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迈向无标记发现工作流程中自上而下方法的常规应用。

Towards a routine application of Top-Down approaches for label-free discovery workflows.

机构信息

Bruker Daltonique S.A., 34, rue de l'industrie, 67160 Wissembourg, France.

Laboratoire de Biochimie et Protéomique Clinique, Institut de Médecine Régénératrice et de Biothérapie, CHU de Montpellier - Hôpital St. Eloi, 34000 Montpellier, France.

出版信息

J Proteomics. 2018 Mar 20;175:12-26. doi: 10.1016/j.jprot.2017.08.003. Epub 2017 Aug 30.

Abstract

UNLABELLED

Thanks to proteomics investigations, our vision of the role of different protein isoforms in the pathophysiology of diseases has largely evolved. The idea that protein biomarkers like tau, amyloid peptides, ApoE, cystatin, or neurogranin are represented in body fluids as single species is obviously over-simplified, as most proteins are present in different isoforms and subjected to numerous processing and post-translational modifications. Measuring the intact mass of proteins by MS has the advantage to provide information on the presence and relative amount of the different proteoforms. Such Top-Down approaches typically require a high degree of sample pre-fractionation to allow the MS system to deliver optimal performance in terms of dynamic range, mass accuracy and resolution. In clinical studies, however, the requirements for pre-analytical robustness and sample size large enough for statistical power restrict the routine use of a high degree of sample pre-fractionation. In this study, we have investigated the capacities of current-generation Ultra-High Resolution Q-Tof systems to deal with high complexity intact protein samples and have evaluated the approach on a cohort of patients suffering from neurodegenerative disease. Statistical analysis has shown that several proteoforms can be used to distinguish Alzheimer disease patients from patients suffering from other neurodegenerative disease.

SIGNIFICANCE

Top-down approaches have an extremely high biological relevance, especially when it comes to biomarker discovery, but the necessary pre-fractionation constraints are not easily compatible with the robustness requirements and the size of clinical sample cohorts. We have demonstrated that intact protein profiling studies could be run on UHR-Q-ToF with limited pre-fractionation. The proteoforms that have been identified as candidate biomarkers in the-proof-of concept study are derived from proteins known to play a role in the pathophysiology process of Alzheimer disease.

摘要

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由于蛋白质组学的研究,我们对不同蛋白质亚型在疾病病理生理学中的作用的认识有了很大的发展。蛋白质生物标志物,如 tau、淀粉样肽、ApoE、胱抑素或神经颗粒蛋白,作为单一物种存在于体液中的观点显然过于简单化,因为大多数蛋白质存在于不同的亚型中,并受到许多加工和翻译后修饰的影响。通过 MS 测量蛋白质的完整质量具有提供有关不同蛋白质亚型存在和相对含量的信息的优势。这种自上而下的方法通常需要高度的样品预分级,以使 MS 系统在动态范围、质量精度和分辨率方面达到最佳性能。然而,在临床研究中,对分析前稳健性和足够大的样本量以进行统计能力的要求限制了高程度样品预分级的常规使用。在这项研究中,我们研究了当前代超高分辨率 Q-Tof 系统处理高复杂性完整蛋白质样品的能力,并在患有神经退行性疾病的患者队列上评估了该方法。统计分析表明,几种蛋白质亚型可用于区分阿尔茨海默病患者和患有其他神经退行性疾病的患者。

意义

自上而下的方法具有极高的生物学相关性,尤其是在生物标志物发现方面,但必要的预分级限制与稳健性要求和临床样本队列的大小不兼容。我们已经证明,在有限的预分级下,可以在 UHR-Q-ToF 上进行完整蛋白质分析研究。在概念验证研究中被确定为候选生物标志物的蛋白质亚型来自已知在阿尔茨海默病病理生理学过程中发挥作用的蛋白质。

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