Dataset Information

Global profiling of protein-DNA and protein-nucleosome binding affinities using quantitative mass spectrometry

ABSTRACT: Interaction proteomics studies have provided fundamental insights into multimeric biomolecular assemblies and cell-scale molecular networks. Significant recent developments in mass spectrometry-based interaction proteomics have been fueled by rapid advances in label-free, isotopic, and isobaric quantitation workflows. Here, we report a quantitative protein-DNA and protein-nucleosome binding assay that uses affinity purifications from nuclear extracts coupled with isobaric chemical labeling and mass spectrometry to quantify apparent binding affinities proteome-wide. We use this assay with a variety of DNA and nucleosome baits to quantify apparent binding affinities of monomeric and multimeric transcription factors and chromatin remodeling complexes.

INSTRUMENT(S): Orbitrap Fusion

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Permanent Cell Line Cell, Hela Cell

DISEASE(S): Cervix Carcinoma

SUBMITTER: Matthew Makowski

LAB HEAD: Michiel Vermeulen

PROVIDER: PXD007132 | Pride | 2018-05-02

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	20161028_Fusion_SA_MM_Kd_HeLa_MeOH_TMT_Sp1_Mut.raw	Raw
	20161028_Fusion_SA_MM_Kd_HeLa_MeOH_TMT_Sp1_Wt.raw	Raw
	20170113_Fusion1_SA_MM_CG_TMT_Kd_SP1_1.raw	Raw
	20170113_Fusion1_SA_MM_CG_TMT_Kd_SP1_2.raw	Raw
	20170222_Fusion1_SA_MM_CG_TMT_Kd_AP1_rep1.raw	Raw

Items per page:

1 - 5 of 49

Publications

Global profiling of protein-DNA and protein-nucleosome binding affinities using quantitative mass spectrometry.

Makowski Matthew M MM Gräwe Cathrin C Foster Benjamin M BM Nguyen Nhuong V NV Bartke Till T Vermeulen Michiel M

Nature communications 20180425 1

Interaction proteomics studies have provided fundamental insights into multimeric biomolecular assemblies and cell-scale molecular networks. Significant recent developments in mass spectrometry-based interaction proteomics have been fueled by rapid advances in label-free, isotopic, and isobaric quantitation workflows. Here, we report a quantitative protein-DNA and protein-nucleosome binding assay that uses affinity purifications from nuclear extracts coupled with isobaric chemical labeling and m ...[more]

PMID: 29695722

Similar Datasets

Project description:The interaction between transcription factors and genomic DNA forms the basis for spatio-temporal control of gene expression. Therefore, these interactions and their impact on disease and cellular fate are extensively studied on a global level, mainly using techniques based on next-generation sequencing. These techniques, however, do not allow an unbiased study of proteins or entire protein complexes that bind to a certain DNA sequence. In recent years, DNA pull-downs followed by quantitative mass spectrometry were introduced to close this gap. Established protocols, however, are based on metabolic labeling techniques or require enormous amounts of cellular material, thus restricting the method to cell lines grown in culture. Furthermore, they require substantial amount of expertise, thus keeping this technique restricted to a limited number of laboratories. Here, we introduce a high-throughput compatible, LC-MS/MS based DNA pull-down that combines on-bead digestion with direct dimethyl labeling or label-free protein quantification. We demonstrate, that our method can efficiently identify transcription factors binding to their known consensus DNA motifs when using nuclear extracts from model cell lines. Subsequently, we apply the method to study DNA-protein interactions in primary foreskin fibroblasts and peripheral blood mononuclear cells (PBMCs) freshly isolated from human donors. We show that the same DNA sequence binds different sets of proteins in an established model cell line as opposed to PBMCs. This stresses the importance of selecting relevant cell extracts for any interaction in question. In-depth nuclear proteomes with absolute quantification of close to 7,000 proteins in K562 cells and PBMCs clearly link these differential interactions to differences in protein abundance. In conclusion, our approach, applicable to primary material and capable of profiling DNA-protein interactions in high-throughput, will likely prove itself as a useful screening platform and will provide invaluable functional data, for example through integration with large scale GWAS.