血浆蛋白质组学是人类疾病研究中的宝贵工具,但需要大量的样品制备才能使用传统的数据依赖性采集(DDA)进行深入分析和生物标志物发现。这里,我们强调了将中等程度的血浆分割和数据无关采集(DIA)相结合,可显著提高蛋白质组覆盖率和深度,同时保持成本效益的有效性.使用从20名COVID-19患者队列中收集的人血浆,我们的方法利用常用的解决方案来耗尽,样品制备,和分馏,然后进行3次液相色谱-质谱/MS(LC-MS/MS)注射,总DIA运行时间为360分钟。我们在每个患者中平均检测到1321种蛋白质,在整个队列中检测到2031种独特的蛋白质。差异分析进一步证明了该方法在血浆蛋白质组学研究和临床生物标志物鉴定中的适用性。在人血浆中鉴定数百种生物浓度低至47ng/L的差异丰富的蛋白质。数据可通过具有标识符PXD047901的ProteomeXchange获得。总之,这项研究引入了一个精简的,深度血浆蛋白质组分析的经济有效方法,将其效用扩展到经典研究环境之外,并在临床环境中实现更大规模的多组学研究。我们的比较分析表明,分馏,无论样品是合并还是单独的后分馏,显著提高了蛋白质定量的数量。这强调了分级在增强血浆蛋白质组分析深度中的价值,从而为在COVID-19等疾病中发现生物标志物提供了更全面的前景。
Plasma proteomics is a precious tool in human disease research but requires extensive sample preparation in order to perform in-depth analysis and biomarker discovery using traditional data-dependent acquisition (DDA). Here, we highlight the efficacy of combining moderate plasma prefractionation and data-independent acquisition (DIA) to significantly improve proteome coverage and depth while remaining cost-efficient. Using human plasma collected from a 20-patient COVID-19 cohort, our method utilizes commonly available solutions for depletion, sample preparation, and
fractionation, followed by 3 liquid chromatography-mass spectrometry/MS (LC-MS/MS) injections for a 360 min total DIA run time. We detect 1321 proteins on average per patient and 2031 unique proteins across the cohort. Differential analysis further demonstrates the applicability of this method for plasma proteomic research and clinical biomarker identification, identifying hundreds of differentially abundant proteins at biological concentrations as low as 47 ng/L in human plasma. Data are available via ProteomeXchange with the identifier PXD047901. In summary, this study introduces a streamlined, cost-effective approach to deep plasma proteome analysis, expanding its utility beyond classical research environments and enabling larger-scale multiomics investigations in clinical settings. Our comparative analysis revealed that
fractionation, whether the samples were pooled or separate postfractionation, significantly improved the number of proteins quantified. This underscores the value of
fractionation in enhancing the depth of plasma proteome analysis, thereby offering a more comprehensive landscape for biomarker discovery in diseases such as COVID-19.