Project PXD010520

PRIDE Assigned Tags:
Biomedical Dataset

Summary

Title

The Human RNA-Binding Proteome and Its Dynamics During Arsenite-Induced Translational Arrest

Description

The data presented here was produced using XRNAX - a novel extraction method for protein-crosslinked RNA from UV-crosslinked cells. We apply XRNAX for three proteomic downstream applications. First, we purify ribonucleotide-crosslinked peptides from XRNAX extracts and use their identification as direct evidence for protein-RNA interfaces. Second, we use SILAC, XRNAX and silica enrichment in order to derive high-confidence RNA-binding proteomes from the three human cell lines MCF7, HEK293 and HeLa. Third, using SILAC we quantify total proteomes and RNA-binding proteomes differentially during a time course experiment of arsenite stress in MCF7 cells.

Sample Processing Protocol

In order to make XRNAX and its applications accessible to a wide audience and to promote the development of second party applications we created a website accessible under www.xrnax.com, where detailed protocols are presented with schemes and illustrations.

Data Processing Protocol

All MS raw files were searched using MaxQuant (1.5.1.2), except for data of nucleotide-crosslinked peptides. The database searched was the reviewed UniProt human proteome (search term: ‘reviewed:yes AND proteome:up000005640’, 20216 entries, retrieved 11 September 2017) and the default Andromeda list of contaminants. All settings were used at their default value, except for specifying SILAC configurations and indicating the appropriate number of fractions per sample. For the differential quantification of RNA-binding during arsenite stress the match-between-runs option was activated, for all other searches this was explicitly not the case. MS data of nucleotide-crosslinked peptides was searched with MSFragger using the same UniProt database as mentioned above. Precursor mass tolerance was set to 1000 Da and the export format set to tsv, otherwise all settings were used at their default value.

Contact

Sophia Foehr, DKFZ
Jeroen Krijgsveld, German Cancer Research Center (DKFZ), Heidelberg, Germany ( lab head )

Submission Date

20/07/2018

Publication Date

06/12/2018

Publication

Publication pending