Department of Medical and Clinical Biophysics, Faculty of Medicine, University of P.J. Šafárik in Košice, 04011 Košice, Slovakia.
Department of Chemistry, National Tsing Hua University, 101, Sec 2, Kuang-Fu Rd., Hsinchu 30013, Taiwan.
Clin Chim Acta. 2020 Aug;507:104-116. doi: 10.1016/j.cca.2020.04.015. Epub 2020 Apr 17.
Discovery of new protein biomarker candidates has become a major research goal in the areas of clinical chemistry, analytical chemistry, and biomedicine. These important species constitute the molecular target when it comes to diagnosis, prognosis, and further monitoring of disease. However, their analysis requires powerful, selective and high-throughput sample preparation and product (analyte) characterisation approaches. In general, manual sample processing is tedious, complex and time-consuming, especially when large numbers of samples have to be processed (e.g., in clinical studies). Automation via microtiter-plate platforms involving robotics has brought improvements in high-throughput performance while comparable or even better precisions and repeatability (intra-day, inter-day) were achieved. At the same time, waste production and exposure of laboratory personnel to hazards were reduced. In comprehensive protein analysis workflows (e.g., liquid chromatography-tandem mass spectrometry analysis), sample preparation is an unavoidable step. This review surveys the recent achievements in automation of bottom-up and top-down protein and/or proteomics approaches. Emphasis is put on high-end multi-well plate robotic platforms developed for clinical analysis and other biomedical applications. The literature from 2013 to date has been covered.
发现新的蛋白质生物标志物候选物已成为临床化学、分析化学和生物医学领域的主要研究目标。这些重要的物质构成了分子靶标，用于疾病的诊断、预后和进一步监测。然而，它们的分析需要强大的、选择性的和高通量的样品制备和产物（分析物）的特征化方法。一般来说，手动样品处理繁琐、复杂且耗时，尤其是当需要处理大量样品时（例如，在临床研究中）。通过涉及机器人的微孔板平台进行自动化已经提高了高通量性能，同时实现了可比甚至更好的精密度和重复性（日内、日间）。同时，减少了废物的产生和实验室人员接触危险物质的风险。在全面的蛋白质分析工作流程（例如，液相色谱-串联质谱分析）中，样品制备是不可避免的步骤。本文综述了近年来在自下而上和自上而下的蛋白质和/或蛋白质组学方法自动化方面的最新进展。重点介绍了为临床分析和其他生物医学应用开发的高端多微孔板机器人平台。涵盖了 2013 年至今的文献。
