Creation of Allotypic Active Sites during Oxidative Stress Hamid Mirzaei and Fred Regnier* Department of Chemistry, Purdue University. West Lafayette, Indiana 47907 Received January 20, 2006
Oxidative stress is a factor in a series of diseases and aging, primarily through irreversible oxidative modification of proteins.1-3 A major question is how nonenzymatic oxidation has the specificity to impact cellular regulation. Here, we report the degree to which in vivo protein oxidation to the ketone and aldehyde level is random using yeast as a simple model system and hydrogen peroxide as an environmental oxidative stress agent. Among 415 affinity-selected proteins identified throughout the matrix of stressed cells, oxidation sites were found in 87, predominantly on lysine, arginine, proline, histidine, threonine, and methionine residues. In almost all cases, one to two specific oxidation sites on the exterior of proteins were identified using MS-derived sequence and publicly available 3-D structural data. This suggests that, when regulation or disease progression is mediated by protein oxidation, specific new “allotypic active sites” are being created in proteins that trigger the process. Keywords: Allotypic active sites • proteomics • oxidative stress • hydrogen peroxide • yeast • biotin hydrazide • avidin affinity chromatography • site-specific oxidation • carbonylation • protein carbonyls • biotinylation • in vivo oxidation
Introduction Post-translational modifications play an important role in regulation. Phosphorylation and glycosylation are among the most prominent, but there are more than a hundred enzymatically driven, site-specific post-translational modifications of proteins in nature.4-11 The notion that biological regulation is based on very specific, genetically coded, enzymatically catalyzed molecular mechanisms is at the heart of systems biology and functional genomics. Aberrations in either the structure or concentration of the enzymes necessary for these modifications can have a large impact on biological systems, often pushing an organism into a disease state. With all the excitement surrounding enzymatically driven post-translational modifications, it is easy to overlook the fact that nonenzymatic post-translational modifications occur as well with equally large impact, even to the level of being responsible for diseases such as Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, multiple sclerosis, heart disease, and diabetes.12-15 Nonenzymatic modifications of proteins are even thought to play a role in aging, where it is suggested that 20-50% of the proteome could be oxidized in an 80-year-old human.5-11 In light of the idea that biological regulation derives from genetically coded specificity in protein structure and function, how can nonenzymatic modifications have the requisite specificity to trigger unique biological phenomena such as those associated with oxidative stress diseases and aging? One of the interesting features of nonenzymatic modifications and the specificity issue is that nature has evolved enzyme * To whom correspondence should be addressed. E-mail: fregnier@ purdue.edu. 10.1021/pr060021d CCC: $33.50
2006 American Chemical Society
systems that recognize and remove them in some cases.16 This is particularly true of protein oxidation by “reactive oxygen species” (ROS) and “reactive nitrogen species” (RNS) that arise from metabolism and the environment. When there is a surge in ROS or RNS, the redox potential of cells is altered. This causes cysteine and methionine oxidation along with several other amino acids. Cells respond during this time by producing an abundant supply of glutathione and a series of enzymes that recognize oxidized functional groups and reduce them back to their normal state. But in extreme cases of oxidative stress, amino acid side chains are oxidized beyond the point of reversible repair. Irreparably damaged proteins are recognized and destroyed by proteasomes when possible.17 Clearly, nature does not ignore oxidatively modified proteins. The fact that nature has evolved systems to eliminate nonenzymatically modified proteins when possible and the association of diseases with aberrations in the protein repair mechanism lead to the conclusion that failure to prevent the production and accumulation of nonspecifically modified proteins can put biological systems at risk, at least in the case of oxidized proteins. In fact, it is known that ROS-induced chronic production of irreversibly oxidized proteins reduces cell growth and can even be lethal.18 The question is how these nonenzymatic modifications have the requisite specificity to alter cellular function in such specific ways as to produce a disease state. The mystery of how nonenzymatic post-translational modifications could impact regulation arises from the assumption that such modifications are nonspecific. This seems to be true in the oxidation of proteins in vitro but is not always the case in vivo. Glycation of hemoglobin both in vitro and in vivo is relatively specific. Furthermore, proteins are in a highly ordered Journal of Proteome Research 2006, 5, 2159-2168
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research articles environment in cells where certain portions of a molecule may be more accessible than others. It is possible that nonenzymatic post-translational modifications in vivo could differ from those in vitro. Tools to address these oxidative stress questions are now becoming available. The study of protein oxidation has recently been facilitated by description of a method in which carbonyl groups on oxidized proteins were specifically labeled with reagents that allowed derivatized conjugates to be selected by affinity chromatography.4 When biotin hydrazide was used to derivatize aldehyde and ketone groups in proteome extracts, oxidized proteins could be selected by avidin affinity chromatography columns along with several naturally biotinylated proteins and proteins associated with the derivatized proteins. When this method is used, oxidative stress agents increase the number of carbonyl-containing proteins in both yeast and rat liver, and yeast cultures survive up to 10% of their total protein being irreversibly oxidized to the carbonyl level.19 Here an extension of this approach is reported that focuses on the specificity of oxidation through the identification of oxidation sites in large numbers of proteins derived from oxidatively stressed yeast cells.
