In Vivo Termini Amino Acid Labeling for Quantitative Proteomics

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In Vivo Termini Amino Acid Labeling for Quantitative Proteomics Ai-Ying Nie,† Lei Zhang,† Guo-Quan Yan,† Jun Yao,† Yang Zhang,† Hao-Jie Lu,*,† Peng-Yuan Yang,† and Fu-Chu He†,‡ † ‡

Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 102206, China

bS Supporting Information ABSTRACT: Quantitative proteomics is one of the research hotspots in the proteomics field and presently maturing rapidly into an important branch. The two most typical quantitative methods, stable isotope labeling with amino acids in cell culture (SILAC) and isobaric tags for relative and absolute quantification (iTRAQ), have been widely and effectively applied in solving various biological and medical problems. Here, we describe a novel quantitative strategy, termed “IVTAL”, for in vivo termini amino acid labeling, which combines some advantages of the two methods above. The core of this strategy is a set of heavy amino acid 13C6-arginine and 13C6-lysine and specific endoproteinase Lys-N and Arg-C that yield some labeled isobaric peptides by cell culture and enzymatic digestion, which are indistinguishable in the MS scan but exhibit multiple MS/MS reporter b, y ion pairs in a full mass range that support quantitation. Relative quantification of cell states can be achieved by calculating the intensity ratio of the corresponding reporter b, y ions in the MS/MS scan. The experimental analysis for various proportions of mixed HeLa cell samples indicated that the novel strategy showed an abundance of reliable quantitative information, a high sensitivity, and a good dynamic range of nearly 2 orders of magnitude. IVTAL, as a highly accurate and reliable quantitative proteomic approach, is expected to be compatible with any cell culture system and to be especially effective for the analysis of multiple post-translational modificational sites in one peptide.

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uantitation, as a rapidly advancing branch of proteomics, has its origin in the technology of two-dimensional polyacrylamide gel electrophoresis (2D PAGE) invented more than 2 decades ago,1,2 in which quantitation was achieved by recording differences in the staining pattern of proteins derived from two states of cell populations or tissues.3,4 Recently, some mass spectrometric methods based on stable isotope quantitation have been established5 10 and have substantially shown great promise for the simultaneous and automated identification and quantitation of complex protein mixtures.11,12 These methods have been applied in the temporal dynamics of signaling pathways,13,14 identification of cancer biomarkers,15,16 and study of protein post-translational modifications.17,18 The established methods, based on how peptides are labeled and quantified, can be classified into two broad classes, mass-difference and isobaric tags.19 Mass-difference methods, such as proteolytic oxygen-18 labeling,8,17 chemical derivatization labeling,9,16 and stable isotope labeling with amino acid in cell culture (SILAC)/amino acid coded mass tagging (AACT),6,10,11 depend on the ratio of intensity or area of light/heavy parent ions in MS scan. Generally, proteolytic oxygen-18 labeling and chemical derivatization labeling tend to give low resolution due to the low efficiency of chemical reaction and the introduction of side reactions. Compared to the former, SILAC is considered to be the most accurate quantification method today due to its nearly complete incorporation of heavy amino acids and sample mixing at the initial steps to minimize differential effects for sample handling. Since a number of multiplexing sets are used, any mass-difference based r 2011 American Chemical Society

method will make the number of peaks in MS scan at least doubled and further aggravate already difficult issues related to sampling of peptides for identification. Isobaric tags methods, by contrast, can overcome the shortcomings faced by massdifference methods. The reason is that these methods can present a higher signal sensitivity due to no precursor mass splitting in MS scan and provide a great deal of quantitative information by some unique reporter ions, such as the reporter group (113 119,121 Da) in isobaric tags for relative and absolute quantification (iTRAQ)7,12 and the reporter group (126 131 Da) in tandem mass tag (TMT)20,21 in the low mass range of the tandem mass spectrometry (MS/MS) scan. Nevertheless, the suppression effect on low-mass reporter ions substantially reduces the accuracy of isobaric tags methods especially in the analysis of highly complex biological samples.22 Besides, the variability in labeling efficiencies also limits the effectiveness of these methods. Presently, there is an emerging consensus that new methods should be established to overcome some drawbacks expressed by mass-difference and isobaric tags methods. A great deal of effort has been devoted to exploring these new methods, and great progress has been made in the past decade. For example, the isobaric peptide termini labeling (IPTL),19 in which after endoproteinase Lys-C digestion, peptides were labeled at C-terminal lysine residues with either 2-methoxy-4,5-dihydro-1H-imidazole Received: April 22, 2011 Accepted: June 21, 2011 Published: June 21, 2011 6026

