Department of Proteomics and Signal Transduction, Systems Biology of Membrane Trafficking Research Group, Max-Planck Institute of Biochemistry, Martinsried, Germany.
School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK.
Nat Commun. 2023 Aug 29;14(1):5252. doi: 10.1038/s41467-023-41000-7.
The Dynamic Organellar Maps (DOMs) approach combines cell fractionation and shotgun-proteomics for global profiling analysis of protein subcellular localization. Here, we enhance the performance of DOMs through data-independent acquisition (DIA) mass spectrometry. DIA-DOMs achieve twice the depth of our previous workflow in the same mass spectrometry runtime, and substantially improve profiling precision and reproducibility. We leverage this gain to establish flexible map formats scaling from high-throughput analyses to extra-deep coverage. Furthermore, we introduce DOM-ABC, a powerful and user-friendly open-source software tool for analyzing profiling data. We apply DIA-DOMs to capture subcellular localization changes in response to starvation and disruption of lysosomal pH in HeLa cells, which identifies a subset of Golgi proteins that cycle through endosomes. An imaging time-course reveals different cycling patterns and confirms the quantitative predictive power of our translocation analysis. DIA-DOMs offer a superior workflow for label-free spatial proteomics as a systematic phenotype discovery tool.
动态细胞器图谱（DOMs）方法结合细胞分级分离和鸟枪法蛋白质组学，用于蛋白质亚细胞定位的全局分析。在这里，我们通过数据非依赖性采集（DIA）质谱法来增强 DOMs 的性能。DIA-DOMs 在相同的质谱运行时间内实现了我们之前工作流程深度的两倍，并且大大提高了分析的精度和重现性。我们利用这一优势建立了灵活的图谱格式，从高通量分析扩展到超深度覆盖。此外，我们引入了 DOM-ABC，这是一个强大且用户友好的开源软件工具，用于分析分析数据。我们应用 DIA-DOMs 来捕获 HeLa 细胞因饥饿和溶酶体 pH 破坏而导致的亚细胞定位变化，从而鉴定出一组通过内体循环的高尔基体蛋白。一个成像时程揭示了不同的循环模式，并证实了我们的易位分析的定量预测能力。DIA-DOMs 作为一种系统表型发现工具，为无标记空间蛋白质组学提供了优越的工作流程。
