Institute of Medical and Biological Engineering, MRC , Seoul National University , Seoul , Korea.
Interdisciplinary Program of Bioengineering , Seoul National University College of Engineering , Seoul , Korea.
J Proteome Res. 2019 May 3;18(5):2337-2345. doi: 10.1021/acs.jproteome.9b00023. Epub 2019 Apr 22.
Reproducible sample preparation remains a significant challenge in large-scale clinical research using selected reaction monitoring-mass spectrometry (SRM-MS), which enables a highly sensitive multiplexed assay. Although automated liquid-handling platforms have tremendous potential for addressing this issue, the high cost of their consumables is a drawback that renders routine operation expensive. Here we evaluated the performance of a liquid-handling platform in preparing serum samples compared with a standard experiment while reducing the outlay for consumables, such as tips, wasted reagents, and reagent stock plates. A total of 26 multiplex assays were quantified by SRM-MS using four sets of 24 pooled human serum aliquots; the four sets used a fixed number (1, 4, 8, or 24) of tips to dispense digestion reagents. This study demonstrated that the use of 4 or 8 tips is comparable to 24 tips (standard experiment), as evidenced by their coefficients of variation: 13.5% (for 4 and 8 tips) versus 12.0% (24 tips). Thus we can save 37% of the total experimental cost compared with the standard experiment, maintaining nearly equivalent reproducibility. The routine operation of cost-effective liquid-handling platforms can enable researchers to process large-scale samples with high throughput, adding credibility to their findings by minimizing human error.
可重现的样品制备仍然是使用选择反应监测 - 质谱（SRM-MS）进行大规模临床研究的一个重大挑战，该方法可实现高度敏感的多重分析。尽管自动化液体处理平台在解决此问题方面具有巨大的潜力，但它们的耗材成本很高，这使得常规操作成本昂贵。在这里，我们评估了液体处理平台在准备血清样品方面的性能，与标准实验相比，同时减少了耗材的支出，例如吸头、浪费的试剂和试剂储备板。总共使用四组 24 个混合人血清等分试样，通过 SRM-MS 定量了 26 个多重分析物；四组使用固定数量（1、4、8 或 24）的吸头来分配消化试剂。这项研究表明，使用 4 或 8 个吸头与使用 24 个吸头（标准实验）相当，这可以从它们的变异系数得到证明：13.5%（用于 4 和 8 个吸头）与 12.0%（24 个吸头）。因此，与标准实验相比，我们可以节省 37%的总实验成本，同时保持几乎相当的重现性。经济高效的液体处理平台的常规操作可以使研究人员以高通量处理大规模样品，通过最小化人为错误，为他们的发现增加可信度。