Materials Biotin hydrazide, ultralinked immobilized monomeric avidin, sodium cyanoborohydride, trifluoroacetic acid (TFA), Slide-A-Lyzer dialysis cassettes, and Coomassie blue (Bradford) protein assay kits were purchased from Pierce (Rockford, IL). Iodoacetamide, dithiothreitol (DTT), trypsin, glycerol, 2-mercaptoethanol, IGEPAL CA-630 nonioninc detergent, and N-Rtosyl-L-lysine chloromethyl ketone (TLCK) were obtained from Sigma Chemical Co. (St. Louis, MO). Sodium phosphate, urea, sodium chloride, and calcium chloride were purchased from Mallinckrodt (St. Louis, MO). Protease inhibitor cocktail was purchased from Roche Diagnostics (Indianapolis, IN). ZipTip pipet tips were purchased from Millipore Corporation (Bedford, MA). Vydac 208TP54 reversed-phase C8 column were purchased from W. R. Grace & Co. (Columbia, MD). Coated nanospray tips were purchased form New Objective, Inc. (Woburn, MA). The affinity selection and reversed-phase chromatography (RPC) analyses were done on a Integral Micro-Analytical Workstation (Framingham, MA) and Dionex LC Packings capillary LC instrument (Sunnyvale, CA). Mass spectral analyses were done using a PE Sciex QSTAR hybrid LC/MS/MS quadrupole TOF mass spectrometer. All spectra were obtained in the positive ion mode. D-biotin,
Methods Yeast Strain and Culture Conditions. The method of Yoo et al.19 was followed in growing Saccharomyces cerevisiae wildtype strain SM1058.20 The cells were grown at 37 °C in yeast extract-peptone-dextrose (YPD) medium (1% yeast extract, 2% peptone, 2% glucose) using a shaking incubator at 200 rpm. Cell growth was determined by optical density (OD) measurements at 600 nm. For processing a mid-log phase culture, the overnight-cultured cells were inoculated in fresh medium to a cell density of 0.2-0.3 OD600. Preparation of Total Protein from Yeast Treated with Hydrogen Peroxide. Exponentially growing cells at a density of 2.4 OD600 were treated with 5 mM hydrogen peroxide to induce oxidative stress. Cells from 50 or 500 mL cultures were 2160
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harvested and then washed twice with cold water by centrifugation at 3000 rpm for 10 min at 4 °C. The pellet was resuspended in lysis buffer (pH 7.4) containing 3.8 mM NaH2PO4‚6H2O, 49.4 mM Na2HPO4‚6H2O, 48.4 mM NaCl, 5 mM KCl, 20% glycerol, 1% 2-mercaptoethanol, 0.3% IGEPAL CA-630 (Sigma) nonionic detergent, Complete-Mini protease inhibitor, and 5 mM biotin-hydrazide. After 30 min, an equal volume of 30 mM sodium cyanoborohydride in lysis buffer was added to reduce CdN bonds. Cells were broken by repeated vortexing at 4 °C for 10 min with an equivalent volume of glass beads (0.6 mm diameter; Sigma, G-8772). Supernatant was collected by centrifugation at 14 000 rpm for 10 min at 4 °C. Protein concentration was measured by the Bradford method using a Coomassie protein assay kit (Pierce).The final supernatant was kept for further processing. Avidin Affinity Selection. Ultralinked immobilized monomeric avidin was