Determining the Mitochondrial Methyl Proteome in Saccharomyces cerevisiae using Heavy Methyl SILAC
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Q Exactive
ORGANISM(S): Saccharomyces Cerevisiae (ncbitaxon:4932)
SUBMITTER: Steven Clarke
PROVIDER: MSV000080107 | MassIVE | Wed Aug 31 01:47:00 BST 2016
REPOSITORIES: MassIVE
Similar Datasets
Project description:Methylation on ribosome subunits and ribosime-associating proteins were compared in a low- and high-SAM conditions using heavy-methyl SILAC. Ribosome proteins were isolated in two ways; one was ultracentrifugation and the other was anti-FLAG immunoprecipitation using HeLa cells transfected with a FLAG-RPS2 expression vector or FLAG-RPL23a expression vector. The cells were grown in medium containing either light- or heavy-labelled methionine and then cycloleucine, an inhibitor of SAM synthesis enzymes, was added to the heavy-labelled culture to reduce intracellular SAM level. Ribosome proteins were purified by either ultracentrifugation or anti-FLAG immunoprecipitation. he samples were separated by SDS-PAGE and were in-gel-digested with trypsin. Files 201211-1 to 4: results from ultracentrifugation, 201219-7 to 9: anti-FLAG IP using FLAG-RPL23a expressing HeLa cells.
2022-04-21 | MSV000089296 | MassIVE
Project description:Methylation is a common and abundant post-translational modification. High-throughput proteomic investigations have reported many methylation sites from complex mixtures of proteins. The lack of consistency between parallel studies, resulting from both false positives and missed identifications, suggests problems with both over-reporting and under-reporting methylation sites. However, isotope labeling can be used effectively to address the issue of false-positives, and fractionation of proteins can increase the probability of identifying methylation sites in lower abundance. Here we have adapted heavy methyl SILAC to analyze fractions of the budding yeast Saccharomyces cerevisiae under respiratory conditions to allow for the production of mitochondria, an organelle whose proteins are often overlooked in larger methyl proteome studies. We have found 12 methylation sites on 11 mitochondrial proteins as well as an additional 14 methylation sites on 9 proteins that are nonmitochondrial. Of these methylation sites, 20 sites have not been previously reported. This study represents the first characterization of the yeast mitochondrial methyl proteome and the second proteomic investigation of global mitochondrial methylation to date in any organism.
| S-EPMC5148652 | biostudies-literature
Project description:The formation of condensates in membraneless organelles is thought to be driven by protein phase separation. Arginine methylation and serine/threonine phosphorylation are important in the phase separation process, however these post-translational modifications are often present in intrinsically disordered regions that are difficult to analyse with standard proteomic techniques. Here we use a multi-protease and multi-MS/MS fragmentation approach, coupled with heavy methyl SILAC and phospho- or methyl-peptide enrichment, for the analysis of arginine methylation and serine/threonine phosphorylation, and to understand their co-occurrence in condensate-associated proteins. For Saccharomyces cerevisiae, we report a 50% increase in the known arginine methylproteome, involving 15 proteins that are almost all condensate-associated. Importantly, some of these proteins have arginine methylation on all predicted sites – providing evidence that this modification can be pervasive. We explored whether arginine methylated condensate-associated proteins are also phosphorylated, and found 12 such proteins to carry phosphoserine or phosphothreonine. In Npl3, Ded1 and Ssbp1, single peptides were found to carry both modifications, indicating a co-occurrence in close proximity and on the same protein molecule. We show that these co-modifications occur in regions of disorder and that arginine methylation is typically on basic regions of disorder. For phosphorylation, its association with charged regions of condensate-associated proteins was less consistent, although some regions with multisite phosphorylation sites were strongly acidic. We conclude that arginine-methylated proteins associated with condensates are typically co-modified with protein phosphorylation.
2021-09-17 | PXD022403 | Pride
Project description:S-adenosylmethionine (SAM) is the principal biological methyl group donor for a diverse range of substrates. It is synthesised in the cytosolic methionine cycle and shuttled throughout the cell. The mitochondrial SAM (mitoSAM) pool depends on import through the inner-membrane S-adenosylmethionine carrier (SAMC) and supports the maturation of metabolites and mitochondrial RNAs. Mutations in SAMC in patients cause a severe metabolic crisis, however, the organellar regulation of mitoSAM and the protein methylation landscape within mitochondria are largely unknown. We developed a fly-compatible SILAC labelling technique and mapped mitochondrial protein methylation sites in Drosophila melanogaster, further showing that SAM is the sole methyl group donor for these modifications, with no contribution from folate-species. This dataset comprises MS-runs used for quality control of methyl-SILAF, the methylome mapping and exclusion of folates as protein methyl-group donors.
