Metabolic labeling with heavy water followed by LC–MS is a high throughput approach to study proteostasis in vivo. Advances in mass spectrometry and sample processing have allowed consistent detection of thousands of proteins at multiple time points. However, freely available automated bioinformatics tools to analyze and extract protein decay rate constants are lacking. Here, we describe d2ome—a robust, automated software solution for in vivo protein turnover analysis. d2ome is highly scalable, uses innovative approaches to nonlinear fitting, implements Grubbs’ outlier detection and removal, uses weighted-averaging of replicates, applies a data dependent elution time windowing, and uses mass accuracy in peak detection. Here, we discuss the application of d2ome in a comparative study of protein turnover in the livers of normal vs Western diet-fed LDLR^–/– mice (mouse model of nonalcoholic fatty liver disease), which contained 256 LC–MS experiments. The study revealed reduced stability of 40S ribosomal protein subunits in the Western diet-fed mice.

中文翻译：

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d2ome，使用重水标记和 LC-MS 进行体内蛋白质周转分析的软件，揭示了 NAFLD 小鼠模型中肝脏蛋白质组动力学的变化

用重水进行代谢标记，然后进行 LC-MS 是一种研究体内蛋白质稳态的高通量方法。质谱和样品处理方面的进步已经允许在多个时间点一致检测数千种蛋白质。然而，缺乏免费可用的自动化生物信息学工具来分析和提取蛋白质衰减率常数。在这里，我们描述了 d2ome——一种用于体内蛋白质周转分析的强大的自动化软件解决方案。d2ome 具有高度可扩展性，使用创新的非线性拟合方法，实施 Grubbs 异常值检测和去除，使用重复加权平均，应用数据相关的洗脱时间窗口，并在峰检测中使用质量精度。这里，^–/–小鼠（非酒精性脂肪性肝病小鼠模型），其中包含 256 个 LC-MS 实验。该研究表明，西方饮食喂养的小鼠中 40S 核糖体蛋白亚基的稳定性降低。