Dataset Information

Protein phosphorylation evolution across 18 fungal species

ABSTRACT: Protein phosphorylation evolution across 18 fungal species. For each species whole cell extracts were digested separately with trypsin and LysC. Each digest was IMAC enriched and analyzed by LC-MS/MS in technical triplicate on an LTQ Orbitrap Velos using a 120min method. Data was searched against the corresponding species using Sequest/Comet, and filtered to 1% FDR at the PSM level. For S.Cerevisiae, S.Pombe and S.Mikatae, cells were grown in triplicate under 3 different conditions: YPD, YPD + mild temperature stress and optimized "best media". For these cells whole cell extracts were produced, digested with trypsin and IMAC enriched and analyzed by LC-MS/MS on an LTQ Orbitrap Velos using a 120min method. Data was searched against the corresponding species using Sequest/Comet, and filtered to 1% FDR at the PSM level. S. cerevisiae cells transformed with tagged versions of CDC33 WT, alanine (S28A) and glutamic acid (S28E) mutants were generated. Mutant strain were grown three distinct (heavy, medium and light) SILAC media under overexpression conditions. Cells for each construct were harvested and pooled together and used for the pull down experiments, done in triplicate. Pulldown eluate was digested with LysC and analyzed on a QExactive instrument with 90min method. Data was searched against S.Cerevisiae database including the tagged CDC33 proteins using Sequest/Comet, and filtered to 1% FDR at the PSM level.

OTHER RELATED OMICS DATASETS IN: PRJNA319164

INSTRUMENT(S): LTQ Orbitrap Velos, Q Exactive

ORGANISM(S): S. Cerevisiae, S. Paradoxus, S. Mikatae, S. Kudriavzevii, S. Bayanus, N. Castellii, C. Glabrata, V. Polyspora, Z. Rouxii, K. Lactis, L. Kluyveri, L. Thermotolerans, L. Waltii, K. Pastoris, M. Guilliermondii, C. Albicans, S. Stipitis, S. Pombe

SUBMITTER: Judit Vill�n

PROVIDER: MSV000079428 | MassIVE | Fri Dec 18 14:33:00 GMT 2015

REPOSITORIES: MassIVE

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Publications

Evolution of protein phosphorylation across 18 fungal species.

Studer Romain A RA Rodriguez-Mias Ricard A RA Haas Kelsey M KM Hsu Joanne I JI Viéitez Cristina C Solé Carme C Swaney Danielle L DL Stanford Lindsay B LB Liachko Ivan I Böttcher René R Dunham Maitreya J MJ de Nadal Eulàlia E Posas Francesc F Beltrao Pedro P Villén Judit J

Science (New York, N.Y.) 20161001 6309

Living organisms have evolved protein phosphorylation, a rapid and versatile mechanism that drives signaling and regulates protein function. We report the phosphoproteomes of 18 fungal species and a phylogenetic-based approach to study phosphosite evolution. We observe rapid divergence, with only a small fraction of phosphosites conserved over hundreds of millions of years. Relative to recently acquired phosphosites, ancient sites are enriched at protein interfaces and are more likely to be func ...[more]

PMID: 27738172

Similar Datasets

Project description:Soybean (Glycine max (L.) Merr. cv Jack) seed development was separated into nine defined stages (S1 to S9). Testa (seed coats) were removed from developing seeds at stages S2, 4, 6, 8, and 9, and subjected to shotgun proteomic profiling. For each stage "total proteins" were isolated from 150mg dry weight of seed coat using a phenol-based method, then reduced, alkylated, and digested with trypsin. The tryptic peptides were separated using a C18-reversed phase matrix, then analyzed using an LTQ Orbitrap Mass Spectrometer. Spectra were searched against the Phytozome G. max DB using the Sorcerer 2 IDA Sequest-based search algorithm. Identities were verified using Scaffold 3. A total of 306 (S2), 328 (S4), 273 (S6), 193 (S8), and 272 (S9) proteins were identified in three out of three biological replicates, and sorted into 11 functional groups: Primary Metabolism, Secondary Metabolism, Cellular Structure, Stress Responses, Nucleic Acid metabolism, Protein Synthesis, Protein Folding, Protein Targeting, Hormones and Signaling, Seed Storage Proteins, and Proteins of Unknown Function. In selected instances, individual seed coat proteins were quantified by spectral counting. The number of proteins involved in intermediary metabolism, flavonoid biosynthesis, protein folding and degradation are discussed as they relate to seed coat function. A database was constructed using the open reading frames of Phytozome G. max DB (updated August 8, 2009), plus a decoy DB generated by reversing the target sequences. Spectra were searched against the combined target-decoy DB using the Sorcerer 2 IDA Sequest-based search algorithm. Identities were verified using the Scaffold 3 program, and the false discovery rate (FDR) was estimated as (Ndecoy/Ntarget). For 186,364 peptide spectra examined, the FDR was between 5.18 and 5.26%. Samples were analyzed in biological triplicate; proteins were included in the results only if they were identified in all three biological replicates. Relative protein abundance was quantified by spectral counting ; data presented are the mean of three independent determinations. The coefficient of variation values calculated for each developmental stage are < 0.0516.

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.