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Improved proteome and phosphoproteome analysis on a cation exchanger by a combined acid and salt gradient Jun Adachi, Kazunari Hashiguchi, Maiko Nagano, Misako Sato, Ayako Sato, Kazuna Fukamizu, Yasushi Ishihama, and Takeshi Tomonaga Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.6b01232 • Publication Date (Web): 20 Jul 2016 Downloaded from http://pubs.acs.org on July 20, 2016

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Analytical Chemistry

Improved proteome and phosphoproteome analysis on a cation exchanger by a combined acid and salt gradient Jun Adachi,*,† Kazunari Hashiguchi,† Maiko Nagano, † Misako Sato, † Ayako Sato, † Kazuna Fukamizu, Yasushi Ishihama,‡ and Takeshi Tomonaga*,†

† †

Laboratory of Proteome Research, National Institute of Biomedical Innovation, Health and Nutrition, Ibaraki, Osaka, Japan Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan. Corresponding Author* J. A.: e-mail, [email protected], T. T., [email protected]; phone, +81 72 641 9820; fax, +81 72 641 9861 ‡

ABSTRACT: Currently used elution methods for strong cation exchange (SCX) chromatography are based on two principles: salt and pH gradient. In this paper, we report the first observation of peptide elution by acid gradient. The degree of peptide separation using C18-SCX StageTip was greatly improved by our acid and salt-based elution method compared with a salt-based elution method. This development enabled us to identify over 22,000 phosphopeptides from two milligrams of protein without laborintensive sample preparation. Our method is simple, robust, scalable, low-cost, and can be easily implemented without any special equipment or techniques. Peptide separation is an important part of bottom-up proteomics workflow because it determines the complexity of the sample and affects the sensitivity of the entire analysis.1 Multidimensional peptide separation is often used in proteomics. Multidimensional separations, which involve the use of two or more separation methods based on independent physical properties, can be used to increase the load capacity for analyzing low abundance or trace components in a peptide mixture.2 These extensive sample preparation and fractionation strategies have been employed for large-scale proteomics including human proteome mapping.3-5 However, these strategies lower the throughput of sample preparation and LC-MS/MS analysis. Thus, it is important to develop methodologies to improve both the depth and throughput of proteome analysis. Stop and go extraction tips (StageTips) have been developed for multidimensional fractionation as well as desalting, filtration, and concentration of peptides prior to mass spectrometry.6 StageTips enable enhancement of the throughput of peptide fractionation with high recovery rates. C18-SCX StageTips were recently used with 96 well plates to estimate the copy numbers of more than 9500 proteins in HeLa cells.7 However, large-scale phosphoproteome analysis using StageTip fractionation has not been reported. In this study, we developed a universal peptide fractionation method using C18-SCX StageTips. We applied our method to phosphoproteome analysis and proteome analysis and compared its peptide separation and identification capabilities with a standard salt-based fractionation method.

EXPERIMENTAL SECTION Sample preparation. HeLa-S3, DLD-1, and SNU-16 cells were cultured in IMEM supplemented with 10% (v/v) fetal bovine serum and penicillin/streptomycin (100 IU/ml) at 37 °C in 10% CO2. The cells were washed with PBS and lysed with lysis buffer (50 mM ammonium bicarbonate, 12 mM sodium deoxycolate, 12 mM sodium lauroyl-sarcosinate, complete protease inhibitor cocktail, and PhosSTOP phosphatase inhibitor cocktail (Roche Applied Science, Mannheim, Germany)). Lysates were incubated at 95 °C for 5 min followed by ultrasonication for 10 min using a Bioruptor sonicator (Cosmo Bio, Tokyo, Japan). 8 Lysed proteins were quan-

