Dataset Information

Asn3 mass accuracy jurkat proteome

ABSTRACT: The use of internal calibrants (the so called lock mass approach) provides much greater accuracy in mass spectrometry based proteomics. However, the polydimethylcyclosiloxane (PCM) peaks commonly used for this purpose are quite unreliable, leading to missing calibrant peaks in spectra and correspondingly lower mass measurement accuracy. Therefore, we here introduce a universally applicable and robust internal calibrant, the tripeptide Asn3. We show that Asn3 is a substantial improvement over PCM both in terms of consistent detection and resulting mass measurement accuracy. Asn3 is also very easy to adopt in the lab, as it requires only minor adjustments to the analytical setup. Data analysis: For mass measurement accuracy (MMA) calculations and comparisons, the following Mascot workflow was used. From the MS/MS data in each LC run, Mascot Generic Files were created using Distiller software (version 2.4.3.3, Matrix Science, London, UK, www.matrixscience.com/distiller.html). These peak lists were then searched with the Mascot search engine (Matrix Science) using the Mascot Daemon interface (version 2.4.0, Matrix Science). Spectra were searched against the Swiss-Prot database (version 13_04 of UniProtKB/Swiss-Prot protein database containing 20,232 sequence entries of human proteins) concatenated with its reversed sequence database. Variable modifications were set to pyro-glutamate formation of amino terminal glutamine and acetylation of the protein N-terminus, whereas fixed modifications only included oxidation of methionine. Mass tolerance on peptide ions was set to 10 ppm (with Mascot’s C13 option set to 1), and the mass tolerance on peptide fragment ions was set to 20 millimass units (mmu), except for the space-charge effect experiment(LMA5) where an extra search was done with a setting of 3 mmu. The peptide charge was set to 1+,2+,3+ and instrument setting was put on ESI-QUAD. Enzyme was set to trypsin allowing for one missed cleavage, and cleavage was allowed when arginine or lysine is followed by proline. Only peptides that were ranked one and scored above the threshold score, set at 99% confidence, were withheld. All data was processed and managed by ms_lims.

INSTRUMENT(S): LTQ Orbitrap Velos, instrument model

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): T Cell, Cell Culture

SUBMITTER: An Staes

PROVIDER: PXD000426 | Pride | 2013-10-22

REPOSITORIES: Pride

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Publications

Asn3, a reliable, robust, and universal lock mass for improved accuracy in LC-MS and LC-MS/MS.

Staes An A Vandenbussche Jonathan J Demol Hans H Goethals Marc M Yilmaz Şule Ş Hulstaert Niels N Degroeve Sven S Kelchtermans Pieter P Martens Lennart L Gevaert Kris K

Analytical chemistry 20131104 22

The use of internal calibrants (the so-called lock mass approach) provides much greater accuracy in mass spectrometry based proteomics. However, the polydimethylcyclosiloxane (PCM) peaks commonly used for this purpose are quite unreliable, leading to missing calibrant peaks in spectra and correspondingly lower mass measurement accuracy. Therefore, we here introduce a universally applicable and robust internal calibrant, the tripeptide Asn3. We show that Asn3 is a substantial improvement over PCM ...[more]

PMID: 24134513

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Project description:Flooding is a serious problem for soybean cultivation because it markedly reduces growth. We found that treatment with ABA enhances survival ratio of soybean under flooding stress. To investigate the role of ABA in soybean under flooding stress, proteomic changes were analyzed. Total protein and nuclear protein fractions from root tips of soybean seedlings that treated with flooding or flooding with ABA were analyzed. Protein samples were cleaned up with chloroform/methanol method and then subjected to in-solution digestion with trypsin and lysyl endopeptidase. Resulting peptides were analyzed on a nanospray LTQ XL Orbitrap MS (Thermo Fisher Scientific) operated in data-dependent acquisition mode with the installed Xcalibur software (version 2.0.7, Thermo Fisher Scientific). Using an Ultimate 3,000 nanoLC system (Dionex), peptides in 0.1% formic acid were loaded onto a C18 PepMap trap column (300 µm ID × 5 mm, Dionex). The peptides were eluted from the trap column and their separation and spraying were done using 0.1% formic acid in acetonitrile at a flow rate of 200 nL/min on a C18 Tip column (75 µm 1D × 120 mm, nano HPLC capillary column, NTTC-360/75-3, Nikkyo Technos) with a spray voltage of 1.5 kV. The elution was done with a linear acetonitrile gradient 8-30% in 120 min for gel free proteomics in 0.1% formic acid. Full-scan mass spectra were acquired in the Orbitrap over a mass range of 400-1,500 m/z with a resolution of 30,000. A lock mass function was used to obtain high mass accuracy. The top 10 most intense precursor ions were selected for collision-induced fragmentation in the linear ion trap at normalized collision energy of 35%. Dynamic exclusion was employed within 90 sec to prevent repetitive selection of peptides.Identification of proteins were performed by Mascot search engine (version 2.3.0.2, Matrix Science) using soybean peptide database (55,787 sequences) obtained from the soybean genome database (Phytozome version 8.0)and a common contaminants database (262 sequences). Parameters used in Mascot searches were follows: Carbamidomethylation of cysteine was set as a fixed modification, and oxidation of methionine was set as a variable modification. Trypsin was specified as the proteolytic enzyme and one missed cleavage was allowed. Peptide mass tolerance was set at 5 ppm, fragment mass tolerance was set at 0.5 Da, and peptide charge was set at +2, +3, and +4. Automatic decoy database search was performed in the search. Mascot results were filtered with Mascot percolator to improve accuracy and sensitivity in the peptide identification. False discovery rates for peptide identification of all searches were less than 1.0%. The Mascot results were used for differential analysis using SIEVE software (version 2.0, Thermo Fisher Scientific).

