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Acetylation dynamics and stoichiometry in Saccharomyces cerevisiae

Acetylation dynamics and stoichiometry in Saccharomyces cerevisiae Article Acetylation dynamics and stoichiometry in Saccharomyces cerevisiae 1 1 2 1 1 Brian T. Weinert , Vytautas Iesmantavicius , Tarek Moustafa , Christian Scholz , Sebastian A. Wagner , 3 2 1,* Christoph Magnes , Rudolf Zechner & Chunaram Choudhary Abstract group to the e-amino group of lysine. Acetylation is a well-known regulatory PTM in the context of nuclear signaling, in particular for Lysine acetylation is a frequently occurring posttranslational modi- regulating gene expression via modification of histones. The role of fication; however, little is known about the origin and regulation acetylation in regulating nuclear processes is consistent with the of most sites. Here we used quantitative mass spectrometry to nuclear localization of most acetyltransferases and proteins with analyze acetylation dynamics and stoichiometry in Saccharomyces acetyllysine-binding bromodomains. A prominent role for non- cerevisiae. We found that acetylation accumulated in growth- nuclear acetylation was suggested by numerous proteomic studies arrested cells in a manner that depended on acetyl-CoA generation showing that lysine acetylation occurs at thousands of sites through- in distinct subcellular compartments. Mitochondrial acetylation out eukaryotic cells (Kim et al, 2006; Choudhary et al, 2009; Zhao levels correlated with acetyl-CoA concentration in vivo and et al, 2010; Weinert et al, 2011; Chen et al, 2012; Henriksen et al, acetyl-CoA acetylated lysine residues nonenzymatically in vitro. 2012; Lundby et al, 2012; Hebert et al, 2013). We developed a method to estimate acetylation stoichiometry and Notably, acetylation has been shown to occur frequently on mitochondrial proteins and a large number of sites are regulated found that the vast majority of mitochondrial and cytoplasmic acetylation had a very low stoichiometry. However, mitochondrial by the sirtuin-class deacetylase-3 (SIRT3; Sol et al, 2012; Hebert acetylation occurred at a significantly higher basal level than et al, 2013; Rardin et al, 2013). These observations, and a number cytoplasmic acetylation, consistent with the distinct acetylation of supporting studies (Newman et al, 2012), have established acet- dynamics and higher acetyl-CoA concentration in mitochondria. ylation as an important regulator of mitochondrial metabolism. High stoichiometry acetylation occurred mostly on histones, However, the mechanisms by which acetylation occurs in this proteins present in histone acetyltransferase and deacetylase organelle are mostly unknown. Several recent reviews speculated complexes, and on transcription factors. These data show that that nonenzymatic acetylation by acetyl-CoA may be widespread a majority of acetylation occurs at very low levels in exponentially in mitochondria (Guan & Xiong, 2010; Newman et al, 2012). Acet- growing yeast and is uniformly affected by exposure to acetyl-CoA. ylation could regulate metabolism through a nonenzymatic mecha- nism, in which case determining the stoichiometry of acetylation is Keywords acetylation; mass spectrometry; mitochondria; proteomics; stoichiometry of critical importance for gauging the effects of acetylation on Subject Categories Post-translational Modifications, Proteolysis & protein function. Proteomics; Genome-Scale & Integrative Biology In this study we used quantitative mass spectrometry (MS) to DOI 10.1002/msb.134766 | Received 6 August 2013 | Revised 6 November measure changes in lysine acetylation abundance in Saccharomyces 2013 | Accepted 11 December 2013 cerevisiae (budding yeast). We found that growth-arrest, combined Mol Syst Biol. (2014) 10: 716 with ongoing metabolism, resulted in the accumulation of acetyla- tion in a manner that depended on acetyl-CoA generation in distinct subcellular compartments. Acetylation dynamics in mitochondria correlated with acetyl-CoA levels in this compartment and we found Introduction that acetyl-CoA nonenzymatically acetylated protein in vitro.We developed a novel method to estimate acetylation stoichiometry and Lysine acetylation is an evolutionarily conserved, reversible post- discovered that the vast majority of acetylation occurred at a very low level. These data provide the first global analysis of acetylation translational modification (PTM) that is known to regulate protein function by site-specific acetylation (catalyzed by acetyltransferases) stoichiometry and indicate that metabolism regulates acetylation and deacetylation (catalyzed by deacetylases). Acetyltransferases levels in distinct subcellular compartments through acetyl-CoA generation. use acetyl-coenzyme A (acetyl-CoA) as a cofactor donating an acetyl 1 The NNF Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark 2 Institute of Molecular Biosciences, University of Graz, Graz, Austria 3 HEALTH – Institute for Biomedicine and Health Sciences, Joanneum Research, Graz, Austria *Corresponding author. Tel: +45 35 32 50 20; Fax: +45 35 32 50 01; E-mail: [email protected] ª 2014 The Authors This is an open access article under the terms of the Creative Commons Attribution License, Molecular Systems Biology 10: 716 | 2014 which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Molecular Systems Biology Acetylation dynamics and stoichiometry Brian T. Weinert et al Results Experimental strategy for quantitative analysis of proteome and PTM dynamics We used stable isotope labeling with amino acids in cell culture (SILAC; Ong et al, 2002) to quantify differences in protein, acetyla- tion, and phosphorylation abundance by MS. Proteins from whole cell lysates were digested to peptides and acetylated peptides enriched using a polyclonal anti-acetyllysine antibody as previously described (Kim et al, 2006; Weinert et al, 2013a). Peptide fractions were analyzed by reversed-phase liquid chromatography coupled to high resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS) and raw MS data were computationally processed using MaxQuant (Cox et al, 2011). The quantitative MS experiments performed in this study are summarized in Supplementary Table S1, and the raw data files have been deposited to the ProteomeXchange (Vizcaino et al, 2013), with the identifier PXD000507. Figure 1. Acetylation is globally increased in stationary phase yeast cells. Acetylation dynamics in growth-arrested yeast cells Box plots showing the distributions of SILAC ratios comparing stationary phase (SP) to exponential phase (EP) yeast for all quantified proteins (proteins), acetylated proteins (acetyl proteins), acetylation sites corrected for protein abundance In previous work we showed that acetylation accumulates in changes (acetyl sites), and phosphorylation sites (phospho sites). The box portion of growth-arrested bacteria (E. coli) cells due to prolonged exposure the plot indicates the middle 50% of the distribution, inner hatch marks denote to, and a higher concentration of, acetyl-phosphate (Weinert et al, 9–91%, and whisker ends 2–98%, outliers are not shown. Acetylation sites 2013a). In order to test whether growth-arrest affects PTMs in a occurring on proteins localized exclusively to mitochondria (Mito.), the cytoplasm (Cyto.), or the nucleus (Nuc.) are shown. Statistical significance was calculated eukaryotic system we compared acetylation, phosphorylation, and using a Wilcoxon test, data is from two biological replicates. protein levels between exponentially growing and stationary phase S. cerevisiae cells. We quantified more than 2600 acetylation sites (Supplementary Table S2), 3300 proteins (Supplementary Table S3), and 6000 phosphorylation sites (Supplementary Table S4) with a high correlation between biological replicates was unaffected when cells were growth-arrested in the presence of (Supplementary Figs S1A–C). Strikingly, stationary phase cells 2-deoxy-D-glucose (2DG; a glucose analog that cannot be metabo- showed increased ( > 2-fold) acetylation at a majority (~70%) of lized beyond the first step of glycolysis), indicating that increased quantified acetylation sites (median threefold increased; Fig 1). In mitochondrial acetylation depended on glycolysis (Fig 2B, Supple- contrast, protein and phosphorylation abundance, while affected in mentary Fig S2A, and Supplementary Table S5). However, nuclear stationary phase cells, was not globally increased (Fig 1), indicat- acetylation was globally reduced in the presence of 2DG (median ing that stationary phase did not cause the accumulation of 3.6-fold), suggesting that nuclear deacetylases remain active under proteins or PTMs generally. Furthermore, Gene Ontology (GO) these conditions. enrichment analysis of protein and phosphorylation site changes In order to examine the dependence of mitochondrial protein revealed both up-regulation and down-regulation of specific pro- acetylation on glycolysis, we quantified acetylation dynamics in cesses in stationary phase cells (Supplementary Figs S1D and E), pda1D cells that are unable to convert pyruvate to acetyl-CoA suggesting that such changes occurred in a regulated manner. (Wenzel et al, 1992), or in cit1D cells that are unable to convert Using subcellular localization data from GFP-tagged proteins (Huh acetyl-CoA to citrate (Kispal et al, 1988; Fig 2A). Mitochondrial et al, 2003), we found that acetylation increased to the greatest acetylation was drastically reduced in exponentially growing pda1D degree on mitochondrial proteins (median 5.7-fold), which was cells (median SILAC ratio pda1D/wild-type = 0.14) and was slightly significantly higher than the median increases seen for cytoplasmic increased in exponentially growing cit1D cells (Fig 2C, Supplemen- (2.6-fold) and nuclear (1.5-fold) proteins (Fig 1). Increased acetyla- tary Fig S2B, and Supplementary Table S6). Loss of Pda1 com- tion of mitochondrial proteins was nearly comprehensive (93% of pletely suppressed the increased acetylation of mitochondrial sites were > 2-fold elevated; Fig 1 and Supplementary Table S2). proteins in growth-arrested cells while loss of Cit1 further increased During glycolysis, glucose is converted to pyruvate, which enters the acetylation of mitochondrial proteins (an additional 1.8-fold) in mitochondria and is further converted to acetyl-CoA by the pyruvate growth-arrested cells (Fig 2D, Supplementary Fig S2C, and Supple- dehydrogenase complex (PDC), pyruvate can also be converted to mentary Table S7). Loss of Cit1 blocks the entry of acetyl-CoA into acetyl-CoA in the cytoplasm via an acetate intermediate (Fig 2A). In the citric acid cycle, thus, further increased acetylation in growth- order to control the transition to stationary phase we growth- arrested cit1D cells is likely due to greater accumulation of acetyl- arrested exponentially growing cultures by transferring the cells into CoA in the mitochondria of these cells. We quantified half as many media containing different carbon sources, and lacking an essential acetylation sites on mitochondrial proteins in pda1D cells compared amino acid (lysine), for ~24 h. Notably, mitochondrial acetylation to cit1D cells, while the frequency of quantified sites on cytoplasmic Molecular Systems Biology 10: 716 | 2014 © 2014 The Authors 2 Brian T. Weinert et al Acetylation dynamics and stoichiometry Molecular Systems Biology and nuclear proteins was not altered (Figs 2C and D), indicating that acetylation of many sites in pda1D cells had diminished to undetectable levels in mitochondria specifically. We next compared growth-arrested yeast in the presence of glu- cose or acetate to test whether acetate would alter the acetylation dynamics in growth-arrested cells. Consistent with conversion of acetate to acetyl-CoA by acetyl-CoA synthetase 2 (Acs2; Fig 2A; Takahashi et al, 2006) in the cytoplasm, acetate preferentially promoted the acetylation of cytoplasmic and nuclear proteins (Fig 2E, Supplementary Fig S2D, and Supplementary Table S8). Acetylation levels in mitochondria correlate with acetyl-CoA concentration We showed that mitochondrial acetylation was suppressed by dele- tion of pda1, suggesting that most mitochondrial acetyl-CoA is gener- ated in a Pda1-dependent manner in the growth conditions used in our study. We compared acetyl-CoA levels between wild-type, pda1D, and cit1D cells (Fig 3A). Acetyl-CoA was reduced by approxi- mately 1/3 in pda1D cells, indicating that the mitochondrial acetyl-CoA pool constitutes at least 1/3 of the total acetyl-CoA pool. However, mitochondria occupy ~1–2% of the total cellular volume in yeast (Uchida et al, 2011), indicating that acetyl-CoA levels are substantially (~20–30-fold) higher in mitochondria compared to the cytoplasm and nucleus. We hypothesized that increased acetylation in growth-arrested cells may occur due to higher concentrations of acetyl-CoA or due to prolonged exposure of proteins to acetyl-CoA. We found that acetyl-CoA levels were reduced in growth-arrested cells (Fig 3A), suggesting that acetylation occurs due to prolonged exposure to acetyl-CoA. However, this difference may be due to reduced recovery of acetyl-CoA from growth-arrested cells, which have a substantially increased cell wall and are known to be refractory to cell lysis. We consistently recovered less protein from growth-arrested cells (data not shown), suggesting that these cells were more difficult to lyse, or that cell size and/or protein content was reduced under these conditions. Such differences in cell physiol- ogy may explain the lower amount of acetyl-CoA per OD of growth-arrested cells as determined by our assay. Regardless, acetyl- CoA levels were elevated in growth-arrested cit1D cells, consistent Figure 2. Quantitative analysis of acetylation dynamics in yeast. with our observation of increased acetylation in these cells. If we A Model showing the formation of acetyl-CoA from glucose and acetate, assume that the reduction of acetyl-CoA in pda1D cells indicates the key enzymes are shown in red type. mitochondrial acetyl-CoA pool in these cells, then mitochondrial B–E The figure shows the conditions analyzed in each experiment, the cell acetyl-CoA in cit1D cells was increased ~1.9-fold and ~1.7-fold after 8 type (wild-type (wt) or indicated mutant strains), the growth state and 16 h growth-arrest, respectively (Fig 3A), mirroring the 1.8-fold [exponential phase (EP) or growth-arrested (GA)], the number of acetylation sites analyzed (# sites), the median Log2 and linear SILAC increase in mitochondrial acetylation in growth-arrested cit1D cells ratios comparing the indicated condition to wild-type EP cells, and the (Fig 2D). subcellular localization of the analyzed acetylation sites on proteins The physiological concentration of acetyl-CoA in yeast is not localized to mitochondria (Mito.), the cytoplasm (Cyto.), or the nucleus well-studied. One study estimated acetyl-CoA levels (3–30 lM) in (Nuc.). Cells were growth-arrested by transferring an exponential phase nutrient-starved yeast undergoing metabolic cycles (Cai et al, 2011), culture into media lacking lysine and containing the indicated