Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA.
J Am Chem Soc. 2010 Mar 24;132(11):3819-30. doi: 10.1021/ja909524e.
In recent years, the biological sciences have seen a surge in the development of methods, including high-throughput global methods, for the quantitative measurement of biomolecule levels (i.e., RNA, proteins, metabolites) from cells and tissues. Just as important as quantitation of biomolecules has been the creation of approaches that uncover the regulatory and signaling connections between biomolecules. Our specific interest is in understanding peptide metabolism in a physiological setting, and this has led us to develop a multidisciplinary approach that integrates genetics, analytical chemistry, synthetic chemistry, biochemistry, and chemical biology to identify the substrates of peptidases in vivo. To accomplish this we utilize a liquid chromatography-mass spectrometry (LC-MS)-based peptidomics platform to measure changes in the peptidome as a function of peptidase activity. Previous analysis of mice lacking the enzyme dipeptidyl peptidase 4 (DPP4(-/-) mice), a biomedically relevant peptidase, using this approach identified a handful of novel endogenous DPP4 substrates. Here, we utilize these substrates and tissues from DPP4(-/-) mice to improve the coverage of the peptidomics platform by optimizing the key steps in the workflow, and in doing so, discover over 70 renal DPP4 substrates (up from 7 at the beginning of our optimization), a 10-fold improvement in our coverage. The sequences of these DPP4 peptide substrates support a broad role for DPP4 in proline-containing peptide catabolism and strengthen a biochemical model that interlinks aminopeptidase and DPP4 activities. Moreover, the improved peptidome coverage also led to the detection of greater numbers of known bioactive peptides (e.g., peptide hormones) during the analysis of gut samples, suggesting additional uses for this optimized workflow. Together these results strengthen our ability to identify endogenous peptide substrates through improved peptidome coverage and demonstrate a broader potential of this peptidomics platform.
近年来,生物学领域出现了大量方法的发展,包括高通量的全局方法,用于定量测量细胞和组织中的生物分子水平(即 RNA、蛋白质、代谢物)。与生物分子的定量同样重要的是,已经开发出了揭示生物分子之间的调节和信号连接的方法。我们特别感兴趣的是在生理环境中理解肽代谢,这导致我们开发了一种多学科的方法,该方法集成了遗传学、分析化学、合成化学、生物化学和化学生物学,以鉴定体内肽酶的底物。为了实现这一目标,我们利用基于液相色谱-质谱(LC-MS)的肽组学平台来测量肽组作为肽酶活性的函数的变化。以前使用这种方法分析缺乏酶二肽基肽酶 4(DPP4(-/-) 小鼠)的小鼠,即一种与生物医学相关的肽酶,鉴定出少数新的内源性 DPP4 底物。在这里,我们利用这些底物和 DPP4(-/-) 小鼠的组织来通过优化工作流程中的关键步骤来提高肽组学平台的覆盖度,并且在此过程中,发现了超过 70 种肾脏 DPP4 底物(在我们开始优化时只有 7 种),覆盖度提高了 10 倍。这些 DPP4 肽底物的序列支持 DPP4 在脯氨酸含量肽代谢中的广泛作用,并加强了将氨肽酶和 DPP4 活性联系起来的生化模型。此外,改进后的肽组覆盖度也导致在分析肠道样本时检测到更多已知的生物活性肽(例如肽激素),这表明这种优化的工作流程有更多的用途。这些结果共同增强了我们通过提高肽组覆盖度识别内源性肽底物的能力,并证明了这种肽组学平台更广泛的潜力。