tified using a DC Protein Assay Kit (Bio-Rad, Hercules, CA, USA), reduced with 10 mM DTT, alkylated with 50 mM iodoacetamide, and sequentially, digested with 1:100 (w/w) trypsin (Roche Applied Science) for 16 h at 37 °C. Peptides were clarified by centrifugation for 10 min at 20,000 g and were desalted on an OASYS HLB cartridge (Waters, Milford, MA, USA). Immobilized metal affinity chromatography (IMAC) enrichment of phosphopeptides was performed as previously described.8 C18-SCX StageTip fractionation. C18-SCX StageTips were prepared according to the original protocol.6,9 StageTips with C18 and cation disks were packed into 200 µl tips using a stacked disk for each. Peptides or phosphopeptides were fractionated on C18-SCX StageTips. The elution buffer contained 0.5% TFA, 30% acetonitrile for fraction 1; 1.0% TFA, 30% acetonitrile for fraction 2; 2.0% TFA, 30% acetonitrile for fraction 3; 3.0% TFA, 30% acetonitrile for fraction 4; 3.0% TFA, 100 mM ammonium acetate, 30% acetonitrile for fraction 5; 4.0% TFA, 500 mM ammonium acetate, 30% acetonitrile for fraction 6; and 500 mM ammonium acetate, 30% acetonitrile for fraction 7, as described in Table S1. Elutes were directly collected in autosampler vials and dried using a SpeedVac centrifuge. LC-MS/MS measurements. LC-MS/MS was performed by coupling an UltiMate 3000 Nano LC system (Thermo Scientific, Bremen, Germany) and an HTC-PAL autosampler (CTC Analytics, Zwingen, Switzerland) to a Q Exactive hybrid quadrupole-Orbitrap mass spectrometer (Thermo Scientific). Peptides were delivered to an Acclaim PepMap RSLC NanoTrap Column (0.075 × 20 mm, Thermo Scientific) at a flow rate of 6 µL/min. After loading and washing, peptides were transferred to an analytical column (75 µm × 30 cm, packed in-house with ReproSil-Pur C18-AQ, 1.9 µm resin, Dr. Maisch, Ammerbuch, Germany) and separated at a flow rate of 280 nL/min using a 45-min or 145-min gradient from 5% to 30% of solvent B (solvent A, 0.1% FA and 2% acetonitrile; solvent B, 0.1% FA and 90% acetonitrile). The Q Exactive instrument was operated in the data-dependent mode. Survey full scan MS spectra (m/z 350 to 1800) were acquired in the Orbitrap with 70,000 resolution after accumulation of ions to a

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Figure 1. Stepwise peptide elution by TFA and ammonium acetate from C18-SCX StageTip. (A) Intensity-based distribution of non-redundant peptides across seven fractions eluted by a combination of TFA and ammonium acetate. (B) Distribution of the number of basic amino acid residues in the peptides. (C, D, E) Distribution of the number of acidic amino acid residues (C), theoretical PI (D), and GRAVY score (E) of identified peptides in each fraction.

3 × 106 target value. Dynamic exclusion was set to 10 s or 30 s.The 12 most intense multiplied charged ions (z ≥ 2) were sequentially accumulated to a 1 × 105 target value and fragmented in the collision cell by higher-energy collisional dissociation (HCD) with a maximum injection time of 120 ms and 35,000 resolution. Typical mass spectrometric conditions were as follows: spray voltage, 2 kV; heated capillary temperature, 250 °C; normalized HCD collision energy, 25%. The MS/MS ion selection threshold was set to 2.5 × 104 counts. A 3.0 Da isolation width was chosen. Peptide and protein identification and quantification. Raw MS data were processed by MaxQuant (version 1.3.0.5) supported by the Andromeda search engine for peak detection and quantification.10 The MS/MS spectra were searched against the UniProt human database with the following search parameters: full tryptic specificity, up to two missed cleavage sites, carbamidomethylation of cysteine residues set as a fixed modification, and N-terminal protein acetylation and methionine oxidation as variable modifications. For phosphoproteome analysis, phosphorylation of serine, threonine, and tyrosine was added for variable modification. The mass spectra were recalibrated using MaxQuant (first search 20 p.p.m. precursor tolerance) and subsequently re-searched with a mass tolerance of 6 p.p.m. The fragment ion mass tolerance was set to 20 p.p.m. Search results were filtered to a maximum false discovery rate (FDR) of 0.01 at the protein, peptide, and PTM-site levels. We required 2 or more unique/razor peptides for protein identification and a ratio count of 2 or more for protein quantification. PTM sites were considered to be fully localized when they were measured with a localization probability >0.75.

