Redox Proteomics of Protein-bound Methionine Oxidation
2011; Elsevier BV; Volume: 10; Issue: 5 Linguagem: Inglês
10.1074/mcp.m110.006866
ISSN1535-9484
AutoresBart Ghesquière, Veronique Jonckheere, Niklaas Colaert, Joost Van Durme, Evy Timmerman, Marc Goethals, Joost Schymkowitz, Frédéric Rousseau, Joël Vandekerckhove, Kris Gevaert,
Tópico(s)Hemoglobin structure and function
ResumoWe here present a new method to measure the degree of protein-bound methionine sulfoxide formation at a proteome-wide scale. In human Jurkat cells that were stressed with hydrogen peroxide, over 2000 oxidation-sensitive methionines in more than 1600 different proteins were mapped and their extent of oxidation was quantified. Meta-analysis of the sequences surrounding the oxidized methionine residues revealed a high preference for neighboring polar residues. Using synthetic methionine sulfoxide containing peptides designed according to the observed sequence preferences in the oxidized Jurkat proteome, we discovered that the substrate specificity of the cellular methionine sulfoxide reductases is a major determinant for the steady-state of methionine oxidation. This was supported by a structural modeling of the MsrA catalytic center. Finally, we applied our method onto a serum proteome from a mouse sepsis model and identified 35 in vivo methionine oxidation events in 27 different proteins. We here present a new method to measure the degree of protein-bound methionine sulfoxide formation at a proteome-wide scale. In human Jurkat cells that were stressed with hydrogen peroxide, over 2000 oxidation-sensitive methionines in more than 1600 different proteins were mapped and their extent of oxidation was quantified. Meta-analysis of the sequences surrounding the oxidized methionine residues revealed a high preference for neighboring polar residues. Using synthetic methionine sulfoxide containing peptides designed according to the observed sequence preferences in the oxidized Jurkat proteome, we discovered that the substrate specificity of the cellular methionine sulfoxide reductases is a major determinant for the steady-state of methionine oxidation. This was supported by a structural modeling of the MsrA catalytic center. Finally, we applied our method onto a serum proteome from a mouse sepsis model and identified 35 in vivo methionine oxidation events in 27 different proteins. Reactive oxygen species (ROS) 1The abbreviations used are:ROSreactive oxygen speciesCOFRADICcombined fractional diagonal chromatographyMetOmethionine sulfoxideMsrmethionine sulfoxide reductaseRP-HPLCreverse phase high performance liquid chromatographyDTTdithiotreitolPBSphosphate-buffered salineFDRfalse discovery rateXICextracted ion chromatogram. are involved in a broad range of processes including signal transduction and gene expression (1Geiszt M. Leto T.L. The Nox family of NAD(P)H oxidases: host defense and beyond.J. Biol. Chem. 2004; 279: 51715-51718Abstract Full Text Full Text PDF PubMed Scopus (379) Google Scholar), receptor activation (2Ravid T. Sweeney C. Gee P. Carraway 3rd, K.L. Goldkorn T. 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Strategies of antioxidant defense.Eur. J. Biochem. 1993; 215: 213-219Crossref PubMed Scopus (1608) Google Scholar). Of interest here is that some reactive oxygen species specifically modify targeted biomolecules, whereas others cause nonspecific damage. Peroxides for instance are generally more selective compared with hydroxyl radicals (6Davies M.J. The oxidative environment and protein damage.Biochim. Biophys. Acta. 2005; 1703: 93-109Crossref PubMed Scopus (1097) Google Scholar). Major ROS targets are proteins, with oxidation occurring both at the peptide backbone and at amino acid side-chains (6Davies M.J. The oxidative environment and protein damage.Biochim. Biophys. Acta. 2005; 1703: 93-109Crossref PubMed Scopus (1097) Google Scholar). The major oxidation product of protein-bound methionine is methionine sulfoxide, further oxidation of which can lead to methionine sulfone, albeit to a much lesser extent (7Nielsen H.K. Loliger J. Hurrell R.F. Reactions of proteins with oxidizing lipids. 