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Analytical Chemistry (MDHI) or with tetradeuterated MDHI-d4 and subsequently their N-termini were derivatized either with tetradeuterated succinic anhydride (SA-d4) or with SA, gave rise to the isobaric mass in the MS scan but fragment pairs with 4 Da difference in the MS/MS scan. However, IPTL only offered a semiquantitative evaluation of IPTL data by mascot scores. Superior to the IPTL method, a novel proteomics approach, termed index-ion triggered MS2 ion quantification (iMSTIQ),23 has been reported for a targeted quantitative proteomics, providing exact quantitation by comparing the relative intensities of multiple pairs of fragment ions derived from isobaric targeted peptides during MS2 analysis. However, both of these two methods had some obvious drawbacks such as tedious steps of chemical derivatization and possible side reactions. Another new method, named “isobaric SILAC with immonium ion splitting”, has also been reported.24 In this method the peptides from two cell states were labeled with either 13C on the carbonyl (C-1) carbon or 15N on the backbone nitrogen. As a result, labeled peptides had the same nominal mass and nearly identical MS/MS spectra but generated some specific reporting immonium ions separated by 1 Da in the low mass range for relative quantification of the parent proteins. This method shared the advantages of classic SILAC such as concision, convenience, and accuracy, whereas the suppression effect of background interference in the low mass range on immonium ions was notable and inevitable. To develop MS-based quantitative methods with high resolution and reliability and solve increasing complexity caused by the multiplexed set used in the MS scan and the suppression effect brought by background interference in the MS/MS scan, we described a novel quantitative strategy, termed “IVTAL”, for in vivo termini amino acid labeling. The core of this strategy is a set of heavy amino acid 13C6-arginine (13C6-Arg) and 13C6-lysine (13C6-Lys) and specific endoproteinase Lys-N and Arg-C that yield some labeled isobaric peptides by cell culture and enzymatic digestion, which are indistinguishable in the MS scan but exhibit multiple MS/MS reporter b, y ion pairs in the full mass range that support quantitation. Relative quantification of cell states can be achieved by calculating the intensity ratio of the corresponding reporter b, y ions in the MS/MS scan. The strategy is compatible with virtually all cell culture conditions, including primary cells. Furthermore, the strategy showed high resolution and reliability and was also convenient and inexpensive. To validate the effectiveness of this strategy, we applied IVTAL to various proportions of mixed samples of two labeled HeLa cell lines. One labeled HeLa cell line was grown in the media lacking essential amino acid arginine and lysine but supplemented by heavy amino acid 13C6-Arg and normal amino acid lysine; the other was grown in the media above supplemented by heavy amino acid 13C6-Lys and normal amino acid arginine.

’ MATERIALS AND METHODS In Vivo Termini Amino Acid Labeling. HeLa cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM, US Biological) depleted of arginine and lysine. The DMEM was supplemented with 10% dialyzed fetal bovine serum, 100 units/mL penicillin, and streptomycin. Cells were grown in media containing normal arginine (Sigma, A6969) and heavy lysine (13C6-Lys, Cambridge Isotope Laboratories, CLM-2247) and containing normal lysine (Sigma, L8662) and heavy arginine (13C6-Arg, Cambridge Isotope Laboratories, CLM-2265) with a

