Dataset Information

Spatial-temporal protein interactome profiling via condensation enhanced crosslinking

ABSTRACT: MS data for the verification of metabolic incorporation of δ-photolysine, calculation for the crosslinking distance by DegP crosslinking, and the proteomics analysis for the dynamic direct interactome of NPM1 as well as the SG-specific interactomes of SARS-CoV-2 Nucleocapsid protein and YTHDF1/2.

ORGANISM(S): Homo Sapiens Escherichia Coli Severe Acute Respiratory Syndrome Coronavirus 2

SUBMITTER: Peng Chen

PROVIDER: PXD052099 | iProX | Wed Sep 11 00:00:00 BST 2024

REPOSITORIES: iProX

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Publications

Spatiotemporal protein interactome profiling through condensation-enhanced photocrosslinking.

Li Kexin K Xie Xiao X Gao Rui R Chen Zhaoming Z Yang Mingdong M Wen Zhihui Z Weng Yicheng Y Fan Xinyuan X Zhang Gong G Liu Lu L Zeng Xiangmei X Han Yu Y Cao Mengrui M Wang Xin X Li Jiaofeng J Yang Zhenlin Z Li Tingting T Chen Peng R PR

Nature chemistry 20241105 1

Resolving protein-protein interactions (PPIs) inside biomolecular condensates is crucial for elucidating their functions and regulation mechanisms. The transient nature of condensates and the multiple localizations of clients, however, have rendered it challenging to determine compartment-specific PPIs. Here we developed a condensation-enhanced, spatially directed, metabolic incorporation-assisted photocrosslinking strategy-termed DenseMAP-for spatiotemporally resolved dissection of the direct p ...[more]

PMID: 39501047

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Project description:Each protein within a regulatory complex associates with the genome by either binding DNA directly or by forming protein-protein interactions with DNA-bound proteins. In the chromatin immunoprecipitation (ChIP) assay, each protein’s unique mode of genomic association may be reflected by their patterns of formaldehyde-induced crosslinks to the DNA sequences that are in very close proximity. The ChIP-exo protocol precisely delineates protein-DNA crosslinking patterns by combining ChIP with 5' to 3' exonuclease digestion. Within a regulatory complex, the physical distance of a regulatory protein to the DNA affects crosslinking efficiencies. Therefore, the spatial organization of a protein-DNA complex could potentially be inferred by analyzing how crosslinking signatures vary between the subunits of a regulatory complex, and how they remain consistent over a set of coordinately regulated regions. Here, we present a computational framework that aligns ChIP-exo crosslinking patterns from multiple proteins across a set of regulatory regions, and which detects and quantifies protein-DNA crosslinking events within the aligned profiles. Our gapped multiple profile alignment approach does not rely on sequence motif features, but rather operates directly on the multi-protein, strand separated ChIP-exo tag patterns. The output of the alignment approach is a set of composite profiles that represent the crosslinking signatures of the complex across analyzed regulatory regions. We then use a probabilistic mixture model to deconvolve individual crosslinking events within the aligned ChIP-exo profiles, enabling consistent measurements of protein-DNA crosslinking strengths across multiple proteins. Lastly, we apply dimensionality reduction to visualize the relative organization of proteins within the regulatory complex. We demonstrate our approach by applying it to characterize regulatory complex organization in three biological settings. Firstly, we demonstrate that our alignment approach can recover the known organization of regulatory proteins at yeast ribosomal protein genes, without relying on any DNA sequence features. Secondly, we apply our gapped alignment and crosslinking quantification approaches to a novel set of ChIP-exo data to characterize the spatial organization of Pol III transcriptional machinery assembly at yeast tRNA genes. Finally, we demonstrate that our approach can be used to quantify changes in protein-DNA complex organization when applied to ChIP-nexus data from Drosophila Pol II transcriptional components in two experimental conditions. Our results suggest that principled analyses of ChIP-exo crosslinking patterns enable inference of spatial organization within protein-DNA complexes.

Dataset Information

Spatial-temporal protein interactome profiling via condensation enhanced crosslinking

Publications

Spatiotemporal protein interactome profiling through condensation-enhanced photocrosslinking.

Similar Datasets

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