Synthetic (Phospho)Peptide Library
Ontology highlight
ABSTRACT:
INSTRUMENT(S): LTQ Orbitrap Velos
ORGANISM(S): Homo Sapiens (ncbitaxon:9606)
SUBMITTER: None Listed
PROVIDER: MSV000091718 | MassIVE | Fri Apr 14 16:51:00 BST 2023
SECONDARY ACCESSION(S): PXD000138
REPOSITORIES: MassIVE
Publications
A large synthetic peptide and phosphopeptide reference library for mass spectrometry-based proteomics.
Marx Harald H Lemeer Simone S Schliep Jan Erik JE Matheron Lucrece L Mohammed Shabaz S Cox Jürgen J Mann Matthias M Heck Albert J R AJ Kuster Bernhard B
Nature biotechnology 20130519 6
We present a peptide library and data resource of >100,000 synthetic, unmodified peptides and their phosphorylated counterparts with known sequences and phosphorylation sites. Analysis of the library by mass spectrometry yielded a data set that we used to evaluate the merits of different search engines (Mascot and Andromeda) and fragmentation methods (beam-type collision-induced dissociation (HCD) and electron transfer dissociation (ETD)) for peptide identification. We also compared the sensitiv ...[more]
Similar Datasets
Project description:The submitted dataset contains raw files from 96 synthetic peptide libraries, using either HCD or ETD as fragmentation technique. The synthesized 96 tryptic peptide libraries containing >100,000 unmodified peptides plus their corresponding >100,000 phosphorylated counterparts with precisely known sequences and modification sites. All these libraries were subjected to LC-MS/MS on an Orbitrap mass spectrometer using HCD and ETD fragmentation. The generated mass spectrometric data deposited in this database can be used in numerous ways to develop, evaluate and improve experimental and computational proteomic strategies. Raw MS data files were converted into Mascot generic format files (MGF) using Mascot Distiller (2.4.2.0, www.matrixscience.com). Important parameters included: i) signal to noise ratio of 20 for MS/MS and ii) time domain off (no merging of spectra of the same precursor). The MGF files were searched against human IPI v3.72 including the sequences of all 96 libraries,using the Mascot search engine (2.3.1, 24). Search settings: Decoy search using a randomized version of the human IPI v3.72 including the sequences of all 96 libraries was enabled; monoisotopic peptide mass (considering up to two 13C isotopes); trypsin/P as protease; a maximum of four missed cleavages; peptide charge +2 and +3; peptide tol. +/- 5 ppm; MS/MS tol. +/- 0.02 Da; instrument type ESI-Trap (for HCD data) or ETD-Trap (for ETD data) respectively; variable modifications: oxidation (M), phospho (ST), phospho (Y). The result files were exported to pepXML and Mascot XML with default options provided by Mascot.
2013-05-05 | PXD000138 | Pride
Project description:The platelet releasate defined by quantitative reversed protein profiling. Dimethyl labeled proteins of platelets in resting (light label) and activated state (collagen and thrombin activation, intermediate label) from three healthy volunteers fractionated by SCX, analyzed on a LTQ Obitrap Velos using a data dependent decision tree method (HCD/ETD).Peak lists were generated from the raw data files using the Proteome Discoverer software package version 1.3.339. Peptide identification was performed by searching the individual peak lists (HCD, ETD-IT and ETD-FT) against a concatenated target-decoy database containing the human sequences in the Uniprot database (release 2012_06) supplemented with a common contaminants database using the Mascot search engine version 2.3 (Matrix Science, London, United Kingdom) via the Proteome Discoverer interface (version 1.3). The search parameters included the use of semitrypsin as proteolytic enzyme allowing up to a maximum of 2 missed cleavages. Carbamidomethylation of cysteines was set as a fixed modification whereas oxidation of methionines and the dimethyl light and intermediate labels on N-termini and lysine residues were set as variable modifications. Precursor mass tolerance was initially set at 50 ppm, while fragment mass tolerance was set at 0.6 Da for ETD-IT fragmentation and 0.05 Da for HCD and ETD-FT fragmentation. Subsequently, the peptide identifications were filtered for true mass accuracy <4 ppm and an ion score of 40 until an FDR <1% at peptide level was achieved.