packed into a stainless steel column (4.6 i.d. × 100 mm, 1.7 mL volume) at 100 psi. The packed column was washed with 10 column volumes of phosphate-buffered saline (PBS) (0.1 M sodium phosphate and 0.15 M NaCl, pH 7.4) and 5 column volumes of Biotin Blocking and Elution buffer (2 mM D-biotin in PBS) to block any nonreversible biotin-binding site on the column. Biotin from reversible biotin-binding sites was removed by washing with 5 column volumes of Regeneration buffer (0.1 M glycine, pH 2.8). Finally, the column was reequilibrated with 10 column volumes of PBS. Five hundred microliters of sample (2 mg/mL), followed by 0.25 mL of PBS, was loaded into the column. The column was incubated at room temperature for 1 h and washed with 10 column volumes of PBS to remove all unbound proteins. Biotinylated proteins were eluted with 10 column volumes of Biotin Blocking and Elution buffer, and the column was regenerated with 10 column volumes of column regeneration buffer ,followed by 10 column volumes of PBS. Reversed-Phase Separation of Biotinylated Proteins. A Vydac 208TP54 reversed-phase C8 column was used to desalt and fractionate biotinylated proteins. The reversed-phase column was equilibrated with 5 column volumes of buffer A (99.5% deionized H2O (dI H2O), 0.5% acetonitrile (ACN), and 0.1% TFA). Urea (6 M) was added to further denature the selected proteins before application to the reversed-phase column. After a 5 column volume wash, a linear 60 min gradient was applied from 100% buffer A to 60% buffer B (5% dI H2O, 95% ACN, and 0.1% TFA) to elute proteins from the column. A total of 27 fractions was collected. Collected fraction were vacuum-dried and stored for digestion. Proteolysis. Urea (6 M) and dithiothreitol (10 mM) were added to proteins fractions. After a 1 h incubation at 65 °C, iodoacetamide was added to a final concentration of 10 mM, and the reaction was allowed to proceed for an additional 30 min at 4 °C. Samples were then diluted 6-fold by addition of 50 mM HEPES (pH 8.0) in 10 mM CaCl2. Sequence grade trypsin (2%) was added and the reaction mixture incubated at 37 °C for at least 8 h. Proteolysis was stopped by addition of tosyl lysine chloroketone (TLCK) (trypsin/TLCK ratio of 1:1 (w/w)). Reversed-Phase Separation of Biotinylated Protein Digest. A Vydac 208TP54 reversed-phase C18 column was used for separation of biotinylated protein digests. The reversed-phase column was equilibrated with 5 column volumes of buffer A. After injection of the tryptic digest, the column was washed with 5 column volumes of buffer A, and bound peptides were eluted with a 60 min linear gradient from 100% buffer A to 60% buffer B.
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Figure 1. Oxidation of lysine in vivo and biotinylation of this oxidatively modified residue in vitro.26 (a) The lysine side chain is oxidized to an aldehyde in vivo. (b) Reaction of this aldehyde group with biotinhydrazide followed by reduction of a formed Schiff base in vitro.