carbon sources, glucose, acetate, or 2-deoxy-D-glucose (2DG). The bar chart conditions that contrast with the excess of glucose and high growth shows the median Log2 SILAC ratios comparing the indicated condition rates of yeast grown on synthetic complete (SC) media in our study. to wild-type EP cells, statistical significance was calculated by Wilcoxon We estimated a similar cellular concentration of ~30 lM acetyl-CoA test. Increased acetylation requires glycolysis (B). Data is from two in exponentially growing cells. However, this estimate assumes biological replicates. Mitochondrial acetylation in exponentially growing cells requires Pda1 (C). Increased mitochondrial acetylation in complete recovery of acetyl-CoA, and is therefore likely to under- growth-arrested cells is suppressed by loss of Pda1 and enhanced by estimate the actual cellular concentration. We showed that loss of Cit1 (D). Data from two biological replicates is shown, significant mitochondrial acetyl-CoA was ~20–30-fold higher than non- differences are relative to wild-type cells. Acetate promotes cytoplasmic mitochondrial acetyl-CoA, suggesting a concentration of acetyl-CoA and nuclear acetylation (E). Data is from two biological replicates. in mitochondria that approaches the millimolar range (~0.5–1mM © 2014 The Authors Molecular Systems Biology 10: 716 | 2014 3 Molecular Systems Biology Acetylation dynamics and stoichiometry Brian T. Weinert et al Figure 3. Acetyl-CoA concentration in cells and nonenzymatic acetylation by acetyl-CoA. A Acetyl-CoA concentration was determined in the indicated cell types during exponential phase (EP) growth or after the indicated time of growth-arrest (GA) in the presence of glucose. Data are from two independent biological replicates. B The bar graph shows the abundance of the indicated, acetylated (ac) peptides relative to an untreated control sample. Error bars indicate standard deviation of the indicated number (n) of independently quantified peptides. The significance (P) of increased acetylation at 100 lM acetyl-CoA was calculated by two-tailed t-test assuming equal variance. C The column graph shows the relative abundance of non-acetylated peptides. Error bars indicate standard deviation of the indicated number (n) of independently quantified peptides. based on our estimates). This estimate is consistent with previous relative abundances of posttranslationally modified and unmodified work showing that acetyl-CoA can reach millimolar levels in rat corresponding peptides (CPs; Olsen et al, 2010; Wu et al, 2011). If liver mitochondria (Garland et al, 1965). the abundance of a modified peptide is substantially altered then the abundance of the CP should be affected in an inverse manner. How- Acetyl-CoA nonenzymatically acetylates protein ever, CP abundance will only be measurably affected if PTM stoichi- ometry is relatively high. Since our results suggested a low A study in 1970 showed that acetyl-CoA could nonenzymatically stoichiometry of modification, we devised a strategy to assay acety- acetylate lysine rich histone fractions and synthetic polylysine at a lation stoichiometry based on partial chemical acetylation of lysine concentration of ~0.5 mM, with increased kinetics at higher pH, and residues. Partial chemical acetylation will cause the greatest relative an activation energy of 7.5 kcal, suggesting that the reaction could increases in acetylation on sites with the lowest initial stoichiome- occur under physiological conditions (Paik et al, 1970). We sought try, while sites with higher initial stoichiometry will be partially or to independently verify nonenzymatic acetylation by acetyl-CoA not at all affected. In order to find conditions that resulted in partial using mass spectrometry and a quantitative strategy based on iso- chemical acetylation, we chemically acetylated bovine serum albu- baric mass tags (Supplementary Fig S3). Bovine serum albumin min (BSA) with acetyl-phosphate (AcP) or acetic anhydride. We (BSA) was treated with increasing concentrations of acetyl-CoA at found that AcP caused partial chemical acetylation that did not mea- physiological pH, modestly, but significantly, increased acetylation surably affect the abundance of CPs, while acetic anhydride caused was seen on several peptides at a concentration of 100 lM acetyl- comprehensive acetylation and resulted in dramatically reduced CoA, while 1 and 10 mM acetyl-CoA caused increased acetylation abundance of CPs (Supplementary Fig S4 and supplemental text). on all peptides analyzed (Fig 3B). In contrast, the abundance of In order to examine acetylation site stoichiometry in S. cerevisiae, non-acetylated peptides was unaffected by acetyl-CoA (Fig 3C). This we used a SILAC-based quantitative approach to quantify chemi- acetylation is likely to be nonenzymatic since we treated a purified cally acetylated and untreated peptides in the same MS experiment extracellular serum protein (BSA) and acetylation did not occur (Fig 4). An untreated control sample was prepared in order to iden- until acetyl-CoA concentration was well in excess of the known tify acetylation sites that occurred in the absence of AcP-treatment range of binding affinities of acetyltransferases for acetyl-CoA (Alb- and to determine the quantitative variability in our experiments. augh et al, 2011a). Treatment with AcP resulted in substantially increased (>2-fold) acetylation at 74% (10 mM AcP) and 88% (100 mM AcP) of acety- Acetylation stoichiometry in yeast lation sites (Fig 5A and Supplementary Table S9). In contrast, <1% of acetylation sites were substantially increased in the untreated The striking increase (median 9.6-fold) in mitochondrial acetylation (0 mM AcP) lysate, reflecting the quantitative accuracy of our in growth-arrested cit1D cells indicated that mitochondrial assays (Fig 5A). An independent experimental replicate was per- acetylation occurred at a low-level (maximum median stoichiometry formed with untreated (0 mM) and 100 mM AcP-treated lysate of ~10% in exponentially growing cells). One method used to (Supplementary Table S9). Acetylation changes were similar in analyze PTM stoichiometry on a global scale is to compare the experimental replicates, as shown by a Spearman’s correlation Molecular Systems Biology 10: 716 | 2014 © 2014 The Authors 4 Brian T. Weinert et al Acetylation dynamics and stoichiometry Molecular Systems Biology and fatty acid synthetase (Fas2; Table 1). Surprisingly, we were unable to detect acetylated peptides from purified Pgk1, and found just one acetylated peptide from purified Fas2, even though we detected unmodified peptides covering 89 and 72% of the Pgk1 and Fas2 protein sequences, respectively. In order to detect acetylation on these proteins we treated cell lysates with 100 mM AcP and puri- fied Pgk1 and Fas2 for AQUA analysis. Comparison to heavy-labeled peptide standards indicated that acetylation stoichiometry, after AcP-treatment, was < 1% at all eight sites, with a median degree of chemical acetylation that was just 0.07% (Table 1, Supplementary Figs S7A–D). AcP-sensitivity was well-correlated with acetylation stoichiometry as determined by the AQUA method (Spearman’s cor- relation of 0.92, Fig 5C), confirming our prediction that low stoi- chiometry sites would be most sensitive to partial chemical acetylation and providing independent validation of our method. We estimated acetylation stoichiometry based on the conserva- tive assumption that chemical acetylation from 100 mM AcP was < 1% at all sites. A site with 10-fold increased acetylation after AcP-treatment was estimated to have a stoichiometry that is < 0.1% while a site with 20-fold increased acetylation was estimated to have a stoichiometry that is < 0.05%. Using this approach we estimated acetylation stoichiometry based on the observed SILAC L/H ratios after treatment with 100 mM AcP and found that 25% of sites were < 0.02% acetylated, 50% of sites were < 0.05% acetylated, 66% of sites were < 0.1% acetylated, and a remarkable 86% of sites were Figure 4. Method used to assay acetyl-phosphate sensitivity in < 1% acetylated (Fig 5D). These estimates contrast with previously yeast lysate. determined phosphorylation site stoichiometries in yeast, where Yeast proteins were metabolically labeled with unlabeled “light” lysine or with 89% of sites were estimated to have stoichiometries that were >1% “heavy” isotope labeled lysine. Protein lysates were treated with acetyl- phosphate (AcP) or were mock-treated by addition of H O. Equal amounts of (Wu et al, 2011; Fig 5E), indicating that a much greater fraction of protein were mixed and digested to peptides with trypsin protease. Acetylated acetylation occurs with a low stoichiometry. It was not possible to (Ac) peptides were immune-affinity enriched using agarose-coupled anti- accurately estimate the stoichiometry of sites that were AcP-insensi- acetyllysine polyclonal antibody and analyzed by MS. Increased acetylation tive (SILAC ratio L/H < 2) as the relative changes in acetylation from AcP treatment causes an increase in the relative abundance of the light labeled peptide, enabling quantification of acetylation changes induced by AcP. were of a similar magnitude to the variability of these measure- ments. Thus, AcP-insensitive sites were estimated to have acetyla- tion stoichiometry that is >1%. coefficient of 0.89 (Supplementary Fig S5). We identified 9415 acet- In order identify independent parameters that could confirm our ylation sites in 100 mM AcP-treated lysates, 1765 sites had SILAC stoichiometry estimates we compared acetylated peptide intensity ratios, and 916 of these sites were previously identified (Supplemen- and abundance-corrected acetylated peptide intensity to AcP-sensi- tary Table S2), or were found in untreated control samples, indicat- tivity (Supplementary Fig S8). We found that correcting acetylated ing that these sites are naturally occurring acetylation sites in yeast. peptide intensity with protein abundances determined by an inten- Using only the 916 naturally occurring sites with SILAC ratios, sity-based absolute quantification (iBAQ) method (Schwanhausser we found that 65% of the sites were more than 10-fold increased in et al, 2011), could best distinguish AcP-insensitive sites (SILAC ratio acetylation (Fig 5B), indicating maximum initial stoichiometry that L/H < 2) from AcP-sensitive sites (SILAC ratio L/H > 2; Fig 5F and was < 10% at these sites. However, acetylation stoichiometry at Supplementary Fig S8) and had the best overall correlation these positions is likely to be lower than 10% (which assumes com- (q = 0.57) with AcP sensitivity (Supplementary Fig S8). These prehensive acetylation) because our analysis of AcP-treated BSA data independently confirmed our stoichiometry estimates based on (Supplementary Fig S4), showed that 100 mM AcP caused partial AcP-sensitivity, as this parameter was calculated using peptide chemical acetylation without a reduction in the abundance of CPs. intensities and protein abundances determined in untreated control CP abundance was similarly unaffected in 100 mM AcP-treated samples. yeast lysate (Supplementary Fig S6), indicating that AcP-treatment We estimated acetylation stoichiometry for the 916 sites with caused a low-level of partial chemical acetylation. SILAC ratios; however, an additional 1540 sites without SILAC In order to better characterize the degree of partial chemical acet- ratios were independently identified as naturally occurring sites ylation by 100 mM AcP, we used an absolute quantification (AQUA) (identified in untreated control samples or in Supplementary method (Gerber et al, 2003), to quantify acetylation levels. Acetylated Table S2). SILAC ratios were estimated for these sites by calculat- and unmodified peptide intensities were compared to heavy-labeled ing the increased intensity of AcP-treated “light” peptides relative peptide standards, allowing us to determine acetylation stoichiometry to an empirically determined detection limit for naturally occurring directly. We analyzed eight acetylation sites with varying sensitivity “heavy” peptides (see Materials and Methods). Using this method to 100 mM AcP on two proteins, 3-phosphoglycerate kinase (Pgk1) we calculated minimum ratios of increased acetylation at 1516 © 2014 The Authors Molecular Systems Biology 10: 716 | 2014 5 Molecular Systems Biology Acetylation dynamics and stoichiometry Brian T. Weinert et al Figure 5. Most acetylation sites are modified with a low stoichiometry. A The majority of yeast acetylation sites are highly sensitive to partial chemical acetylation by AcP. The histogram shows the distribution of SILAC L/H ratios for the indicated samples. B AcP caused substantially increased acetylation at a majority of sites. The histogram shows acetylation changes induced by 100 mM AcP in two experimental replicates, only sites that were independently identified in cells without AcP treatment are shown. C Acetylation stoichiometry is inversely proportional to AcP-sensitivity. The scatterplot shows the relationship between AcP-sensitivity (SILAC ratio L/H 100 mM AcP) and acetylation stoichiometry (Log10 stoichiometry) as determined by AQUA analysis (Table 1). The Spearmans correlation (q) and the significance by two-tailed test (P-value) are shown. D Most acetylation occurs with a low stoichiometry. Absolute acetylation site stoichiometries were estimated based on relative abundance changes (SILAC ratio L/H) after treatment with 100 mM AcP and using an estimate that AcP treatment caused < 1% chemical acetylation. E For comparison, previously determined phosphorylation site stoichiometries are shown (Wu et al, 2011). F iBAQ-based abundance corrected acetylated peptide intensity (I/iBAQ-A) is proportional to AcP sensitivity. The box plots show the distributions of I/iBAQ-A values for the indicated classes of acetylation sites. AcP-insensitive sites had a significantly (p) higher distribution of I/iBAQ-A values compared to either AcP-sensitive sites or sites without SILAC ratios. Significance was calculated by Wilcoxen test. G Sites without SILAC ratios are highly sensitive to AcP. The minimum ratio of increased acetylation was determined by calculating the increased intensity of AcP- treated “light” peptides relative to an empirically determined detection limit for “heavy” SILAC peptides (see Materials and Methods). H Absolute acetylation stoichiometry of sites without SILAC ratios was estimated to be very low. Stoichiometry was estimated by the same method used to estimate stoichiometry of sites with SILAC ratios in (D) using the minimum ratios of increased acetylation shown in (G). sites and found that AcP caused a median 70-fold increase in acet- abundance-corrected peptide intensity (I/iBAQ-A) distributions for ylation (Fig 5G). Assuming that 100 mM AcP caused < 1% chemi- these sites (Fig 5F). By including these data we estimated acetyla- cal acetylation, the substantially increased acetylation at these tion stoichiometry at a total of 2432 sites in exponentially growing sites indicated a very low stoichiometry of acetylation (Fig 5H) yeast and found that 95% of all acetylation