Cross-link assisted spatial proteomics to map sub-organelle proteomes and membrane protein topology

The specific functions of cellular organelles and sub-compartments depend on their protein content, which can be characterized by spatial proteomics approaches. However, many spatial proteomics methods are limited in their ability to resolve organellar sub-compartments, profile multiple sub-compartments in parallel, and/or characterize membrane-associated proteomes. Here, we develop a cross-linking assisted spatial proteomics (CLASP) strategy that addresses these shortcomings. Using human mitochondria as a model system, we show that CLASP can elucidate spatial proteomes of all mitochondrial sub-compartments and provide topological insight into the mitochondrial membrane proteome in a single experiment. Biochemical and imaging-based follow-up studies demonstrate that CLASP allows discovering mitochondria-associated proteins and revising previous protein sub-compartment localization and membrane topology data. This study extends the scope of cross-linking mass spectrometry beyond protein structure and interaction analysis towards spatial proteomics, establishes a method for concomitant profiling of sub-organelle and membrane proteomes, and provides a resource for mitochondrial spatial biology

细胞细胞器及其亚区室的特定功能依赖于其蛋白质组成，而该组成可通过空间蛋白质组学（spatial proteomics）方法进行表征。然而，多数空间蛋白质组学方法在解析细胞器亚区室、并行表征多个亚区室以及表征膜相关蛋白质组的能力上存在局限。本研究开发了交联辅助空间蛋白质组学（cross-linking assisted spatial proteomics, CLASP）策略，以克服上述缺陷。以人类线粒体作为模型系统，我们证实CLASP可在单次实验中解析所有线粒体亚区室的空间蛋白质组，并为线粒体膜蛋白质组提供拓扑学层面的解析视角。基于生化与成像的后续验证实验证实，CLASP可用于发现线粒体相关蛋白，并修正已有的蛋白质亚区室定位及膜拓扑学数据。本研究将交联质谱（cross-linking mass spectrometry）的应用范围从蛋白质结构与相互作用分析拓展至空间蛋白质组学领域，建立了可同时分析亚细胞器与膜蛋白质组的方法，并为线粒体空间生物学提供了宝贵的研究资源。