Project description:Flooding injury is one of the abiotic constraints on soybean growth. An experimental system established for evaluating flooding injury in soybean seedlings indicated that the degree of injury is dependent on seedling density in floodwater. To understand the molecular mechanism responsible for the injury, proteomic alterations in soybean seedlings that correlated with severity of stress were analyzed using label-free quantitative proteomics. Two-day-old soybeans, seedlings flooded for 2 days and hypocotyls of seedlings grown for 3 days after flooding were analyzed. The radicles of soybean seedlings were separated to root tips (RT), roots without tip (RwoT) and hypocotyls (Hypo). Protein was extracted from these organs by TCA/Acetone method. Protein samples were cleaned up with chloroform/methanol method and then subjected to in-solution digestion with trypsin. Resulting peptides were analyzed on a nanospray LTQ XL Orbitrap MS (Thermo Fisher Scientific) operated in data-dependent acquisition mode with the installed Xcalibur software (version 2.0.7, Thermo Fisher Scientific). Using an Ultimate 3,000 nanoLC system (Dionex), peptides in 0.1% formic acid were loaded onto a C18 PepMap trap column (300 µm ID × 5 mm, Dionex). The peptides were eluted from the trap column and their separation and spraying were done using 0.1% formic acid in acetonitrile at a flow rate of 200 nL/min on a C18 Tip column (75 µm 1D × 120 mm, nano HPLC capillary column, NTTC-360/75-3, Nikkyo Technos) with a spray voltage of 1.5 kV. The elution was done with a linear acetonitrile gradient 8-30% in 120 min for gel free proteomics in 0.1% formic acid. Full-scan mass spectra were acquired in the Orbitrap over a mass range of 400-1,500 m/z with a resolution of 30,000. A lock mass function was used to obtain high mass accuracy. The top 6 most intense precursor ions were selected for collision-induced fragmentation in the linear ion trap at normalized collision energy of 35%. Dynamic exclusion was employed within 90 sec to prevent repetitive selection of peptides.Identification of proteins were performed by Mascot search engine (version 2.3.0.2, Matrix Science) using soybean peptide database (55,787 sequences) obtained from the soybean genome database (Phytozome version 8.0)and a common contaminants database (262 sequences). Parameters used in Mascot searches were follows: Carbamidomethylation of cysteine was set as a fixed modification, and oxidation of methionine was set as a variable modification. Trypsin was specified as the proteolytic enzyme and one missed cleavage was allowed. Peptide mass tolerance was set at 5 ppm, fragment mass tolerance was set at 0.5 Da, and peptide charge was set at +2, +3, and +4. Automatic decoy database search was performed in the search. Mascot results were filtered with Mascot percolator to improve accuracy and sensitivity in the peptide identification. False discovery rates for peptide identification of all searches were less than 1.0%. The Mascot results were used for differential analysis using SIEVE software (version 1.3, Thermo Fisher Scientific)