occurs at an estimated and this finding was independently verified by examining the stoichiometry that is < 1%. Molecular Systems Biology 10: 716 | 2014 © 2014 The Authors 6 Brian T. Weinert et al Acetylation dynamics and stoichiometry Molecular Systems Biology Table 1. Absolute quantification (AQUA) of acetylated peptides from Pgk1 and Fas2. Acetylation stoichiometry was determined by AQUA for Pgk1 and Fas2 after treatment with 100 mM AcP (see Supplementary Fig S6). Initial stoichiometry was calculated by dividing the stoichiometry in 100 mM AcP by the Ratio L/H 100 mM AcP and the degree of chemical acetylation is the difference between the initial stoichiometry and the stoichiometry in 100 mM AcP Stoichiometry Ratio L/H Initial Degree chemical Protein Peptide sequence 100 mM AcP (%) 100 mM AcP stoichiometry (%) acetylation (%) Pgk1 AAGFLLEK(ac)ELK 0.023 80.8 0.0003 0.02 Pgk1 AGAEIVPK(ac)LMEK 0.095 41.5 0.0023 0.09 Pgk1 FAAGTK(ac)ALLDEVVK 0.119 27.7 0.0043 0.11 Fas2 QVLDVDPVYKDVA(ac)PTGPK 0.032 108.3 0.0003 0.03 Fas2 LIEPELFNGYNPE(ac)K 0.092 33.5 0.0027 0.09 Fas2 GATLYIP(ac)ALR 0.068 11.3 0.0060 0.06 Fas2 SEGNPVIGVFQ(ac)FLTGHPK 0.016 5.3 0.0031 0.01 Fas2 AND(ac)NESATINEMMK 0.181 1.7 0.1055 0.08 Functional analysis of proteins with high stoichiometry (Fig 6E). Similarly, nuclear proteins were least biased to detect acet- acetylation sites ylation on abundant proteins, as this subcellular compartment con- tained the most high stoichiometry acetylation sites (Fig 6E). Thus, In order to characterize proteins with AcP-insensitive, high stoichi- the abundance of proteins with observed acetylation sites is consis- ometry sites we used GO term enrichment analysis. Proteins with tent with our stoichiometry estimates. AcP-insensitive sites were significantly more frequently associated Acetylated sites with high stoichiometry are likely to be impor- with nuclear processes (Fig 6A). More than half of all AcP-insensi- tant for protein function. Many previously known regulatory acety- tive sites occurred on histones, proteins present in histone deacety- lation sites were AcP-insensitive, including Smc3 lysines 112 and lase (HDAC) or histone acetyltransferase (HAT) complexes, and on 113 (Zhang et al, 2008), Sas2 (MYST homolog) lysine 168 (Yuan transcription factors. We compared the effect of AcP-treatment on et al, 2012), Yng2 lysine 170 (Lin et al, 2008), RTT109 lysine 290 proteins present in different subcellular compartments (Fig 6B). (Albaugh et al, 2011b), SNF2 lysines 1494 and 1498 (Kim et al, Consistent with GO term analysis, 77% of the high-stoichiometry, 2010), histone H2AZ (Htz1) lysines 4, 9, 11, and 15 (Babiarz et al, AcP-insensitive sites occurred on nuclear proteins. In contrast, 97% 2006; Millar et al, 2006; Lin et al, 2008), histone H3 (Hht1) lysines of mitochondrial and 94% of cytoplasmic acetylation sites were 19, 24, and 57 (Zhang et al, 1998; Suka et al, 2001; Hyland et al, AcP-sensitive, indicating that the vast majority of acetylation sites in 2005), histone H4 (Hhf1) lysines 6, 9, 13, and 17 (Suka et al, 2001) these subcellular compartments were acetylated at a low stoichiom- and histone H2B (Htb2) lysines 16 and 17. These 20 sites constitute etry. Notably, mitochondrial acetylation sites were significantly 18% of the 111 AcP-insensitive sites that we identified, indicating (p = 5.8e , Wilcoxon test) less affected (median 14-fold increased) that AcP-insensitivity is a good predictor of functionally important by AcP than cytoplasmic sites (median 30-fold increased; Fig 6B), acetylation sites. The enrichment of functionally characterized sites suggesting a higher basal level of acetylation in mitochondria. This within the group of AcP-insensitive sites is highly significant finding was independently confirmed by a significantly higher distri- (p = 1e , Fisher exact test). Furthermore, known functional sites bution of acetylated peptide I/iBAQ-A for mitochondrial proteins had significantly higher I/iBAQ-A values, indicating that this param- than cytoplasmic proteins (Fig 6C). In contrast, non-acetylated pep- eter is also useful in distinguishing functionally-relevant, high- tide I/iBAQ-A was similarly distributed between mitochondrial and stoichiometry sites (Supplementary Fig S9B and Supplementary cytoplasmic proteins (Fig 6C). It is also notable that the distribution Table S9). of AcP-sensitivity for nuclear proteins was bi-modal, indicating distinct populations of high and low stoichiometry acetylation sites in the nucleus. The subcellular localization of high-stoichiometry, Discussion AcP-insensitive sites was significantly different to low-stoichiome- try, AcP-sensitive sites and low-stoichiometry sites without SILAC While acetylation has been identified on thousands of proteins in ratios in all three compartments (Fig 6D). diverse subcellular compartments, the mechanisms of non-nuclear MS analysis is biased towards abundant proteins, which are acetylation and its regulation are not well understood. We found more readily detected in the MS. Nearly every abundant protein that acetylation levels were dynamically affected by growth-arrest identified by MS was also acetylated (Fig 6E), and the frequency of and the generation of acetyl-CoA in distinct subcellular compart- detected acetylation sites was proportional to protein abundance ments. Acetyl-CoA was previously shown to exist in distinct mito- (Supplementary Fig S9A), indicating that protein abundance is a chondrial and non-mitochondrial pools in yeast (Takahashi et al, limiting factor in the identification of many sites. The technical bias 2006). We showed that mitochondrial acetylation occurs within to detect acetylation on abundant proteins was less pronounced for mitochondria and is uniformly affected by growth-arrest and the mitochondrial proteins compared with cytoplasmic proteins, consis- generation of acetyl-CoA by the PDC. We found that acetyl-CoA tent with our estimation of higher acetylation levels in mitochondria levels correlated with acetylation changes in mitochondria and we © 2014 The Authors Molecular Systems Biology 10: 716 | 2014 7 Molecular Systems Biology Acetylation dynamics and stoichiometry Brian T. Weinert et al Figure 6. Functional analysis of high stoichiometry acetylation sites. A AcP-insensitive acetylation sites occur on proteins associated with nuclear processes. Gene Ontology (GO) term enrichment was performed by comparing proteins with AcP-insensitive acetylation sites (ratio L/H < 2) to all acetylated proteins. The bar graph shows the percentage of AcP-insensitive sites occurring on proteins associated with the indicated GO terms. P-values (P) indicate the statistical significance of GO term enrichment by Fishers exact test. B AcP-insensitive acetylation sites occur on nuclear proteins. The histogram shows the distribution of SILAC L/H ratios occurring on proteins localized to the indicated subcellular compartments. C Acetylated peptides from mitochondrial proteins have a significantly higher median I/iBAQ-A value compared to acetylated peptides from cytoplasmic proteins. The box plots show the I/iBAQ-A distributions for the indicated classes of peptides occurring on mitochondrial (Mito.) or cytoplasmic (Cyto.) proteins. Signficance (p) was determined by Wilcoxon test. D AcP-insensitive sites (SILAC Ratio < 2) have a significantly different subcellular distribution. Sites without SILAC ratios (No ratio) have a similar subcellular distribution to AcP-sensitive sites (SILAC Ratio > 2). The bar graph shows the fraction of sites localized to the indicated subcellular compartments; mitochondria (Mito.), cytoplasm (Cyto.), or nucleus (Nuc.). Significance (P) was calculated by Fisher exact test. E Detection of acetylation sites is biased to occur on abundant proteins and this bias is more pronounced for sites with the lowest estimated stoichiometries. The histograms show the distributions of iBAQ protein abundances for observed proteins (n = 3,104). The distributions of the indicated classes of acetylated proteins occurring exclusively in the indicated subcellular compartments is shown in red. The numbers of acetylated proteins are shown in parenthesis and the median Log10 iBAQ abundance for these acetylated proteins is shown. confirmed that acetyl-CoA can nonenzymatically acetylate proteins. lar compartments. Mutations that blocked acetyl-CoA generation or Our analysis of acetylation stoichiometry showed that the vast its downstream conversion to citrate had opposing effects on mito- majority of acetylation occurs at very low levels, an important chondrial acetylation in growth-arrested yeast cells, linking acetyl- observation with widespread implications for understanding non- CoA levels to mitochondrial acetylation levels. We furthermore nuclear acetylation. showed that acetyl-CoA levels correlated with acetylation abun- A few recent reviews speculated that acetylation may occur dance in mitochondria. Growth-arrest in the presence of glucose or nonenzymatically by exposure to acetyl-CoA, particularly in mito- acetate affected acetylation levels in a manner that was consistent chondria where a protein acetyltransferase activity has not been with separate mitochondrial and non-mitochondrial acetyl-CoA definitively identified (Guan & Xiong, 2010; Newman et al, 2012). pools and generation. Mitochondrial proteins had a significantly Acetyl-CoA has been previously shown to nonenzymatically acety- higher basal level of acetylation than cytoplasmic proteins, consis- late proteins (Paik et al, 1970) and the elevated pH in the mito- tent with our results indicating a higher concentration of acetyl- chondrial matrix would favor this reaction (Paik et al, 1970; Llopis CoA in this organelle. Acetylation is widespread in yeast (Henrik- et al, 1998; Abad et al, 2004; Wagner & Payne, 2013). In addition, sen et al, 2012), yet the number of known acetyltransferases in recent work showed that lysines can be nonenzymatically modified yeast is small (~15; Cherry et al, 2012), particularly compared to by other glycolytic intermediates, such as 1,3-bisphosphoglycerate the number of kinases catalyzing protein phosphorylation (~130; (Moellering & Cravatt, 2013), and succinyl-CoA (Wagner & Payne, Manning et al, 2002; Cherry et al, 2012). Moreover, most acety- 2013; Weinert et al, 2013b). We found that nearly all acetylation ltransferases have known nuclear functions, consistent with our occurred at a low-level and was uniformly regulated by manipula- observation that the majority of high stoichiometry acetylation tions that affected the generation of acetyl-CoA in distinct subcellu- occurred in the nucleus. Thus, the global acetylation dynamics that Molecular Systems Biology 10: 716 | 2014 © 2014 The Authors 8 Brian T. Weinert et al Acetylation dynamics and stoichiometry Molecular Systems Biology we observed in growth-arrested yeast, their dependence on distinct Materials and Methods acetyl-CoA pools and generation, a preponderance of low stoichi- ometry acetylation, and the restriction of high stoichiometry acety- Yeast growth and lysate preparation lation to the nucleus, are highly consistent with a nonenzymatic mechanism of acetylation. These observations contrast with the Wild-type Saccharomyces cerevisiae cells (BY4742, MATalpha canonical model of protein regulation by site-specific PTMs and his3D1 leu2D0 lys2D0 ura3D0; ThermoFisher Scientific, Slangerup, indicate that acetylation may act in a global manner to regulate Denmark), pda1D (BY4742, pda1::KanMX; ThermoFisher Scientific), proteins, or conversely, that most acetylation occurs as a low-level and cit1D (BY4742, cit1::KanMX; Open Biosystems) were cultured in protein lesion that accumulates under specific conditions. How- synthetic complete media (US Biological, Salem, MA, USA) supple- 12 14 13 15 ever, widespread low-level acetylation could occur due to a pro- mented with C N -lysine (SILAC “light”) or C N -lysine 6 2 6 2 miscuous acetyltransferase activity that is sensitive to changes in (SILAC “heavy”). Cells were harvested at the indicated time points, acetyl-CoA levels. washed once with sterile H O, and resuspended in lysis buffer To better understand our estimates of acetylation stoichiometry, (50 mM Tris, pH7.5, 150 mM NaCl, 1 mM EDTA, 1x mini complete it is important to note that individual lysines may vary in the degree protease inhibitor cocktail (Roche, Basel, Switzerland), 5 mM of chemical acetylation by AcP. Without knowing the exact degree sodium fluoride, 1 mM sodium orthovanadate, 5 mM beta-glycero- of chemical acetylation at each position it is not possible to make a phosphate, 10 mM nicotinamide, and 5 lM tricostatin A) at precise estimate of acetylation stoichiometry. In order to account for ~50 OD cells/ml lysis buffer. The cell suspension was frozen this variability we based our estimates on the conservative assump- drop-wise in liquid nitrogen and ground in a liquid nitrogen tion that the degree of partial chemical acetylation by AcP was <1%. chilled steel container by the Retsch MM 400 Ball Mill (Retsch, Since we determined that 100 mM AcP caused a median chemical Haan, Germany) for 5 min at 25 Hz. The lysate was thawed, NP-40 acetylation of just 0.07% (between 0.01 and 0.11%), we are likely and sodium deoxycholate were added to a final concentration of 1 to overestimate the stoichiometry of acetylation. Thus, stoichiome- and 0.1%, respectively, and clarified by centrifugation. The lysate try estimates are presented as less than (<) values, to designate an supernatent was precipitated with four volumes 20°C acetone. The estimated stoichiometry that is less than the indicated amount. In acetone precipitate was dissolved in urea solution (6 M urea, 2 M addition, some lysines may be inaccessible or otherwise unreactive, thio-urea, 10 mM Hepes pH8.0) and protein concentration resulting in an incorrect estimate of high stoichiometry acetylation. determined by Quick-Start Bradford assay (Bio-Rad, Copenhagen, Regardless of these limitations, the results obtained using our Denmark). approach indicated that it was able to distinguish acetylation stoichi- Chemical acetylation of BSA and yeast lysate ometry at the site level. Absolute quantification indicated that acety- lation stoichiometry was inversely proportional to AcP-sensitivity (Table 1, Fig 5C). The highly significant bias to identify high stoichi- For treatment of BSA with acetyl-CoA, BSA was prepared in PBS ometry sites on nuclear proteins indicated that the identification of (pH 7.2) at 10 mg/ml and mixed with 1/10 volume acetyl-CoA (Sigma, Copenhagen, Denmark) prepared fresh in H O. Reactions such sites was non-random. Similarly, sites we predicted to have high stoichiometry were significantly more likely to have known were incubated at 30°C for 4 h and stopped by addition of nine vol- functional roles. Our method further distinguished between low umes 20°C acetone. Acetone precipitated protein was resuspended stoichiometry acetylation in the cytoplasm and mitochondria, indi- in 200 ll of 100 mM triethyl ammonium bicarbonate (TEAB) and digested to peptides by addition of 1/100 (w/w) trypsin protease cating that the difference in acetylation levels between these two subcellular compartments was greater than the inherent variability (Sigma) and incubation at 37°C for 16 h. Tryptic peptides were of lysine reactivity with AcP. Thus, the resolution of our assay was labeled with TMT sixplex isobaric mass tags (ThermoFisher not limited by the variability in lysine reactivity. Scientific) according to the manufacturer’s instructions. Chemical acetylation with acetic anhydride was performed as described (Guan Phosphorylation is known to regulate proteins in a site-selective manner and is one of the most extensively studied and widespread et al, 2010). Briefly, 20 ml of 1 mg/ml BSA (Sigma) was prepared in PTMs in eukaryotic cells. The number of detected phosphorylation 0.1 M Na CO . 