Dataset Information

Mycobacterium tuberculosis ATP-binding Proteome

ABSTRACT: Mtb was grown as either an actively growing normal culture or as a hypoxia-induced dormant culture. Whole cell lysates of live bacteria were obtained by mechanical disruption with silica beads. ATP-binding proteins were covalently labeled with desthiobiotin-tagged ATP (ActivX, Thermo Pierce). This chemoproteomic approach profiled the ATP-binding proteins present in either metabolic state. Labeled proteins were enriched via streptavidin affinity chromatography, digested with trypsin and subjected to tandem mass spectrometry (LC-MS/MS) for the identification of proteins containing a desthiobiotin modification of lysine (K +196 Da). Differential abundance of nucleotide binding proteins between the two growth conditions were quantified using label-free spectral counting and normalized spectral abundance factors (NSAF). DATABASE SEARCHING: Tandem mass spectra were extracted, charge state deconvoluted and deisotoped by Xcalibur version 2.2 SP1. All MS/MS samples were analyzed using Mascot (Matrix Science, London, UK; version 2.3.02) and SEQUEST (Thermo Fisher Scientific, San Jose, CA, USA; version v.27, rev. 11). Mascot and SEQUEST were set up to search the MtbReverse041712 database (7992 entries) assuming the digestion enzyme Trypsin. Parameters for both search engines were set to a fragment ion mass tolerance of 1.0 Da and a parent ion tolerance of 2.5 Da. Oxidation of methionine, iodoacetamide derivative of cysteine and the desthiobiotin modification of lysine were specified in Mascot and SEQUEST as variable modifications. PROTEIN IDENTIFICATION AND LABEL-FREE QUANTITATION-- Scaffold (version Scaffold_3.6.1, Proteome Software Inc., Portland, OR) was used to validate MS/MS based peptide and protein identifications. Peptide identifications were accepted if they exceeded specific database search engine thresholds. Mascot identifications required ion scores to be greater than the associated identity scores and 50, 65, 65 and 65 for singly, doubly, triply and quadruply charged peptides. SEQUEST identifications required deltaCn scores of greater than 0.2 and XCorr scores of greater than 1.8, 2.0, 3.0 and 4.0 for singly, doubly, triply and quadruply charged peptides. Proteins identifications were accepted if they contained at least one identified peptide in at least two biological replicates. Peptide spectra meeting the most minimum requirement were manually inspected for quality. Quantification of proteins was performed on normalized spectral abundance factors for each protein (NSAF). BLAST-BASED SEQUENCE DESCRIPTION: The most relevant description for each of the sequences was acquired based on the significant BLAST results. The homologs for the sequences were retrieved using the Blastp algorithm and the nonredundant database of NCBI. The Blast2GO suite was used. GENE ONTOLOGY ANNOTATION: The Pfam domains were mapped to Gene Ontology (GO) terms using the lookup table provided by Pfam2go (http://www.geneontology.org/external2go/pfam2go). An in-house script was written to retrieve GO annotations based on the root term as "molecular function" and their distance from the root term. PFAM DOMAIN-BASED ANNOTATION: The InterPro and Pfam IDs corresponding to the GO term "ATP binding" (GO ID:0005524) were retrieved using the QuickGO (www.ebi.ac.uk/QuickGO/) and InterPro BioMart web services (http://www.ebi.ac.uk/interpro/biomart/martview). The ATP-binding associated domains were queried against the ATP-binding proteome data sets according to spectral quality (high, medium, low confidence). Their Pfam and InterPro descriptions, were identified using the InterProscan Web service, which was accessed via the Pipeline Pilot (Accelrys) implementation in the sequence analysis collection.

REANALYSED by: PAe004062

INSTRUMENT(S): LTQ

ORGANISM(S): Mycobacterium Tuberculosis H37rv

SUBMITTER: Karen Dobos

PROVIDER: PXD000141 | Pride | 2013-04-08

REPOSITORIES: Pride

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Publications

A chemical proteomics approach to profiling the ATP-binding proteome of Mycobacterium tuberculosis.

Wolfe Lisa M LM Veeraraghavan Usha U Idicula-Thomas Susan S Schürer Stephan S Wennerberg Krister K Reynolds Robert R Besra Gurdyal S GS Dobos Karen M KM

Molecular & cellular proteomics : MCP 20130305 6

Tuberculosis, caused by Mycobacterium tuberculosis, remains one of the leading causes of death worldwide despite extensive research, directly observed therapy using multidrug regimens, and the widespread use of a vaccine. The majority of patients harbor the bacterium in a state of metabolic dormancy. New drugs with novel modes of action are needed to target essential metabolic pathways in M. tuberculosis; ATP-competitive enzyme inhibitors are one such class. Previous screening efforts for ATP-co ...[more]

PMID: 23462205

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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.