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final concentration of 84 μg/mL for arginine and 146 μg/mL for lysine, respectively. Additionally, in order to prevent arginine from conversing proline, normal L-proline (Sigma, P5607) was supplemented to the media with a final concentration of 200 μg/mL.25 Cells were tested for full incorporation of the label after six passages. Protein Extraction and Digestion. Collected cells were washed twice with phosphate-buffered saline (PBS) to remove serum proteins and then lysed in a buffer containing 7 M urea, 2 M thiourea, 1 mM phenylmethanesulfonyl fluoride (PMSF), 50 mM dithiothreitol (DTT), and phosphatase and protease inhibitors (Complete tablets; Roche Diagnostics). The lysate was sonicated for three cycles of 5 s each and centrifuged to collect the supernatant. Protein quantitation was performed using the Bradford protein assay, and the lysates were mixed in protein concentration ratios of 1:1, 1:5, 5:1, and 1:10. The protein mixtures were reduced by DTT with a final concentration of 10 mM in 25 mM ammonium bicarbonate (ABC) solution at 37 °C for 1 h, then alkylated by iodoacetamide (IAA) with a final concentration of 55 mM in 25 mM ABC solution at room temperature for 45 min in dark conditions, and finally precipitated overnight by ice acetone. After centrifugation, the deposited proteins were digested overnight with metalloendoproteinase Lys-N at a substrate/enzyme ratio of 85:1 (w/w) in 25 mM ABC, pH 9.5 at 37 °C.26 The resulting peptides were lyophilized and subsequently digested by endoproteinase Arg-C at a substrate/ enzyme ratio of 200:1 (w/w) in 25 mM ABC, pH 7.6 at 37 °C for 18 h. The final peptides were dried in vacuum and resuspended in 10 mM KH2PO4 in 25% acetonitrile (ACN). 2D-SCX-LC MS/MS. The peptide mixtures were first separated by strong cation exchange (SCX) chromatography on an Agilent 1100 HPLC system using a PolySULFOETHYL A column (2.1 mm  100 mm, 5 μm, 200 Å, PolyLC) with a gradient of pure buffer A (10 mM KH2PO4 in 25% ACN) in 5 min, 0 25% buffer B (350 mM KCl, 10 mM KH2PO4 in 25% ACN) in 55 min, 25 100% buffer B in 5 min, 100% buffer B in 5 min, and 100 0% buffer B in 5 min at a flow rate of 200 μL/min and detected at 214 nm. As a result, 28 fractions of peptide mixtures were collected, thoroughly dried using a vacuum centrifuge, resuspended with 5% ACN in 0.1% formic acid (FA) and separated by nano LC, and analyzed by online electrospray tandem mass spectrometry. The experiments were performed on a nano ACQUITY UPLC system (Waters Corporation, Milford) connected to an LTQ-Orbitrap XL mass spectrometer (Thermo Electron Corp., Bremen, Germany) equipped with an online nanoelectrospray ion source (Michrom Bioresources, Auburn). The separation of the peptides was performed in a Captrap Peptide column and a 100 μm i.d.  15 cm reverse phase column (Michrom Bioresources, Auburn). The peptide mixtures were injected onto the trap-column with a flow of 20 μL/min for 5 min and subsequently eluted with a three-step linear gradient, starting from 5% B to 45% B in 90 min (A, water with 0.1% FA; B, ACN with 0.1% FA), then increasing to 80% B in 5 min, and finally hold on 80% B for 5 min. The column was re-equilibrated at initial conditions for 15 min. The column flow rate was maintained at 500 nL/min and column temperature was maintained at 35 °C. The electrospray voltage of 2.0 kV versus the inlet of the mass spectrometer was used. The LTQ-Orbitrap XL mass spectrometer was operated in the data-dependent mode to switch automatically between MS and MS/MS acquisition. Full MS scan with two microscans (m/z 400 1600) was acquired in the Orbitrap with a mass resolution 6027