100 ll acetic anhydride (Sigma) was added slowly 2 3 sites increases with organism complexity, reflecting its role in regu- over 10 min in a glass beaker with constant stirring, followed by 400 ll pyridine (Sigma) over 30 min, also with constant stirring. lating diverse cellular processes. In contrast, acetylation occurs as frequently in bacteria as in human cells (Weinert et al, 2013a). Simi- The reaction was then left to incubate at room temperature for 4 h lar to bacteria, acetylation is overrepresented in mitochondria com- and quenched by addition of 400 ll 1 M Tris-base (Sigma). Organic solvents were removed by five rounds of centrifuge filtration in an pared with phosphorylation (Weinert et al, 2011). Thus the frequency of acetylation is uncoupled from organism complexity, Amicon Ultra 15 (Millipore, Billerica, MA, USA) with a 10 kD suggesting that nonenzymatic acetylation may play a large role in molecular weight cutoff. For treatment with AcP, BSA was prepared the generation of these sites. We showed that basal acetylation lev- in yeast lysis buffer (as above, with NP-40 and deoxycholate added) at a concentration of 20 mg/ml. Yeast lysate was similarly prepared els are elevated in mitochondria, likely due to a higher concentra- tion of acetyl-CoA in this organelle. These observations suggest that at a concentration of 20 mg/ml. BSA or yeast lysate was then mixed the endosymbiotic evolution of mitochondria as the metabolic cen- with 1/10 volume of H O or AcP [freshly prepared in H O, potas- 2 2 ters of eukaryotic cells may have limited widespread acetylation sium lithium salt (Sigma)] at either 100 mM or 1 M concentration for a final concentration of 10 or 100 mM AcP, respectively. Reac- outside of mitochondria by compartmentalizing acetyl-CoA gener- ated during metabolism, thereby enabling the evolution of acetyla- tions were incubated at 37°C for 90 min. BSA was mixed with 4x tion signaling in the nucleus. nuPAGE SDS-polyacrylamide loading buffer (Life Technologies, © 2014 The Authors Molecular Systems Biology 10: 716 | 2014 9 Molecular Systems Biology Acetylation dynamics and stoichiometry Brian T. Weinert et al Naerum, Denmark) and separated by SDS-polyacrylamide gel 2012). All quantitative MS experiments performed in this study are electrophoresis using NuPAGE gels (Life Technologies). In-gel tryptic summarized in Supplementary Table S1. The mass spectrometry pro- digestion and peptide isolation were performed essentially as teomics data have been deposited to the ProteomeXchange Consor- described (Shevchenko et al, 1996). For yeast lysate, the reactions tium (http://proteomecentral.proteomexchange.org) via the PRIDE were stopped by addition of 5–10 volumes 20°C acetone and incu- partner repository (Vizcaino et al, 2013) with the dataset identifier bated at 20°C for 1–2 h. Acetone precipitated protein was resus- PXD000507. pended in 8 M urea solution (6 M urea, 2 M thio-urea, 10 mM Hepes pH8.0) and the concentration determined by Quick Start Peptide identification and computational analysis Bradford assay (BioRad). Equal amounts of protein were mixed, Raw data files were processed using MaxQuant software (developer diluted to 2 M urea by addition of 3 volume 50 mM Hepes, pH8.5, proteolyzed by addition of 1:200 (w/w) trypsin protease (Sigma) for version 1.2.7.1) as described (http://www.maxquant.org/; Cox 16–20 h at room temperature. Peptides were purified by C18 et al, 2011). Parent ion (MS) and fragment (MS2) spectra were Sep-Pack classic cartridge (Waters, Waltham, MA, USA). Peptides searched against the Saccharomyces Genome Database (SGD) gen- ome release r63, January 5, 2010. The search was performed using were acidified by addition of trifluoroacetic acid (TFA) to 1% and applied to a Sep-Pack column that was pre-equilibrated with 5 ml the integrated Andromeda search engine and both forward and acetonitrile and twice with 5 ml 0.1% TFA. The column was reversed (decoy) versions of the databases (Cox et al, 2011). Pep- tides were additionally filtered for a minimum posterior error proba- washed twice with 5 ml 0.1% TFA and once with 5 ml H O. Peptides were eluted with 3 ml 50% acetonitrile in H 0, 100 llof bility (PEP) score of 0.01, resulting in data sets with estimated false 10x IP buffer (500 mM MOPS, pH 7.2, 500 mM NaCl) was added, discovery rates that were less than the standard 1% used in most and the acetonitrile was removed by vacuum centrifugation to a proteomic studies (Supplementary Table S1). Quantification of TMT mass tags may be inaccurate if additional peptides are co-isolated final volume of ~1 ml. Peptide concentration was determined by absorbance at 280 nm using a nanodrop (ThermoFisher Scientific) with the targeted peptide ion (Ting et al, 2011). In order to mini- spectrophotometer (~6 mg/ml). An aliquot of 200 lg peptides was mize this effect we restricted the quantification of TMT mass tags to set aside for subsequent proteome analysis and the remaining MS/MS scans in which the targeted parent ion constituted a mini- mum of 90% of the total ion current. Mass recalibration was per- peptides were used for acetyllysine enrichment (described below). formed using high confidence identifications based on a initial “first Peptide preparation, acetyllysine enrichment, and search” using a 20 part per million (ppm) mass tolerance for parent peptide fractionation ion masses and 20 ppm (HCD) or 0.5 Dalton (CID) for fragment ions. Spectra were subsequently searched with a mass tolerance of In-solution protein digestion, peptide purification, and acetyllysine 6 ppm for parent ions and 20 ppm (HCD) or 0.5 Dalton (CID) for peptide enrichment were performed essentially as described (Kim fragment ions, with strict trypsin specificity, and allowing up to two et al, 2006; Weinert et al, 2013a). Immuno-enriched peptides were missed cleavage sites. Cysteine carbamidomethylation was searched as a fixed modification, whereas N-acetyl protein and oxidized eluted from anti-acetyllysine antibody resin using acidified H O [0.2% trifluoroacetic acid (TFA)]. Peptide eluates were loaded methionine were searched as variable modifications. Where appro- directly onto a strong cation exchange (SCX) microtip column pre- priate, acetyllysine was added as a variable modification. pared as described (Rappsilber et al, 2007; Wisniewski et al, 2009). Acetyl-CoA assay Peptide eluates were briefly evaporated to remove acetonitrile and then loaded onto C18 stage-tips as described (Rappsilber et al, 2007). Proteome measurements were made by fractionation of total Frozen yeast pellets (~100 OD nm) were deproteinized in 400 ll peptides by the SCX microcolumn method and analyzed by mass 1 N perchloric acid (PCA) containing 13C2 acetyl-CoA as an internal standard (ISTD), mixed with 200 ll 0.4 mm acid washed glass- spectrometry. beads and vortexed for 2 min at 4°C. Homogenates were centrifuged Quantitative mass spectrometric analysis for 10 min, 10 000 g at 4°C. Supernatant (200 ll) was neutralized by adding repeated aliquots (10 ll) of 3 M KHCO3 under constant We used stable isotope labeling with amino acids in cell culture vortexing, until bubble evolution ceases (90 ll in total). KClO4 was (SILAC; Ong et al, 2002), to measure changes in protein, lysine acet- pelleted by centrifugation for 5 min, 10 000 g at 4°C. Acetyl-CoA ylation, and phosphorylation abundance. Peptide fractions were from the supernatant was measured as described previously, using analyzed by online nanoflow LC-MS/MS using a Proxeon easy nLC ISTD for calibration (Magnes et al, 2008). Results were normalized system (ThermoFisher Scientific) connected to an LTQ Orbitrap to OD 600 nm measured after extraction. Velos (ThermoFisher Scientific) or Q-Exactive (ThermoFisher Scientific) mass spectrometer. The LTQ Orbitrap Velos instrument AQUA analysis was operated under Xcalibur 2.1 (ThermoFisher Scientific) with the LTQ Orbitrap Tune Plus Developers Kit version 2.6.0.1042 software Yeast strains expressing GFP-tagged Pgk1 and Fas2 at endogenous in the data dependent mode to automatically switch between MS levels from the chromosomal locus (Huh et al, 2003) were and MS/MS acquisition as described (Weinert et al, 2011). The obtained from Life Technologies. Protein extracts were prepared Q-Exactive was operated using Xcalibur 2.2 (ThermoFisher Scientific) exactly as above when treating whole cell lysate with AcP. After in the data dependent mode to automatically switch between MS and treatment with AcP (or mock-treatment) the GFP-tagged proteins MS/MS acquisition as described (Michalski et al, 2011; Kelstrup et al, were enriched using GFP-trap affinity resin (ChromoTek, Martinsried, Molecular Systems Biology 10: 716 | 2014 © 2014 The Authors 10 Brian T. Weinert et al Acetylation dynamics and stoichiometry Molecular Systems Biology Germany) and the proteins eluted by boiling in 2x tris glycine Albaugh BN, Arnold KM, Denu JM (2011a) KAT(ching) metabolism by the tail: insight into the links between lysine acetyltransferases and metabolism. sample buffer (Life Technologies). Proteins were resolved on pre- ChemBioChem 12: 290 – 298 cast tris glycine gels (Life Technologies) and peptides recovered by standard in-gel digestion (Shevchenko et al, 1996). Heavy-labeled Albaugh BN, Arnold KM, Lee S, Denu JM (2011b) Autoacetylation of the AQUA peptide standards (AQUA quant pro; ThermoFisher Scien- histone acetyltransferase Rtt109. J Biol Chem 286: 24694 – 24701 Babiarz JE, Halley JE, Rine J (2006) Telomeric heterochromatin boundaries tific) were mixed with Pgk1 and Fas2 peptides at the indicated require NuA4-dependent acetylation of histone variant H2A.Z in concentrations and analyzed by MS. Untreated protein was ana- lyzed in four independent experiments and AcP-treated protein in Saccharomyces cerevisiae. Genes Dev 20: 700 – 710 two independent experiments, all with comparable results. Cai L, Sutter BM, Li B, Tu BP (2011) Acetyl-CoA induces cell growth and proliferation by promoting the acetylation of histones at growth genes. Mol Cell 42: 426 – 437 Data analysis Chen Y, Zhao W, Yang JS, Cheng Z, Luo H, Lu Z, Tan M, Gu W, Zhao Y (2012) Quantitative acetylome analysis reveals the roles of SIRT1 in regulating Gene Ontology (GO) association and enrichment analysis was diverse substrates and cellular pathways. Mol Cell Proteomics 11: performed using the Database for Annotation, Visualization and 1048 – 1062 Integrated Discovery (DAVID) v6.7 (da Huang et al, 2009). Statisti- cal tests were performed using R (http://www.r-project.org/ Cherry JM, Hong EL, Amundsen C, Balakrishnan R, Binkley G, Chan ET, Christie KR, Costanzo MC, Dwight SS, Engel SR, Fisk DG, Hirschman JE, index.html). Box plots were generated using Sparklines for Excel Hitz BC, Karra K, Krieger CJ, Miyasato SR, Nash RS, Park J, Skrzypek MS, (http://sparklines-excel.blogspot.com/). The detection limit for nat- Simison M et al (2012) Saccharomyces Genome Database: the genomics urally occurring acetylated peptides used to calculate minimum increased acetylation in Fig 5G was determined by ranking the resource of budding yeast. Nucleic Acids Res 40: D700 – D705 Choudhary C, Kumar C, Gnad F, Nielsen ML, Rehman M, Walther TC, Olsen observed “heavy” labeled peptides by peptide intensity and calcu- JV, Mann M (2009) Lysine acetylation targets protein complexes and lating the median intensity of the bottom 10%. This intensity value was an order of magnitude higher than the least intense “heavy” co-regulates major cellular functions. Science 325: 834 – 840 peptide observed in our experiments, thus the estimates of Cox J, Neuhauser N, Michalski A, Scheltema RA, Olsen JV, Mann M (2011) Andromeda: a peptide search engine integrated into the MaxQuant increased acetylation based on this detection limit are conserva- environment. J Proteome Res 10: 1794 – 1805 tive. Garland PB, Shepherd D, Yates DW (1965) Steady-state concentrations of Supplementary information for this article is available online: coenzyme A, acetyl-coenzyme A and long-chain fatty acyl-coenzyme A in http://msb.embopress.org rat-liver mitochondria oxidizing palmitate. Biochem J 97: 587 – 594 Gerber SA, Rush J, Stemman O, Kirschner MW, Gygi SP (2003) Absolute quantification of proteins and phosphoproteins from cell lysates by Acknowledgements tandem MS. Proc Natl Acad Sci USA 100: 6940 – 6945 We thank the members of the department of proteomics at CPR for their help- Guan KL, Xiong Y (2010) Regulation of intermediary metabolism by protein ful discussions. We thank the PRIDE team for helping make our data accessible acetylation. Trends Biochem Sci 36: 108 – 116 to everybody. This work is supported by the European Commission’s 7th Guan KL, Yu W, Lin Y, Xiong Y, Zhao S (2010) Generation of acetyllysine antibodies Framework Program grants Proteomics Research Infrastructure Maximizing and affinity enrichment of acetylated peptides. Nat Protoc 5: 1583 – 1595 knowledge EXchange and access (XS) (INFRASTRUCTURESF7-2010-262067/ Hebert AS, Dittenhafer-Reed KE, Yu W, Bailey DJ, Selen ES, Boersma MD, PRIME-XS), and the Lundbeck Foundation (R48-A4649). SAW is supported by a Carson JJ, Tonelli M, Balloon AJ, Higbee AJ, Westphall MS, Pagliarini DJ, postdoctoral grant from The Danish Council for Independent Research (FSS: Prolla TA, Assadi-Porter F, Roy S, Denu JM, Coon JJ (2013) Calorie 10-085134). The Center for Protein Research is supported by a grant from the restriction and SIRT3 trigger global reprogramming of the mitochondrial Novo Nordisk Foundation. protein acetylome. 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EMBO J 31: 58 – 70 Rappsilber J, Mann M, Ishihama Y (2007) Protocol for micro-purification, Zhang J, Shi X, Li Y, Kim BJ, Jia J, Huang Z, Yang T, Fu X, Jung SY, Wang Y, Zhang P, enrichment, pre-fractionation and storage of peptides for proteomics Kim ST, Pan X, Qin J (2008) Acetylation of Smc3 by Eco1 is required for S phase using StageTips. Nat Protoc 2: 1896 – 1906 sister chromatid cohesion in both human and yeast. Mol Cell 31: 143 – 151 Rardin MJ, Newman JC, Held JM, Cusack MP, Sorensen DJ, Li B, Schilling B, Zhang W, Bone JR, Edmondson DG, Turner BM, Roth SY (1998) Essential and Mooney SD, Kahn CR, Verdin E, Gibson BW (2013) Label-free quantitative redundant functions of histone acetylation revealed by mutation of target proteomics of the lysine acetylome in mitochondria identifies substrates lysines and loss of the Gcn5p acetyltransferase. EMBO J 17: 3155 – 3167 of SIRT3 in metabolic pathways. Proc Natl Acad Sci USA 110: 6601 – 6606 Zhao S, Xu W, Jiang W, Yu W, Lin Y, Zhang T, Yao J, Zhou L, Zeng Y, Li H, Li Y, Schwanhausser B, Busse D, Li N, Dittmar G, Schuchhardt J, Wolf J, Chen W, Shi J, An W, Hancock SM, He F, Qin L, Chin J, Yang P, Chen X, Lei Q et al Selbach M (2011) Global quantification of mammalian gene expression (2010) Regulation of cellular metabolism by protein lysine acetylation. control. Nature 473: 337 – 342 Science 327: 1000 – 1004 Molecular Systems Biology 10: 716 | 2014 © 2014 The Authors http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Molecular Systems Biology Springer Journals

