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发现蛋白质组学中无标记定量分析以及技术因素和蛋白质丰度自然变异的影响

Assessment of Label-Free Quantification in Discovery Proteomics and Impact of Technological Factors and Natural Variability of Protein Abundance.

作者信息

Al Shweiki Mhd Rami, Mönchgesang Susann, Majovsky Petra, Thieme Domenika, Trutschel Diana, Hoehenwarter Wolfgang

机构信息

Research Group Proteome Analytics, Leibniz Institute of Plant Biochemistry , Weinberg 3, 06120 Halle (Saale), Germany.

Department of Stress and Developmental Biology, Leibniz Institute of Plant Biochemistry , Weinberg 3, 06120 Halle (Saale), Germany.

出版信息

J Proteome Res. 2017 Apr 7;16(4):1410-1424. doi: 10.1021/acs.jproteome.6b00645. Epub 2017 Feb 28.

Abstract

We evaluated the state of label-free discovery proteomics focusing especially on technological contributions and contributions of naturally occurring differences in protein abundance to the intersample variability in protein abundance estimates in this highly peptide-centric technology. First, the performance of popular quantitative proteomics software, Proteome Discoverer, Scaffold, MaxQuant, and Progenesis QIP, was benchmarked using their default parameters and some modified settings. Beyond this, the intersample variability in protein abundance estimates was decomposed into variability introduced by the entire technology itself and variable protein amounts inherent to individual plants of the Arabidopsis thaliana Col-0 accession. The technical component was considerably higher than the biological intersample variability, suggesting an effect on the degree and validity of reported biological changes in protein abundance. Surprisingly, the biological variability, protein abundance estimates, and protein fold changes were recorded differently by the software used to quantify the proteins, warranting caution in the comparison of discovery proteomics results. As expected, ∼99% of the proteome was invariant in the isogenic plants in the absence of environmental factors; however, few proteins showed substantial quantitative variability. This naturally occurring variation between individual organisms can have an impact on the causality of reported protein fold changes.

摘要

我们评估了无标记发现蛋白质组学的现状,特别关注在这种高度以肽为中心的技术中,技术贡献以及蛋白质丰度的自然差异对蛋白质丰度估计中样本间变异性的贡献。首先,使用其默认参数和一些修改设置,对流行的定量蛋白质组学软件Proteome Discoverer、Scaffold、MaxQuant和Progenesis QIP的性能进行了基准测试。除此之外,蛋白质丰度估计中的样本间变异性被分解为由整个技术本身引入的变异性以及拟南芥Col-0生态型个体植物固有的可变蛋白质含量。技术成分显著高于生物学样本间变异性,这表明对报道的蛋白质丰度生物学变化的程度和有效性有影响。令人惊讶的是,用于定量蛋白质的软件对生物学变异性、蛋白质丰度估计和蛋白质倍数变化的记录不同,因此在比较发现蛋白质组学结果时需要谨慎。正如预期的那样,在没有环境因素的情况下,同基因植物中约99%的蛋白质组是不变的;然而,很少有蛋白质表现出显著的定量变异性。个体生物体之间这种自然发生的变异可能会对报道的蛋白质倍数变化的因果关系产生影响。

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