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A High-Confidence Human Plasma Proteome Reference Set with Estimated Concentrations in PeptideAtlas

机译:估计浓度的PeptideAtlas高可信度人类血浆蛋白质组学参考集

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摘要

Human blood plasma can be obtained relatively noninva-sively and contains proteins from most, if not all, tissues of the body. Therefore, an extensive, quantitative catalog of plasma proteins is an important starting point for the discovery of disease biomarkers. In 2005, we showed that different proteomics measurements using different sample preparation and analysis techniques identify significantly different sets of proteins, and that a comprehensive plasma proteome can be compiled only by combining data from many different experiments. Applying advanced computational methods developed for the analysis and integration of very large and diverse data sets generated by tandem MS measurements of tryptic peptides, we have now compiled a high-confidence human plasma proteome reference set with well over twice the identified proteins of previous high-confidence sets. It includes a hierarchy of protein identifications at different levels of redundancy following a clearly defined scheme, which we propose as a standard that can be applied to any proteomics data set to facilitate cross-proteome analyses. Further, to aid in development of blood-based diagnostics using techniques such as selected reaction monitoring, we provide a rough estimate of protein concentrations using spectral counting. We identified 20,433 distinct peptides, from which we inferred a highly nonredundant set of 1929 protein sequences at a false discovery rate of 1%. We have made this resource available via PeptideAtlas, a large, multiorganism, publicly accessible compendium of peptides identified in tandem MS experiments conducted by laboratories around the world.
机译:人体血浆可以相对无创地获得,并且包含人体大部分(如果不是全部)组织中的蛋白质。因此,广泛,定量的血浆蛋白目录是发现疾病生物标志物的重要起点。在2005年,我们表明使用不同的样品制备和分析技术进行的不同蛋白质组学测量可识别出显着不同的蛋白质组,并且仅通过组合来自许多不同实验的数据就可以编译出完整的血浆蛋白质组。应用先进的计算方法来分析和整合通过串联MS测量胰蛋白酶肽产生的大量数据,我们现在已经建立了一个高可信度的人类血浆蛋白质组参考集,其鉴定的蛋白质是以前鉴定的高蛋白的两倍以上。置信集。它遵循明确定义的方案,包括在不同冗余级别的蛋白质鉴定的层次结构,我们建议将其作为可应用于任何蛋白质组学数据集的标准,以促进跨蛋白质组分析。此外,为了帮助使用诸如选择的反应监测之类的技术开发基于血液的诊断方法,我们使用光谱计数提供了蛋白质浓度的粗略估计。我们鉴定了20,433个不同的肽,从中我们以1%的错误发现率推断出高度非冗余的1929个蛋白质序列。我们已经通过PeptideAtlas提供了该资源,PeptideAtlas是一个大型的,可公开访问的大型肽汇编,该汇编在全球实验室进行的串联MS实验中得到了鉴定。

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