Acetylation dynamics and stoichiometry in Saccharomyces cerevisiae

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Article Acetylation dynamics and stoichiometry in Saccharomyces cerevisiae 1 1 2 1 1 Brian T. Weinert , Vytautas Iesmantavicius , Tarek Moustafa , Christian Scholz , Sebastian A. Wagner , 3 2 1,* Christoph Magnes , Rudolf Zechner & Chunaram Choudhary Abstract group to the e-amino group of lysine. Acetylation is a well-known regulatory PTM in the context of nuclear signaling, in particular for Lysine acetylation is a frequently occurring posttranslational modi- regulating gene expression via modification of histones. The role of fication; however, little is known about the origin and regulation acetylation in regulating nuclear processes is consistent with the of most sites. Here we used quantitative mass spectrometry to nuclear localization of most acetyltransferases and proteins with analyze acetylation dynamics and stoichiometry in Saccharomyces acetyllysine-binding bromodomains. A prominent role for non- cerevisiae. We found that acetylation accumulated in growth- nuclear acetylation was suggested by numerous proteomic studies arrested cells in a manner that depended on acetyl-CoA generation showing that lysine acetylation occurs at thousands of sites through- in distinct subcellular compartments. Mitochondrial acetylation out eukaryotic cells (Kim et al, 2006; Choudhary et al, 2009; Zhao levels correlated with acetyl-CoA concentration in vivo and et al, 2010; Weinert et al, 2011; Chen et al, 2012; Henriksen et al, acetyl-CoA acetylated lysine residues nonenzymatically in vitro. 2012; Lundby et al, 2012; Hebert et al, 2013). We developed a method to estimate acetylation stoichiometry and Notably, acetylation has been shown to occur frequently on mitochondrial proteins and a large number of sites are regulated found that the vast majority of mitochondrial and cytoplasmic acetylation had a very low stoichiometry. However, mitochondrial by the sirtuin-class deacetylase-3 (SIRT3; Sol et al, 2012; Hebert acetylation occurred at a significantly higher basal level than et al, 2013; Rardin et al, 2013). These observations, and a number cytoplasmic acetylation, consistent with the distinct acetylation of supporting studies (Newman et al, 2012), have established acet- dynamics and higher acetyl-CoA concentration in mitochondria. ylation as an important regulator of mitochondrial metabolism. High stoichiometry acetylation occurred mostly on histones, However, the mechanisms by which acetylation occurs in this proteins present in histone acetyltransferase and deacetylase organelle are mostly unknown. Several recent reviews speculated complexes, and on transcription factors. These data show that that nonenzymatic acetylation by acetyl-CoA may be widespread a majority of acetylation occurs at very low levels in exponentially in mitochondria (Guan & Xiong, 2010; Newman et al, 2012). Acet- growing yeast and is uniformly affected by exposure to acetyl-CoA. ylation could regulate metabolism through a nonenzymatic mecha- nism, in which case determining the stoichiometry of acetylation is Keywords acetylation; mass spectrometry; mitochondria; proteomics; stoichiometry of critical importance for gauging the effects of acetylation on Subject Categories Post-translational Modifications, Proteolysis & protein function. Proteomics; Genome-Scale & Integrative Biology In this study we used quantitative mass spectrometry (MS) to DOI 10.1002/msb.134766 | Received 6 August 2013 | Revised 6 November measure changes in lysine acetylation abundance in Saccharomyces 2013 | Accepted 11 December 2013 cerevisiae (budding yeast). We found that growth-arrest, combined Mol Syst Biol. (2014) 10: 716 with ongoing metabolism, resulted in the accumulation of acetyla- tion in a manner that depended on acetyl-CoA generation in distinct subcellular compartments. Acetylation dynamics in mitochondria correlated with acetyl-CoA levels in this compartment and we found Introduction that acetyl-CoA nonenzymatically acetylated protein in vitro.We developed a novel method to estimate acetylation stoichiometry and Lysine acetylation is an evolutionarily conserved, reversible post- discovered that the vast majority of acetylation occurred at a very low level. These data provide the first global analysis of acetylation translational modification (PTM) that is known to regulate protein function by site-specific acetylation (catalyzed by acetyltransferases) stoichiometry and indicate that metabolism regulates acetylation and deacetylation (catalyzed by deacetylases). Acetyltransferases levels in distinct subcellular compartments through acetyl-CoA generation. use acetyl-coenzyme A (acetyl-CoA) as a cofactor donating an acetyl 1 The NNF Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark 2 Institute of Molecular Biosciences, University of Graz, Graz, Austria 3 HEALTH – Institute for Biomedicine and Health Sciences, Joanneum Research, Graz, Austria *Corresponding author. Tel: +45 35 32 50 20; Fax: +45 35 32 50 01; E-mail: [email protected] ª 2014 The Authors This is an open access article under the terms of the Creative Commons Attribution License, Molecular Systems Biology 10: 716 | 2014 which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Molecular Systems Biology Acetylation dynamics and stoichiometry Brian T. Weinert et al Results Experimental strategy for quantitative analysis of proteome and PTM dynamics We used stable isotope labeling with amino acids in cell culture (SILAC; Ong et al, 2002) to quantify differences in protein, acetyla- tion, and phosphorylation abundance by MS. Proteins from whole cell lysates were digested to peptides and acetylated peptides enriched using a polyclonal anti-acetyllysine antibody as previously described (Kim et al, 2006; Weinert et al, 2013a). Peptide fractions were analyzed by reversed-phase liquid chromatography coupled to high resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS) and raw MS data were computationally processed using MaxQuant (Cox et al, 2011). The quantitative MS experiments performed in this study are summarized in Supplementary Table S1, and the raw data files have been deposited to the ProteomeXchange (Vizcaino et al, 2013), with the identifier PXD000507. Figure 1. Acetylation is globally increased in stationary phase yeast cells. Acetylation dynamics in growth-arrested yeast cells Box plots showing the distributions of SILAC ratios comparing stationary phase (SP) to exponential phase (EP) yeast for all quantified proteins (proteins), acetylated proteins (acetyl proteins), acetylation sites corrected for protein abundance In previous work we showed that acetylation accumulates in changes (acetyl sites), and phosphorylation sites (phospho sites). The box portion of growth-arrested bacteria (E. coli) cells due to prolonged exposure the plot indicates the middle 50% of the distribution, inner hatch marks denote to, and a higher concentration of, acetyl-phosphate (Weinert et al, 9–91%, and whisker ends 2–98%, outliers are not shown. Acetylation sites 2013a). In order to test whether growth-arrest affects PTMs in a occurring on proteins localized exclusively to mitochondria (Mito.), the cytoplasm (Cyto.), or the nucleus (Nuc.) are shown. Statistical significance was calculated eukaryotic system we compared acetylation, phosphorylation, and using a Wilcoxon test, data is from two biological replicates. protein levels between exponentially growing and stationary phase S. cerevisiae cells. We quantified more than 2600 acetylation sites (Supplementary Table S2), 3300 proteins (Supplementary Table S3), and 6000 phosphorylation sites (Supplementary Table S4) with a high correlation between biological replicates was unaffected when cells were growth-arrested in the presence of (Supplementary Figs S1A–C). Strikingly, stationary phase cells 2-deoxy-D-glucose (2DG; a glucose analog that cannot be metabo- showed increased ( > 2-fold) acetylation at a majority (~70%) of lized beyond the first step of glycolysis), indicating that increased quantified acetylation sites (median threefold increased; Fig 1). In mitochondrial acetylation depended on glycolysis (Fig 2B, Supple- contrast, protein and phosphorylation abundance, while affected in mentary Fig S2A, and Supplementary Table S5). However, nuclear stationary phase cells, was not globally increased (Fig 1), indicat- acetylation was globally reduced in the presence of 2DG (median ing that stationary phase did not cause the accumulation of 3.6-fold), suggesting that nuclear deacetylases remain active under proteins or PTMs generally. Furthermore, Gene Ontology (GO) these conditions. enrichment analysis of protein and phosphorylation site changes In order to examine the dependence of mitochondrial protein revealed both up-regulation and down-regulation of specific pro- acetylation on glycolysis, we quantified acetylation dynamics in cesses in stationary phase cells (Supplementary Figs S1D and E), pda1D cells that are unable to convert pyruvate to acetyl-CoA suggesting that such changes occurred in a regulated manner. (Wenzel et al, 1992), or in cit1D cells that are unable to convert Using subcellular localization data from GFP-tagged proteins (Huh acetyl-CoA to citrate (Kispal et al, 1988; Fig 2A). Mitochondrial et al, 2003), we found that acetylation increased to the greatest acetylation was drastically reduced in exponentially growing pda1D degree on mitochondrial proteins (median 5.7-fold), which was cells (median SILAC ratio pda1D/wild-type = 0.14) and was slightly significantly higher than the median increases seen for cytoplasmic increased in exponentially growing cit1D cells (Fig 2C, Supplemen- (2.6-fold) and nuclear (1.5-fold) proteins (Fig 1). Increased acetyla- tary Fig S2B, and Supplementary Table S6). Loss of Pda1 com- tion of mitochondrial proteins was nearly comprehensive (93% of pletely suppressed the increased acetylation of mitochondrial sites were > 2-fold elevated; Fig 1 and Supplementary Table S2). proteins in growth-arrested cells while loss of Cit1 further increased During glycolysis, glucose is converted to pyruvate, which enters the acetylation of mitochondrial proteins (an additional 1.8-fold) in mitochondria and is further converted to acetyl-CoA by the pyruvate growth-arrested cells (Fig 2D, Supplementary Fig S2C, and Supple- dehydrogenase complex (PDC), pyruvate can also be converted to mentary Table S7). Loss of Cit1 blocks the entry of acetyl-CoA into acetyl-CoA in the cytoplasm via an acetate intermediate (Fig 2A). In the citric acid cycle, thus, further increased acetylation in growth- order to control the transition to stationary phase we growth- arrested cit1D cells is likely due to greater accumulation of acetyl- arrested exponentially growing cultures by transferring the cells into CoA in the mitochondria of these cells. We quantified half as many media containing different carbon sources, and lacking an essential acetylation sites on mitochondrial proteins in pda1D cells compared amino acid (lysine), for ~24 h. Notably, mitochondrial acetylation to cit1D cells, while the frequency of quantified sites on cytoplasmic Molecular Systems Biology 10: 716 | 2014 © 2014 The Authors 2 Brian T. Weinert et al Acetylation dynamics and stoichiometry Molecular Systems Biology and nuclear proteins was not altered (Figs 2C and D), indicating that acetylation of many sites in pda1D cells had diminished to undetectable levels in mitochondria specifically. We next compared growth-arrested yeast in the presence of glu- cose or acetate to test whether acetate would alter the acetylation dynamics in growth-arrested cells. Consistent with conversion of acetate to acetyl-CoA by acetyl-CoA synthetase 2 (Acs2; Fig 2A; Takahashi et al, 2006) in the cytoplasm, acetate preferentially promoted the acetylation of cytoplasmic and nuclear proteins (Fig 2E, Supplementary Fig S2D, and Supplementary Table S8). Acetylation levels in mitochondria correlate with acetyl-CoA concentration We showed that mitochondrial acetylation was suppressed by dele- tion of pda1, suggesting that most mitochondrial acetyl-CoA is gener- ated in a Pda1-dependent manner in the growth conditions used in our study. We compared acetyl-CoA levels between wild-type, pda1D, and cit1D cells (Fig 3A). Acetyl-CoA was reduced by approxi- mately 1/3 in pda1D cells, indicating that the mitochondrial acetyl-CoA pool constitutes at least 1/3 of the total acetyl-CoA pool. However, mitochondria occupy ~1–2% of the total cellular volume in yeast (Uchida et al, 2011), indicating that acetyl-CoA levels are substantially (~20–30-fold) higher in mitochondria compared to the cytoplasm and nucleus. We hypothesized that increased acetylation in growth-arrested cells may occur due to higher concentrations of acetyl-CoA or due to prolonged exposure of proteins to acetyl-CoA. We found that acetyl-CoA levels were reduced in growth-arrested cells (Fig 3A), suggesting that acetylation occurs due to prolonged exposure to acetyl-CoA. However, this difference may be due to reduced recovery of acetyl-CoA from growth-arrested cells, which have a substantially increased cell wall and are known to be refractory to cell lysis. We consistently recovered less protein from growth-arrested cells (data not shown), suggesting that these cells were more difficult to lyse, or that cell size and/or protein content was reduced under these conditions. Such differences in cell physiol- ogy may explain the lower amount of acetyl-CoA per OD of growth-arrested cells as determined by our assay. Regardless, acetyl- CoA levels were elevated in growth-arrested cit1D cells, consistent Figure 2. Quantitative analysis of acetylation dynamics in yeast. with our observation of increased acetylation in these cells. If we A Model showing the formation of acetyl-CoA from glucose and acetate, assume that the reduction of acetyl-CoA in pda1D cells indicates the key enzymes are shown in red type. mitochondrial acetyl-CoA pool in these cells, then mitochondrial B–E The figure shows the conditions analyzed in each experiment, the cell acetyl-CoA in cit1D cells was increased ~1.9-fold and ~1.7-fold after 8 type (wild-type (wt) or indicated mutant strains), the growth state and 16 h growth-arrest, respectively (Fig 3A), mirroring the 1.8-fold [exponential phase (EP) or growth-arrested (GA)], the number of acetylation sites analyzed (# sites), the median Log2 and linear SILAC