Mass Spectrometry of Digested Fractions. The nanospray ionization mode was used to examine column fractions. Trypsin-digested fractions were desalted using Millipore ZipTips. Desalted digests were loaded into coated nanospray tips. Nanospray ionization was achieved at 1200 V with 25 units of curtain gas. Collision energy was adjusted for each peptide according to its m/z to yield comprehensive fragmentation. After acquisition of MS spectral data, MS/MS data were submitted to MASCOT for database searches and identification of the corresponding peptides and proteins. Analyst software version 1.0 of MASCOT was used to create the peak list from a raw data. No smoothing of the data, signal-to-noise ratio, or peak de-isotoping was applied. Charge states were determined manually and specified during a MASCOT search for each peptide. The centroid of MS/MS peaks was determined using the following parameters. The merge distance was set at 100 ppm with minimum and maximum widths of 10 and 500 ppm, respectively. The percentage height was set a 50%. The online version of MASCOT was used for all searches. Peptides were searched individually. The following search parameters
were used for peptide identification: database, NCBInr; taxonomy, S. cerevisiae (72 412 entries); enzyme, trypsin, missed cleavages, 4; fixed modification, carboxymethylation of cysteine; peptide tolerance, (1.2 Da; MS/MS tolerance, (0.6 Da; peptide charge was specified for each peptide; monoisotopic peaks were used for identification. The MASCOT scoring system was used as a measure of identification certainty. A detailed description of the peptide scoring system used by MASCOT can be found at http://www.matrixscience.com/help/scoring_help. The score threshold was adjusted to a 5% rate of false positives. Any protein that was identified by the search engine based on a single peptide was not reported, even if the peptide score was high. When five or more different peptides from a single protein were identified in a fraction, the protein was considered to be positively identified, even when the peptide scores did not exceed the identity threshold.
Results Analytical Strategy. Oxidative cleavage of bonds in proteins can take place in multiple ways. Protein backbone cleavage Journal of Proteome Research • Vol. 5, No. 9, 2006 2161
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Figure 2. (a) Avidin affinity selection of oxidized proteins from yeast cultures stressed by hydrogen peroxide. The control sample was derived from the yeast culture in the absence of hydrogen peroxide. The peak observed in the control represents naturally biotinylated proteins along with naturally occurring oxidized proteins. (b) The C8 RPC profile of affinity-selected proteins. Fractions were collected in such a way as to best isolate proteins in the peaks. A total of 27 fractions was collected and individually trypsin-digested prior to MS/MS analysis. (c) C18 RPC profile of fraction 17 tryptic digest. The low level of complexity eliminates the real need for use of further separation steps. (d) The average ion intensity spectrum of fraction 17 tryptic digest RPC profile. (e) Direct nanospray mass spectrum of fraction 17 that was ZipTip-desalted. Four peptides found in the HPLC/MS profile were not found in the ZipTip/MS approach. This indicates that the analytical capacity of the mass spectrometer was not exceeded in either case. The ZipTip MS profile is slightly more noisy to the nature of nanospray ionization technique, but it ionizes peptides with higher intensity which leads to better MS/MS spectra.
occurs by either the R-amidation pathway or oxidation of glutamyl side chains leading to the formation of a polypeptide with an R-ketoacyl derivative at the N-terminal amino acid.21 Bond cleavage also occurs in amino acid sides chains with formation of carbonyl groups as is the case with lysine, arginine, 2162
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proline, and threonine.22-26 There are also other mechanisms that lead to the production of protein carbonyls by addition of carbonyl-containing groups to the protein structure such as in the case of 4-hydroxy-2-nonenal and malondialdehyde from lipid peroxidation.27,28 Carbonyl groups can also be introduced