2014-02-03 | PXD000072 | Pride
Project description:Here we evaluate and explore a peptide-centric antibody generated to selectively enrich peptides containing the cAMP-dependent protein kinase A (PKA) consensus motif. This targeted phospho-proteomic strategy is used to profile temporal quantitative changes of protein PKA substrates in Jurkat T-lymphocytes upon prostaglandin E2 stimulation, which increases intracellular cAMP activating PKA. Our method combines ultra-high specificity PKA-motif-based immunoaffinity purification with cost-efficient stable isotope dimethyl labeling. The data set coprises of 4 raw files, 3 of them (IP, IP_2 and IP_3) are the LC-MSMS technical replicates of the eluate of the immunoprecipitation, while the MIX raw files correpsond to the LC-MSMS analysis of the pre-IP cell lysate digest.Each raw data file was processed and quantified with Proteome Discoverer (version 1.3, Thermo Scientific). Peak lists containing HCD and ETD fragmentation were generated with a signal-to-noise threshold of 1.5. The ETD non-fragment filter was also taken into account with the following settings: the precursor peak was removed within a 4 Da window, charged reduced precursors were removed within a 2 Da window, and neutral losses from charged reduced precursors were removed within a 2 Da window and the maximum neutral loss mass was set to 120 Da. All generated peak lists of the IP were searched against a concatenated forward-decoy Swissprot human database (version 2012_09, 40,992 sequences) while the MIX file was searched against a Swissprot database version 2012_09 with taxonomy Homo sapiens (20,235 sequences) by the use of Mascot software (version 2.3.02 Matrix Science). The database search was performed with the following parameters: a mass tolerance of ±50 ppm for precursor masses; ±0.6 Da for ETD-ion trap fragment ions; ±0.05 Da for HCD and ETD-Orbi trap fragment ions, allowing two missed cleavages, cysteine carbamidomethylation as fixed modification. Light, intermediate and heavy dimethylation of peptide N-termini and lysine residues; methionine oxidation; phosphorylation on serine and threonine (only for the IP) were set as variable modifications. The enzyme was specified as Lys-C and the fragment ion type was specified as electrospray ionization FTMS-ECD, ETD-TRAP, and ESI-QUAD-TOF for the corresponding mass spectra. The phosphorylation site localization of the identified phosphopeptides was performed by the phosphoRS algorithm 2.0. The dimethyl-based quantitation method was chosen in Proteome Discoverer, with mass precision requirement of 2 ppm for consecutive precursor mass measurements. We applied 0.5 min of retention time tolerance for isotope pattern multiplets and allowed spectra with maximum 1 missing channels to be quantified. After identification and quantification, we combined all results originating from the same biological replica and filtered them with the following criteria: (i) mass deviations of ±10 ppm, (ii) Mascot Ion Score of at least 20, (iii) a minimum of 6 amino-acid residues per peptide and (iv) position rank 1. Mascot results of the MIX analysis were filtered with the same parameters and with the integrated Percolator based filter using an FDR <1% (based on PSMs).