increase in mitochondrial acetylation in growth-arrested cit1D cells ratios comparing the indicated condition to wild-type EP cells, and the (Fig 2D). subcellular localization of the analyzed acetylation sites on proteins The physiological concentration of acetyl-CoA in yeast is not localized to mitochondria (Mito.), the cytoplasm (Cyto.), or the nucleus well-studied. One study estimated acetyl-CoA levels (3–30 lM) in (Nuc.). Cells were growth-arrested by transferring an exponential phase nutrient-starved yeast undergoing metabolic cycles (Cai et al, 2011), culture into media lacking lysine and containing the indicated carbon sources, glucose, acetate, or 2-deoxy-D-glucose (2DG). The bar chart conditions that contrast with the excess of glucose and high growth shows the median Log2 SILAC ratios comparing the indicated condition rates of yeast grown on synthetic complete (SC) media in our study. to wild-type EP cells, statistical significance was calculated by Wilcoxon We estimated a similar cellular concentration of ~30 lM acetyl-CoA test. Increased acetylation requires glycolysis (B). Data is from two in exponentially growing cells. However, this estimate assumes biological replicates. Mitochondrial acetylation in exponentially growing cells requires Pda1 (C). Increased mitochondrial acetylation in complete recovery of acetyl-CoA, and is therefore likely to under- growth-arrested cells is suppressed by loss of Pda1 and enhanced by estimate the actual cellular concentration. We showed that loss of Cit1 (D). Data from two biological replicates is shown, significant mitochondrial acetyl-CoA was ~20–30-fold higher than non- differences are relative to wild-type cells. Acetate promotes cytoplasmic mitochondrial acetyl-CoA, suggesting a concentration of acetyl-CoA and nuclear acetylation (E). Data is from two biological replicates. in mitochondria that approaches the millimolar range (~0.5–1mM © 2014 The Authors Molecular Systems Biology 10: 716 | 2014 3 Molecular Systems Biology Acetylation dynamics and stoichiometry Brian T. Weinert et al Figure 3. Acetyl-CoA concentration in cells and nonenzymatic acetylation by acetyl-CoA. A Acetyl-CoA concentration was determined in the indicated cell types during exponential phase (EP) growth or after the indicated time of growth-arrest (GA) in the presence of glucose. Data are from two independent biological replicates. B The bar graph shows the abundance of the indicated, acetylated (ac) peptides relative to an untreated control sample. Error bars indicate standard deviation of the indicated number (n) of independently quantified peptides. The significance (P) of increased acetylation at 100 lM acetyl-CoA was calculated by two-tailed t-test assuming equal variance. C The column graph shows the relative abundance of non-acetylated peptides. Error bars indicate standard deviation of the indicated number (n) of independently quantified peptides. based on our estimates). This estimate is consistent with previous relative abundances of posttranslationally modified and unmodified work showing that acetyl-CoA can reach millimolar levels in rat corresponding peptides (CPs; Olsen et al, 2010; Wu et al, 2011). If liver mitochondria (Garland et al, 1965). the abundance of a modified peptide is substantially altered then the abundance of the CP should be affected in an inverse manner. How- Acetyl-CoA nonenzymatically acetylates protein ever, CP abundance will only be measurably affected if PTM stoichi- ometry is relatively high. Since our results suggested a low A study in 1970 showed that acetyl-CoA could nonenzymatically stoichiometry of modification, we devised a strategy to assay acety- acetylate lysine rich histone fractions and synthetic polylysine at a lation stoichiometry based on partial chemical acetylation of lysine concentration of ~0.5 mM, with increased kinetics at higher pH, and residues. Partial chemical acetylation will cause the greatest relative an activation energy of 7.5 kcal, suggesting that the reaction could increases in acetylation on sites with the lowest initial stoichiome- occur under physiological conditions (Paik et al, 1970). We sought try, while sites with higher initial stoichiometry will be partially or to independently verify nonenzymatic acetylation by acetyl-CoA not at all affected. In order to find conditions that resulted in partial using mass spectrometry and a quantitative strategy based on iso- chemical acetylation, we chemically acetylated bovine serum albu- baric mass tags (Supplementary Fig S3). Bovine serum albumin min (BSA) with acetyl-phosphate (AcP) or acetic anhydride. We (BSA) was treated with increasing concentrations of acetyl-CoA at found that AcP caused partial chemical acetylation that did not mea- physiological pH, modestly, but significantly, increased acetylation surably affect the abundance of CPs, while acetic anhydride caused was seen on several peptides at a concentration of 100 lM acetyl- comprehensive acetylation and resulted in dramatically reduced CoA, while 1 and 10 mM acetyl-CoA caused increased acetylation abundance of CPs (Supplementary Fig S4 and supplemental text). on all peptides analyzed (Fig 3B). In contrast, the abundance of In order to examine acetylation site stoichiometry in S. cerevisiae, non-acetylated peptides was unaffected by acetyl-CoA (Fig 3C). This we used a SILAC-based quantitative approach to quantify chemi- acetylation is likely to be nonenzymatic since we treated a purified cally acetylated and untreated peptides in the same MS experiment extracellular serum protein (BSA) and acetylation did not occur (Fig 4). An untreated control sample was prepared in order to iden- until acetyl-CoA concentration was well in excess of the known tify acetylation sites that occurred in the absence of AcP-treatment range of binding affinities of acetyltransferases for acetyl-CoA (Alb- and to determine the quantitative variability in our experiments. augh et al, 2011a). Treatment with AcP resulted in substantially increased (>2-fold) acetylation at 74% (10 mM AcP) and 88% (100 mM AcP) of acety- Acetylation stoichiometry in yeast lation sites (Fig 5A and Supplementary Table S9). In contrast, <1% of acetylation sites were substantially increased in the untreated The striking increase (median 9.6-fold) in mitochondrial acetylation (0 mM AcP) lysate, reflecting the quantitative accuracy of our in growth-arrested cit1D cells indicated that mitochondrial assays (Fig 5A). An independent experimental replicate was per- acetylation occurred at a low-level (maximum median stoichiometry formed with untreated (0 mM) and 100 mM AcP-treated lysate of ~10% in exponentially growing cells). One method used to (Supplementary Table S9). Acetylation changes were similar in analyze PTM stoichiometry on a global scale is to compare the experimental replicates, as shown by a Spearman’s correlation Molecular Systems Biology 10: 716 | 2014 © 2014 The Authors 4 Brian T. Weinert et al Acetylation dynamics and stoichiometry Molecular Systems Biology and fatty acid synthetase (Fas2; Table 1). Surprisingly, we were unable to detect acetylated peptides from purified Pgk1, and found just one acetylated peptide from purified Fas2, even though we detected unmodified peptides covering 89 and 72% of the Pgk1 and Fas2 protein sequences, respectively. In order to detect acetylation on these proteins we treated cell lysates with 100 mM AcP and puri- fied Pgk1 and Fas2 for AQUA analysis. Comparison to heavy-labeled peptide standards indicated that acetylation stoichiometry, after AcP-treatment, was < 1% at all eight sites, with a median degree of chemical acetylation that was just 0.07% (Table 1, Supplementary Figs S7A–D). AcP-sensitivity was well-correlated with acetylation stoichiometry as determined by the AQUA method (Spearman’s cor- relation of 0.92, Fig 5C), confirming our prediction that low stoi- chiometry sites would be most sensitive to partial chemical acetylation and providing independent validation of our method. We estimated acetylation stoichiometry based on the conserva- tive assumption that chemical acetylation from 100 mM AcP was < 1% at all sites. A site with 10-fold increased acetylation after AcP-treatment was estimated to have a stoichiometry that is < 0.1% while a site with 20-fold increased acetylation was estimated to have a stoichiometry that is < 0.05%. Using this approach we estimated acetylation stoichiometry based on the observed SILAC L/H ratios after treatment with 100 mM AcP and found that 25% of sites were < 0.02% acetylated, 50% of sites were < 0.05% acetylated, 66% of sites were < 0.1% acetylated, and a remarkable 86% of sites were Figure 4. Method used to assay acetyl-phosphate sensitivity in < 1% acetylated (Fig 5D). These estimates contrast with previously yeast lysate. determined phosphorylation site stoichiometries in yeast, where Yeast proteins were metabolically labeled with unlabeled “light” lysine or with 89% of sites were estimated to have stoichiometries that were >1% “heavy” isotope labeled lysine. Protein lysates were treated with acetyl- phosphate (AcP) or were mock-treated by addition of H O. Equal amounts of (Wu et al, 2011; Fig 5E), indicating that a much greater fraction of protein were mixed and digested to peptides with trypsin protease. Acetylated acetylation occurs with a low stoichiometry. It was not possible to (Ac) peptides were immune-affinity enriched using agarose-coupled anti- accurately estimate the stoichiometry of sites that were AcP-insensi- acetyllysine polyclonal antibody and analyzed by MS. Increased acetylation tive (SILAC ratio L/H < 2) as the relative changes in acetylation from AcP treatment causes an increase in the relative abundance of the light labeled peptide, enabling quantification of acetylation changes induced by AcP. were of a similar magnitude to the variability of these measure- ments. Thus, AcP-insensitive sites were estimated to have acetyla- tion stoichiometry that is >1%. coefficient of 0.89 (Supplementary Fig S5). We identified 9415 acet- In order identify independent parameters that could confirm our ylation sites in 100 mM AcP-treated lysates, 1765 sites had SILAC stoichiometry estimates we compared acetylated peptide intensity ratios, and 916 of these sites were previously identified (Supplemen- and abundance-corrected acetylated peptide intensity to AcP-sensi- tary Table S2), or were found in untreated control samples, indicat- tivity (Supplementary Fig S8). We found that correcting acetylated ing that these sites are naturally occurring acetylation sites in yeast. peptide intensity with protein abundances determined by an inten- Using only the 916 naturally occurring sites with SILAC ratios, sity-based absolute quantification (iBAQ) method (Schwanhausser we found that 65% of the sites were more than 10-fold increased in et al, 2011), could best distinguish AcP-insensitive sites (SILAC ratio acetylation (Fig 5B), indicating maximum initial stoichiometry that L/H < 2) from AcP-sensitive sites (SILAC ratio L/H > 2; Fig 5F and was < 10% at these sites. However, acetylation stoichiometry at Supplementary Fig S8) and had the best overall correlation these positions is likely to be lower than 10% (which assumes com- (q = 0.57) with AcP sensitivity (Supplementary Fig S8). These prehensive acetylation) because our analysis of AcP-treated BSA data independently confirmed our stoichiometry estimates based on (Supplementary Fig S4), showed that 100 mM AcP caused partial AcP-sensitivity, as this parameter was calculated using peptide chemical acetylation without a reduction in the abundance of CPs. intensities and protein abundances determined in untreated control CP abundance was similarly unaffected in 100 mM AcP-treated samples. yeast lysate (Supplementary Fig S6), indicating that AcP-treatment We estimated acetylation stoichiometry for the 916 sites with caused a low-level of partial chemical acetylation. SILAC ratios; however, an additional 1540 sites without SILAC In order to better characterize the degree of partial chemical acet- ratios were independently identified as naturally occurring sites ylation by 100 mM AcP, we used an absolute quantification (AQUA) (identified in untreated control samples or in Supplementary method (Gerber et al, 2003), to quantify acetylation levels. Acetylated Table S2). SILAC ratios were estimated for these sites by calculat- and unmodified peptide intensities were compared to heavy-labeled ing the increased intensity of AcP-treated “light” peptides relative peptide standards, allowing us to determine acetylation stoichiometry to an empirically determined detection limit for naturally occurring directly. We analyzed eight acetylation sites with varying sensitivity “heavy” peptides (see Materials and Methods). Using this method to 100 mM AcP on two proteins, 3-phosphoglycerate kinase (Pgk1) we calculated minimum ratios of increased acetylation at 1516 © 2014 The Authors Molecular Systems Biology 10: 716 | 2014 5 Molecular Systems Biology Acetylation dynamics and stoichiometry Brian T. Weinert et al Figure 5. Most acetylation sites are modified with a low stoichiometry. A The majority of yeast acetylation sites are highly sensitive to partial chemical acetylation by AcP. The histogram shows the distribution of SILAC L/H ratios for the indicated samples. B AcP caused substantially increased acetylation at a majority of sites. The histogram shows acetylation changes induced by 100 mM AcP in two experimental replicates, only sites that were independently identified in cells without AcP treatment are shown. C Acetylation stoichiometry is inversely proportional to AcP-sensitivity. The scatterplot shows the relationship between AcP-sensitivity (SILAC ratio L/H 100 mM AcP) and acetylation stoichiometry (Log10 stoichiometry) as determined by AQUA analysis (Table 1). The Spearmans correlation (q) and the significance by two-tailed test (P-value) are shown. D Most acetylation occurs with a low stoichiometry. Absolute acetylation site stoichiometries were estimated based on relative abundance changes (SILAC ratio L/H) after treatment with 100 mM AcP and using an estimate that AcP treatment caused < 1% chemical acetylation. E For comparison, previously determined phosphorylation site stoichiometries are shown (Wu et al, 2011). F iBAQ-based abundance corrected acetylated peptide intensity (I/iBAQ-A) is proportional to AcP sensitivity. The box plots show the distributions of I/iBAQ-A values for the indicated classes of acetylation sites. AcP-insensitive sites had a significantly (p) higher distribution of I/iBAQ-A values compared to either AcP-sensitive sites or sites without SILAC ratios. Significance was calculated by Wilcoxen test. G Sites without SILAC ratios are highly sensitive to AcP. The minimum ratio of increased acetylation was determined by calculating the increased intensity of AcP- treated “light” peptides relative to an empirically determined detection limit for “heavy” SILAC peptides (see Materials and Methods). H Absolute acetylation stoichiometry of sites without SILAC ratios was estimated to be very low. Stoichiometry was estimated by the same method used