Spatially resolved mapping of proteome turnover dynamics with subcellular precision

• Published in: Nature communications 2023-11, Vol.14 (1), p.7217-7217, Article 7217
• Main Authors: Yuan, Feng, Li, Yi, Zhou, Xinyue, Meng, Peiyuan, Zou, Peng
• Format: Article
• Language: English
• Subjects: 631/45/475; 631/92/470/1463; 82/58; Differentiation; Dynamics; Endoplasmic reticulum; Humanities and Social Sciences; Isotopes; Labeling; Macromolecules; Mapping; Mitochondria; multidisciplinary; Peptide mapping; Physiology; Protein turnover; Proteins; Proteomes; Proteomics; Science; Science (multidisciplinary); Spatial discrimination; Spatial resolution; Stable isotopes; Turnover rate
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-023-42861-8

Cellular activities are commonly associated with dynamic proteomic changes at the subcellular level. Although several techniques are available to quantify whole-cell protein turnover dynamics, such measurements often lack sufficient spatial resolution at the subcellular level. Herein, we report the development of prox-SILAC method that combines proximity-dependent protein labeling (APEX2/HRP) with metabolic incorporation of stable isotopes (pulse-SILAC) to map newly synthesized proteins with subcellular spatial resolution. We apply prox-SILAC to investigate proteome dynamics in the mitochondrial matrix and the endoplasmic reticulum (ER) lumen. Our analysis reveals a highly heterogeneous distribution in protein turnover dynamics within macromolecular machineries such as the mitochondrial ribosome and respiratory complexes I-V, thus shedding light on their mechanism of hierarchical assembly. Furthermore, we investigate the dynamic changes of ER proteome when cells are challenged with stress or undergoing stimulated differentiation, identifying subsets of proteins with unique patterns of turnover dynamics, which may play key regulatory roles in alleviating stress or promoting differentiation. We envision that prox-SILAC could be broadly applied to profile protein turnover at various subcellular compartments, under both physiological and pathological conditions. Mapping protein turnover dynamics with subcellular precision is crucial for understanding cell physiology and pathology. Here, the authors leveraged APEX2-mediated proximity labeling to develop prox-SILAC methods to profile protein turnover rates in the mitochondria and endoplasmic reticulum.