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Analytical Chemistry of 60 000 at m/z 400, followed by eight sequential LTQ-MS/MS scans. Dynamic exclusion was used with two repeat counts, 10 s repeat duration, and 90 s exclusion duration. For MS/MS, precursor ions were activated using 35% normalized collision energy at the default activation q of 0.25. Three replicates for technical reproducibility were processed. Protein Identification and Quantification. All MS/MS spectra were searched using SEQUEST [v.28 (revision 12), Thermo Electron Corp.], which is the database search engine for peptide identifications against the human UniProt database (release 2010-04 with 20 331 entries). The searching parameters were set up as follows: Although the enzymes used for Lys-N cleavage before lysine and Arg-C cleavage after arginine cannot be selected simultaneously in the SEQUEST, the peptides produced by the two enzymes could be included in peptides produced by the partial cleavage of Arg-C or Lys-N. Therefore, here partial Arg-C cleavage with two missed cleavages was set up; oxidation of methionine was set up as variable modification; carbamidomethylation of cystein and +6.0201 Da for lysine or arginine were set as two fixed modifications; the peptide mass tolerance was 25 ppm, and the fragment ion tolerance was 1 Da. Trans Proteomic Pipeline software (revision 4.2) (Institute of Systems Biology, Seattle, WA) was then utilized to identify proteins based upon the Peptide Prophet probability27 with a p-value over 0.90 and the Protein Prophet probability28 with a p-value over 0.95. False discovery rate (FDR) was limited to less than 1%.Two sets above were combined together to identify the peptides and proteins, considering that the score of peptide identified and FDR could be affected if only one set was used in identification. To obtain protein quantitative information, some in-house built scripts edited by Perl (version 5.10) and MatLab (version 7.10) were used to extract the intensity values of the b, y ions of identified peptides from the DTA files generated by SEQUEST with a tolerance of 6 Da for +1 charged fragments, 3 Da for +2 charged fragments. Moreover, only the peptides including more than six pairs of b, y ions were quantified and the outlier datapoints of the ratios of b, y ion pairs were removed using the commonly used statistic method of the box plot. These quantified peptides above were grouped into proteins and then statistically analyzed to get the mean, standard deviation, and coefficient of variance of the quantified proteins.

’ RESULTS AND DISCUSSION In Vivo Termini Amino Acid Labeling Strategy. In vivo termini amino acid labeling strategy is a comprehensive method holding the strengths of SILAC and isobaric tags. To put this novel strategy into effect, two necessary requirements must be satisfied. One is two kinds of heavy amino acids; furthermore, the heavy amino acids to be used must satisfy some conditions as follows: essential amino acids, the same mass increase in labeled peptides, relative high abundance in human protein compositions, and easy availability; the other is the corresponding enzymes, easily available, and able to give rise to isobaric peptides in MS scan after cutting the C-termini and the N-termini of the heavy amino acids mentioned above, respectively. The abundance, heavy forms, and mass increase of some essential amino acids commercially available are shown in Table S-1 in the Supporting Information. According to the first requirement, lysine and arginine with a mass difference of 4 or 17 Da, leucine and isoleucine with a mass difference of 7 Da, and any two of the amino acid group

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Scheme 1. Schematic of In Vivo Termini Amino Acid Labeling Strategy a

a

Cell states A and B were, respectively, grown in media supplemented by C6-lysine and 13C6-arginine, mixed, digested by endoproteinase Lys-N and Arg-C, and produced some isobaric and mass-difference peptides in MS scan. These isobaric peptides were indistinguishable in the MS scan but exhibited multiple MS/MS reporter b, y ion pairs in a full mass range that support quantitation. Relative quantification of the two states was achieved at the MS/MS level using the b, y ion pairs with a mass difference of 6 Da. These mass-difference peptides in the MS scan provided some complementary quantitative information as shown with the dotted line. 13

(leucine, valine, lysine, and arginine) with a mass difference of 6 Da can be the candidates. Taking the second requirement into consideration, only heavy lysine and arginine with a mass difference of 4, 6, and 17 Da are qualified. In addition, compared to the abundances of other essential amino acids, lysine and arginine have a relative high abundance of 5.73% and 5.64%, respectively. Currently, the cutting of N-termini of arginine is not available due to the lack of the corresponding enzyme although the cutting of the C-termini of lysine29,30 can be achieved, while both C-termini of arginine and N-termini of lysine can be cut by endoproteinase Arg-C30,31 and metalloendopeptidase Lys-N.26,32 Therefore, endoproteinase Arg-C and metalloendopeptidase Lys-N were selected as the corresponding enzymes for heavy lysine and arginine. Here, take the 13C6-lysine and 13 C6-arginine, for example, in our study. In order to predict the protein quantification coverage of Arg-C and Lys-N digest in the human UniProt database, homemade software was used on the condition that unique peptides had more than five amino acids and 93% of the total proteins could be quantified by mass spectrometry. The workflow of IVTAL is shown in Scheme 1. First, cell state A and cell state B were, respectively, adapted in media with 13C6lysine and media with 13C6-arginine for a sufficient time to obtain a near complete (98% or more) protein labeling, then harvested, and lysed. The extract of the two cell states was mixed at the very beginning of the experiment before processing the steps of fractions and enrichments. The protein mixtures were digested by endoproteinase Lys-N and Arg-C, which produced some isobaric peptides that consisted of peptides with 13C6-Lys at 6028

