Dataset Information

Protein methylation analysis of Jurkat cells

ABSTRACT: Protein methylation, especially in arginine and lysine, is one of most important post-translational modifications (PTMs). In this project, we developed a novel chemical strategy which enabled almost complete depletion of histidine-conatining peptides in protein digestion and thereby resulted in the identification of more low-abundance arginine/lysine methylpeptides.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Qi Wang

LAB HEAD: Mingliang Ye

PROVIDER: PXD023845 | Pride | 2021-03-08

REPOSITORIES: Pride

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Dataset's files

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			Action	DRS
	Table_S1._Identified_methylation_forms_in_this_study.xlsx	Xlsx
	WQ1_QE_hmJurkat_TL_DM_Rep1.raw	Raw
	WQ1_QE_hmJurkat_TL_DM_Rep2.raw	Raw
	WQ1_QE_hmJurkat_TL_DM_Rep3.raw	Raw
	WQ1_hmJurkatT_TLA_DM_SCX_Enrichment_ACR_Dehis_Rep1.raw	Raw

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Project description:The covalent attachment of methyl groups to the side-chain of arginine residues is known to play essential roles in regulation of transcription, protein function and RNA metabolism. The specific N-methylation of arginine residues is catalyzed by a small family of gene products known as protein arginine methyltransferases; however, very little is known about which arginine residues become methylated on target substrates. Here we describe an unbiased methodology that combines single-step immunoenrichment of methylated peptides with high-resolution mass spectrometry to identify endogenous arginine mono-methylation (MMA) sites. We thereby identify 1,027 site-specific MMA sites on 494 human proteins, discovering numerous novel mono-methylation targets and confirming the majority of currently known MMA substrates. Nuclear RNA-binding proteins involved in RNA processing, RNA localization, transcription, and chromatin remodeling are prominently found modified with MMA. Despite this, MMA sites prominently are located outside RNA-binding domains as compared to the proteome-wide distribution of arginine residues. Quantification of arginine methylation in cells treated with Actinomycin D uncovers strong site-specific regulation of MMA sites during transcriptional arrest. Interestingly, several MMA sites are down-regulated after a few hours of under transcriptional arrest. In contrast, the corresponding di-methylation or protein expression level is not altered in expression, confirming that MMA sites contain regulated functions on their own. Collectively, we present a site-specific MMA dataset in human cells and demonstrate for the first time that MMA is a dynamic post-translational modification regulated during transcriptional arrest by a hitherto uncharacterized arginine demethylase. Data analysis: All raw data analysis was performed with MaxQuant software suite version 1.2.6.20 supported by the Andromeda search engine. Data was searched against a concatenated target/decoy (forward and reversed) version of the UniProtKB Human database encompassing 71,434 protein entries. Mass tolerance for searches was set to maximum 7 ppm for peptide masses and 20 ppm for HCD fragment ion masses. Data was searched with carbamidomethylation as a fixed modification and protein N-terminal acetylation, methionine oxidation and mono-methylation on lysine and arginine as variable modifications. A maximum of three mis-cleavages was allowed while requiring strict trypsin specificity, and only peptides with a minimum sequence length of seven were considered for further data analysis. Peptide assignments were statistically evaluated in a Bayesian model on the basis of sequence length and Andromeda score. Only peptides and proteins with a false discovery rate (FDR) of less than 1% were accepted, estimated on the basis of the number of accepted reverse hits. Protein sequences of common contaminants such as human keratins and proteases used were added to the database.

Project description:Protein extraction and proteolytic digestion were performed using a Filter-Assisted Sample Preparation (FASP) protocol. In case of phosphopeptide enrichment immobilized Fe(III) affinity chromatography (Fe-IMAC) was performed. The peptides were fractionated using an HPLC system fitted with an SCX column. 10 sample datasets were used: 1. CRC_N: Normal tissue samples were obtained from 20 colorectal cancer patients, no quantification.Phosphopeptide enrichment was performed. 2. CRC_T: Human colorectal cancer tissue samples were obtained from 20 patients, no quantification. Phosphopeptide enrichment was performed. 3. CRC_iTRAQ: Human colorectal cancer tissue samples were obtained from 24 patients, iTRAQ quantification. 4. CRC_phospho_iTRAQ:Human colorectal cancer tissue samples were obtained from 24 patients, iTRAQ quantification.Phosphopeptide enrichment was performed. 5. HCT116_iTRAQ: Human colon cancer cell HCT116, iTRAQ quantification. 6. HCT116_phospho_iTRAQ: Human colon cancer cell HCT116, phosphopeptide enrichment, iTRAQ quantification. 7. SW_SILAC_HL: Human colon cancer cell SW480 and SW620, SW480 and SW620 were grown in SILAC media, containing l-arginine (Arg0) and l-lysine (Lys0) (SW480; light), or 13C615N4-l-arginine (Arg10) and 13C6-l-Lysine (Lys6) (SW620; heavy). 8. SW_SILAC_LH: SW480 and SW620 were grown in SILAC media, containing l-arginine (Arg0) and l-lysine (Lys0) (SW620; light), or 13C615N4-l-arginine (Arg10) and 13C6-l-Lysine (Lys6) (SW480; heavy). 9. SW_phospho_SILAC_HL: SW480 and SW620 were grown in SILAC media, containing l-arginine (Arg0) and l-lysine (Lys0) (SW480; light), or 13C615N4-l-arginine (Arg10) and 13C6-l-Lysine (Lys6) (SW620; heavy). Phosphopeptide enrichment was performed. 10. SW_phospho_SILAC_LH: SW480 and SW620 were grown in SILAC media, containing l-arginine (Arg0) and l-lysine (Lys0) (SW620; light), or 13C615N4-l-arginine (Arg10) and 13C6-l-Lysine (Lys6) (SW480; heavy). Phosphopeptide enrichment was performed. For creation of xml and mgf files, Proteome Discoverer 1.3 and Mascot v2.3 software were used.

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Protein methylation analysis of Jurkat cells

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