Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Proteome data for CAT-seq and synchronous labeling

ABSTRACT: RAW proteome data for CAT-seq and synchronous labeling

ORGANISM(S): Homo Sapiens Mus Musculus

SUBMITTER: Xinyuan Fan

PROVIDER: PXD065542 | iProX | Fri Jun 27 00:00:00 BST 2025

REPOSITORIES: iProX

ACCESS DATA

Json Xml

Similar Datasets

Time-Resolved Photocatalytic Proximity Labeling Uncovers ER Proteome Dynamics Underlying UPR to Apoptosis Transition [RNAseq_EMC2_knockdown]

Project description: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.

2025-07-23 | GSE298442 | GEO

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

2025-07-23 | GSE298441 | GEO

CAT-seq: A Chemical Strategy for Subcellular-Resolved RNA Profiling and Synchronous Multi-omics Investigation

Project description:Understanding cellular functions in health and disease requires dissecting spatiotemporal variations in the subcellular transcriptome. Mitochondria, with their independent RNA metabolism, play pivotal roles in numerous biological processes. Existing methods for mitochondrial RNA profiling suffer from limitations such as low resolution, contamination, and dependence on genetic manipulation. Here, we present CAT-seq, a bioorthogonal photocatalytic labeling strategy that enables high-resolution, in situ profiling of mitochondrial RNA in living cells without genetic manipulation. Through systematic exploration of quinone methide warheads, we identified an efficient RNA labeling probe. Rigorous validation and optimization enabled CAT-seq to successfully profile mitochondrial RNA, track RNA dynamics in HeLa cells, and even the challenging RAW 264.7 macrophages, achieving ~60% specificity. Furthermore, leveraging the unique reactivity of distinct quinone methides, we established an orthogonal labeling system enabling synchronous RNA and protein multi-omics profiling within the same sample. This allows us to unravel the intricate link between mitochondrial RNA and protein changes. Applying synchronous multi-omics to RAW 264.7 cells during immune response revealed an underlying mitochondrial remodeling mechanism behind oxidative phosphorylation pathway reduction. By integrating bioorthogonal photocatalytic chemistry with proximity-based labeling, CAT-seq offers a general, catalytic, and non-genetic approach for subcellular RNA and multi-omics investigations. This opens up exciting avenues for studying diverse physiological and pathological processes with RNA involvement.

2025-06-24 | GSE255007 | GEO

Effect of 4sU labeling on quantification bias in nucleotide conversion RNA-seq data

Project description:Effect of 4sU labeling on quantification bias in nucleotide conversion RNA-seq data

| PRJNA954780 | ENA

BAP-seq proximity labeling of subcellular compartments

Project description:BAP-seq proximity labeling of subcellular compartments

| PRJNA954517 | ENA

Halfpipe: a tool for analyzing metabolic labeling RNA-seq data to quantify RNA half-lives

Project description:We introduce Halfpipe, a tool for analyzing RNA-seq data from metabolic RNA labeling experiments. Its main features are the absolute quantification of 4sU-labeling-induced T>C conversions in the data, calculating the proportion of newly synthesized transcripts, and estimating (compartment-specific) RNA half-lives. Halfpipe excels at correcting critical biases caused by typically low labeling efficiency. We measure and compare the RNA metabolism in the G1 phase and during the mitosis of synchronized human cells. We find that RNA half-lives of constantly expressed RNAs are similar in mitosis and G1 phase, suggesting that RNA stability of those genes is constant throughout the cell cycle. Our estimates correlate well with literature values and with known RNA sequence features.

2025-02-26 | GSE278274 | GEO

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

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

| PRJNA1269465 | ENA

Time-Resolved Photocatalytic Proximity Labeling Uncovers ER Proteome Dynamics Underlying UPR to Apoptosis Transition [RNAseq_EMC2_knockdown]

Project description:Time-Resolved Photocatalytic Proximity Labeling Uncovers ER Proteome Dynamics Underlying UPR to Apoptosis Transition [RNAseq_EMC2_knockdown]

| PRJNA1269464 | ENA

Effect of 4sU labeling durations on quantification bias in nucleotide conversion RNA-seq data

Project description:Effect of 4sU labeling durations on quantification bias in nucleotide conversion RNA-seq data

| PRJNA954792 | ENA

Effect of 4sU labeling concentrations on quantification bias in nucleotide conversion RNA-seq data

Project description:Effect of 4sU labeling concentrations on quantification bias in nucleotide conversion RNA-seq data

| PRJNA954793 | ENA