Dataset Information

Proteome analysis of U2OS whole cell lysates

ABSTRACT: LC-MS analysis of 18 OGE fractions optained from normally grown U2OS cell lysates. The generation of mathematical models of biological processes, the simulation of these processes under different conditions, and the comparison and integration of multiple data sets are explicit goals of systems biology that require the knowledge of the absolute quantity of the system’s components. To date, systematic estimates of cellular protein concentrations have been exceptionally scarce. Here, we provide a quantitative description of the proteome of a commonly used human cell line in two functional states, interphase and mitosis. We show that these human cultured cells express at least 10000 proteins and that the quantified proteins span a concentration range of seven orders of magnitude up to 20000000 copies per cell. We discuss how protein abundance is linked to function and evolution. Regarding the bioinformatics pipeline employed: the acquired raw files were converted to the centroid mxxml and mgf-format using MassMatrix mass spectrometric data file conversion tools (version 3.9, http://www.massmatrix.org) and searched using MASCOT (version 2.4) against a decoy database of the predicted proteome from homo sapiens extracted from the UniProt/SwissProt database (downloaded on 16/05/2012) and including known contaminants such as keratins/trypsin. The search criteria were set as follows: full tryptic specificity was required (cleavage after lysine or arginine residues); 3 missed cleavages were allowed; carbamidomethylation (C) was set as fixed modification; oxidation (M) as variable modification. The mass tolerance was set to 15 ppm for precursor ions and 0.5 Da for fragment ions.

INSTRUMENT(S): LTQ Orbitrap

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Permanent Cell Line Cell, Cell Culture

SUBMITTER: Alexander Schmidt

LAB HEAD: Alexander Schmidt

PROVIDER: PXD000157 | Pride | 2013-02-22

REPOSITORIES: Pride

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Publications

The quantitative proteome of a human cell line.

Beck Martin M Schmidt Alexander A Malmstroem Johan J Claassen Manfred M Ori Alessandro A Szymborska Anna A Herzog Franz F Rinner Oliver O Ellenberg Jan J Aebersold Ruedi R

Molecular systems biology 20111108

The generation of mathematical models of biological processes, the simulation of these processes under different conditions, and the comparison and integration of multiple data sets are explicit goals of systems biology that require the knowledge of the absolute quantity of the system's components. To date, systematic estimates of cellular protein concentrations have been exceptionally scarce. Here, we provide a quantitative description of the proteome of a commonly used human cell line in two f ...[more]

PMID: 22068332

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Project description:Datasets contain protein identification and raw data from MALDI protein identifications. Identified proteins resulted from a comparison of GLC1 and GLC1 SCLC cell lines using 2D DIGE. MALDI-TOF-MS analyses were performed on an UltraFlexTM II (Bruker Daltonics) instrument according to the instructions of the manufacturer. The instrument was equipped with a scoutTM MTP MALDI target. The spectra were acquired in the positive ion mode according to the settings given by the manufacturer. For external calibration, a peptide standard (m/z 757.399, 1296.684, 1619.822, 2093.086 and 3147.471) was used. The MALDI-PMF spectra were processed using the FlexAnalysis™ 2.4 software (Bruker Daltonics) and converted in the .xml format. For peak detection, the spectra were subjected to an internal recalibration using 13 different monoisotopic masses from autolysis products of trypsin and fragments of keratins ranging from m/z 842.509 – 2825.406. Following parameters were applied: snap peak detection algorithm, signal to noise threshold of 6, maximal number of peaks 100, quality factor threshold 50 and baseline subtraction TopHat. The generated mass lists were subsequently sent to ProteinScapeTM 1.3 (Bruker Daltonics, Bremen, Germany), triggering database searches using ProFound (Version 2002.03.01, Proteometrics LLC) and MASCOT (Version 2.3.02, Matrix Science, London, UK). The following search parameters were selected: fixed cysteine modification with propionamide, variable modification due to methionine oxidation, one maximal missed cleavage sites in case of incomplete trypsin hydrolysis and no details about 2-DE derived protein mass and pI. Using the Score booster function of ProteinScapeTM the mass lists were recalibrated and background masses removed using a list containing 44 masses occurring in a minimum of 10% of generated peak lists. The database searches were run with a mass tolerance of 40 ppm using UniProt’s human complete proteome set (downloaded on 26.10.2012) containing 68.109 protein entries. The used database is a composite database consisting of the UniProtKB entries and a duplicate of the same database, in which the amino acid sequence of each protein entry was randomly shuffled. Proteins reaching Profound score > 1.5 or Mascot score > 64 were considered as identified. Using these criteria one decoy database entry was found by the search engines indicating high confidence of protein identifications. If several database entries of homologues proteins matched these criteria only the entry with the highest score was reported.

