TurnoveR: A Skyline External Tool for Analysis of Protein Turnover in Metabolic Labeling Studies
TurnoveR: A Skyline External Tool for Analysis of Protein Turnover in Metabolic Labeling Studies
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DOI：
10.1021/acs.jproteome.2c00173
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发表时间：
2022-09-27
影响因子：
4.4
通讯作者：
Schilling, Birgit
中科院分区：
文献类型：
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作者：
Basisty, Nathan;Shulman, Nicholas;Schilling, Birgit
尽管蛋白质周转在生物学和疾病中起着核心作用，但由于分析体内周转率的计算工作流程的复杂性，蛋白质周转在大多数蛋白质组学研究中是一个很大程度上未被充分研究的方面。为了满足这一需求，我们开发了一种新的计算工具TurnoveR，可以通过Skyline（一种免费开源的蛋白质组学软件平台）中代谢标记实验的质谱分析准确计算蛋白质周转率。TurnoveR是一个简单的图形界面，可以将蛋白质周转分析无缝集成到Skyline中的传统蛋白质组学工作流程中，使用户能够利用软件内置的先进灵活的数据可视化和管理功能。TurnoveR的计算流水线执行关键步骤来确定蛋白质周转率，包括同位素物解复用、同位素池校正、统计分析以及生成数据报告和可视化。该工作流程与许多质谱平台兼容，并概括了先前研究中计算的治疗组之间的转换率和转换率的差异变化。我们希望将TurnoveR添加到广泛使用的Skyline蛋白质组学软件中，将有助于在高度相关的生物模型中更广泛地利用蛋白质周转分析，包括衰老，神经退行性变和骨骼肌萎缩。
In spite of its central role in biology and disease, protein turnover is a largely understudied aspect of most proteomic studies due to the complexity of computational workflows that analyze in vivo turnover rates. To address this need, we developed a new computational tool, TurnoveR, to accurately calculate protein turnover rates from mass spectrometric analysis of metabolic labeling experiments in Skyline, a free and open-source proteomics software platform. TurnoveR is a straightforward graphical interface that enables seamless integration of protein turnover analysis into a traditional proteomics workflow in Skyline, allowing users to take advantage of the advanced and flexible data visualization and curation features built into the software. The computational pipeline of TurnoveR performs critical steps to determine protein turnover rates, including isotopologue demultiplexing, precursor-pool correction, statistical analysis, and generation of data reports and visualizations. This workflow is compatible with many mass spectrometric platforms and recapitulates turnover rates and differential changes in turnover rates between treatment groups calculated in previous studies. We expect that the addition of TurnoveR to the widely used Skyline proteomics software will facilitate wider utilization of protein turnover analysis in highly relevant biological models, including aging, neurodegeneration, and skeletal muscle atrophy.