组合物的样品时具有有限的再现性。 在这项工作中,我们为数据无关的采集(Dia)标准组科提供了一个概念证明。 为此,我们使用DIA质谱分析了Metaprootomes,引入了开源数据分析软件包,Diatools,这使得能够准确和一致地定量Dia Metaprootomics数据。 我们展示了使用实验室组装的微生物混合物以及人粪便样品在肠道微生物肿瘤的方法中的方法。

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