2013-07-25 | PXD000148 | Pride
Project description:In this project, we aim to pair-wise analyze the genomes, transcriptomes and proteomes of in-bred rats originating from two different genetic backgrounds. These two strains are Brown Norway (BN-Lx) and Spontaneously Hypertensive Rats (SHR). First, we re-sequenced the genomes for both BN and SHR rats, followed by RNA-seq and proteomics of their liver tissues. We then append novel predicted gene models, non-synonymous SNPs and INDELs (derived from genome re-sequencing), as well as transcript variants such as RNA-editing and alternative splicing (derived from RNA-seq) that can diversify existing protein sequences onto the ENSEMBL rat FASTA (Build 68) to build an enhanced database. For proteomics studies, equal amount of liver lysates were digested with trypsin, LysC, GluC, AspN and chymotrypsin and were individually fractionated with strong cationic exchange chromatography. Doubly- and triply-charged fractions were analyzed with an Triple-TOF 5600 with collision-activated dissociation (CAD); while electron-transfer dissociation (ETD) was applied for fractions containing triple charges and above with a LTQ-Orbitrap Velos. Data analysis: Peak List generation: For Wiff files generated from TripleTOF 5600, tandem MS spectra were de-isotoped, charge- deconvoluted and peak lists converted to Mascot generic format (MGF) files using AB Sciex Data Converter (version 1.1). For data generated from the LTQ-Orbitrap Velos, Raw files were converted to MGF files using Proteome Discoverer (version 1.3). The non-fragment filter was used to simplify ETD spectra and the Top N filter for the HCD spectra. Three MGF files were generated (one for HCD, one for ETD IT and one for ETD FT). The files with an orbitrap readout were deisotoped and charge de-convoluted. Database Searching: All MGF files were queried with Mascot search engine (version 2.3) via Proteome Discoverer version 1.3 (PD 1.3, Thermo Fisher) for submission. The spectra were searched against in-house database (NGS_COMBINED). One of the five different enzymes used (Trypsin/P, LysC/P, Chymotrypsin, GluC-DE and AspN_ambic) were selected for each file and up to 9 missed cleavages were allowed. Cysteine carbamidomethylation was set as fixed modification, and oxidation of methionine and acetylation of the N-term as variable modifications. Peptide tolerance was initially set to 50 ppm and the MS/MS tolerance was set to 0.1 Da (for TOF readout), 0.02 Da (orbitrap readout) and 0.5 Da (ion trap readout). All peptide-spectrum matches (PSMs) were evaluated with Percolator for validation. We classified each PSM based on their q value. For proteins identification, we used set a high stringency filter of q = 0 (0% FDR). For peaks lists that do not yield any peptide matches, we exported them with PD 1.3 for further analysis. De novo search with PEAKS: Unassigned peak lists that are exported were re-analyzed with another software suite i.e. PEAKS Studio (version 6.0). The identification workflows is as follows. Peak lists were first filtered with a quality value of 0.65 as suggested by the manufacturer followed by de novo spectra interpretation. In this step, both peptide tolerance and MS/MS tolerance were set according to MASCOT search. To broaden the search space for these unassigned spectra, we additionally set de-amidation of asparagine and glutamine, and pyro-glu from glutamic acid and glutamine as variable modifications, on top of the other modifications indicated above. Maximum allowed variable PTM per peptide was set to 3. Finally de novo interpreted PSMs were submitted to PEAKS DB database matching, this time allowing semi-enzymatic specificity and a maximum cleavages per peptide of 2. Database used was set to NGS_COMBINED. FDR was estimated using decoy-fusion. The genomics and transcriptomics data are already deposited in the respective EBI repositories. Some of these data are derived from an already published manuscript. For the genomics data (from: Genetic basis of transcriptome differences between the founder strains of the rat HXB/BXH recombinant inbred panel by Simonis et al PMID:22541052) DNA data in Sequence Read Archive (SRA): BN-Lx genome: ERP001355 http://www.ebi.ac.uk/ena/data/view/ERP001355, SHR genome: ERP001371, BN reference genome: ERP000510, http://www.ebi.ac.uk/ena/data/view/ERP000510. RNA data in ArrayExpress: BN-Lx and SHR fragment RNA-seq data: E-MTAB-1029 http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1029, BN-Lx and SHR paired-end RNA-seq data: to be submitted.
