Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, USA.
Vanderbilt Institute of Chemical Biology, Vanderbilt University, Nashville, Tennessee 37232, USA.
Mol Omics. 2022 Oct 31;18(9):828-839. doi: 10.1039/d2mo00122e.
Automation is necessary to increase sample processing throughput for large-scale clinical analyses. Replacement of manual pipettes with robotic liquid handler systems is especially helpful in processing blood-based samples, such as plasma and serum. These samples are very heterogenous, and protein expression can vary greatly from sample-to-sample, even for healthy controls. Detection of true biological changes requires that variation from sample preparation steps and downstream analytical detection methods, such as mass spectrometry, remains low. In this mini-review, we discuss plasma proteomics protocols and the benefits of automation towards enabling detection of low abundant proteins and providing low sample error and increased sample throughput. This discussion includes considerations for automation of major sample depletion and/or enrichment strategies for plasma toward mass spectrometry detection.
自动化对于提高大规模临床分析的样品处理通量是必要的。用机器人液体处理系统替代手动移液器，对于处理基于血液的样品（如血浆和血清）特别有帮助。这些样品非常不均匀，即使对于健康对照，蛋白质表达也会在样品间有很大差异。要检测真正的生物学变化，就需要使来自样品制备步骤和下游分析检测方法（如质谱）的差异保持在低水平。在这篇迷你综述中，我们讨论了血浆蛋白质组学方案，以及自动化在检测低丰度蛋白质和提供低样品误差以及增加样品通量方面的优势。这一讨论包括了对用于质谱检测的血浆主要样品耗竭和/或富集策略进行自动化的考虑因素。