1. Analytical measurements of lipid oxidation and of amino acid losses in a whey protein-methyl linolenate model system.Br. J. Nutr. 1985; 53: 61-73Crossref PubMed Scopus (76) Google Scholar). The (patho)physiological importance of this modification is reflected by the methionine sulfoxide reductases (Msr) that are present in nearly all organisms (8Ezraty B. Aussel L. Barras F. Methionine sulfoxide reductases in prokaryotes.Biochim. Biophys. Acta. 2005; 1703: 221-229Crossref PubMed Scopus (130) Google Scholar, 9Weissbach H. Resnick L. Brot N. Methionine sulfoxide reductases: history and cellular role in protecting against oxidative damage.Biochim. Biophys. Acta. 2005; 1703: 203-212Crossref PubMed Scopus (242) Google Scholar): decreased activity of these enzymes was associated with aging and Alzheimer disease (10Moskovitz J. Methionine sulfoxide reductases: ubiquitous enzymes involved in antioxidant defense, protein regulation, and prevention of aging-associated diseases.Biochim. Biophys. Acta. 2005; 1703: 213-219Crossref PubMed Scopus (251) Google Scholar), and abnormal dopamine signaling was recently found in the methionine sulfoxide reductase A knockout mouse (11Oien D.B. Ortiz A.N. Rittel A.G. Dobrowsky R.T. Johnson M.A. Levant B. Fowler S.C. Moskovitz J. Dopamine D2 receptor function is compromised in the brain of the methionine sulfoxide reductase A knockout mouse.J. Neurochem. 2010; Crossref PubMed Scopus (18) Google Scholar). Oxidation of methionine can lead to loss of enzyme activity as shown for a brain voltage-dependent potassium channel (12Ciorba M.A. Heinemann S.H. Weissbach H. Brot N. Hoshi T. Modulation of potassium channel function by methionine oxidation and reduction.Proc. Natl. Acad. Sci. U.S.A. 1997; 94: 9932-9937Crossref PubMed Scopus (208) Google Scholar). Other studies suggest that methionine oxidation prevents methylation (13Bonvini E. Bougnoux P. Stevenson H.C. Miller P. Hoffman T. Activation of the oxidative burst in human monocytes is associated with inhibition of methionine-dependent methylation of neutral lipids and phospholipids.J. Clin. Invest. 1984; 73: 1629-1637Crossref PubMed Scopus (15) Google Scholar) or has an effect on phosphorylation on serines and threonines proximate to the oxidized site (14Hardin S.C. Larue C.T. Oh M.H. Jain V. Huber S.C. Coupling oxidative signals to protein phosphorylation via methionine oxidation in Arabidopsis.Biochem. J. 2009; 422: 305-312Crossref PubMed Scopus (99) Google Scholar). In this respect, protein kinases are also targeted by methionine oxidation affecting their activity (e.g. (15Erickson J.R. Joiner M.L. Guan X. Kutschke W. Yang J. Oddis C.V. Bartlett R.K. Lowe J.S. O'Donnell S.E. Aykin-Burns N. Zimmerman M.C. Zimmerman K. Ham A.J. Weiss R.M. Spitz D.R. Shea M.A. Colbran R.J. Mohler P.J. Anderson M.E. A dynamic pathway for calcium-independent activation of CaMKII by methionine oxidation.Cell. 2008; 133: 462-474Abstract Full Text Full Text PDF PubMed Scopus (852) Google Scholar)). Further, oxidation of surface methionines increases the protein surface hydrophobicity (16Chao C.C. Ma Y.S. Stadtman E.R. Modification of protein surface hydrophobicity and methionine oxidation by oxidative systems.Proc. Natl. Acad. Sci. U.S.A. 1997; 94: 2969-2974Crossref PubMed Scopus (261) Google Scholar) and may perturb native protein folding, and such oxidized proteins further often become targets for degradation by the proteasome (17Hershko A. Ciechanover A. The ubiquitin pathway for the degradation of intracellular proteins.Prog. Nucleic Acids Res. Mol. Biol. 1986; 33 (301): 19-56Crossref PubMed Scopus (133) Google Scholar). reactive oxygen species combined fractional diagonal chromatography methionine sulfoxide methionine sulfoxide reductase reverse phase high performance liquid chromatography dithiotreitol phosphate-buffered saline false discovery rate extracted ion chromatogram. Although methionines are utmost susceptible to oxidation by several types of ROS (18Vogt W. Oxidation of methionyl residues in proteins: tools, targets, and reversal.Free Radic. Biol. Med. 1995; 18: 93-105Crossref PubMed Scopus (785) Google Scholar), no adequate proteomic methodologies exist to characterize the exact sites of oxidation and quantify the degree of oxidation. Only very recently, Oien et al. generated polyclonal antibodies against oxidized methionines (19Oien D.B. Canello T. Gabizon R. Gasset M. Lundquist B.L. Burns J.M. Moskovitz J. Detection of oxidized methionine in selected proteins, cellular extracts and blood serums by novel antimethionine sulfoxide antibodies.Arch. Biochem. Biophys. 