Haslam Carl, Hellicar John, Dunn Adrian, Fuetterer Arne, Hardy Neil, Marshall Peter, Paape Rainer, Pemberton Michelle, Resemannand Anja, Leveridge Melanie
Department of Biological Sciences, GlaxoSmithKline, Stevenage, UK.
Department of Chemical Sciences, GlaxoSmithKline, Stevenage, UK.
J Biomol Screen. 2016 Feb;21(2):176-86. doi: 10.1177/1087057115608605. Epub 2015 Oct 1.
Mass spectrometry (MS) offers a label-free, direct-detection method, in contrast to fluorescent or colorimetric methodologies. Over recent years, solid-phase extraction-based techniques, such as the Agilent RapidFire system, have emerged that are capable of analyzing samples in <10 s. While dramatically faster than liquid chromatography-coupled MS, an analysis time of 8-10 s is still considered relatively slow for full-diversity high-throughput screening (HTS). Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF) offers an alternative for high-throughput MS detection. However, sample preparation and deposition onto the MALDI target, as well as interference from matrix ions, have been considered limitations for the use of MALDI for screening assays. Here we describe the development and validation of assays for both small-molecule and peptide analytes using MALDI-TOF coupled with nanoliter liquid handling. Using the JMJD2c histone demethylase and acetylcholinesterase as model systems, we have generated robust data in a 1536 format and also increased sample deposition to 6144 samples per target. Using these methods, we demonstrate that this technology can deliver fast sample analysis time with low sample volume, and data comparable to that of current RapidFire assays.
与荧光或比色法不同，质谱（MS）提供了一种无标记的直接检测方法。近年来，出现了基于固相萃取的技术，如安捷伦RapidFire系统，能够在不到10秒的时间内分析样品。虽然比液相色谱联用质谱快得多，但8 - 10秒的分析时间对于全多样性高通量筛选（HTS）来说仍被认为相对较慢。基质辅助激光解吸/电离飞行时间质谱（MALDI-TOF）为高通量质谱检测提供了一种替代方法。然而，样品制备、沉积到MALDI靶上以及基质离子的干扰一直被认为是使用MALDI进行筛选分析的局限性。在这里，我们描述了使用MALDI-TOF结合纳升级液体处理对小分子和肽类分析物进行分析方法的开发和验证。以JMJD2c组蛋白去甲基化酶和乙酰胆碱酯酶作为模型系统，我们以1536孔板的形式生成了可靠的数据，并且每个靶的样品沉积量增加到了6144个样品。使用这些方法，我们证明了该技术能够以低样品量实现快速的样品分析时间，并且数据与当前的RapidFire分析相当。
