Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, United States of America.
Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America.
PLoS One. 2019 Feb 14;14(2):e0211582. doi: 10.1371/journal.pone.0211582. eCollection 2019.
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-质谱联用系统在速度和灵敏度方面的改进,推动了对许多物种蛋白质组进行全面系统分析的显著进展。这些努力产生了大量的蛋白质组数据集,为深入了解生物过程和识别在不同实验条件下丰度变化显著的诊断蛋白提供了线索。然而,这些全面的系统实验通常是针对后续的、基于假设的实验的起点,以阐明现象的程度或诊断标记的实用性,其中需要分析许多样本。要从少数发现实验过渡到对数百个样本进行定量分析,需要大量资源来开发灵敏和特异性方法,并以高通量方式进行分析。为了辅助这些工作,我们开发了一个工作流程,该流程使用从发现蛋白质组学实验、保留时间预测和标准流量色谱获得的数据来快速开发靶向蛋白质组学分析方法。我们通过开发多重反应监测(MRM)分析方法来定量分析来自多个微生物在不同实验条件下的多种代谢途径的蛋白质,证明了该工作流程的有效性。使用该工作流程,还可以针对从在线存储库下载的鸟枪法蛋白质组数据集的预定/动态采集方法中的肽进行靶向分析,使用适当的对照样本或标准肽进行验证,并在短短几分钟内开始分析数百个样本。