Dataset Information

R-DeeP: Proteome-wide and Quantitative Identification of RNA-Dependent Proteins by Density Gradient Ultracentrifugation.

ABSTRACT: The comprehensive but specific identification of RNA-binding proteins as well as the discovery of RNA-associated protein functions remain major challenges in RNA biology. Here we adapt the concept of RNA dependence, defining a protein as RNA dependent when its interactome depends on RNA. We converted this concept into a proteome-wide, unbiased, and enrichment-free screen called R-DeeP (RNA-dependent proteins), based on density gradient ultracentrifugation. Quantitative mass spectrometry identified 1,784 RNA-dependent proteins, including 537 lacking known links to RNA. Exploiting the quantitative nature of R-DeeP, proteins were classified as not, partially, or completely RNA dependent. R-DeeP identified the transcription factor CTCF as completely RNA dependent, and we uncovered that RNA is required for the CTCF-chromatin association. Additionally, R-DeeP allows reconstruction of protein complexes based on co-segregation. The whole dataset is available at http://R-DeeP.dkfz.de, providing proteome-wide, specific, and quantitative identification of proteins with RNA-dependent interactions and aiming at future functional discovery of RNA-protein complexes.

SUBMITTER: Caudron-Herger M

PROVIDER: S-EPMC6625853 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Publications

R-DeeP: Proteome-wide and Quantitative Identification of RNA-Dependent Proteins by Density Gradient Ultracentrifugation.

Caudron-Herger Maiwen M Rusin Scott F SF Adamo Mark E ME Seiler Jeanette J Schmid Vera K VK Barreau Elsa E Kettenbach Arminja N AN Diederichs Sven S

Molecular cell 20190507 1

The comprehensive but specific identification of RNA-binding proteins as well as the discovery of RNA-associated protein functions remain major challenges in RNA biology. Here we adapt the concept of RNA dependence, defining a protein as RNA dependent when its interactome depends on RNA. We converted this concept into a proteome-wide, unbiased, and enrichment-free screen called R-DeeP (RNA-dependent proteins), based on density gradient ultracentrifugation. Quantitative mass spectrometry identifi ...[more]

PMID: 31076284

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Project description:Although the bioactive sphingolipid ceramide is an important cell signaling molecule, relatively few direct ceramide-interacting proteins are known. We used an approach combining yeast surface cDNA display and deep sequencing technology to identify novel proteins binding directly to ceramide. We identified 234 candidate ceramide-binding protein fragments and validated binding for 20. Most (17) bound selectively to ceramide, although a few (3) bound to other lipids as well. Several novel ceramide-binding domains were discovered, including the EF-hand calcium-binding motif, the heat shock chaperonin-binding motif STI1, the SCP2 sterol-binding domain, and the tetratricopeptide repeat region motif. Interestingly, four of the verified ceramide-binding proteins (HPCA, HPCAL1, NCS1, and VSNL1) and an additional three candidate ceramide-binding proteins (NCALD, HPCAL4, and KCNIP3) belong to the neuronal calcium sensor family of EF hand-containing proteins. We used mutagenesis to map the ceramide-binding site in HPCA and to create a mutant HPCA that does not bind to ceramide. We demonstrated selective binding to ceramide by mammalian cell-produced wild type but not mutant HPCA. Intriguingly, we also identified a fragment from prostaglandin D2synthase that binds preferentially to ceramide 1-phosphate. The wide variety of proteins and domains capable of binding to ceramide suggests that many of the signaling functions of ceramide may be regulated by direct binding to these proteins. Based on the deep sequencing data, we estimate that our yeast surface cDNA display library covers ?60% of the human proteome and our selection/deep sequencing protocol can identify target-interacting protein fragments that are present at extremely low frequency in the starting library. Thus, the yeast surface cDNA display/deep sequencing approach is a rapid, comprehensive, and flexible method for the analysis of protein-ligand interactions, particularly for the study of non-protein ligands.

Dataset Information

R-DeeP: Proteome-wide and Quantitative Identification of RNA-Dependent Proteins by Density Gradient Ultracentrifugation.

Publications

R-DeeP: Proteome-wide and Quantitative Identification of RNA-Dependent Proteins by Density Gradient Ultracentrifugation.

Similar Datasets

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