A rapid methods development workflow for high-throughput quantitative proteomic applications

Recent improvements in the speed and sensitivity of liquid chromatography-mass spectrometry systems have driven significant progress toward system-wide characterization of the proteome of many species. These efforts create large proteomic datasets that provide insight into biological processes and identify diagnostic proteins whose abundance changes significantly under different experimental conditions. Yet, these system-wide experiments are typically the starting point for hypothesis-driven, follow-up experiments to elucidate the extent of the phenomenon or the utility of the diagnostic marker, wherein many samples must be analyzed. Transitioning from a few discovery experiments to quantitative analyses on hundreds of samples requires significant resources both to develop sensitive and specific methods as well as analyze them in a high-throughput manner. To aid these efforts, we developed a workflow using data acquired from discovery proteomic experiments, retention time prediction, and standard-flow chromatography to rapidly develop targeted proteomic assays. We demonstrated this workflow by developing MRM assays to quantify proteins of multiple metabolic pathways from multiple microbes under different experimental conditions. With this workflow, one can also target peptides in scheduled/dynamic acquisition methods from a shotgun proteomic dataset downloaded from online repositories, validate with appropriate control samples or standard peptides, and begin analyzing hundreds of samples in only a few minutes.近年来，液相色谱-质谱（liquid chromatography-mass spectrometry）系统的速度与灵敏度持续优化，推动了众多物种蛋白质组（proteome）的全系统表征研究取得重大进展。此类研究产出了大规模蛋白质组数据集（proteomic datasets），可为生物学过程解析提供重要洞见，并能识别在不同实验条件下丰度发生显著变化的诊断用蛋白质（diagnostic proteins）。然而，这类全系统实验通常是假说驱动实验（hypothesis-driven experiments）的起点，用于阐明目标现象的波及范围或诊断标志物（diagnostic marker）的应用价值，而这类后续实验需对大量样本开展分析。从少量发现型蛋白质组实验（discovery proteomic experiments）转向数百个样本的定量分析，需要投入大量资源以开发灵敏且特异性强的分析方法，并以高通量（high-throughput）方式完成样本检测。为助力此类研究工作，我们基于发现型蛋白质组实验获取的数据、保留时间预测（retention time prediction）技术及标准流速色谱（standard-flow chromatography）技术，开发了一套可快速构建靶向蛋白质组分析检测方法（targeted proteomic assays）的工作流程。我们通过开发多反应监测（MRM, multiple reaction monitoring）检测方法，对不同实验条件下多种微生物体内多条代谢通路的蛋白质进行定量，验证了该工作流程的有效性。借助该工作流程，研究人员还可从在线数据库下载的鸟枪蛋白质组数据集（shotgun proteomic dataset）中选取目标肽段，采用预设/动态采集方法（scheduled/dynamic acquisition methods）进行检测，并通过合适的对照样本（control samples）或标准肽段（standard peptides）完成验证，最终仅需数分钟即可完成数百个样本的分析。