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into proteins by reaction with ketoamines, keto aldehydes, and deoxyeosones generated as a result of glycation. 12,29 An important aspect of all these carbonyl group producing reactions is that none of them are genetically coded. The central strategy in this work was to affinity-select proteins that had carbonyl groups introduced during oxidative stress. Proteins from lysates of H2O2-stressed yeast cultures were derivatized with biotin hydrazide, reduced with sodium cyanoborohydride, and after dialysis were applied to an avidin affinity chromatography column. Figure 1 shows the in vivo oxidation of lysine (Figure 1a) and in vitro derivatization of the damaged side chain for affinity selection (Figure 1b). After elution with PBS buffer to remove nonadsorbed proteins, bound proteins were eluted (Figure 2a). Since affinity selection was carried out using a nondenaturing buffer, nonbiotinylated proteins would also be selected if they are associated with biotinylated proteins or interact with column matrix. Proteins captured by the avidin column were then fractionated on a Vydac C8 reversed-phase chromatography (RPC) column (Figure 2b). A total of 27 fractions was collected in such a manner in order to best isolate the eluted proteins from adjacent peaks. The RPC fractions were then digested with trypsin and analyzed by nanospray ionization-mass spectrometry (nanoESI-MS). The possibility that sample complexity increased ion suppression during nanospray ionization-mass spectrometry (ESI-MS) and reduced the number of proteins identified was evaluated in two ways. One was by further fractionation of peptide mixtures with a C18 RPC column followed by direct ESI-MS analysis (Figure 2c,d). The other was by introducing mixtures directly into the mass spectrometer using nanospray ionization after desalting with ZipTips (Figure 2e). The purpose of this study was to evaluate whether this protein fractionation approach followed by trypsin digestion provides the simplification required to avoid exceeding the analytical capacity of mass spectrometers and hence eliminate the need for further timeconsuming separation steps. MASCOT Searches for Identification of Affinity-Selected Proteins. Identification of oxidatively degraded and biotinylated peptides with an automated search engine is difficult. Oxidized peptides do not yield high scores in general and are difficult to distinguish from false positives for several reasons. One is that oxidation induces cross-linking, and cross-linked peptides arising from different protein molecules are very difficult to identify. A second is that including multiple oxidative modifications as variable modifications in searches increases the score threshold. Another is that peptides produced as a result of oxidative fragmentation lack the C-terminal specificity that is required for enzyme-specific identification. One of the reasons for fractionation at the protein level in these studies was so that after proteolysis all the peptides from a protein would be in the same fraction and could be treated as a separate sample in data analysis. This is one of the great strengths of the 2-D gel electrophoresis approach as well. Confidence that a protein has been correctly identified increases substantially when multiple peptide matches from the protein are found together. Moreover, identification of oxidized peptides that have a low score can be verified based on the presence of other high-scoring peptides derived from the same protein. Also, peptides in LC fractions are derived from a limited number of proteins. MASCOT searches of databases for the identification of oxidized proteins in this study were achieved by using a limited set of variable modifications (listed in Table 1) known to occur
Table 1. List of All Amino Acid Modificationsa 1 2 3 4 5 6 7 8 9 10 11 12 13
Thereonine oxidized and biotinylated4,22 Proline oxidized and biotinylated4,23 Arginine oxidized and biotinylated4,24 Lysine oxidized and biotinylated4,26 Hydroxylation of histidine and tryptophan37,38 Methionine oxidation39 Histidine oxidation to aspartic acid40-42 Tryptophan oxidation to formylkynurenin43 Tyrosine oxidation to aminotyrosine44 Sodiation of aspartic acid and glutamic acid Sodiation at the C-terminus Cysteine alkylated with iodoacetamide Tryptophan oxidation to kynurenin45
a Modifications in peptides are shown as superscripts for corresponding amino acids in the sequence. Further information regarding mass difference of the modified amino acids can be accessed via the Unimod Web site.