Project description:Many protein activities are driven by ATP binding and hydrolysis. Here, we explore the ATP binding proteome of the model plant Arabidopsis thaliana using Acyl-ATP (AcATP) probes. These probes target ATP binding sites and covalently label lysine residues in the ATP binding pocket. Protein extracts were labelled with NHS-LC-Biotin, purified over neutravidin and eluted with formic acid. Eluted proteins were separated by 1-D SDS Gel and digested with Trypsin. Peptide mixtures were analysed by LC-MS/MS on an LTQ Velos. Spectra were searched using Mascot 2.3 using a fixed modification of cysteine (57.02 Da for carbamidomethyl), and variable modifications of methionine (15.99 Da for oxidation) and lysine (339.16 and 355.16 Da for BHAc and OBHAc labeling, respectively). A mass tolerance was set to 0.3 Da for the precursor ions and 0.4 Da for fragment ions. Up to two mis-cleavages for trypsin were permitted since the labeling would prevent cleavage at the labeled lysine. The MS2 spectra were searched against the TAIR10_pep_2012 (version November 2012) containing 35386 proteins of Arabidopsis thaliana, supplemented with a small database with 1095 artefact proteins and a reversed decoy database of the same proteins (totals 72962 entries). An oxidized version of the modifier was observed. Alternatively Arabidopsis leaf proteome was labeled with desthiobiotin-acyl ATP and digested with trypsin. Labeled peptides were purified on streptavidin matrix and sequenced by LC-MS/MS on an LTQ linear ion trap. Here the MS2 spectra were searched using SEQUEST against the TAIR9_pep_20090619 database (version June 2009) containing 32,769 proteins of Arabidopsis thaliana. MS2 searches included fixed iodoacetamide modification of cysteine (57 Da for alkylation), and variable modifications of methionine (16 Da for oxidation) and lysine (196 Da for DBAcATP labeling). Up to three mis-cleavages with trypsin were allowed and non-tryptic or half-tryptic peptides were excluded. A mass tolerance was set to 3 Da for the precursor ions and 1 Da for fragment ions.

Project description:1D-LC-MS/MS analysis of OGE-prefractionated and TMT labeled mouse samples consiting of 2 unstimulated and 2 stimulated T-cell samples. The acquired raw-files were converted to the mascot generic file (mgf) format using the msconvert tool (part of ProteoWizard, version 3.0.4624 (2013-6-3)). Using the MASCOT algorithm (Matrix Science, Version 2.4.0), the mgf files were searched against a decoy database containing normal and reverse sequences of the predicted SwissProt entries of mus musculus (www.ebi.ac.uk, release date 16/05/2012) and commonly observed contaminants (in total 33,832 sequences) generated using the SequenceReverser tool from the MaxQuant software (Version 1.0.13.13). The precursor ion tolerance was set to 10 ppm and fragment ion tolerance was set to 0.01 Da. The search criteria were set as follows: full tryptic specificity was required (cleavage after lysine or arginine residues unless followed by proline), 2 missed cleavages were allowed, carbamidomethylation (C), TMT6plex (K and peptide n-terminus) were set as fixed modification and oxidation (M) as a variable modification. Next, the database search results were imported to the Scaffold Q+ software (version 4.1.1, Proteome Software Inc., Portland, OR) and the protein false identification rate was set to 1% based on the number of decoy hits. Specifically, peptide identifications were accepted if they could be established at greater than 94.0% probability to achieve an FDR less than 1.0% by the scaffold local FDR algorithm. Protein identifications were accepted if they could be established at greater than 6.0% probability to achieve an FDR less than 1.0% and contained at least 1 identified peptide. Protein probabilities were assigned by the Protein Prophet program (Nesvizhskii, et al, Anal. Chem. 2003; 75(17):4646-58). Proteins that contained similar peptides and could not be differentiated based on MS/MS analysis alone were grouped to satisfy the principles of parsimony. Proteins sharing significant peptide evidence were grouped into clusters. For quantification, acquired reporter ion intensities in the experiment were globally normalized across all acquisition runs. Individual quantitative samples were normalized within each acquisition run. Intensities for each peptide identification were normalized within the assigned protein. The reference channels were normalized to produce a 1:1 fold change. All normalization calculations were performed using medians to multiplicatively normalize data. A list of identified and quantified proteins is available in the xls file.

Project description:LCVs purified by immuno-magnetic separation and density gradient centrifugation (fraction 4) were resolved by 1D-SDS-PAGE, the gel lanes were excised in ten equidistant pieces and subjected to trypsin digestion. For the subsequent LC-MS/MS measurements, the digests were separated by reversed phase column chromatography using an EASYnLC apparatus with self-packed columns in a one-column setup. Following loading/ desalting in 0.1% acetic acid in water at a flow rate of 700 nL/min (maximum 220 bar), the peptides were separated by applying a binary non-linear gradient from 5-50% acetonitrile in 0.1% acetic acid over 70 min. The LC was coupled online to a LTQ-Velos Orbitrap mass spectrometer (Thermo Fisher, Bremen, Germany) at a spray voltage of 2.4 kV. After a survey scan in the Orbitrap (r = 30,000), MS/MS data were recorded for the twenty most intensive precursor ions in the linear ion trap. Singly charged ions were not taken into account for MS/MS analysis. The lock mass option was enabled throughout all analyses. After mass spectrometric measurement, MS data was converted into the mzxml format (version 3.1) by ReAdW version 4.3.1 and subsequently subjected to database searching via Sorcerer using Sequest (version 27, revision 11; SageN, Milptas, CA, USA) without charge state deconvolution and deisotoping performed. Database searching was performed either with a database of combined entries of L. pneumophila strain Philadelphia-1 (NC002942) and D. discoideum, or with a database of combined entries of L. pneumophila strain Philadelphia-1 and Mus musculus. Both databases were used as target/decoy databases with a list of common contaminants added (30739 and 64993 entries, respectively). Sequest was used assuming trypsinisation with a fragment ion mass tolerance of 1.00 Da and a search tolerance of 10 ppm for the overview scans. Oxidation of methionine was specified in Sequest as a variable modification. Scaffold (version 3.5.1, Proteome Software Inc., Portland, OR, USA) was used to filter and validate MS/MS-based peptide and protein identifications. Peptide identifications were accepted when spectra exceeded Xcorr values of 2.2, 3.3 and 3.8 for doubly, triply and quadruply peptides with deltaCN values of more than 0.1. Protein identifications are based on at least 2 unique peptides. Proteins that contained similar peptides and could not be differentiated based on MS/MS analysis alone were grouped to meet the principle of parsimony.

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