2009; 485: 35-40Crossref PubMed Scopus (50) Google Scholar) and although these antibodies identified oxidized proteins, they were unable to identify the exact site of oxidation. By considering the 16-Da mass increase upon oxidation, Rosen et al. (20Rosen H. Klebanoff S.J. Wang Y. Brot N. Heinecke J.W. Fu X. Methionine oxidation contributes to bacterial killing by the myeloperoxidase system of neutrophils.Proc. Natl. Acad. Sci. U.S.A. 2009; 106: 18686-18691Crossref PubMed Scopus (128) Google Scholar) used spectral counting of both oxidized and nonoxidized peptide species to calculate the general degree of methionine oxidation. However, because methionine sulfoxide containing peptides were not enriched prior to analysis, it may be expected that many such peptides were overlooked given the complex background of the analyte mixture, and further no attempt was made to distinguish artificial methionine oxidation occurring during sample handling from in vivo oxidation. We here present a COFRADIC (combined fractional diagonal chromatography) proteomics technology to map in vivo oxidized methionines and quantify their degree of oxidation. COFRADIC generally isolates a specific set of peptides by altering a peptide functional group or the side-chain of targeted amino acids in between consecutive and identical reverse phase-high performance liquid chromatography (RP-HPLC) peptide separations (21Gevaert K. Van Damme J. Goethals M. Thomas G.R. Hoorelbeke B. Demol H. Martens L. Puype M. Staes A. Vandekerckhove J. Chromatographic isolation of methionine-containing peptides for gel-free proteome analysis: identification of more than 800 Escherichia coli proteins.Mol. Cell. Proteomics. 2002; 1: 896-903Abstract Full Text Full Text PDF PubMed Scopus (212) Google Scholar). We here took advantage of an enzymatic reduction of methionine sulfoxides using a mixture of MsrA and MsrB3. The hydrophobic shift introduced in this way allowed sorting of methionine sulfoxide containing peptides. Cellular methionine oxidation was studied in human Jurkat T-cells under hydrogen peroxide stress. In total, 2626 methionine sulfoxide containing peptides in 1655 proteins were identified and their degree of oxidation was quantified. Bioinformatic analysis of the data pointed to a sequence motif favoring cellular methionine oxidation. Peptide studies further revealed that the rates of both MsrA methionine sulfoxide reduction and unexpectedly, also methionine oxidation are influenced by the primary sequence surrounding the methionine. Structural modeling studies on MsrA further confirmed our results. Finally, we performed a differential analysis on serum from a female C57BL6/J mouse in which septic shock was induced by intravenous Salmonella infection, and identified 35 in vivo oxidized methionine sites in 27 different proteins. The peptide NH2.IPMYSIITPNVLR.COOH was in-house synthesized using Fmoc-based chemistry. Two nanomols of this peptide was dissolved in 100 μl 1% acetic acid and treated with 0.5% (w/v) of hydrogen peroxide (Sigma-Aldrich, Steinheim, Germany) during 30 min at 30 °C followed by immediate injection onto a RP-HPLC column (2.1 mm internal diameter × 150 mm (length) 300SB-C18 column, Zorbax®, Agilent, Waldbronn, Germany) using an Agilent 1100 Series HPLC system. Following a 10 min wash with HPLC solvent A (10 mm ammonium acetate in water/acetonitrile, 98/2 (v/v), water (LC-MS grade, Biosolve, Valkenswaard, The Netherlands), and acetonitrile (HPLC grade, Baker, Deventer, The Netherlands)), a linear gradient to 100% solvent B (10 mm ammonium acetate in water/acetonitrile, 30/70 (v/v)) was applied over 100 min. Using Agilent's electronic flow controller, a constant flow of 80 μl/min was used. The oxidized peptide was collected and split into aliquots of 500 pmol that were vacuum dried. These aliquots