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差速超速离心通过富集细胞外囊泡实现深度血浆蛋白质组学分析。

Differential ultracentrifugation enables deep plasma proteomics through enrichment of extracellular vesicles.

作者信息

Kverneland Anders H, Østergaard Ole, Emdal Kristina Bennet, Svane Inge Marie, Olsen Jesper Velgaard

机构信息

Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.

National Center of Cancer Immune Therapy, Department of Oncology, Copenhagen University Hospital - Herlev and Gentofte, Herlev, Denmark.

出版信息

Proteomics. 2023 Apr;23(7-8):e2200039. doi: 10.1002/pmic.202200039. Epub 2022 Nov 27.

Abstract

Human plasma is a rich source of biomedical information and biomarkers. However, the enormous dynamic range of plasma proteins limits its accessibility to mass spectrometric (MS) analysis. Here, we show that enrichment of extracellular vesicles (EVs) by ultracentrifugation increases plasma proteome depth by an order of magnitude. With this approach, more than two thousand proteins are routinely and reproducibly quantified by label-free quantification and data independent acquisition (DIA) in single-shot liquid chromatography tandem mass spectrometry runs of less than one hour. We present an optimized plasma proteomics workflow that enables high-throughput with very short chromatographic gradients analyzing hundred samples per day with deep proteome coverage, especially when including a study-specific spectral library generated by repeated injection and gas-phase fractionation of pooled samples. Finally, we test the workflow on clinical biobank samples from malignant melanoma patients in immunotherapy to demonstrate the improved proteome coverage supporting the potential for future biomarker discovery.

摘要

人血浆是生物医学信息和生物标志物的丰富来源。然而,血浆蛋白质的巨大动态范围限制了其进行质谱(MS)分析的可及性。在此,我们表明通过超速离心富集细胞外囊泡(EVs)可使血浆蛋白质组深度增加一个数量级。采用这种方法,在单次运行时间不到一小时的液相色谱串联质谱分析中,通过无标记定量和数据非依赖采集(DIA)可常规且可重复地定量两千多种蛋白质。我们提出了一种优化的血浆蛋白质组学工作流程,该流程通过非常短的色谱梯度实现高通量,每天可分析数百个样本,具有深度蛋白质组覆盖,特别是当包括通过对混合样本进行重复进样和气相分级生成的特定研究光谱库时。最后,我们在接受免疫治疗的恶性黑色素瘤患者的临床生物样本库样本上测试了该工作流程,以证明蛋白质组覆盖的改善,支持未来发现生物标志物的潜力。

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