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Analytical Chemistry

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Figure 1. MS profile of the HeLa cell mixture with a ratio of 1:1 (A) and MS/MS profile of the precursor (m/z = 664.89, z = 2) (B). These pairs of b, y ions in part B were assigned to the peptide of K*IDIIPNPQER (K* = 13C6-lysine) and KIDIIPNPQER# (R# = 13C6-arginine), and by the calculation, the mean of the intensity ratios of the b, y ion pairs is 1.09 (B).

the N-termini and normal arginine at the C-termini from state A and the peptides with normal lysine at the N-termini and 13C6Arg at the C-termini from state B. These produced isobaric peptides had identical physicochemical properties and were indistinguishable in the chromatogram and thus exhibited some single masses in the MS scan but yield b, y ion pairs with a mass

difference of 6 Da for quantitation by their intensity ratios in the MS/MS scan. Compared to the quantitation by a single specific reporter ion for one peptide in the low mass range in isobaric tags such as iTRAQ and TMT and by a single peak intensity for one peptide in mass-difference methods such as SILAC and ICAT (isotope-coded affinity tags), the quantitation in IVTAL was 6029

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Analytical Chemistry achieved by multiple b, y ion pairs in full mass range. Therefore, IVTAL has a more accurate and reliable quantitation superior to isobaric tags and mass-difference methods. Another significant advantage was that quantitation was simultaneous to the protein identification. Additionally, some labeled peptides with a mass

Figure 2. Calculated intensity ratios of five different peptides from HeLa cell samples with various protein concentration proportions by IVTAL.

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difference of 6 Da in MS scan, as a supplement, provided more quantitative information. Here, quantitation was decided by the intensity ratio of the b ions of the peak pairs with lower masses derived from protein state B and the higher masses from protein state A and vice versa for the y-ions. Identification of In Vivo Termini Amino Acid Labeled HeLa Cells. The result of database searching was that 2 381 proteins and 13 518 peptides were identified when +6.0201 Da for lysine was set as a fixed modification and 1 926 proteins and 11 166 peptides were identified when +6.0201 Da for arginine was set as a fixed modification. With the combination of the above two search results, 5 644 nonredundant peptides and 1 434 nonredundant proteins were identified after canceling repeated entries (Supporting Information, Excel spreadsheet). Three types of peptides can be obtained after Lys-N and Arg-C digestion in our method. A total of 35.33% of the nonredundant peptides were the first type of peptides both starting with lysine and ending with arginine that were the key components to establish IVTAL, 32.71% of the nonredundant peptides were the second type of peptides either starting with lysine or ending with arginine that were able to provide classic SILAC quantitative information based on the occurring pairs of precursors in the MS scan, and 31.95% of the nonredundant peptides were the last type of peptides neither starting with lysine nor ending with arginine that were only used for protein identification. Quantification of In Vivo Termini Amino Acid Labeled HeLa Cells. After identification of proteins and peptides, the

Figure 3. MS/MS spectra of the peptide K*AEAGAGSATEFQFR (K* = 13C6-lysine) and KAEAGAGSATEFQFR# (R# = 13C6-arginine) with the ratio of 1:1, 1:5, and 1:10. 6030

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Table 1. Number of Quantified Proteins and Peptides, Mean, Standard Deviation, and Coefficient of Variance of the Quantified Protein and the Number of Identified Proteins and Peptides for the Samples with a Ratio of 1:1 in Three Runs number of quantified

number of quantified

standard

coefficient of

number of identified

number of identified

run no.

