Abelin Jennifer G, Patel Jinal, Lu Xiaodong, Feeney Caitlin M, Fagbami Lola, Creech Amanda L, Hu Roger, Lam Daniel, Davison Desiree, Pino Lindsay, Qiao Jana W, Kuhn Eric, Officer Adam, Li Jianxue, Abbatiello Susan, Subramanian Aravind, Sidman Richard, Snyder Evan, Carr Steven A, Jaffe Jacob D
From the ‡Broad Institute of MIT and Harvard, 415 Main St. Cambridge, Massachusetts 02142;
§Beth-Israel Deaconess Medical Center, Boston, Massachusetts, 02215;
Mol Cell Proteomics. 2016 May;15(5):1622-41. doi: 10.1074/mcp.M116.058354. Epub 2016 Feb 24.
Profiling post-translational modifications represents an alternative dimension to gene expression data in characterizing cellular processes. Many cellular responses to drugs are mediated by changes in cellular phosphosignaling. We sought to develop a common platform on which phosphosignaling responses could be profiled across thousands of samples, and created a targeted MS assay that profiles a reduced-representation set of phosphopeptides that we show to be strong indicators of responses to chemical perturbagens.To develop the assay, we investigated the coordinate regulation of phosphosites in samples derived from three cell lines treated with 26 different bioactive small molecules. Phosphopeptide analytes were selected from these discovery studies by clustering and picking 1 to 2 proxy members from each cluster. A quantitative, targeted parallel reaction monitoring assay was developed to directly measure 96 reduced-representation probes. Sample processing for proteolytic digestion, protein quantification, peptide desalting, and phosphopeptide enrichment have been fully automated, making possible the simultaneous processing of 96 samples in only 3 days, with a plate phosphopeptide enrichment variance of 12%. This highly reproducible process allowed ∼95% of the reduced-representation phosphopeptide probes to be detected in ∼200 samples.The performance of the assay was evaluated by measuring the probes in new samples generated under treatment conditions from discovery experiments, recapitulating the observations of deeper experiments using a fraction of the analytical effort. We measured these probes in new experiments varying the treatments, cell types, and timepoints to demonstrate generalizability. We demonstrated that the assay is sensitive to disruptions in common signaling pathways (e.g. MAPK, PI3K/mTOR, and CDK). The high-throughput, reduced-representation phosphoproteomics assay provides a platform for the comparison of perturbations across a range of biological conditions, suitable for profiling thousands of samples. We believe the assay will prove highly useful for classification of known and novel drug and genetic mechanisms through comparison of phosphoproteomic signatures.
对翻译后修饰进行分析,是在表征细胞过程中基因表达数据的另一个维度。细胞对药物的许多反应是由细胞磷酸信号的变化介导的。我们试图开发一个通用平台,在该平台上可以对数千个样本的磷酸信号反应进行分析,并创建了一种靶向质谱分析方法,该方法可分析一组代表性降低的磷酸肽,我们发现这些磷酸肽是对化学干扰物反应的有力指标。为了开发该分析方法,我们研究了来自三种细胞系的样本中磷酸化位点的协同调节,这些细胞系用26种不同的生物活性小分子进行处理。通过聚类并从每个聚类中挑选1至2个代理成员,从这些发现研究中选择磷酸肽分析物。开发了一种定量、靶向平行反应监测分析方法,以直接测量96个代表性降低的探针。蛋白水解消化、蛋白质定量、肽脱盐和磷酸肽富集的样本处理已完全自动化,仅需3天就能同时处理96个样本,平板磷酸肽富集差异为12%。这个高度可重复的过程使得在约200个样本中能够检测到约95%的代表性降低的磷酸肽探针。通过在发现实验的处理条件下生成的新样本中测量探针,评估了该分析方法的性能,用一部分分析工作概括了更深入实验的观察结果。我们在新的实验中测量了这些探针,改变了处理方式、细胞类型和时间点,以证明其通用性。我们证明该分析方法对常见信号通路(如MAPK、PI3K/mTOR和CDK)的破坏敏感。这种高通量、代表性降低的磷酸蛋白质组学分析方法提供了一个平台,用于比较一系列生物学条件下的干扰情况,适用于对数千个样本进行分析。我们相信,通过比较磷酸蛋白质组学特征,该分析方法将被证明对已知和新型药物及遗传机制的分类非常有用。