were then used for reduction with MsrA (Jena Bioscience, Jena, Germany), MsrB (Jena Bioscience) or a mix of both reductases. The oxidized peptides were redissolved in 95 μl 25 mm Tris.HCl pH 7.6 containing 10 mm dithiotreitol (DTT). To this mixture, 2.5 μl of the stock solution of MsrA and/or MsrB was added and reduction was allowed for 2 h at 37 °C. The enzymes were then removed using a Ni-NTA (ProbondTM Resin from Invitrogen, Paisley, UK). In practice, 20 μl of 50% slurry (in ethanol) was placed on a Pierce® Spin Cups-Paper Filter (Thermo Scientific, Waltham, MA) and washed twice with 150 μl 25 mm Tris HCl pH 7.6. Next, the reaction mixture was put onto the spin column and binding of the His-tagged MsrA and MsrB enzymes to the Ni-NTA beads was allowed for 20 min at room temperature, followed by a centrifugation step for 4 min at 200 × g. The mixture was acidified with 5 μl 20% acetic acid and analyzed by RP-HPLC as described above. Heavy SILAC medium was prepared by adding 13C5-methionine (Cambridge Isotope Laboratories, MA) to a final concentration of 15 mg/ml (101 μm) together with 20 IU/ml penicillin, 20 μg/ml streptomycin and 10% (v/v) dialyzed fetal calf serum (devoid of all substances less than about 10 kDa, Invitrogen) to methionine-free RPMI 1640 medium (Invitrogen). Light SILAC-medium was RPMI 1640 medium containing 10% (v/v) dialyzed fetal calf serum, 20 IU/ml penicillin and 20 μg/ml streptomycin. To ensure complete metabolic labeling, Jurkat cells (ATCC, Teddington, UK) were grown for 7 days prior to H2O2 treatment. For each proteomics experiment, 100-ml cell suspension (300 × 103 cells/ml) was centrifuged for 5 min at 1500 × g, the pellet was washed twice with ice-cold phosphate-buffered saline (PBS) and redissolved in 50 ml PBS (37 °C). For the first experiment, 5.5 μl of 30% (w/v) H2O2 (Sigma) (a final H2O2 concentration of about 1 mm) was added to heavy-labeled cells and these cells were incubated for one hour at 37 °C after which a second bolus of 11 μl 30% H2O2 was added and cells were incubated for an additional hour. Following incubation, cells were centrifuged for 5 min at 1500 × g and cell pellets were washed three times with ice-cold PBS to remove all H2O2. An analogous proteomics experiment but with swapped labeling was carried out. Cell pellets were lysed in 500 μl 300 mm Tris HCl (pH 8.7) containing 150 mm NaCl, 1 mm EDTA (Sigma-Aldrich), 0.8% 3-[(3-cholamidopropyl)dimethylammonio]-1-propanesulfonic acid (Sigma-Aldrich), 1 m guanidinium hydrochloride, and the appropriate amount of the complete protease inhibitor mixture (Roche, Basel, Switzerland). Cell lysis was performed for 10 min on ice followed by sonication and cellular debris were removed by centrifugation for 30 min at 16,000 × g and 4 °C. Alkylation of cysteines was carried out by adding iodoacetamide (Sigma-Aldrich) and triscarboxyethylphosphine (Pierce, Rockford, IL) to final concentrations of 60 mm and 20 mm respectively, for 30 min at 37 °C. Both samples were desalted on a NAP™-5 column (Amersham Biosciences, Uppsala, Sweden) in 1 ml of 50 mm ammonium bicarbonate (pH 8.0). Prior to digestion, protein concentrations were measured using the Bio-Rad Protein Assay. Samples were heated for 10 min at 95 °C and immediately put on ice for another 15 min. Sequencing-grade modified trypsin (Promega, Madison, WI) was added in a 1/100 (w/w) enzyme-to-substrate ratio and following overnight digestion at 37 °C, the volume was reduced to 500 μl by vacuum drying. 100 μl (corresponding to ∼150 μg of protein material) of the digest of the control setup was acidified with 10 μl 10% acetic acid and oxidation of methionines was carried out using 0.5% (w/v) H2O2 during 30 min at 30 °C. Following oxidation, the pH was adjusted to 8.0 by adding 30 μl of a 1 m stock solution of triethylammoniumbicarbonate (Sigma-Aldrich). Fifty microliters of 50% catalase-agarose slurry was washed twice with 50 mm TEAB on a spin-cup paper filter (Thermo Scientific), the reaction mixture was then added to the catalase-agarose to neutralize H2O2 during 5 min at 30 °C. 100 μl (∼150 μg of protein material) of the proteome digest of H2O2-treated cells was treated analogously except