during oxidative stress. The structure of these oxidative modifications can be found in the literature.30 The “digestion enzyme” in data searches was set to trypsin with chymotryptic activity.31 Because oxidative modification of lysine and arginine residues removes them as trypsin cleavage sites, there will be more miscleavages than normal. This is why the potential for four miscleavages was used to query databases. Carbamidomethylation of cysteine was specified as a constant modification in addition to monoisotopic mass values in peptide database searches. Characterization of Oxidized Proteins. A total of 1703 peptides from 415 proteins were identified by the protocol outlined in Figure 2. This is an average of 4.1 peptides per protein. Carbonylation sites were identified in 99 of these proteins. In addition to identification of oxidation sites, protein identification was based on the recognition of other nonoxidized peptides from the same protein.32 An average of 3.1 peptides (a total of 308) was identified per carbonylated protein. Since the goal of this research was to locate the oxidation sites in yeast proteins, other oxidative modifications were also included in search variables. A complete list of oxidative modifications included in search variables is listed in Table 1. These oxidative modifications are well-known, and their occurrence as a result of oxidative stress is well-established. Although the biotinylated oxidation site was not observed in all cases, other oxidative modifications were recognized in 70 other proteins with an average of 1.36 oxidation sites per protein. This result does not mean that the biotinylation site did or did not exist, it simply means it was not detected. This is the first time specific oxidation sites in such a large number of proteins have been reported. A condensed list of oxidized proteins is available in the Supporting Information accompanying this paper. Since the uncertainty involved in trying to identify parent proteins based on a single peptide is well-known33, 34, proteins were only tabulated as “identified” when several peptides were found. Proteins are referenced in the supplementary data tables (Supporting Information) by their name and NCBI database accession number. Figure 3a shows the distribution of identified proteins based on the number of peptides identified. A significant percentage of proteins (54%) was identified with four peptides and more. Figure 3b shows the amino acid oxidation frequency. Histidine, methionine, and lysine are the most frequently oxidized amino acids based on oxidation site identified for yeast proteins stressed with hydrogen peroxide. These values may depend on the nature of ROS, as well as their endo- or exogenicity. Journal of Proteome Research • Vol. 5, No. 9, 2006 2163
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Figure 3. (a)Protein distribution based on number of peptide identified. Any protein identified with a single high-score peptide was not considered a hit and was eliminated. Only proteins identified with five or more low-score peptides were reported as hits. (b) Amino acid oxidation frequency plot. These percentages may be specific to exogenous hydrogen peroxide.
Cellular and Molecular Weight Distribution of Oxidized Proteins. Figure 4a shows that the oxidatively modified proteins were randomly distributed inside cells. Oxidized proteins were found in the nucleus (nucleoplasm, nucleolus, nuclear chromosomes, and nuclear chromatin), mitochondria (outer membrane bound), cytoplasm, Golgi apparatus, ribosomes, proteasomes, endoplasmic reticulum, incipient bud sites, spliceosomes, plasma membranes, cytoplasmic microtubules, endosomes, and vacuolar membrane. This diversity was expected. The rationale in using an external stress agent was to make the stress as nonspecific as possible. In contrast, ROS generated by metabolites in mitochondria would be expected to be more localized. Even though the cellular distribution of oxidized proteins is diverse, certain organelles appear to be more extensively stressed. Stress intensity manifests itself in the number of oxidized proteins found from a certain organelle. Ribosomes are an example of such biased stress. 2164
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Figure 4b shows the molecular weight distribution of oxidized proteins across the yeast proteome. In this 3-D histogram, the molecular weight of proteins is presented in 20 kDa wide bins, the y axis is the frequency of finding a protein in a certain MW bin, the x axis is the bin values for molecular weight, and the z axis represents oxidized and native yeast population. There appears to be no significant molecular weight bias within the oxidized protein population. Identification of Oxidation Sites. As noted in the Introduction, it is expected that this nonenzymatically driven protein oxidation should lack specificity. Using native protein structures from public databases, we investigated the location of oxidized amino acids in native protein structures. The data reported below from these studies is not meant to imply that the 3-D structures used in this analysis are in any way related to the actual structure of a protein during or after oxidation. Protein conformation could change during oxidation and facilitate
Allotypic Active Sites during Oxidative Stress
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Figure 4. (a) Distribution of oxidized proteins across cellular organelles. Suborganelle distributions were not included in this plot, but they can be found in oxidized proteins table available in Supporting Information. (b) This plot compares the molecular weight distribution of oxidized proteins with the entire yeast native proteome. Front histogram represents oxidized protein molecular weight distribution, while the histogram in the back corresponds to that for native proteins. To make visual comparison easier, values of the bin for oxidized proteins were multiplied by 10. No clear bias is evident.