2021-02-21 | PXD019654 | Pride
Project description:All large-scale LC-MS/MS post-translational methylation site discovery experiments require methylpeptide spectrum matches (methyl-PSMs) to be identified at acceptably low false discovery rates (FDRs). To meet estimated methyl-PSM FDRs, methyl-PSM filtering criteria are often determined using the target-decoy approach. The efficacy of this methyl-PSM filtering approach has, however, yet to be thoroughly evaluated. Here we conduct a systematic analysis of methyl-PSM FDRs across a range of sample preparation workflows (each differing in their exposure to the alcohols methanol and isopropanol) and mass spectrometric instrument platforms (each employing a different mode of MS/MS dissociation). Through 13CD3-methionine labeling (heavy-methyl SILAC) of S. cerevisiae cells and in-depth manual data inspection, accurate lists of true positive methyl-PSMs were determined, allowing methyl-PSM FDRs to be compared to target-decoy approach-derived methyl-PSM FDR estimates. These results show that global FDR estimates produce extremely unreliable methyl-PSM filtering criteria; we demonstrate that this is an unavoidable consequence of the high number of amino acid combinations capable of producing peptide sequences that are isobaric to methylated peptides of a different sequence. Separate methyl-PSM FDR estimates were also found to be unreliable due to prevalent sources of false positive methyl-PSMs that produce high peptide identity score distributions. Incorrect methylation site localizations, peptides containing cysteinyl-S-β-propionamide, and methylated glutamic or aspartic acid residues can partially, but not wholly, account for these false positive methyl-PSMs. Together these results indicate that the target-decoy approach is an unreliable means of estimating methyl-PSM FDRs and methyl-PSM filtering criteria. We suggest that orthogonal methylpeptide validation (e.g. heavy-methyl SILAC or its offshoots) should be considered a prerequisite for obtaining high confidence methyl-PSMs in large-scale LC-MS/MS methylation site discovery experiments, and make recommendations on how to reduce methyl-PSM FDRs in samples not amenable to heavy isotope labeling.
2016-01-05 | PXD002857 | Pride
Project description:Purpose: The goals of this study is to compare the transcriptome (RNA-seq) modulations in Saccharomyces cerevisiae exposed to two rare earth elements. Lanthanum and ytterbium were used as representative of light and heavy rare earth elements, respectively. Methods: mRNA were sequenced from Saccharomyces cerevisiae exposed to two different rare earth elements. Lanthanum and ytterbium were used as representative of light and heavy rare earth elements respectively. The transcriptome of S. cerevisiae was analysed after being exposed for one hour to the EC10 (Effective concentration 10 %) and the EC50 (Effective concentration 50 %) of lanthanum (50 and 160 µM) and ytterbium (6 and 8 µM). The sequence reads were trimmed using Trimmomativ v0.36.1 and FastQC v0.67 used for quality check. Reads passing the quality check were mapped on the reference genome (S288C R64-2-1 of 2015-01-31 from https://www.yeastgenome.org/) of S. cerevisiae using TopHat v2.1.1. Reads that were mapped on the reference genome were quantified using HTSeq-count v0.6.1p1. Finally, differential gene expression analysis between treatments was carried out using DESeq2 v1.14.1. Differentially expressed genes between conditions were obtained and expressed as log2-fold change with adjusted p-values calculated via a Benjamini-Hochberg test. A cut-off adjusted p-value of < 0.01 was applied. Results: The transcription of genes related to several crucial pathways was modulated in response to both REEs, such as oxidative-reduction processes, DNA replication, and carbohydrate metabolism. REE-specific responses involving the cell wall and the pheromone signalling pathways were highlighted, while these were not reported for other metals. REE exposure also modified the expression and abundance of several ion transport systems, for which strong discrepancies were observed between the two contrasted REEs. Conclusions: Our results demonstrate the discrepancies in yeast response to different rare earth elements (light vs heavy rare earth elements). This results are valuable to prioritize key genes and proteins involved in REE detoxification mechanisms that would deserve further characterisation to better understand the REE toxicity on the environment and human health.
2021-06-01 | GSE175826 | GEO
Project description:Protein arginine (R) methylation is a post-translational modification that has been shown to play a role in various biological processes, such as RNA splicing, DNA repair, immune response, signal transduction and tumor development. Here, we present a dataset of high-quality methylations obtained from several different heavy methyl SILAC (hmSILAC) experiments analyzed with a machine learning model that was trained to recognize hmSILAC doublets and show that this model allows for improved high-confidence identification of methyl-peptides. The results of our analysis of the interactions between R-methylated proteins further support the idea that this modification plays a role in modulating protein:protein interactions and suggest a potential new role of R methylation in immunity and macrophage metabolism. Moreover, we intersect the methyl-site dataset with a phosphosite dataset to investigate the cross-talk between R methylation and phosphorylation. Finally, we explore the application of hmSILAC to identify unconventional methylated residues on both histone and non-histone proteins.
2022-06-02 | PXD027949 | Pride
Project description:TFIIH mutants treated with methyl methanesulfonate
| PRJNA91569 | ENA
Project description:SILAC labeled HT-1080 cell lysate (K0R0 and K8R10) were treated with active or catalytic inactive SETMAR methyltransferase enzyme. Samples were combined and proteins modified by methyl-lysine enriched by 3xMBT. Quantitative comparison identified candidate proteins with increase methylation following incubation with SETMAR.
2016-06-24 | PXD001635 | Pride
Project description:We developed a novel in-vitro experimental method to characterize the protein-DNA interaction specificity and methylation sensitivity, we called Methyl-Spec-seq. In this data set, mouse ZFP57 (F1-F3) was used as a positive control example to show that Methyl-Spec-seq can determine the relative binding energy for variants with different methylation property, i.e., unmethylated, top hemimethylated, bottom hemimethylated, duplex methylated by either chemical synthesis or enzymatic treatment.
2017-08-31 | GSE98686 | GEO