that, instead of hydrogen peroxide, an equal volume of water was added. Finally, samples were mixed in a 1/1 (w/w) ratio and the volume was reduced to 100 μl by vacuum drying. The peptide mixture was acidified to a final concentration of 1% acetic acid for RP-HPLC separation onto a 2.1 mm internal diameter × 150 mm 300SB-C18 column (Zorbax®, Agilent) with an Agilent 1100 Series HPLC system using the conditions described above. Peptides eluting between 20 and 80 min were collected in 60 fractions of 1 min each (80 μl) in a 96-well plate. Primary fractions that were separated by 15 min were pooled and vacuum dried. Prior to a series of secondary RP-HPLC separations under identical conditions as the primary one, each pooled fraction was redissolved in 90 μl 25 mm Tris HCl pH 7.6 containing 10 mm DTT, 4 μl of each stock solution of MsrA and MsrB was added and reduction of methionine sulfoxides took place for 3 h at 37 °C. The reductases were then removed as described above after which the peptide mixture was acidified with 10 μl of a 10% acetic acid solution and separated by RP-HPLC. Reduced methionyl peptides were collected in an interval ranging from 2 to 10 min following the collection interval of each primary fraction. Such peptides were collected in six fractions and, because per secondary run four primary fractions were pooled, 24 secondary fractions were collected per run. A total of 360 secondary fractions containing methionyl peptides were in this way collected and to reduce analysis time on the mass spectrometer, secondary fractions that were separated by 15 min were further pooled and vacuum dried. Prior to liquid chromatography-tandem MS (LC-MS/MS) analysis, methionyl peptides were converted into their sulfone form by performic acid oxidation (22Gevaert K. Pinxteren J. Demol H. Hugelier K. Staes A. Van Damme J. Martens L. Vandekerckhove J. Four stage liquid chromatographic selection of methionyl peptides for peptide-centric proteome analysis: the proteome of human multipotent adult progenitor cells.J. Proteome Res. 2006; 5: 1415-1428Crossref PubMed Scopus (25) Google Scholar). In practice, 900 μl of formic acid (Sigma-Aldrich) was added to 100 μl of 30% hydrogen peroxide (Sigma-Aldrich) and the mixture was kept for 60 min at 25 °C. Eight microliters of this solution was added to the peptides and the oxidation took place for 45 min on ice followed by the addition of 500 μl water (Baker B.V.) after which the peptide samples were vacuum dried. The dried peptide fractions were redissolved in 15 μl 2% acetonitrile and 8 μl was used for LC-MS/MS analysis using an Ultimate 3000 nano-HPLC system (Dionex, Amsterdam, The Netherlands) in-line connected to a LTQ Orbitrap XL mass spectrometer (Thermo Electron, Bremen, Germany). The mass spectrometer was operated in data-dependent mode, automatically switching between MS and MS/MS acquisition for the six most abundant ion peaks per MS spectrum. Full scan MS spectra were acquired at a target value of 1E6 with a resolution of 30,000. The six most intense ions were then isolated for fragmentation in the linear ion trap. In the LTQ, MS/MS scans were recorded in profile mode at a target value of 5000. Peptides were fragmented after filling the ion trap with a maximum ion time of 10 ms and a maximum of 1E4 ion counts. From the MS/MS data in each LC-run, Mascot generic files (mgf) were created using the Mascot Distiller software (version 2.2.1.0, Matrix Science). When generating these peak lists, grouping of spectra was performed with a maximum intermediate retention time of 30 s and maximum intermediate scan count of five, used where possible. Grouping was done with 0.1-Da tolerance on the precursor ion. A peak list was only generated when the MS/MS spectrum contained more than 10 peaks, no deisotoping was performed and the relative S/N limit was set at two. MS/MS peak lists were searched with Mascot using the Mascot Daemon interface (version 2.2.0, Matrix Science). Spectra were searched against the Swiss-Prot database (version 56.4) and taxonomy was set to Homo sapiens (20,328 entries). Variable modifications were set to pyro-glutamate formation of N-terminal glutamine and acetylation of the