further oxidation. It is even possible that conformational changes could have led to oxidation. On the basis of sequence data from tandem mass spectrometry and publicly available 3-D structures, it was found in 87 cases that lysine, arginine, proline, histidine, threonine, tryptophan, or methionine residues oxidized by ROS occurred in the native structure at one or sometimes two specific regions
on the exterior of native proteins and that only a small number of the potential oxidation sites in proteins were oxidized. One example was ribosomal protein L19 (Figure 5a). Of the 69 potential oxidation sites in this protein based on the presence of lysine, arginine, proline, histidine, threonine, tryptophan, and methionine in the whole protein, only three amino acids (tryptophan 23, histidine 58, and arginine 136) were found to Journal of Proteome Research • Vol. 5, No. 9, 2006 2165
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Figure 5. (a) Ribosomal protein L19 was identified by 26 peptides. Of 69 potential oxidation sites, only 3 were found to be actually oxidized. (b) Translational elongation factor EF-1 was identified by 15 peptides. Only 4 oxidation sites were identified, while the number of potential oxidation sites is 143. (c) Chain B of the 80s-Eef2-Sordarin complex was oxidized at 7 sites, 6 of them clustered very closely at a short sequence of 26 amino acids. (d) Carbamyl phosphate synthetase was oxidized at 5 sites clustering at 2 distinctive sites. (e) RNA polymerase III, a protein of 1149 amino acids and 321 potential oxidation sites, was found to be oxidized at 4 discontinuous sites.
be oxidized. This clearly indicates a nonrandom preference in ROS-based oxidation of this protein. The translational elongation factor EF-1 provides another example (Figure 5b). Of the 143 potential oxidation sites in this protein of 458 amino acids, only 4 oxidation sites were identified. It is interesting that tryptophan 23 was oxidized to both hydroxytryptophan and formylkynurenin, indicating that this site is specifically prone to oxidation. Clustering of oxidized amino acids was found at both contiguous and discontinuous sites in protein structures. In contiguous clustering, all the oxidized amino acids were found 2166
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within a short segment of the primary structure (data table is available in Supporting Information). An example of such a case was found in chain B of the ribosomal 80s-Eef2-Sordarin complex (Figure 5c). This is a protein of 253 amino acids of which 6 peptides were identified. Of the estimated 78 potential oxidation sites, only 7 were found to be oxidized to the aldehydes/ketone level. Sites found to be oxidized were at histidine 138, lysine 191, methionine 203, histidine 208, histidine 210, histidine 215, and histidine 217. A cluster of oxidation sites is seen in the primary structure of this protein (Figure 5c) ranging from lysine 191 through tryptophan 217. Another
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example of oxidative clustering was seen with carbamyl phosphate synthetase (Figure 5d). Seven oxidation sites were identified in six peptides. Lysine 1080, methionine 1088, and lysine 1097 formed one oxidation site cluster and proline 629 and lysine 635 another. Clustering of oxidized amino acids was also found at discontinuous sites. One example can be found in ribosomal protein L19 (Figure 5a). This is a protein of 189 potential amino acids oxidation sites distributed evenly across the protein sequence. Oxidation was observed at tryptophan 23, histidine 58, and arginine 136. Another example of distributed sites can be found in RNA polymerase III (Figure 5e). RNA polymerase III is a protein of 1149 amino acids and 321 potential oxidation sites of which 4 were found to be oxidized. These oxidation sites are lysine 53, thereonine 330, methionine 449, and histidine 456. The distribution of oxidation sites seems wider than other cases; however, the occurrence of oxidation at specific sites indicates targeted oxidation.
