Comprehensive and Scalable Highly Automated MS-Based Proteomic Workflow for Clinical Biomarker Discovery in Human Plasma

工作流程 人血浆 生物标志物发现 联营 计算机科学 自动化 周转时间 蛋白质组学 生物信息学 化学 色谱法 人工智能 工程类 数据库 生物 操作系统 生物化学 基因 机械工程
作者
Loı̈c Dayon,Antonio Núñez Galindo,John Corthésy,Ornella Cominetti,Martin Kussmann
出处
期刊:Journal of Proteome Research [American Chemical Society]
卷期号:13 (8): 3837-3845 被引量:52
标识
DOI:10.1021/pr500635f
摘要

Over the past decade, mass spectrometric performance has greatly improved in terms of sensitivity, dynamic range, and speed. By contrast, only limited progress has been accomplished with regard to automation, throughput, and robustness of the proteomic sample preparation process upstream of mass spectrometry. The present work delivers an optimized analysis of human plasma samples in both small preclinical and large clinical studies, enabled by the development of a highly automated quantitative proteomic workflow. Several iterative evaluation and validation steps were performed before process "design freeze" and development completion. A robotic liquid handling workflow and platform (including reduction, alkylation, digestion, TMT labeling, pooling, and purification) were shown to provide better quantitative trueness and precision than manual operation at the bench. Depletion of the most abundant human plasma proteins and subsequent buffer exchange were also developed and integrated. Finally, 96 identical pooled human plasma samples were prepared in a 96-well plate format, and each sample was individually subjected to our developed workflow. This test revealed increased throughput and robustness compared with to-date published manual or less automated workflows. Our workflow is ready-to-use for future (pre-) clinical studies. We expect our work to facilitate, accelerate, and improve clinical proteomic discovery in human blood plasma.
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