protein's N terminus. Fixed modifications were methionine sulfone and carbamidomethylated cysteine sulfon. Mass tolerance of the precursor ions was set to ±10 ppm and of fragment ions to ±0.5 Da. The peptide charge was set to 1+, 2+, or 3+ and one missed tryptic cleavage site was allowed. Also, Mascot's C13 setting was to one. Further, the different SILAC labels (here, 13C5-methionine or 13C5-methionine) are, during database searching, automatically accounted for by Mascot by selecting these labels in the Mascot Distiller environment. Of note here is that in this context, such labels are considered as so-called "exclusive modifications" that allow any given peptide to hold any of the selected isotopic labels, and, in this way, Mascot tries to optimize the number of significant spectrum-to-peptide matches. Only peptides that were ranked one and scored above the identity threshold score set at 99% confidence were withheld. We calculated the false discovery rate (FDR) based on the method of Elias and Gygi, 2007 (23Elias J.E. Gygi S.P. Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry.Nat. Methods. 2007; 4: 207-214Crossref PubMed Scopus (2827) Google Scholar) using the following formula: FDR = 2*(#false positives)/(#all identifications). Therefore, we created a shuffled database of the Swiss-Prot Homo sapiens database and concatenated this database to the "forward" Swiss-Prot Homo sapiens database using DBToolkit (24Martens L. Vandekerckhove J. Gevaert K. DBToolkit: processing protein databases for peptide-centric proteomics.Bioinformatics. 2005; 21: 3584-3585Crossref PubMed Scopus (120) Google Scholar). For the quantitation protocol, we calculated that 0.20% and 0.27% false positive sequences were present in the forward and reverse labeling proteome analysis, respectively. For the validation protocol, we estimated the FDR at 0.29% and 0.28% for the forward and reverse proteome analysis, respectively. Mascot Distiller Quantitation Toolbox was used in the "precursor" mode for quantification of the identified peptides. Mascot Distiller detects peaks by trying to fit an ideal isotopic distribution on experimental data. This distribution is predicted using average amino acid compositions for a peptide. This is followed by extraction of the extracted ion chromatogram (XIC) signal of both peptide components (light and heavy) from the raw data. Ratios are then calculated from the area below the light and heavy isotopic envelope of the corresponding peptides (integration method "trapezium" and integration source "survey"). To calculate this ratio value, a least squares fit to the component intensities from the scans in the XIC peak was created. MS scans used for this ratio calculation are situated in the elution peak of the precursor determined by the Distiller software (XIC threshold 0.3, XIC smooth 1, max. XIC width 250). To validate the calculated ratio, the standard error on the least square fit has to be below 0.16 and correlation of the isotopic envelope should be above 0.97. Peptides (supplemental Figs. S7, S10, and S11) were in-house synthesized using Fmoc-based chemistry. Four nmol of each peptide was oxidized into its methionine sulfoxide form with 0.5% (w/v) H2O2 in 100 μl of 0.5% trifluoroacetic acid for 30 min at 30 °C, after which the peptide was immediately analyzed by RP-HPLC (see above). Peptide-sulfoxide forms were collected and split into 1 nmol fractions in 100 μl of 25 mm Tris HCl pH 7.6 with 10 mm of DTT. Three of these fractions were treated with 2 μg of MsrA and 2 μg of MsrB3 for 30 min at 37 °C, followed by acidification to 1% trifluoroacetic acid (final concentration). The remaining peptide fraction served as a negative control. Reaction mixtures were separated by RP-HPLC (see above) and the degree of reduction was measured by comparing the integrated peak surfaces of the oxidized and the reduced peptides. Data from three independent experiments for each peptide were compiled. One nmol of each peptide was dissolved in 85 μl 25 mm Tris HCl pH 7.6. Methionine oxidation was carried out with 0.1% (w/v) of hydrogen peroxide during 10 min at 25 °C followed by immediate separation of the peptide mixture over a RP-HPLC