Minkoff Benjamin B, Burch Heather L, Sussman Michael R
Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA.
Methods Mol Biol. 2014;1062:353-79. doi: 10.1007/978-1-62703-580-4_19.
Within the past two decades, the biological application of mass spectrometric technology has seen great advances in terms of innovations in hardware, software, and reagents. Concurrently, the burgeoning field of proteomics has followed closely (Yates et al., Annu Rev Biomed Eng 11:49-79, 2009)-and with it, importantly, the ability to globally assay altered levels of posttranslational modifications in response to a variety of stimuli. Though many posttranslational modifications have been described, a major focus of these efforts has been protein-level phosphorylation of serine, threonine, and tyrosine residues (Schreiber et al., Proteomics 8:4416-4432, 2008). The desire to examine changes across signal transduction cascades and networks in their entirety using a single mass spectrometric analysis accounts for this push-namely, preservation and enrichment of the transient yet informative phosphoryl side group. Analyzing global changes in phosphorylation allows inferences surrounding cascades/networks as a whole to be made. Towards this same end, much work has explored ways to permit quantitation and combine experimental samples such that more than one replicate or experimental condition can be identically processed and analyzed, cutting down on experimental and instrument variability, in addition to instrument run time. One such technique that has emerged is metabolic labeling (Gouw et al., Mol Cell Proteomics 9:11-24, 2010), wherein biological samples are labeled in living cells with nonradioactive heavy isotopes such as (15)N or (13)C. Since metabolic labeling in living organisms allows one to combine the material to be processed at the earliest possible step, before the tissue is homogenized, it provides a unique and excellent method for comparing experimental samples in a high-throughput, reproducible fashion with minimal technical variability. This chapter describes a pipeline used for labeling living Arabidopsis thaliana plants with nitrogen-15 ((15)N) and how this can be used, in conjunction with a technique for enrichment of phosphorylated peptides (phosphopeptides), to determine changes in A. thaliana's phosphoproteome on an untargeted, global scale.
在过去二十年中,质谱技术的生物学应用在硬件、软件和试剂创新方面取得了巨大进展。与此同时,新兴的蛋白质组学领域也紧随其后(耶茨等人,《生物医学工程年度评论》11:49 - 79,2009年),重要的是,随之而来的是能够全面分析响应各种刺激时翻译后修饰水平的变化。尽管已经描述了许多翻译后修饰,但这些努力的一个主要重点是丝氨酸、苏氨酸和酪氨酸残基的蛋白质水平磷酸化(施赖伯等人,《蛋白质组学》8:4416 - 4432,2008年)。使用单一质谱分析来全面检查信号转导级联和网络中的变化的愿望导致了这种推动——即保留和富集短暂但信息丰富的磷酸化侧链基团。分析磷酸化的全局变化有助于对整个级联/网络进行推断。为了实现同一目标,许多工作探索了允许定量和组合实验样品的方法,以便可以对多个重复样本或实验条件进行相同的处理和分析,从而减少实验和仪器的变异性以及仪器运行时间。其中一种出现的技术是代谢标记(古等人,《分子细胞蛋白质组学》9:11 - 24,2010年),其中生物样品在活细胞中用非放射性重同位素如(15)N或(13)C进行标记。由于在活生物体中的代谢标记允许在组织匀浆之前的最早步骤将待处理的材料合并,它提供了一种独特且出色的方法,以高通量、可重复的方式比较实验样品,同时技术变异性最小。本章描述了一种用于用氮 - 15((15)N)标记活的拟南芥植物的流程,以及如何将其与磷酸化肽(磷酸肽)富集技术结合使用,以在非靶向的全局规模上确定拟南芥磷酸化蛋白质组的变化。