intensity-based distribution of the peptides was mapped across the seven fractions (Figure 1A). Figure 1B shows the basicity of the identified peptides in each fraction as represented by the number of basic residues (Lys, Arg, and His). The basicity showed a clear dependence on the order of the fractions. The theoretical PI values also showed this dependency (Figure 1D), whereas acidity, represented by the number of acidic residues (Asp and Glu), and hydrophobicity did not show the dependency (Figure 1C, 1E). These data suggest that the peptide elution by TFA gradient is affected by the positive charge of the peptides.

RESULTS AND DISCUSSION Peptide elution from C18-SCX StageTips by acid and salt gradient. Elution methods of SCX chromatography are based on two principles: salt and pH gradient. In this paper, we report the first elution of peptides by trifluoroacetic acid (TFA) gradient (Figure 1). Twenty micrograms of tryptic peptides from Hela-S3 cells were fractionated into seven fractions on C18-SCX StageTips. TFA concentration was increased from 0.5% (first fraction) to 3% (fourth fraction). We used TFA and ammonium acetate as the eluent in the last three fractions. In total, 87,160 non-redundant peptides were quantified, and the

Figure 2. Comparison of stepwise peptide elution by hydrochloric acid (HCl), formic acid (FA), TFA and TFA and ammonium acetate (AA). Twenty micrograms of tryptic peptides were fractionated into seven fractions. Each fraction was analyzed using 45min LC-gradient. The intensitybased distribution of non-redundant peptides across seven fractions eluted by hydrochloric acid or formic acid gradient is visualized.


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We attempted to elute peptides by hydrochloric acid gradient, formic acid gradient, and TFA gradient. As shown in Figure 2, peptides could be eluted by the hydrochloric acid gradient as well as by the TFA gradient; in contrast, formic acid showed a poor elution profile. The pH value range of the hydrochloric acid gradient was 1.34-0.08, that of TFA gradient was 1.360.37, and that of formic acid gradient 2.35-1.57. Therefore, our data suggests that the strength of the acid is an important factor in the elution of peptides from SCX disks. Furthermore, the combination of TFA and ammonium acetate gradient showed the best peptide identification among these elution methods. Next, we examined the reproducibility of the fractionation. We compared technical (MS) replicates and process (fractionation) replicates and found that the intensity distributions across seven fractions were very similar between these experiments (Figure S1). Furthermore, the correlation coefficients of peptide intensity between the technical replicates and process replicates are almost identical (Figure S2). This indicates that the process variance introduced by our fractionation is very low. Salt gradients are often used for peptide elution from SCXStageTips.9 We compared the acid-based fractionation and salt-based fractionation methods (Figure 3, Figure S3); 83,056 non-redundant peptides were quantified by acid-based fractionation, whereas 77,372 peptides were quantified by saltbased fractionation. As shown in Figure 3A, the intensity distribution and number of identified peptides across seven fractions were biased in fractions 1 and 2 in salt-based fractionation, whereas these fractions were not biased in acid-based fractionation. The distribution patterns of the peptide basicity were also different in the acid-based fractions compared to the salt-based fractions (Figure 3B). For example, peptides containing three basic residues were mainly eluted in fractions 5, 6, and 7 by acid-based fractionation, whereas these peptides were mainly eluted in fractions 2 to 7 by salt-based fractionation. These data indicate that the resolution of acid-based fractionation is superior to that of salt-based fractionation.