column (see above). The degree of oxidation was measured by comparing the integrated peak surfaces of the oxidized and the nonoxidized peptides. Data from three independent experiments for each peptide were compiled. The structure of bovine MsrA with Protein Database code 1FVA was used as template for building the homology model of human MsrA using the FoldX force field (25Schymkowitz J. Borg J. Stricher F. Nys R. Rousseau F. Serrano L. The FoldX web server: an online force field.Nucleic Acids Res. 2005; 33: W382-388Crossref PubMed Scopus (1547) Google Scholar). The structure of 1FVA was first energy minimized with FoldX to get the most accurate energy predictions. The crystal contact between the neighboring molecules in the structure of the MrsA homolog of M. tuberculosis with PDB code 1NWA was reconstructed by using the Crystallize command in YASARA (26Krieger E. Koraimann G. Vriend G. Increasing the precision of comparative models with YASARA NOVA–a self-parameterizing force field.Proteins. 2002; 47: 393-402Crossref PubMed Scopus (1164) Google Scholar). This command applies crystal symmetry and unit cell data to reconstruct crystal packing of the molecules. Structural superposition of the human model with the bacterial homolog allowed us to position the crystal packing hexapeptide in the human model to obtain a human MsrA-peptide complex model. Superposition and RMSD calculation of the bacterial structure with the bovine structure was carried out in YASARA using the MUSTANG (27Konagurthu A.S. Whisstock J.C. Stuckey P.J. Lesk A.M. MUSTANG: a multiple structural alignment algorithm.Proteins. 2006; 64: 559-574Crossref PubMed Scopus (542) Google Scholar) superposition algorithm. After mutating all but the methionine residue in the peptide, FoldX was run to build in silico mutations on each position to every amino acid and calculate the energy difference with alanine as reference. All molecular graphics were created with YASARA (http://www.yasara.org) and PovRay (http://www.povray.org). Female C57BL6/J mice were from Janvier (Le Genest-St Isle, France) and used at the age of 8 to 10 weeks. The mice were maintained in a temperature-controlled, air-conditioned SPF animal facility with 14 h/10 h light/dark cycles and received food and water ad libitum. All experiments were approved by the animal ethics committee of the Faculty of Sciences of Ghent University (Belgium) and performed according to its guidelines. Pathogenic Salmonella enteritidis (serovar typhimurium) were from ATCC. Bacteria were diluted in lipopolysaccharide-free PBS to a concentration of 4 × 107 colony-forming units per ml and 0.25 ml was intravenously injected per mouse in the right tail vein. Mice were bled daily at 9 am at the retro-orbital plexus. Blood was allowed to clot for 60 min at 37 °C and further overnight at 4 °C. The clot was removed and cells were pelleted by centrifugation at 14,000 x rpm for 15 min. Serum was separated and stored at −20 °C until further use. Serum samples collected at day 0, 1, and 4 were each pooled to obtain a total volume of 150 μl of crude serum per condition, followed by depletion of the top three most abundant proteins: albumin, immunoglobulin G, and transferrin. A commercially available affinity system was used for this purpose (Multiple Affinity Removal System, Agilent Technologies). Two milliliters of the depleted serum was reduced to 900 μl by vacuum drying. The pH of the solution was adjusted to 8.7 by addition of 100 μl of 1 m Tris HCl pH 8.7. Alkylation of cysteines was carried out using final concentrations of 60 mm of iodoacetamide and 30 mm of TCEP for 30 min at 37 °C. Excess reagents were removed by desalting over a NAP-10 (Amersham Biosciences) desalting column in 1.5 ml of 50 mm triethylammonium bicarbonate buffer pH 7.8. The protein concentration was determined using the Bradford assay. Proteins were heated prior to digestion for 10 min at 95 °C and after cooling down on ice, endoLys C (endoproteinase Lys C, Roche Diagnostics Gmbh, Mannheim, Germany) was added in a 1/200 ratio (w/w) followed by digestion overnight at 37 °C. After digestion, peptides were propi
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