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2013-08-02 | PXD000174 | Pride
Project description:Propargyl labeled ubiquitin was immobilized on beads and used for click-chemistry based pull downs. Covalently linked proteins were washed and digested off-bead, or eluted with strong acid and loaded into a SDS-PAGE gel. Digestion with Lys-C, trypsin consequetively and LC-MS/MS. Both dimethyl labeling, as well as qualitative measurements were done. For both the qualitative and the quantitative dataset peak lists were generated from the raw data files using the Proteome Discoverer software package version 1.3.339. Peptide identification was performed by searching the combined peak lists of the entire gel lane (10 bands) against a concatenated target-decoy database containing the human sequences in the Uniprot database (release 2012_06) supplemented with a common contaminants database using the Mascot search engine version 2.3 via the Proteome Discoverer interface. The search parameters included the use of trypsin as proteolytic enzyme allowing up to a maximum of 2 missed cleavages. For the qualitative dataset, carbamidomethylation of cysteines was set as a fixed modification whereas oxidation of methionines was set as variable modification. Precursor mass tolerance was initially set at 50 ppm, while fragment mass tolerance was set at 0.6 Da. Subsequently, the peptide identifications were filtered for true mass accuracy <10 ppm and an ion score of 25. For the quantitative dataset carbamidomethylation of cysteines was set as a fixed modification whereas oxidation of methionines and the dimethyl light and intermediate labels on N-termini and lysine residues were set as variable modifications. Precursor mass tolerance was initially set at 50 ppm, while fragment mass tolerance was set at 0.6 Da for ETD-IT fragmentation and 0.05 Da for HCD and ETD-FT fragmentation. Subsequently, the peptide identifications were filtered for true mass accuracy <10 ppm and an ion score of 25.
2013-08-14 | PXD000073 | Pride
Project description:Multidimensional peptide fractionation is widely used in proteomics to reduce the complexity of peptide mixtures prior to mass spectrometric analysis. Here, we describe the sequential use of strong cation exchange and reversed phase liquid chromatography in both basic and acidic pH buffers for separating tryptic peptides from complex mixtures of proteins. Strong cation exchange exclusively separates peptide by their charge state into neutral, singly and multi-charged species. To further reduce complexity, each peptide group was separated by reversed phase liquid chromatography at basic pH and the resultant fractions were analyzed by LC-MS/MS. This workflow was applied to a soluble protein lysate from mouse embryonic fibroblast cells were more than 5000 proteins from 30470 peptides were identified. The high selectivity displayed during the SCX step (95% to 100%) and the overlaps between proteins identified from the SCX-separated peptide groups, result in additional assets of the procedure that significantly increase the confidence of protein identifications. Raw data files were processed with Mascot Distiller (2.2), the mgf files were searched with Mascot Daemon (2.4), all data was stored in ms_lims Fixed modifications: cysteine alkylation Variable modifications: methionine oxidation, protein N-terminus acetylation, pyroglutamate formation of N-terminal glutamine, cyclic carbamate formation of N-terminal threonine or serine Enzyme: trypsin/P with 2 missed cleavages allowed Precursor mass tolerance: 10 ppm Peptide fragment mass tolerance: 0.5 Da Database: Swiss Prot mouse (version 56.4) The xml files of RH0 - RH1 - RH2 CID were created with pride converter 2.5.5 because this is still able to link to ms_lims. The old converter can not deal with ETD spectra, so the xml file of RH2 ETD was created with the new pride converter 2.0.3. But there is no link possible with ms_lims here, the dat files were used for xml file creation. Because of this, there's a small difference between the number of proteins and peptides in the xml file and the ones reported in the manuscript. Therefor, an extra excel file is submitted that contains all of the ETD identifications that were used in the manuscript.