Discussion The data presented here show that, in a simple eukaryotic system in which an exogenous oxidative stress agent enters cells randomly, oxidation of many proteins, but not necessarily all, occurs with a high level of specificity. It is concluded this will be true of ROS-based oxidative stress in general, applying to oxidative stress in mitochondria and probably all eukaryotes. This is of critical importance in cases where protein oxidation is a factor in a disease or alteration of cellular regulation. It means that biological phenomena triggered by protein oxidation are due to the creation of new structures at specific sites in proteins and that these sites are responsible for altering the regulatory state of the system. Moreover, as with sites in other proteins that trigger specific biological phenomena, these sites can be viewed as active sites, albeit new, nongenetically coded active sites. For this reason, these sites can be referred to as “allotypic active sites”, the term allotypic designating that they are a different, nongenetically determined type of active site. But not all oxidation sites will alter regulation. In the majority of cases, the allotypic site will do nothing more than cause the protein to be destroyed by proteosomes. Studies of ROS-induced oxidation of R-synuclein in mammalian catecholaminergic neurons provide support for this hypothesis. All the oxidative stress induced post-translational modifications in this protein occurred in a single region comprising a 20-residue stretch of amino acids at the Cterminus of the protein.35 These discrete post-translational modifications impair mitochondrial function and seem to play a role in neurological disorders such as Parkinson’s disease. Further studies showed that in vitro metal-catalyzed oxidation of transferrin also results in site specific oxidation.36 More studies are needed in other biological systems before it can be unequivocally concluded that in all systems there is a high degree of specificity in ROS oxidation. Even though strong evidence has been provided to support the concept that proteins are likely to be oxidized at specific sites that potentially form new, allotypic active sites, there is a possibility that other proteins are randomly oxidized. The fact that random oxidation was not observed in these studies could be because it is hard to detect. Random oxidation would in effect produce large numbers of isoforms of a protein, each with a unique set of modifications at differing sites. Especially in low-abundance proteins, the concentration of all these modified peptides arising from a large number of sites would be below a detectable level. Among 415 identified proteins
eluted from the avidin affinity column, only 87 were identified to have specific sites of oxidation. Whether failure to detect oxidation in the other proteins was because they were randomly oxidized or simply associated with oxidized proteins that were affinity-captured is not clear.
Conclusions It is concluded that environmental ROS can cause large numbers of proteins to be oxidized at a small number of specific sites. Moreover, these nongenetically coded sites of oxidation are frequently biologically active and can be referred to as “allotypic active sites” based on the fact that they are different in origin from other biologically active sites in proteins. It is postulated that allotypic active sites produced by nonenzymatic oxidation can be of two types. One will be those that alter or destroy genetically determined active sites in proteins either directly or by altering protein conformation. In so doing, they probably initiate their own degradation. It is unlikely that this type of oxidative modification will be of major significance in oxidative stress diseases and aging since the protein can be replaced. It is further concluded that the second and more serious case will be when an allotypic active site initiates the formation of a new, nongenetically coded protein conformation or intermolecular complex that alters cellular function and is difficult to destroy. As we know from Alzheimer’s and Parkinson’s disease, the formation of oxidatively induced protein complexes that are difficult to degrade has a major impact on cellular function. This will be particularly true when the rate of structural aberrant production occurs faster than cell division because it allows these aberrant proteins to accumulate, as, for example, in the neurological tissue of the elderly. Another important feature of this allotypic active site hypothesis is that it explains how a summation or history of irreparable oxidative events could occur, as in aging. Each oxidative stress event will produce proteins with a long half-life, if they are degraded at all. One of the most interesting features of this hypothesis is that it predicts that (1) the reactivity of many oxidized amino acids in the active site is sufficiently large that they will be further altered during complex formation and (2) protein complexes formed from allotypic active sites will leave a unique, nongenetically coded structural signature of unnatural amino acids.
Acknowledgment. This work was supported by National Institutes of Health grants R01 AG025362 and P30-AG13319. Supporting Information Available: List of software used for the protein searches and a table listing the oxidized proteins identified. This material is available free of charge via the Internet at http://pubs.acs.org. References (1) Berlett, B. S.; Stadtman, E. R. Protein oxidation in aging, disease, and oxidative stress. J. Biol. Chem. 1997, 272 (33), 20313-20316. (2) Rumora, L.; Petrik, J.; Zanic-Grubisic, T. Oxidative stress and cell death. Biochemia Med. 2003, 13 (3-4), 75-82. (3) Schoeneich, C. Methionine oxidation by reactive oxygen species: reaction mechanisms and relevance to Alzheimer’s disease. Biochim. Biophys. Acta 2005, 1703 (2), 111-119. (4) Mirzaei, H.; Regnier, F. Affinity chromatographic selection of carbonylated proteins followed by identification of oxidation sites using tandem mass spectrometry. Anal. Chem. 2005, 77 (8), 23862392.
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