Project description:Abstract still has to be written. The obtained peptide mixtures were introduced into an LC-MS/MS system, the Ultimate 3000 (Dionex, Amsterdam, The Netherlands) in-line connected to an LTQ Orbitrap XL mass spectrometer (Thermo Fisher Scientific, Bremen, Germany). Samples were first loaded on a trapping column (made in-house, 100 um internal diameter (I.D.) x 20 mm, 5 um beads C18 Reprosil-HD, Dr. Maisch). After back-flushing from the trapping column, the sample was loaded on a reverse-phase column (made in-house, 75 um I.D. x 150 mm, 5 um beads C18 Reprosil-HD, Dr. Maisch). Peptides were loaded with solvent A (0.1% trifluoroacetic acid, 2% acetonitrile), and were separated with a linear gradient from 2% solvent A' (0.05% formic acid) to 55% solvent B' (0.05% formic acid and 80% acetonitrile) at a flow rate of 300 nL/min followed by a wash reaching 100% solvent B'. The mass spectrometer was operated in data-dependent mode, automatically switching between MS and MS/MS acquisition for the six most abundant peaks in a given MS spectrum. Full scan MS spectra were acquired in the Orbitrap at a target value of 1E6 with a resolution of 60,000. The six most intense ions were then isolated for fragmentation in the linear ion trap, with a dynamic exclusion of 60 s. Peptides were fragmented after filling the ion trap at a target value of 1E4 ion counts. From the MS/MS data in each LC run, Mascot Generic Files were created using the Mascot Distiller software (version 2.3.01, Matrix Science). While generating these peak lists, grouping of spectra was allowed with a maximum intermediate retention time of 30 s and a maximum intermediate scan count of 5 was used where possible. Grouping was done with 0.005 Da precursor tolerance. A peak list was only generated when the MS/MS spectrum contained more than 10 peaks. There was no de-isotoping and the relative signal to noise limit was set at 2. These peak lists were then searched with the Mascot search engine (Matrix Science) using the Mascot Daemon interface (version 2.3, Matrix Science). Spectra were searched against the human (H. sapiens) Swiss-Prot database. 13C2D3-acetylation of lysine side-chains, carbamidomethylation of cysteine and methionine oxidation to methionine-sulfoxide were set as fixed modifications for the N-terminal COFRADIC analyses. Variable modifications were 13C2D3-acetylation and acetylation of protein N-termini. Pyroglutamate formation of N-terminal glutamine was additionally set as a variable modification. Mass tolerance on precursor ions was set to 10 ppm (with Mascot's C13 option set to 1) and on fragment ions to 0.5 Da. Endoproteinase semi-Arg-C/P (Arg-C specificity with arginine-proline cleavage allowed) was set as enzyme allowing no missed cleavages. The peptide charge was set to 1+, 2+, 3+ and instrument setting was put to ESI-TRAP. Only peptides that were ranked one and scored above the threshold score, set at 99% confidence, were withheld. Quantification of the degree of Nt-Acetylation was performed as described previously (1). All data management was done in ms_lims (2).

Project description:Cerebella from wild-type and cGKI knockout mice, on 129/Sv background, were subjected to protein digestion using trypsin o/n and chemically labeled with dimethyl labeling. After labeling the samples were mixed and subjected to both strong cation exchange and phosphopeptide enrichment. The SCX fractions and the enriched phosphopeptides were then analyzed on an Orbitrap mass spectrometer. Data analysis: For each raw data file recorded by the mass spectrometer, peak lists were generated using Proteome Discoverer (version 1.3, Thermo Scientific, Bremen, Germany) using a standardized workflow. Peak lists, generated in Proteome Discoverer, were searched against a Swiss-Prot database (version 2.3.02, taxonomy Mus musculus, 32402 protein entries) supplemented with frequently observed contaminants, using Mascot (version 2.3.02 Matrix Science, London, UK). The database search was performed by using the following paramenters: a mass tolerance of 50 ppm for the precursor masses and +/-0.6 Da for CID/ETD fragment ions and +/-0.05 Da for HCD fragments. Enzyme speciﬁcity was set to Trypsin with 2 missed cleavages allowed. Carbarmidomethylation of cysteines was set as fixed modification, oxidation of methionine and dimethyl labeling (L, I, H) of lysine residues and N termini, and phosphorylation (S, T, Y) (for the phosphoproteome analysis) were used as variable modifications. Percolator was used to ﬁlter the PSMs for <1% false discovery-rate. Phosphorylation sites were localized by applying phosphoRS (pRS) (v2.0). Triplex dimethyl labeling was used as quantification method, with a mass precision for the 2 ppm for consecutive precursor mass scan. A retention time tolerance of 0.5 min was used to account effect of deuterium on retention time. To further filter for high quality data we used the following parameters: high confidence peptide spectrum matches, minimal Mascot score of 20, minimal peptide length of 6 and only unique rank 1 peptide. For the phosphopeptides analysis, the search rank 1 peptide was added to the previous filters. For the identification and quantitation of the proteins, only the unique peptides were considered.

Dataset Information

Asn3 mass accuracy jurkat proteome

Publications

Asn3, a reliable, robust, and universal lock mass for improved accuracy in LC-MS and LC-MS/MS.

Similar Datasets

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