to estimate stoichiometry of sites with SILAC ratios in (D) using the minimum ratios of increased acetylation shown in (G). sites and found that AcP caused a median 70-fold increase in acet- abundance-corrected peptide intensity (I/iBAQ-A) distributions for ylation (Fig 5G). Assuming that 100 mM AcP caused < 1% chemi- these sites (Fig 5F). By including these data we estimated acetyla- cal acetylation, the substantially increased acetylation at these tion stoichiometry at a total of 2432 sites in exponentially growing sites indicated a very low stoichiometry of acetylation (Fig 5H) yeast and found that 95% of all acetylation occurs at an estimated and this finding was independently verified by examining the stoichiometry that is < 1%. Molecular Systems Biology 10: 716 | 2014 © 2014 The Authors 6 Brian T. Weinert et al Acetylation dynamics and stoichiometry Molecular Systems Biology Table 1. Absolute quantification (AQUA) of acetylated peptides from Pgk1 and Fas2. Acetylation stoichiometry was determined by AQUA for Pgk1 and Fas2 after treatment with 100 mM AcP (see Supplementary Fig S6). Initial stoichiometry was calculated by dividing the stoichiometry in 100 mM AcP by the Ratio L/H 100 mM AcP and the degree of chemical acetylation is the difference between the initial stoichiometry and the stoichiometry in 100 mM AcP Stoichiometry Ratio L/H Initial Degree chemical Protein Peptide sequence 100 mM AcP (%) 100 mM AcP stoichiometry (%) acetylation (%) Pgk1 AAGFLLEK(ac)ELK 0.023 80.8 0.0003 0.02 Pgk1 AGAEIVPK(ac)LMEK 0.095 41.5 0.0023 0.09 Pgk1 FAAGTK(ac)ALLDEVVK 0.119 27.7 0.0043 0.11 Fas2 QVLDVDPVYKDVA(ac)PTGPK 0.032 108.3 0.0003 0.03 Fas2 LIEPELFNGYNPE(ac)K 0.092 33.5 0.0027 0.09 Fas2 GATLYIP(ac)ALR 0.068 11.3 0.0060 0.06 Fas2 SEGNPVIGVFQ(ac)FLTGHPK 0.016 5.3 0.0031 0.01 Fas2 AND(ac)NESATINEMMK 0.181 1.7 0.1055 0.08 Functional analysis of proteins with high stoichiometry (Fig 6E). Similarly, nuclear proteins were least biased to detect acet- acetylation sites ylation on abundant proteins, as this subcellular compartment con- tained the most high stoichiometry acetylation sites (Fig 6E). Thus, In order to characterize proteins with AcP-insensitive, high stoichi- the abundance of proteins with observed acetylation sites is consis- ometry sites we used GO term enrichment analysis. Proteins with tent with our stoichiometry estimates. AcP-insensitive sites were significantly more frequently associated Acetylated sites with high stoichiometry are likely to be impor- with nuclear processes (Fig 6A). More than half of all AcP-insensi- tant for protein function. Many previously known regulatory acety- tive sites occurred on histones, proteins present in histone deacety- lation sites were AcP-insensitive, including Smc3 lysines 112 and lase (HDAC) or histone acetyltransferase (HAT) complexes, and on 113 (Zhang et al, 2008), Sas2 (MYST homolog) lysine 168 (Yuan transcription factors. We compared the effect of AcP-treatment on et al, 2012), Yng2 lysine 170 (Lin et al, 2008), RTT109 lysine 290 proteins present in different subcellular compartments (Fig 6B). (Albaugh et al, 2011b), SNF2 lysines 1494 and 1498 (Kim et al, Consistent with GO term analysis, 77% of the high-stoichiometry, 2010), histone H2AZ (Htz1) lysines 4, 9, 11, and 15 (Babiarz et al, AcP-insensitive sites occurred on nuclear proteins. In contrast, 97% 2006; Millar et al, 2006; Lin et al, 2008), histone H3 (Hht1) lysines of mitochondrial and 94% of cytoplasmic acetylation sites were 19, 24, and 57 (Zhang et al, 1998; Suka et al, 2001; Hyland et al, AcP-sensitive, indicating that the vast majority of acetylation sites in 2005), histone H4 (Hhf1) lysines 6, 9, 13, and 17 (Suka et al, 2001) these subcellular compartments were acetylated at a low stoichiom- and histone H2B (Htb2) lysines 16 and 17. These 20 sites constitute etry. Notably, mitochondrial acetylation sites were significantly 18% of the 111 AcP-insensitive sites that we identified, indicating (p = 5.8e , Wilcoxon test) less affected (median 14-fold increased) that AcP-insensitivity is a good predictor of functionally important by AcP than cytoplasmic sites (median 30-fold increased; Fig 6B), acetylation sites. The enrichment of functionally characterized sites suggesting a higher basal level of acetylation in mitochondria. This within the group of AcP-insensitive sites is highly significant finding was independently confirmed by a significantly higher distri- (p = 1e , Fisher exact test). Furthermore, known functional sites bution of acetylated peptide I/iBAQ-A for mitochondrial proteins had significantly higher I/iBAQ-A values, indicating that this param- than cytoplasmic proteins (Fig 6C). In contrast, non-acetylated pep- eter is also useful in distinguishing functionally-relevant, high- tide I/iBAQ-A was similarly distributed between mitochondrial and stoichiometry sites (Supplementary Fig S9B and Supplementary cytoplasmic proteins (Fig 6C). It is also notable that the distribution Table S9). of AcP-sensitivity for nuclear proteins was bi-modal, indicating distinct populations of high and low stoichiometry acetylation sites in the nucleus. The subcellular localization of high-stoichiometry, Discussion AcP-insensitive sites was significantly different to low-stoichiome- try, AcP-sensitive sites and low-stoichiometry sites without SILAC While acetylation has been identified on thousands of proteins in ratios in all three compartments (Fig 6D). diverse subcellular compartments, the mechanisms of non-nuclear MS analysis is biased towards abundant proteins, which are acetylation and its regulation are not well understood. We found more readily detected in the MS. Nearly every abundant protein that acetylation levels were dynamically affected by growth-arrest identified by MS was also acetylated (Fig 6E), and the frequency of and the generation of acetyl-CoA in distinct subcellular compart- detected acetylation sites was proportional to protein abundance ments. Acetyl-CoA was previously shown to exist in distinct mito- (Supplementary Fig S9A), indicating that protein abundance is a chondrial and non-mitochondrial pools in yeast (Takahashi et al, limiting factor in the identification of many sites. The technical bias 2006). We showed that mitochondrial acetylation occurs within to detect acetylation on abundant proteins was less pronounced for mitochondria and is uniformly affected by growth-arrest and the mitochondrial proteins compared with cytoplasmic proteins, consis- generation of acetyl-CoA by the PDC. We found that acetyl-CoA tent with our estimation of higher acetylation levels in mitochondria levels correlated with acetylation changes in mitochondria and we © 2014 The Authors Molecular Systems Biology 10: 716 | 2014 7 Molecular Systems Biology Acetylation dynamics and stoichiometry Brian T. Weinert et al Figure 6. Functional analysis of high stoichiometry acetylation sites. A AcP-insensitive acetylation sites occur on proteins associated with nuclear processes. Gene Ontology (GO) term enrichment was performed by comparing proteins with AcP-insensitive acetylation sites (ratio L/H < 2) to all acetylated proteins. The bar graph shows the percentage of AcP-insensitive sites occurring on proteins associated with the indicated GO terms. P-values (P) indicate the statistical significance of GO term enrichment by Fishers exact test. B AcP-insensitive acetylation sites occur on nuclear proteins. The histogram shows the distribution of SILAC L/H ratios occurring on proteins localized to the indicated subcellular compartments. C Acetylated peptides from mitochondrial proteins have a significantly higher median I/iBAQ-A value compared to acetylated peptides from cytoplasmic proteins. The box plots show the I/iBAQ-A distributions for the indicated classes of peptides occurring on mitochondrial (Mito.) or cytoplasmic (Cyto.) proteins. Signficance (p) was determined by Wilcoxon test. D AcP-insensitive sites (SILAC Ratio < 2) have a significantly different subcellular distribution. Sites without SILAC ratios (No ratio) have a similar subcellular distribution to AcP-sensitive sites (SILAC Ratio > 2). The bar graph shows the fraction of sites localized to the indicated subcellular compartments; mitochondria (Mito.), cytoplasm (Cyto.), or nucleus (Nuc.). Significance (P) was calculated by Fisher exact test. E Detection of acetylation sites is biased to occur on abundant proteins and this bias is more pronounced for sites with the lowest estimated stoichiometries. The histograms show the distributions of iBAQ protein abundances for observed proteins (n = 3,104). The distributions of the indicated classes of acetylated proteins occurring exclusively in the indicated subcellular compartments is shown in red. The numbers of acetylated proteins are shown in parenthesis and the median Log10 iBAQ abundance for these acetylated proteins is shown. confirmed that acetyl-CoA can nonenzymatically acetylate proteins. lar compartments. Mutations that blocked acetyl-CoA generation or Our analysis of acetylation stoichiometry showed that the vast its downstream conversion to citrate had opposing effects on mito- majority of acetylation occurs at very low levels, an important chondrial acetylation in growth-arrested yeast cells, linking acetyl- observation with widespread implications for understanding non- CoA levels to mitochondrial acetylation levels. We furthermore nuclear acetylation. showed that acetyl-CoA levels correlated with acetylation abun- A few recent reviews speculated that acetylation may occur dance in mitochondria. Growth-arrest in the presence of glucose or nonenzymatically by exposure to acetyl-CoA, particularly in mito- acetate affected acetylation levels in a manner that was consistent chondria where a protein acetyltransferase activity has not been with separate mitochondrial and non-mitochondrial acetyl-CoA definitively identified (Guan & Xiong, 2010; Newman et al, 2012). pools and generation. Mitochondrial proteins had a significantly Acetyl-CoA has been previously shown to nonenzymatically acety- higher basal level of acetylation than cytoplasmic proteins, consis- late proteins (Paik et al, 1970) and the elevated pH in the mito- tent with our results indicating a higher concentration of acetyl- chondrial matrix would favor this reaction (Paik et al, 1970; Llopis CoA in this organelle. Acetylation is widespread in yeast (Henrik- et al, 1998; Abad et al, 2004; Wagner & Payne, 2013). In addition, sen et al, 2012), yet the number of known acetyltransferases in recent work showed that lysines can be nonenzymatically modified yeast is small (~15; Cherry et al, 2012), particularly compared to by other glycolytic intermediates, such as 1,3-bisphosphoglycerate the number of kinases catalyzing protein phosphorylation (~130; (Moellering & Cravatt, 2013), and succinyl-CoA (Wagner & Payne, Manning et al, 2002; Cherry et al, 2012). Moreover, most acety- 2013; Weinert et al, 2013b). We found that nearly all acetylation ltransferases have known nuclear functions, consistent with our occurred at a low-level and was uniformly regulated by manipula- observation that the majority of high stoichiometry acetylation tions that affected the generation of acetyl-CoA in distinct subcellu- occurred in the nucleus. Thus, the global acetylation dynamics that Molecular Systems Biology 10: 716 | 2014 © 2014 The Authors 8 Brian T. Weinert et al Acetylation dynamics and stoichiometry Molecular Systems Biology we observed in growth-arrested yeast, their dependence on distinct Materials and Methods acetyl-CoA pools and generation, a preponderance of low stoichi- ometry acetylation, and the restriction of high stoichiometry acety- Yeast growth and lysate preparation lation to the nucleus, are highly consistent with a nonenzymatic mechanism of acetylation. These observations contrast with the Wild-type Saccharomyces cerevisiae cells (BY4742, MATalpha canonical model of protein regulation by site-specific PTMs and his3D1 leu2D0 lys2D0 ura3D0; ThermoFisher Scientific, Slangerup, indicate that acetylation may act in a global manner to regulate Denmark), pda1D (BY4742, pda1::KanMX; ThermoFisher Scientific), proteins, or conversely, that most acetylation occurs as a low-level and cit1D (BY4742, cit1::KanMX; Open Biosystems) were cultured in protein lesion that accumulates under specific conditions. How- synthetic complete media (US Biological, Salem, MA, USA) supple- 12 14 13 15 ever, widespread low-level acetylation could occur due to a pro- mented with C N -lysine (SILAC “light”) or C N -lysine 6 2 6 2 miscuous acetyltransferase activity that is sensitive to changes in (SILAC “heavy”). Cells were harvested at the indicated time points, acetyl-CoA levels. washed once with sterile H O, and resuspended in lysis buffer To better understand our estimates of acetylation stoichiometry, (50 mM Tris, pH7.5, 150 mM NaCl, 1 mM EDTA, 1x mini complete it is important to note that individual lysines may vary in the degree protease inhibitor cocktail (Roche, Basel, Switzerland), 5 mM of chemical acetylation by AcP. Without knowing the exact degree sodium fluoride, 1 mM sodium orthovanadate, 5 mM beta-glycero- of chemical acetylation at each position it is not possible to make a phosphate, 10 mM nicotinamide, and 5 lM tricostatin A) at precise estimate of acetylation stoichiometry. In order to account for ~50 OD cells/ml lysis buffer. The cell suspension was frozen this variability we based our estimates on the conservative assump- drop-wise in liquid nitrogen and ground in a liquid nitrogen tion that the degree of partial chemical acetylation by AcP was <1%. chilled steel container by the Retsch MM 400 Ball Mill (Retsch, Since we determined that 100 mM AcP caused a median chemical Haan, Germany) for 5 min at 25 Hz. The lysate was thawed, NP-40 acetylation of just 0.07% (between 0.01 and 0.11%), we are likely and sodium deoxycholate were added to a final concentration of 1 to overestimate the stoichiometry of acetylation. Thus, stoichiome- and 0.1%, respectively, and clarified by centrifugation. The lysate try estimates are presented as less than (<) values, to designate an supernatent was precipitated with four volumes 20°C acetone. The estimated stoichiometry that is less than the indicated amount. In acetone precipitate was dissolved in urea solution (6 M urea, 2 M addition, some lysines may be inaccessible or otherwise unreactive, thio-urea, 10 mM Hepes pH8.0) and protein concentration resulting in an incorrect estimate of high stoichiometry acetylation. determined by Quick-Start Bradford assay (Bio-Rad, Copenhagen, Regardless of these limitations, the results obtained using our Denmark). approach indicated that it was able to distinguish acetylation stoichi- Chemical acetylation of BSA and yeast lysate ometry at the site level. Absolute quantification indicated that acety- lation stoichiometry was inversely proportional to AcP-sensitivity (Table 1, Fig 5C). The highly significant bias to identify high stoichi- For treatment of BSA with acetyl-CoA, BSA was prepared in PBS ometry sites on nuclear proteins indicated that the identification of (pH 7.2) at 10 mg/ml and mixed with 1/10 volume acetyl-CoA (Sigma, Copenhagen, Denmark) prepared fresh in H O. Reactions such sites was non-random. Similarly, sites we predicted to have high stoichiometry were significantly more likely to have known were incubated at 30°C for 4 h and stopped by addition of nine vol- functional roles. Our method further distinguished between low umes 20°C acetone. Acetone precipitated protein was resuspended stoichiometry acetylation in the cytoplasm and mitochondria, indi- in 200 ll of 100 mM triethyl ammonium bicarbonate (TEAB) and digested to peptides by addition of 1/100 (w/w) trypsin protease cating that the difference in acetylation levels between these two subcellular compartments was greater than the inherent variability (Sigma) and incubation at 37°C for 16 h. Tryptic peptides were of lysine reactivity with AcP. Thus, the resolution of our assay was labeled with TMT sixplex isobaric mass tags (ThermoFisher not limited by the variability in lysine reactivity. Scientific) according to the manufacturer’s instructions. Chemical acetylation with acetic anhydride was performed as described (Guan Phosphorylation is known to regulate proteins in a site-selective manner and is one of the most extensively studied and widespread et al, 2010). Briefly, 20 ml of 1 mg/ml BSA (Sigma) was prepared in PTMs in eukaryotic cells. The number of detected phosphorylation 0.1 M Na CO . 