Department of Biochemistry and Cambridge Systems Biology Centre, University of Cambridge, 80 Tennis Court Rd, Cambridge, CB2 1GA, UK.
Biognosys AG, Wagistrasse 21, CH-8952, Schlieren, Switzerland.
Sci Rep. 2018 Mar 12;8(1):4346. doi: 10.1038/s41598-018-22610-4.
Quantitative proteomics is key for basic research, but needs improvements to satisfy an increasing demand for large sample series in diagnostics, academia and industry. A switch from nanoflowrate to microflowrate chromatography can improve throughput and reduce costs. However, concerns about undersampling and coverage have so far hampered its broad application. We used a QTOF mass spectrometer of the penultimate generation (TripleTOF5600), converted a nanoLC system into a microflow platform, and adapted a SWATH regime for large sample series by implementing retention time- and batch correction strategies. From 3 µg to 5 µg of unfractionated tryptic digests that are obtained from proteomics-typical amounts of starting material, microLC-SWATH-MS quantifies up to 4000 human or 1750 yeast proteins in an hour or less. In the acquisition of 750 yeast proteomes, retention times varied between 2% and 5%, and quantified the typical peptide with 5-8% signal variation in replicates, and below 20% in samples acquired over a five-months period. Providing precise quantities without being dependent on the latest hardware, our study demonstrates that the combination of microflow chromatography and data-independent acquisition strategies has the potential to overcome current bottlenecks in academia and industry, enabling the cost-effective generation of precise quantitative proteomes in large scale.
定量蛋白质组学是基础研究的关键,但需要改进以满足诊断、学术界和工业界对大量样本系列日益增长的需求。从纳流率到微流率色谱的转变可以提高通量并降低成本。然而,对采样不足和覆盖范围的担忧迄今为止阻碍了其广泛应用。我们使用了上一代的 QTOF 质谱仪(TripleTOF5600),将纳流 LC 系统转换为微流平台,并通过实施保留时间和批处理校正策略,为大量样本系列适应了 SWATH 方案。从 3μg 到 5μg 的未经分级的胰蛋白酶消化物,这些消化物是从蛋白质组学典型的起始材料量中获得的,微 LC-SWATH-MS 在一小时或更短的时间内可以定量多达 4000 个人类或 1750 个酵母蛋白质。在获得 750 个酵母蛋白质组的过程中,保留时间变化在 2%到 5%之间,在重复实验中定量典型肽的信号变化在 5%到 8%之间,在五个月的时间内采集的样本中变化在 20%以下。我们的研究表明,微流色谱和数据非依赖性采集策略的结合具有克服学术界和工业界当前瓶颈的潜力,能够以经济高效的方式生成大规模精确的定量蛋白质组。