Figure 3. Comparison of stepwise peptide elution by acid-based gradient and salt-based gradient from C18-SCX StageTips. (A) A heat map indi-

cates the intensity-based distribution of tryptic peptides across seven fractions eluted by TFA-based gradient and ammonium acetate-based gradient. (B) Distributions of the number of basic amino acid residues in the peptides are compared between TFA-based elution and ammonium acetate-based elution.

Phosphopeptide fractionation by acid-based gradient from C18-SCX StageTips. Phosphoproteomics is a widespread method that has been successfully used for various dynamic signaling studies on a global scale. However, largescale phosphoproteomics studies (depth of >20,000 sites in a single experiment) usually require a large amount of samples and extensive fractionation by strong cation exchange chromatography, hydrophilic interaction chromatography, or basic reversed-phase chromatography, followed by phosphopeptide enrichment (Figure S4A). This complex workflow hampers scalability, robustness, and reproducibility. Thus, we attempted to simplify the workflow using our developed acid-based SCX fractionation method. As shown in Figure S4B, we designed a workflow in which phosphopeptide enrichment was performed before fractionation. This straightforward workflow can reduce sample numbers at the phosphopeptide enrichment step, thus dramatically enhancing the throughput of the total process of sample preparation.

Figure 4. Comparison of stepwise phosphopeptide elution by acid-based gradient and salt-based gradient from C18-SCX StageTips. (A) Intensitybased distribution of phosphopeptides across seven fractions eluted by TFA-based gradient and ammonium acetate-based gradient were visualized. (B) Comparison of the distributions of the number of basic amino acid residues in phosphopeptides between TFA-based elution and ammonium acetate-based elution. (C) Comparison of the identified number of phosphorylated serine, threonine, and tyrosine sites between TFA-based elution and ammonium acetate-based elution.


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Table 1. Number of identified distinct phosphopeptides fractionated by acid-based gradient.

At first, we compared the intensity-based peptide distribution across seven fractions resulting from acid- and salt-based fractionation of phosphopeptides (Figure 4A). Acid-based fractionation showed superior separation, whereas salt-based fractionation showed “smeared” separation. Acid-based fractionation showed a 34% increase in the number of quantified phosphopeptides compared with salt-based fractionation. We also found that the basicity of the phosphopeptide is dependent on the order of acid-based fractionation; however, it is not strongly dependent on the order of salt-based fractionation (Figure 4B). In terms of the identified phosphorylated amino acids, acid-based fractionation showed 25, 27, and 102% increases in the number of identified phosphorylated serine, threonine, and tyrosine sites compared with salt-based fractionation (Figure 4C). The distribution of multiphosphorylated peptides across the fractions was similar between these methods (Table S2). Next, we evaluated the performance of our “simple”phosphoproteome analysis in a large-scale analysis. As shown in Table 1, we identified ~24,000 distinct phosphopeptides in 21 h (3 h × 7 fractions) of MS measurements from two milligrams of protein. Furthermore, more than 28,000 phosphopeptides were identified in replicate experiments (Table 1, Figure S5). In terms of reproducibility, the correlation coefficients of the intensities of the peptides were greater than 0.89 in all fractions in replicate experiments (Figure S6). Low throughput is considered to be a drawback of phosphoproteome analysis. Typical large-scale phosphoproteome analysis employs a “prefractionation-enrichment” strategy (Figure S4). This strategy is effective in covering lowabundance key signaling molecules; however, the throughput and reproducibility of the workflow are decreased. The acidbased SCX fractionation method developed in this study enables enhanced throughput of sample preparation by employing an “enrichment-fractionation” approach; >22,000 phosphopeptides were identified in 21 h. Our method is very simple and addresses the “trade-off” problem between the throughput and depth of phosphoproteome analysis; therefore, this method contributes to the performance of deep, large-scale analysis without additional equipment or techniques and at no additional cost. Recently, high throughput approaches without peptide fractionation (one-shot approach) have been reported.11,12 Especially, the EasyPhos platform developed by Mann’s group enabled the quantification of >10,000 sites by single-run MS measurement. The EasyPhos platform also uses StageTips; thus, our fractionation method and the EasyPhos platform are complementary. The combination of these technologies is expected to enable deep proteome analysis with simpler preparation steps without sacrificing throughput. Furthermore, acid-based SCX separation on StageTips is expected to contribute to various types of proteome analysis, including other modification analyses13 such as ubiquitination and acety-