2013-11-27 | PXD000210 | Pride
Project description:Capillary zone electrophoresis (CZE)-tandem mass spectrometry (MS/MS) has been recognized as an efficient approach for top-down proteomics recently for its high-capacity separation and highly sensitive detection of proteoforms. However, the commonly used collision-based dissociation methods often cannot provide extensive fragmentation of proteoforms for thorough characterization. Activated ion electron transfer dissociation (AI-ETD), that combines infrared photoactivation concurrent with ETD, has shown better performance for proteoform fragmentation than higher energy-collisional dissociation (HCD) and standard ETD. Here, we present the first application of CZE-AI-ETD on an Orbitrap Fusion Lumos mass spectrometer for large-scale top-down proteomics of Escherichia coli (E. coli) cells. CZE-AI-ETD outperformed CZE-ETD regarding proteoform and protein identifications (IDs). CZE-AI-ETD reached comparable proteoform and protein IDs with CZE-HCD. CZE-AI-ETD tended to generate better expectation values (E-values) of proteoforms than CZE-HCD and CZE-ETD, indicating higher quality of MS/MS spectra from AI-ETD respecting the number of sequence-informative fragment ions generated. CZE-AI-ETD showed great reproducibility regarding the proteoform and protein IDs with relative standard deviations less than 4% and 2% (n=3). Coupling size exclusion chromatography (SEC) to CZE-AI-ETD identified 3028 proteoforms and 387 proteins from E. coli cells with 1% spectrum-level and 5% proteoform-level false discovery rates. The data represents the largest top-down proteomics dataset using the AI-ETD method so far. Single-shot CZE-AI-ETD of one SEC fraction identified 957 proteoforms and 253 proteins. N-terminal truncations, signal peptide cleavage, N-terminal methionine removal and various post-translational modifications including protein N-terminal acetylation, methylation, S-thiolation, disulfide bonds, and lysine succinylation were detected.
2019-06-11 | PXD012247 | Pride
Project description:The oomycete Phytophthora infestans is the causal agent of late blight in potato and tomato. Since the underlying processes that govern pathogenicity and development in P. infestans are largely unknown, we have performed a large-scale phosphoproteomics study of six different P. infestans life stages. We have obtained quantitative data for 2922 phosphopeptides and compared their abundance in different life stages. The samples were analysed on an LTQ Orbitrap XL ETD, operated in data dependent mode to automatically perform Orbitrap-MS and LTQ-MS/MS analysis. The raw data from the Orbitrap was converted to .mgf files using ProteoWizard. The Proteios software environment was used to search the mgf files with Mascot version 2.3.01 against a database consisting of all P. infestans proteins in UniProt as of 2010-04-22, concatenated with an equal size decoy database (random protein sequences with conserved protein length and amino acid distribution, in total 36,512 target and decoy protein entries). Search tolerances were set to 7 ppm for MS and 0.5 Da for MS/MS. One missed cleavage was allowed. Carbamidomethylation of cysteine residues was selected as a fixed modification and oxidation of methionine residues and phosphorylation of serine, threonine and tyrosine residues were selected as variable modifications. Search results were exported from Mascot as XML, including query level results, with a modification to the export script to include protein accession numbers also for the query (spectrum) level results. All search results, including the top ranked peptide for each spectrum, were imported to Proteios, where q values were calculated using the target-decoy method.
2014-03-27 | PXD000433 | Pride
Project description:Plasmodium falciparum schizont proteins were extracted using SDS, digested with trypsin and phosphopeptides were enriched using IMAC. Phosphopeptides were analysed using either decision tree or data dependent neutral loss triggered ETD acquisition. All raw MS data files were processed and converted into MGF file format using Proteome Discoverer 1.1 (Thermo Scientific). A precursor filter of 600-10000 Da and a non-fragment filter were applied to ETD spectra to remove un-reacted precursor peaks, charge reduced precursor peaks, neutral losses from charge reduced precursors and FT Overtones using default settings. All ion trap spectra with less than 15 fragmentation peaks were removed and a signal to noise filter of 3 was applied to all spectra. All datasets were searched using Mascot v2.2 (Matrix Science) against a combined Human (IPI, 2010) and Plasmodium falciparum (GeneDB) sequence database (79,637 sequences) using the following search parameters: trypsin with a maximum of 3 missed cleavages, 10 ppm for MS mass tolerance, 0.5 Da for MS/MS mass tolerance, with Acetyl (Protein N-term), Oxidation (M), Deamidated (NQ), Carbamidomethyl (C) and Phospho ST set as variable modifications. ETD spectra were searched using c, z and y ion series and CID data was searched using b and y ion series. All searches used Mascot’s automated decoy database searching.
2014-04-24 | PXD000070 | Pride