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一种经济高效的高通量血浆和血清蛋白质组学工作流程可用于绘制全胰切除伴胰岛自体移植对分子影响的图谱。

A Cost-Effective High-Throughput Plasma and Serum Proteomics Workflow Enables Mapping of the Molecular Impact of Total Pancreatectomy with Islet Autotransplantation.

机构信息

Department of Pathology , Harvard Medical School , Boston , Massachusetts , United States.

Department of Pathology , Boston Children's Hospital , Boston , Massachusetts , United States.

出版信息

J Proteome Res. 2018 May 4;17(5):1983-1992. doi: 10.1021/acs.jproteome.8b00111. Epub 2018 Apr 19.

DOI:10.1021/acs.jproteome.8b00111
PMID:29641209
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6791589/
Abstract

Blood is an ideal body fluid for the discovery or monitoring of diagnostic and prognostic protein biomarkers. However, discovering robust biomarkers requires the analysis of large numbers of samples to appropriately represent interindividual variability. To address this analytical challenge, we established a high-throughput and cost-effective proteomics workflow for accurate and comprehensive proteomics at an analytical depth applicable for clinical studies. For validation, we processed 1 μL each from 62 plasma samples in 96-well plates and analyzed the product by quantitative data-independent acquisition liquid chromatography/mass spectrometry; the data were queried using feature quantification with Spectronaut. To show the applicability of our workflow to serum, we analyzed a unique set of samples from 48 chronic pancreatitis patients, pre and post total pancreatectomy with islet autotransplantation (TPIAT) surgery. We identified 16 serum proteins with statistically significant abundance alterations, which represent a molecular signature distinct from that of chronic pancreatitis. In summary, we established a cost-efficient high-throughput workflow for comprehensive proteomics using PVDF-membrane-based digestion that is robust, automatable, and applicable to small plasma and serum volumes, e.g., finger stick. Application of this plasma/serum proteomics workflow resulted in the first mapping of the molecular implications of TPIAT on the serum proteome.

摘要

血液是发现或监测诊断和预后蛋白生物标志物的理想体液。然而,发现稳健的生物标志物需要分析大量的样本,以适当代表个体间的变异性。为了解决这一分析挑战,我们建立了一种高通量且具有成本效益的蛋白质组学工作流程,用于在适用于临床研究的分析深度上进行准确和全面的蛋白质组学分析。为了进行验证,我们从 96 孔板中的 62 个血浆样本中各处理 1μL,并通过定量数据非依赖性采集液相色谱/质谱法对产物进行分析;使用 Spectronaut 进行特征量化查询数据。为了展示我们的工作流程对血清的适用性,我们分析了一组来自 48 例慢性胰腺炎患者的独特样本,这些患者在接受全胰切除术伴胰岛自体移植(TPIAT)手术后的术前和术后。我们鉴定出 16 种血清蛋白的丰度发生了统计学上显著的改变,这些蛋白代表了与慢性胰腺炎不同的分子特征。总之,我们建立了一种基于 PVDF 膜消化的高效、高通量的全面蛋白质组学工作流程,该流程具有稳健性、自动化性,并且适用于小体积的血浆和血清,例如指尖采血。该血浆/血清蛋白质组学工作流程的应用首次描绘了 TPIAT 对血清蛋白质组的分子影响。

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