lation analysis or exsome protein analysis, which require high recovery rates due to limited sample amounts.

CONCLUSION In this study, we developed an acid-based SCX fractionation method using StageTips. Compared with a typical salt-based fractionation method, acid-based fractionation showed superior separation performance, which resulted in a 34% increase in distinct phosphopeptide identification. Furthermore, this method enables large-scale phosphopeptide quantitation (>20,000 sites) using an “enrichment-fractionation” approach (enrichment of phosphopeptides first, followed by peptide fractionation). These characteristics of our method addressed the “trade-off” problem between throughput and depth of phosphoproteome analysis. Acid-based SCX fractionation is robust, scalable, low-cost, MS-friendly, and can be easily implemented without any special equipment or techniques. Thus, our fractionation method has the potential to be applied to other fields where SCX chromatography is used.

AUTHOR INFORMATION Corresponding Author * Address: 7-6-8 Saito-Asagi, Ibaraki, Osaka 567-0085, Japan. TEL: +81 72 641 9820. Fax: +81 72 641 9861. E-mail: [email protected], [email protected]

ACKNOWLEDGMENT This work was supported by Grants-in-Aid, Research on Development of New Drugs 16ak0101011h0005 to Y.Y. from the Ministry of Health, Labour, and Welfare of Japan and Japan Agency for Medical Research and Development. This work was supported by Grants-in-Aid 26640098 to J.A. from the Ministry of Education, Science, Sports, and Culture of Japan.

ASSOCIATED CONTENT Supporting Information Supporting Information Available: Figure S1. Reproducibility of stepwise peptide elution from C18-SCX StageTips. Figure S2. Scatter plot of peptide intensities. Figure S3. Reproducibility of protein and peptide identifications. Figure S4. Workflows of the conventional phosphoproteomics and “simple” phosphoproteomics developed in this study. Figure S5. Reproducibility of phosphopeptide identification by our “simple” phosphoproteome analysis method. Figure S6. Scatter plot of phosphopeptide intensities depicting the reproducibility across fractionation replicates of TFA-based SCX fractions. Table S1. Composition of buffers used for fractionation on C18-SCX StageTips. Table S2. Comparison of the degree of phosphorylation in each fraction between acid-based fractionation and salt-based fractionation. This material is available free of charge via the Internet at http://pubs.acs.org.