Project description:The opportunistic pathogen Staphylococcus aureus has become a major threat for human health and well-being by developing resistance to antibiotics, and by its fast evolution into new lineages that rapidly spread within the healthy human population. This calls for the development of active or passive immunization strategies to prevent or treat acute phase infections. Since no such anti-staphylococcal immunization approaches are available as yet, the present studies were aimed at identifying new leads for their development. For this purpose, we thoroughly profiled the cell surface-exposed staphylococcal proteome by combining two surface shaving approaches. In parallel, non-covalently cell wall-bound proteins were extracted with KSCN and analyzed by gel-free proteomics, and also the exoproteome was analyzed through gel-free proteomics. Lastly, we screened a selection of the identified cell wall-attached proteins for binding of immunoglobulin G from patients that have been challenged with different types of S. aureus over extended periods of time due to chronic wound colonization. The combined results of these analyses highlight particular cell surface-exposed S. aureus proteins with highly immunogenic epitopes as potentially powerful targets for the development of protective anti-staphylococcal immunization strategies. Bioinformatics pipeline: Reduction and alkylation, desalting of the samples, mass spectrometric (MS) analysis and database searches were performed as previously described (PMID: 20662103). The strain-specific uniprot databases were used for the /S. aureus/ strains Newman and USA300, respectively including concatenated reversed databases with 5250 and 5298 entries. Validation of MS/MS-based peptide and protein identifications was performed with Scaffold (version Scaffold_2_04_00, Proteome Software Inc., Portland, OR). Peptide identifications were accepted if they exceeded the specific database search engine thresholds. Sequest identifications required at least deltaCn scores of greater than 0.10 and XCorr scores of greater than 1.9, 2.2, 3.8 and 3.8 for singly, doubly, triply and quadruply charged peptides, respectively. All experiments were conducted in independent triplicates. Peptides were only accepted as identified if they were detected in at least two out of the three replicates per sample set. With these filter parameters no false positive hits were obtained.

Project description:The loss of von Hippel-Lindau (VHL) protein function leads to highly vascular renal tumors characterized by an aggressive course of disease and refractoriness to chemotherapy and radiotherapy. Loss of VHL in renal tumors also differs from tumors of other organs in that the oncogenic cascade is mediated by an increase in the levels of hypoxia-inducible factor-2alpha (HIF2alpha) instead of hypoxia-inducible factor-1alpha (HIF1alpha). MS/MS data generated by data dependent acquisition via the LTQ-FT were extracted by BioWorks version 3.3 and searched against a composite IPI human protein sequence database (IPI _human_v 3.73.par) containing both forward and randomized sequences using Mascot version 2.2 (Matrix Science, Boston, MA) search algorithm. Mascot was searched with a fragment ion mass tolerance of 0.80 Da and a parent ion tolerance of 15.0 ppm assuming trypsin as the digestion enzyme with the possibility of one missed cleavage. Carbamidomethylation of cysteine was specified as a fixed modification, while oxidation of methionine, N-terminal protein acetylation, N-terminal peptide and lysine carbamoylation, and phosphorylation of serine and threonine were specified as variable modifications. The analysis of VHL-wt (Caki-2) human RCC and VHL-mut (786-O) cells was carried out from three independent, biological samples from each cell line (tryptic digests of Caki-2 and 786-O, respectively) and duplicate injections were made for each sample. Data processing was accomplished using two software tools: Scaffold (version Scaffold 3.0, Proteome Software Inc., Portland, OR) and Progenesis LC-MS (version 3.0, Nonlinear Dynamics, Durham, NC). Scaffold was employed to validate MS/MS-based peptide and protein identifications from Mascot database searching. Initial peptide identifications were accepted if they could be established at greater than 95% probability as specified by the Peptide Prophet algorithm [20]. Protein probabilities were assigned by the Protein Prophet algorithm [21]. Protein identifications were accepted, if they reached greater than 99% probability and contained at least 2 identified unique peptides. These identification criteria typically established < 0.01% false discovery rate based on a decoy database search strategy at the protein level. Extracted peptide intensities were evaluated with Progenesis LC-MS to obtain label-free relative quantification from the raw data files. The software created a single aggregate run based on LC retention time of each analysis to contain all MS data with distinguished peptide ions and, then, further feature outline maps were generated for detection and quantification of peptide ions from individual analyses using default program parameters. Peptide quantifications were performed by summing peak intensities followed by normalization, data filtering to retain only ions with positive charges (z) of two and three, and exporting peak lists to query against the IPI human protein sequence database using Mascot (see Database Search subsection above). Proteins were accepted as differentially expressed following analysis of variance (ANOVA, P<0.05), requiring at least a twofold change in expression and also passing validation by Peptide Prophet and Protein Prophet using protein identifications from Scaffold.

Dataset Information

Mycobacterium tuberculosis ATP-binding Proteome

Publications

A chemical proteomics approach to profiling the ATP-binding proteome of Mycobacterium tuberculosis.

Similar Datasets

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