proteins

peptides

mean

deviation

variance

proteins

peptides

1 2

886 732

1483 1146

1.0758 1.0751

0.2088 0.1913

0.1941 0.1779

1860 1675

4626 3874

3

870

1416

1.0685

0.2077

0.1944

1704

4128

Figure 4. The logarithmic diagram of the calculated mean for quantified proteins by fragment pairs in MS/MS and peptides with mass differences in the MS scan.

intensity values of pairs of b, y ions of the first type of peptides were extracted from the SEQUEST.dat files with an in-house built peak matching script with more than six pairs of b, y ions used for quantifying of each peptide. Subsequently, the peptides above were associated with the corresponding identified proteins using an in-house programmed script and the corresponding peptide ratios were averaged to arrive at protein level ratios. Figure 1A is a MS profile of the HeLa cell mixture with a ratio of 1:1. The precursor (m/z = 664.89, z = 2) with high signal intensity was selected to generate pairs of b, y ions in the MS/MS scan (Figure 1B). These pairs of b, y ions were assigned to the peptide of K*IDIIPNPQER (K* = 13C6-lysine) and KIDIIPNPQER# (R# = 13C6-arginine) after a SEQUEST search and can be used to quantify these two peptides by their intensity ratios. By the calculation, the mean of the intensity ratios of the b, y ion pairs, with a standard deviation of 0.2282, is 1.09 that is very close to the true value of 1.0, which can validate the accuracy of IVTAL. This can be ascribed to the use of multiple data points for one peptide. In order to further validate the dynamic range of IVAL, HeLa cell samples with proportions of 5:1, 1:5, and 1:10 were quantified. Figure 2 gives the intensity ratios of five different peptides from HeLa cell samples with different protein concentration ratios. In all cases the calculated intensity ratios of the b, y ion pairs fit well with the expected ratios although some deviations were observed in quantification with a higher fold (i.e., 10-fold). MS/MS spectra of the peptide of K*AEAGAGSATEFQFR (K* = 13C6-lysine) and KAEAGAGSATEFQFR# (R# = 13C6-arginine) with the ratio of 1:1, 1:5, and 1:10 were shown in Figure 3, presenting a good dynamic range across nearly 2 orders of magnitude and providing a reliable protein quantification. The corresponding number of proteins and peptides identified

and quantified were shown in Table S-2 in the Supporting Information. Furthermore, the reproducibility and reliability of this method were verified, and 1094 proteins were totally quantified by three replicated analyses of the samples with the ratio of 1:1. A percentage between 45% and 55% for the identified proteins could be fairly accurately quantified in each sample ratio, and some detailed results for the sample with a ratio of 1:1, including the number of quantified proteins and peptides, mean, standard deviation, coefficient of variance, and the number of identified protein and peptides, were shown in Table 1, from which we could easily notice that this new method provided high reproducibility and reliability in quantitative proteomics analysis. Quantification of Complementary Labeled Peptides. Except the quantitative results provided by the first type of peptides both starting with lysine and ending with arginine, the second type of peptides either starting with lysine or ending with arginine can also be used for quantification based on the observed pairs of precursors in MS scan similar to classic SILAC (Figure S-1 in the Supporting Information). The intensities of pairs of precursors in MS scan were also extracted by an in-house edited script and used to obtain the quantitative information of 868 proteins with a mean of 1.511, a standard deviation of 1.511, and a coefficient of variance of 1.000 without any screening with regard to the ratio of 1:1. As is shown in the logarithmic diagram (Figure 4), some ratios too large or too small would lead to some bigger deviations. After excluding proteins from quantification that were quantified with a single peptide, 297 proteins were quantified from the second type of peptides with a mean of 1.377, a standard deviation of 1.139, and a coefficient of variance of 0.827. All the above statistical parameters were much worse than IVTAL, which indicates that IVTAL has a better accuracy due to 6031