REFERENCES


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(1) Altelaar, A. F.; Heck, A. J. Curr Opin Chem Biol 2012, 16, 206-213. (2) Link, A. J.; Eng, J.; Schieltz, D. M.; Carmack, E.; Mize, G. J.; Morris, D. R.; Garvik, B. M.; Yates, J. R., 3rd. Nat Biotechnol 1999, 17, 676-682. (3) Kim, M. S.; Pinto, S. M.; Getnet, D.; Nirujogi, R. S.; Manda, S. S.; Chaerkady, R.; Madugundu, A. K.; Kelkar, D. S.; Isserlin, R.; Jain, S.; Thomas, J. K.; Muthusamy, B.; Leal-Rojas, P.; Kumar, P.; Sahasrabuddhe, N. A.; Balakrishnan, L.; Advani, J.; George, B.; Renuse, S.; Selvan, L. D.; Patil, A. H.; Nanjappa, V.; Radhakrishnan, A.; Prasad, S.; Subbannayya, T.; Raju, R.; Kumar, M.; Sreenivasamurthy, S. K.; Marimuthu, A.; Sathe, G. J.; Chavan, S.; Datta, K. K.; Subbannayya, Y.; Sahu, A.; Yelamanchi, S. D.; Jayaram, S.; Rajagopalan, P.; Sharma, J.; Murthy, K. R.; Syed, N.; Goel, R.; Khan, A. A.; Ahmad, S.; Dey, G.; Mudgal, K.; Chatterjee, A.; Huang, T. C.; Zhong, J.; Wu, X.; Shaw, P. G.; Freed, D.; Zahari, M. S.; Mukherjee, K. K.; Shankar, S.; Mahadevan, A.; Lam, H.; Mitchell, C. J.; Shankar, S. K.; Satishchandra, P.; Schroeder, J. T.; Sirdeshmukh, R.; Maitra, A.; Leach, S. D.; Drake, C. G.; Halushka, M. K.; Prasad, T. S.; Hruban, R. H.; Kerr, C. L.; Bader, G. D.; Iacobuzio-Donahue, C. A.; Gowda, H.; Pandey, A. Nature 2014, 509, 575-581. (4) Wilhelm, M.; Schlegl, J.; Hahne, H.; Moghaddas Gholami, A.; Lieberenz, M.; Savitski, M. M.; Ziegler, E.; Butzmann, L.; Gessulat, S.; Marx, H.; Mathieson, T.; Lemeer, S.; Schnatbaum, K.; Reimer, U.; Wenschuh, H.; Mollenhauer, M.; SlottaHuspenina, J.; Boese, J. H.; Bantscheff, M.; Gerstmair, A.; Faerber, F.; Kuster, B. Nature 2014, 509, 582-587. (5) Huttlin, E. L.; Jedrychowski, M. P.; Elias, J. E.; Goswami, T.; Rad, R.; Beausoleil, S. A.; Villen, J.; Haas, W.; Sowa, M. E.; Gygi, S. P. Cell 2010, 143, 1174-1189. (6) Ishihama, Y.; Rappsilber, J.; Mann, M. J Proteome Res 2006, 5, 988-994. (7) Kulak, N. A.; Pichler, G.; Paron, I.; Nagaraj, N.; Mann, M. Nat Methods 2014, 11, 319-324. (8) Narumi, R.; Murakami, T.; Kuga, T.; Adachi, J.; Shiromizu, T.; Muraoka, S.; Kume, H.; Kodera, Y.; Matsumoto, M.; Nakayama, K.; Miyamoto, Y.; Ishitobi, M.; Inaji, H.; Kato, K.; Tomonaga, T. J Proteome Res 2012, 11, 5311-5322. (9) Rappsilber, J.; Mann, M.; Ishihama, Y. Nat Protoc 2007, 2, 1896-1906. (10) Cox, J.; Mann, M. Nat Biotechnol 2008, 26, 1367-1372. (11) de Graaf, E. L.; Giansanti, P.; Altelaar, A. F.; Heck, A. J. Mol Cell Proteomics 2014, 13, 2426-2434. (12) Humphrey, S. J.; Azimifar, S. B.; Mann, M. Nat Biotechnol 2015, 33, 990-995. (13) Mertins, P.; Qiao, J. W.; Patel, J.; Udeshi, N. D.; Clauser, K. R.; Mani, D. R.; Burgess, M. W.; Gillette, M. A.; Jaffe, J. D.; Carr, S. A. Nat Methods 2013, 10, 634-637.


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Estimated model In this study

Elution by salt (KCl)

Trap

Elution by high-pH

Elution by strong acid (TFA)

Positively charged molecules K+

H+

Negatively charged beads Cl-

CF3COO-

Neutral or negatively charged molecules


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Improved Proteome and Phosphoproteome ... - ACS Publications

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