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Time-Resolved Photocatalytic Proximity Labeling Uncovers ER Proteome Dynamics Underlying UPR to Apoptosis Transition [RNAseq_thapsigargin_treatment]

GSE298441 Homo sapiens Expression profiling by high throughput sequencing 8 samples Submitted 2025/07/23 Platform GPL11154
Summary
Apoptosis is a critical outcome of stress-induced processes, with the endoplasmic reticulum (ER) playing a central role in apoptotic protein processing and stress signal transduction. Profiling the ER proteome during stress to cell death offers valuable insights into these processes, but existing methods often suffer from a loss of in situ information or requirement of genetic manipulation. In this study, we introduce CAT-ER, a novel non-genetic ER proteomics system that provides in situ labeling, spatiotemporal resolution, and compatibility across diverse cell types. By combining an ER-targeted iridium photocatalyst with a thio-quinone methide (thioQM) probe, CAT-ER achieves high specificity in enriching ER proteins, comparable to traditional enzymatic methods. Importantly, CAT-ER is free of genetic manipulation, allowing its use in hard-to-transfect cell types like HeLa and immune cells (e.g., Raji, Jurkat, and RAW264.7). Given the high spatiotemporal resolution of CAT-ER, we revealed dynamic ER proteome changes during thapsigargin (Tg)-induced unfolded protein response (UPR) to apoptosis. Notably, NFIP2 mitigated ER stress by halting translation when UPR initiated, while compromised EMC2 delayed apoptosis during prolonged stress. These findings provide novel insights into the molecular dynamics linking the UPR and apoptosis. Collectively, CAT-ER serves as a versatile tool for spatiotemporal proteomic analysis without the need for genetic manipulation, offering a powerful approach to study ER dynamics in various biological contexts.
Published in
Time-resolved photocatalytic proximity labeling uncovers ER proteome dynamics underlying UPR-to-apoptosis transition
Zhou N, Zhang Y, Chen PR et al. · Proceedings of the National Academy of Sciences of the United States of America 2025 · PMID 40768357 · doi:10.1073/pnas.2503115122
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Also filed as BioProject PRJNA1269465 and SRA study SRP588512. Searching any of these in the dataset finder brings you back here.

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