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Figure 5. MS/MS of the peptide K*SVTEQGAELSNEER (K* = 13C6-lysine) and KSVTEQGAELSNEER# (R# = 13C6-arginine) of the 14-3-3 protein, insets A and B are the enlarged views of b9+2 (468.62 and 465.93) with a mass difference of 3 Da and b9+1 (936.25 and 930.38) with a mass difference of 6 Da.

the use of multiple data points for one peptide. However, the information provided by the second type of peptides can play a complementary role in IVTAL. Other Useful Features of In Vivo Termini Amino Acid Labeling. The experimental analysis showed that the termini labeled peptides do not differ in retention time on reversed phase chromatography,19 ensuring accurate, reliable, and easy quantification from MS/MS spectra. Like iTRAQ and some other isobaric tags methods, in IVTAL the same precursors can avoid some repeated fragmentations of the labeled and unlabeled peptides and provide more information than the conventional mass-difference methods due to more unrepeated fragmentations, making a highly efficient mass spectrometry scanning and identification. Besides, all the kinds of mass spectrometries could be used without the limitation of ion trap occurring in the isobaric tags methods. From the view of identification, a unique and valuable advantage is that the differences in fragment masses would give additional specificity to the assignment of peptide sequence, especially for the fragments with multiple charges. Generally, it is hard to judge the fragments with multiple charges in low-resolution tandem mass spectra. However, in our method an important human protein of the 14-3-3 protein has been accurately and reliably identified by various fragments including b9+1 (936.25 and 930.38) with a mass difference of 6 Da and b9+2 (468.62 and 465.93) with a mass difference of 3 Da (Figure.5). This feature can avoid incorrect assignment of peptide sequences to provide an exact identification and subsequent quantitation and can also be well applied in processing de novo sequencing.

’ CONCLUSIONS On the basis of the strengths of isobaric tags and massdifference methods, we successfully proposed a comprehensive and improved quantitative strategy and validated its effectiveness by applying it in the HeLa cell samples with various protein proportions. The experimental results indicated that this novel strategy could well solve increasingly difficult issues with the use of a multiplexed set in the MS scan and the suppression effect on the low-mass reporter ions in the MS/MS scan and thus provide a highly accurate and highly reliable quantitation by each labeled peptide supported by multiple b, y ion pairs. Moreover, this strategy also provided some complementary quantitative information by the labeled peptides with mass differences in the MS scan and the exact assignment of various charged fragments for identification. IVTAL, in light of its concision, accuracy, and reliability, promises to be applied and popularized in the quantitative proteomics field. ’ ASSOCIATED CONTENT

bS

Supporting Information. Additional information as noted in text. This material is available free of charge via the Internet at http://pubs.acs.org.

’ AUTHOR INFORMATION Corresponding Author

*E-mail: [email protected]. Phone: +0086-021-54237618. Fax: +0086-021-54237961. 6032