100 ll acetic anhydride (Sigma) was added slowly 2 3 sites increases with organism complexity, reflecting its role in regu- over 10 min in a glass beaker with constant stirring, followed by 400 ll pyridine (Sigma) over 30 min, also with constant stirring. lating diverse cellular processes. In contrast, acetylation occurs as frequently in bacteria as in human cells (Weinert et al, 2013a). Simi- The reaction was then left to incubate at room temperature for 4 h lar to bacteria, acetylation is overrepresented in mitochondria com- and quenched by addition of 400 ll 1 M Tris-base (Sigma). Organic solvents were removed by five rounds of centrifuge filtration in an pared with phosphorylation (Weinert et al, 2011). Thus the frequency of acetylation is uncoupled from organism complexity, Amicon Ultra 15 (Millipore, Billerica, MA, USA) with a 10 kD suggesting that nonenzymatic acetylation may play a large role in molecular weight cutoff. For treatment with AcP, BSA was prepared the generation of these sites. We showed that basal acetylation lev- in yeast lysis buffer (as above, with NP-40 and deoxycholate added) at a concentration of 20 mg/ml. Yeast lysate was similarly prepared els are elevated in mitochondria, likely due to a higher concentra- tion of acetyl-CoA in this organelle. These observations suggest that at a concentration of 20 mg/ml. BSA or yeast lysate was then mixed the endosymbiotic evolution of mitochondria as the metabolic cen- with 1/10 volume of H O or AcP [freshly prepared in H O, potas- 2 2 ters of eukaryotic cells may have limited widespread acetylation sium lithium salt (Sigma)] at either 100 mM or 1 M concentration for a final concentration of 10 or 100 mM AcP, respectively. Reac- outside of mitochondria by compartmentalizing acetyl-CoA gener- ated during metabolism, thereby enabling the evolution of acetyla- tions were incubated at 37°C for 90 min. BSA was mixed with 4x tion signaling in the nucleus. nuPAGE SDS-polyacrylamide loading buffer (Life Technologies, © 2014 The Authors Molecular Systems Biology 10: 716 | 2014 9 Molecular Systems Biology Acetylation dynamics and stoichiometry Brian T. Weinert et al Naerum, Denmark) and separated by SDS-polyacrylamide gel 2012). All quantitative MS experiments performed in this study are electrophoresis using NuPAGE gels (Life Technologies). In-gel tryptic summarized in Supplementary Table S1. The mass spectrometry pro- digestion and peptide isolation were performed essentially as teomics data have been deposited to the ProteomeXchange Consor- described (Shevchenko et al, 1996). For yeast lysate, the reactions tium (http://proteomecentral.proteomexchange.org) via the PRIDE were stopped by addition of 5–10 volumes 20°C acetone and incu- partner repository (Vizcaino et al, 2013) with the dataset identifier bated at 20°C for 1–2 h. Acetone precipitated protein was resus- PXD000507. pended in 8 M urea solution (6 M urea, 2 M thio-urea, 10 mM Hepes pH8.0) and the concentration determined by Quick Start Peptide identification and computational analysis Bradford assay (BioRad). Equal amounts of protein were mixed, Raw data files were processed using MaxQuant software (developer diluted to 2 M urea by addition of 3 volume 50 mM Hepes, pH8.5, proteolyzed by addition of 1:200 (w/w) trypsin protease (Sigma) for version 1.2.7.1) as described (http://www.maxquant.org/; Cox 16–20 h at room temperature. Peptides were purified by C18 et al, 2011). Parent ion (MS) and fragment (MS2) spectra were Sep-Pack classic cartridge (Waters, Waltham, MA, USA). Peptides searched against the Saccharomyces Genome Database (SGD) gen- ome release r63, January 5, 2010. The search was performed using were acidified by addition of trifluoroacetic acid (TFA) to 1% and applied to a Sep-Pack column that was pre-equilibrated with 5 ml the integrated Andromeda search engine and both forward and acetonitrile and twice with 5 ml 0.1% TFA. The column was reversed (decoy) versions of the databases (Cox et al, 2011). Pep- tides were additionally filtered for a minimum posterior error proba- washed twice with 5 ml 0.1% TFA and once with 5 ml H O. Peptides were eluted with 3 ml 50% acetonitrile in H 0, 100 llof bility (PEP) score of 0.01, resulting in data sets with estimated false 10x IP buffer (500 mM MOPS, pH 7.2, 500 mM NaCl) was added, discovery rates that were less than the standard 1% used in most and the acetonitrile was removed by vacuum centrifugation to a proteomic studies (Supplementary Table S1). Quantification of TMT mass tags may be inaccurate if additional peptides are co-isolated final volume of ~1 ml. Peptide concentration was determined by absorbance at 280 nm using a nanodrop (ThermoFisher Scientific) with the targeted peptide ion (Ting et al, 2011). In order to mini- spectrophotometer (~6 mg/ml). An aliquot of 200 lg peptides was mize this effect we restricted the quantification of TMT mass tags to set aside for subsequent proteome analysis and the remaining MS/MS scans in which the targeted parent ion constituted a mini- mum of 90% of the total ion current. Mass recalibration was per- peptides were used for acetyllysine enrichment (described below). formed using high confidence identifications based on a initial “first Peptide preparation, acetyllysine enrichment, and search” using a 20 part per million (ppm) mass tolerance for parent peptide fractionation ion masses and 20 ppm (HCD) or 0.5 Dalton (CID) for fragment ions. Spectra were subsequently searched with a mass tolerance of In-solution protein digestion, peptide purification, and acetyllysine 6 ppm for parent ions and 20 ppm (HCD) or 0.5 Dalton (CID) for peptide enrichment were performed essentially as described (Kim fragment ions, with strict trypsin specificity, and allowing up to two et al, 2006; Weinert et al, 2013a). Immuno-enriched peptides were missed cleavage sites. Cysteine carbamidomethylation was searched as a fixed modification, whereas N-acetyl protein and oxidized eluted from anti-acetyllysine antibody resin using acidified H O [0.2% trifluoroacetic acid (TFA)]. Peptide eluates were loaded methionine were searched as variable modifications. Where appro- directly onto a strong cation exchange (SCX) microtip column pre- priate, acetyllysine was added as a variable modification. pared as described (Rappsilber et al, 2007; Wisniewski et al, 2009). Acetyl-CoA assay Peptide eluates were briefly evaporated to remove acetonitrile and then loaded onto C18 stage-tips as described (Rappsilber et al, 2007). Proteome measurements were made by fractionation of total Frozen yeast pellets (~100 OD nm) were deproteinized in 400 ll peptides by the SCX microcolumn method and analyzed by mass 1 N perchloric acid (PCA) containing 13C2 acetyl-CoA as an internal standard (ISTD), mixed with 200 ll 0.4 mm acid washed glass- spectrometry. beads and vortexed for 2 min at 4°C. Homogenates were centrifuged Quantitative mass spectrometric analysis for 10 min, 10 000 g at 4°C. Supernatant (200 ll) was neutralized by adding repeated aliquots (10 ll) of 3 M KHCO3 under constant We used stable isotope labeling with amino acids in cell culture vortexing, until bubble evolution ceases (90 ll in total). KClO4 was (SILAC; Ong et al, 2002), to measure changes in protein, lysine acet- pelleted by centrifugation for 5 min, 10 000 g at 4°C. Acetyl-CoA ylation, and phosphorylation abundance. Peptide fractions were from the supernatant was measured as described previously, using analyzed by online nanoflow LC-MS/MS using a Proxeon easy nLC ISTD for calibration (Magnes et al, 2008). Results were normalized system (ThermoFisher Scientific) connected to an LTQ Orbitrap to OD 600 nm measured after extraction. Velos (ThermoFisher Scientific) or Q-Exactive (ThermoFisher Scientific) mass spectrometer. The LTQ Orbitrap Velos instrument AQUA analysis was operated under Xcalibur 2.1 (ThermoFisher Scientific) with the LTQ Orbitrap Tune Plus Developers Kit version 2.6.0.1042 software Yeast strains expressing GFP-tagged Pgk1 and Fas2 at endogenous in the data dependent mode to automatically switch between MS levels from the chromosomal locus (Huh et al, 2003) were and MS/MS acquisition as described (Weinert et al, 2011). The obtained from Life Technologies. Protein extracts were prepared Q-Exactive was operated using Xcalibur 2.2 (ThermoFisher Scientific) exactly as above when treating whole cell lysate with AcP. After in the data dependent mode to automatically switch between MS and treatment with AcP (or mock-treatment) the GFP-tagged proteins MS/MS acquisition as described (Michalski et al, 2011; Kelstrup et al, were enriched using GFP-trap affinity resin (ChromoTek, Martinsried, Molecular Systems Biology 10: 716 | 2014 © 2014 The Authors 10 Brian T. Weinert et al Acetylation dynamics and stoichiometry Molecular Systems Biology Germany) and the proteins eluted by boiling in 2x tris glycine Albaugh BN, Arnold KM, Denu JM (2011a) KAT(ching) metabolism by the tail: insight into the links between lysine acetyltransferases and metabolism. sample buffer (Life Technologies). Proteins were resolved on pre- ChemBioChem 12: 290 – 298 cast tris glycine gels (Life Technologies) and peptides recovered by standard in-gel digestion (Shevchenko et al, 1996). Heavy-labeled Albaugh BN, Arnold KM, Lee S, Denu JM (2011b) Autoacetylation of the AQUA peptide standards (AQUA quant pro; ThermoFisher Scien- histone acetyltransferase Rtt109. J Biol Chem 286: 24694 – 24701 Babiarz JE, Halley JE, Rine J (2006) Telomeric heterochromatin boundaries tific) were mixed with Pgk1 and Fas2 peptides at the indicated require NuA4-dependent acetylation of histone variant H2A.Z in concentrations and analyzed by MS. Untreated protein was ana- lyzed in four independent experiments and AcP-treated protein in Saccharomyces cerevisiae. Genes Dev 20: 700 – 710 two independent experiments, all with comparable results. Cai L, Sutter BM, Li B, Tu BP (2011) Acetyl-CoA induces cell growth and proliferation by promoting the acetylation of histones at growth genes. Mol Cell 42: 426 – 437 Data analysis Chen Y, Zhao W, Yang JS, Cheng Z, Luo H, Lu Z, Tan M, Gu W, Zhao Y (2012) Quantitative acetylome analysis reveals the roles of SIRT1 in regulating Gene Ontology (GO) association and enrichment analysis was diverse substrates and cellular pathways. Mol Cell Proteomics 11: performed using the Database for Annotation, Visualization and 1048 – 1062 Integrated Discovery (DAVID) v6.7 (da Huang et al, 2009). Statisti- cal tests were performed using R (http://www.r-project.org/ Cherry JM, Hong EL, Amundsen C, Balakrishnan R, Binkley G, Chan ET, Christie KR, Costanzo MC, Dwight SS, Engel SR, Fisk DG, Hirschman JE, index.html). Box plots were generated using Sparklines for Excel Hitz BC, Karra K, Krieger CJ, Miyasato SR, Nash RS, Park J, Skrzypek MS, (http://sparklines-excel.blogspot.com/). The detection limit for nat- Simison M et al (2012) Saccharomyces Genome Database: the genomics urally occurring acetylated peptides used to calculate minimum increased acetylation in Fig 5G was determined by ranking the resource of budding yeast. Nucleic Acids Res 40: D700 – D705 Choudhary C, Kumar C, Gnad F, Nielsen ML, Rehman M, Walther TC, Olsen observed “heavy” labeled peptides by peptide intensity and calcu- JV, Mann M (2009) Lysine acetylation targets protein complexes and lating the median intensity of the bottom 10%. This intensity value was an order of magnitude higher than the least intense “heavy” co-regulates major cellular functions. Science 325: 834 – 840 peptide observed in our experiments, thus the estimates of Cox J, Neuhauser N, Michalski A, Scheltema RA, Olsen JV, Mann M (2011) Andromeda: a peptide search engine integrated into the MaxQuant increased acetylation based on this detection limit are conserva- environment. J Proteome Res 10: 1794 – 1805 tive. Garland PB, Shepherd D, Yates DW (1965) Steady-state concentrations of Supplementary information for this article is available online: coenzyme A, acetyl-coenzyme A and long-chain fatty acyl-coenzyme A in http://msb.embopress.org rat-liver mitochondria oxidizing palmitate. Biochem J 97: 587 – 594 Gerber SA, Rush J, Stemman O, Kirschner MW, Gygi SP (2003) Absolute quantification of proteins and phosphoproteins from cell lysates by Acknowledgements tandem MS. Proc Natl Acad Sci USA 100: 6940 – 6945 We thank the members of the department of proteomics at CPR for their help- Guan KL, Xiong Y (2010) Regulation of intermediary metabolism by protein ful discussions. We thank the PRIDE team for helping make our data accessible acetylation. Trends Biochem Sci 36: 108 – 116 to everybody. This work is supported by the European Commission’s 7th Guan KL, Yu W, Lin Y, Xiong Y, Zhao S (2010) Generation of acetyllysine antibodies Framework Program grants Proteomics Research Infrastructure Maximizing and affinity enrichment of acetylated peptides. Nat Protoc 5: 1583 – 1595 knowledge EXchange and access (XS) (INFRASTRUCTURESF7-2010-262067/ Hebert AS, Dittenhafer-Reed KE, Yu W, Bailey DJ, Selen ES, Boersma MD, PRIME-XS), and the Lundbeck Foundation (R48-A4649). SAW is supported by a Carson JJ, Tonelli M, Balloon AJ, Higbee AJ, Westphall MS, Pagliarini DJ, postdoctoral grant from The Danish Council for Independent Research (FSS: Prolla TA, Assadi-Porter F, Roy S, Denu JM, Coon JJ (2013) Calorie 10-085134). The Center for Protein Research is supported by a grant from the restriction and SIRT3 trigger global reprogramming of the mitochondrial Novo Nordisk Foundation. protein acetylome. 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Journal

Molecular Systems Biology – Springer Journals

Published: Jan 31, 2014

Keywords: acetylation; mass spectrometry; mitochondria; proteomics; stoichiometry

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