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’ ACKNOWLEDGMENT We gratefully thank Xiaofeng Xiao and Shuai Zuo for technical advice on the cell culture. The work was supported by National Science and Technology Key Project of China (Grants 2007CB914100, 2009CB825607, and 2010CB912700), National Science Foundation of China (Grants 21025519, 31070732, and 20875016), Ministry of Education of China (Grant 20080246011), and Shanghai Projects (Grants Shuguang, Eastern Scholar, and B109). ’ REFERENCES (1) O’Farrell, P. H. J. Biol. Chem. 1975, 250, 4007–4021. (2) Klose, J.; Kobalz, U. Electrophoresis 1995, 16, 1034–1059. (3) Unlu, M.; Morgan, M. E.; Minden, J. S. Electrophoresis 1997, 18, 2071–2077. (4) Morris, J. S.; Clark, B. N.; Wei, W.; Gutstein, H. B. J. Proteome Res. 2010, 9, 595–604. (5) Gygi, S. P.; Rist, B.; Gerber, S. A.; Turecek, F.; Gelb, M. H.; Aebersold, R. Nat. Biotechnol. 1999, 17, 994–999. (6) Ong, S. E.; Blagoev, B.; Kratchmarova, I.; Kristensen, D. B.; Steen, H.; Pandey, A.; Mann, M. Mol. Cell. Proteomics 2002, 1, 376–386. (7) Ross, P. L.; Huang, Y. N.; Marchese, J. N.; Williamson, B.; Parker, K.; Hattan, S.; Khainovski, N.; Pillai, S.; Dey, S.; Daniels, S.; Purkayastha, S.; Juhasz, P.; Martin, S.; Bartlet-Jones, M.; He, F.; Jacobson, A.; Pappin, D. J. Mol. Cell. Proteomics 2004, 3, 1154–1169. (8) Sakai, J.; Kojima, S.; Yanagi, K.; Kanaoka, M. Proteomics 2005, 5, 16–23. (9) Zhang, X.; Jin, Q. K.; Carr, S. A.; Annan, R. S. Rapid Commun. Mass Spectrom. 2002, 16, 2325–2332. (10) Zhu, H.; Pan, S.; Gu, S.; Bradbury, E. M.; Chen, X. Rapid Commun. Mass Spectrom. 2002, 16, 2115–2123. (11) Graumann, J.; Hubner, N. C.; Kim, J. B.; Ko, K.; Moser, M.; Kumar, C.; Cox, J.; Sch€oler, H.; Mann, M. Mol. Cell. Proteomics 2008, 7, 672–683. (12) Keshamouni, V. G.; Michailidis, G.; Grasso, C. S.; Anthwal, S.; Strahler, J. R.; Walker, A.; Arenberg, D. A.; Reddy, R. C.; Akulapalli, S.; Thannickal, V. J. J. Proteome Res. 2006, 5, 1143–1154. (13) Blagoev, B.; Ong, S. E.; Kratchmarova, I.; Mann, M. Nat. Biotechnol. 2004, 22, 1139–1145. (14) Andersen, J. S.; Lam, Y. W.; Leung, A. K. L.; Ong, S.-E.; Lyon, C. E.; Lamond, A. I.; Mann, M. Nature 2005, 433, 77–83. (15) DeSouza, L. V.; Romaschin, A. D.; Colgan, T. J.; Siu, K. W. Anal. Chem. 2009, 81, 3462–3470. (16) Xie, L. Q.; Zhao, C.; Cai, S. J.; Xu, Y.; Huang, L. Y.; Bian, J. S.; Shen, C. P.; Lu, H. J.; Yang, P. Y. J. Proteome Res. 2010, 9, 4701–4709. (17) Liu, Z.; Cao, J.; He, Y. F.; Qiao, L.; Xu, C. J.; Lu, H. J.; Yang, P. Y. J. Proteome Res. 2010, 9, 227–236. (18) Meierhofer, D.; Wang, X.; Huang, L.; Kaiser, P. J. Proteome Res. 2008, 7, 4566–4576. (19) Koehler, C. J.; Strozynski, M.; Kozielski, F.; Treumann, A.; Thiede, B. J. Proteome Res. 2009, 8, 4333–4341. (20) Thompson, A.; Schafer, J.; Kuhn, K.; Kienle, S.; Schwarz, J.; Schmidt, G.; Neumann, T.; Johnstone, R.; Mohammed, A. K.; Hamon, C. Anal. Chem. 2003, 75, 1895–1904. (21) Dayon, L.; Turck, N.; Kienle, S.; Schulz-Knappe, P.; Hochstrasser, D. F.; Scherl, A.; Sanchez, J. C. Anal. Chem. 2010, 82, 848–858. (22) Ow, Y. S.; Salim, M.; Noirel, J.; Evans, C.; Rehman, I.; Wright, C. P. J. Proteome Res. 2009, 8, 5347–5355. (23) Yan, W.; Luo, J.; Robinson, M.; Eng, J.; Aebersold, R.; Ranish, J. Mol. Cell. Proteomics 2011, 10, 1–15. (24) Colzani, M.; Sch€utz, F.; Potts, A.; Waridel, P.; Quadroni, M. Mol. Cell. Proteomics 2008, 7, 927–937. (25) Bendall, S. C.; Hughes, C.; Stewart, M. H.; Doble, B.; Bhatia, M.; Lajoie, G. A. Mol. Cell. Proteomics 2008, 7, 1587–1597.

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