Anal. Chem. 2005, 77, 4947-4954
Assessing the Effects of Diurnal Variation on the Composition of Human Parotid Saliva: Quantitative Analysis of Native Peptides Using iTRAQ Reagents Markus Hardt,† H. Ewa Witkowska,†,‡ Sally Webb,§ Lindsay R. Thomas,† Scott E. Dixon,‡ Steven C. Hall,†,‡ and Susan J. Fisher*,†,‡,|,⊥
Departments of Cell and Tissue Biology, Anatomy, and Pharmaceutical Chemistry, Biomolecular Resource Center Mass Spectrometry Facility, University of California San Francisco, San Francisco, California 94143, and Applied Biosystems, Foster City, California 94404
Changes in salivary composition correlate with disease susceptibility, disease state, or both. However, use of saliva for diagnostic purposes is complicated by the glandspecific effects of circadian rhythm or diurnal variation. We recently characterized a suite of peptides in the e10-kDa fraction of human parotid saliva that included many novel species. In this study, we used novel iTRAQ labeling chemistry to investigate possible diurnal effects on peptide generation. We collected samples produced by gustatory stimulation as the ductal secretions at four time points under conditions that minimized proteolysis, pooled them according to collection time, and isolated the LMW fractions. Samples collected at each collection time were derivatized with a different isobaric iTRAQ reagent. The labeled samples were combined, separated by reversed-phase HPLC, co-spotted with matrix on MALDI targets, and analyzed by MALDI TOF/TOF mass spectrometry. With this approach, we achieved relative quantification of the parotid peptides at four time points. In several cases, abundance during the day changed dramatically. iTRAQ tagging improved the efficiency of MS/MS fragmentation, which in turn allowed the identification of several novel peptides. Our results demonstrated both the utility of this method and the importance of diurnal effects on the composition of the human parotid saliva peptidome. Biomarker discovery has become a focus of proteomic studies designed to mine body fluids as potentially rich sources of diagnostic markers.1 Saliva, in particular, because of its accessibility and ease of collection, is an important source of novel * To whom correspondence should be addressed. Tel.: (415) 476-5297. Fax: (415) 502-7338. E-mail:
[email protected]. † Department of Cell and Tissue Biology, University of California San Francisco. ‡ Biomolecular Resource Center Mass Spectrometry Facility, University of California San Francisco. § Applied Biosystems. | Department of Anatomy, University of California San Francisco. ⊥ Department Pharmaceutical Chemistry, University of California San Francisco. (1) Villanueva, J.; Philip, J.; Entenberg, D.; Chaparro, C. A.; Tanwar, M. K.; Holland, E. C.; Tempst, P. Anal. Chem. 2004, 76, 1560-1570. 10.1021/ac050161r CCC: $30.25 Published on Web 07/07/2005
© 2005 American Chemical Society
diagnostic markers and therapeutic targets.2-6 However, many factors, such as circadian rhythm or diurnal variation, affect salivary protein composition.7-10 Recent studies, including work from our group, have shown that the low-molecular-weight (LMW) fraction of parotid saliva, which is rich in peptides, is far more complex than previously thought.11,12 In addition, we demonstrated that one of the novel peptides we discovered has antifungal activity. These findings suggest the possibility that, on an individual basis, the salivary peptide repertoire may play an important selective role in governing the colonization of the oral flora. To determine whether differences in the composition of the salivary peptidome correlate with specific disease states, we first needed to identify the possible effects of diurnal variation, which could be an important confounding variable introduced during the sample collection process. This consideration gains additional relevance in light of the fact that the abundance of certain salivary peptides (histatins 1, 3, and 5 and statherin) varies during the day,8,10 as determined by HPLC separation with A280 as a measure of relative quantitation. However, because of complexities in the composition of the LMW fraction of parotid saliva, this approach has limited utility: many peptides that do not contain aromatic amino acid residues cannot be detected using this method. Thus, (2) Tanida, T.; Okamoto, T.; Okamoto, A.; Wang, H.; Hamada, T.; Ueta, E.; Osaki, T. J. Oral Pathol. Med. 2003, 32, 586-594. (3) Robinson, C. P.; Yamachika, S.; Alford, C. E.; Cooper, C.; Pichardo, E. L.; Shah, N.; Peck, A. B.; Humphreys-Beher, M. G. Proc. Natl. Acad. Sci. U. S. A. 1997, 94, 5767-5771. (4) Lopez Solis, R.; Puente Diaz, M.; Morales Bozo, I.; Weis, U. K.; Diaz, F. Biochim. Biophys. Acta 2003, 1621, 41-47. (5) Albo, F.; Antonangeli, R.; Cavazza, A.; Marini, M.; Roda, L. G.; Rossi, P. Int. Immunopharmacol. 2001, 1, 1777-1788. (6) Denver, R.; Tzanidis, A.; Martin, P.; Krum, H. Lancet 2000, 355, 468-469. (7) Dawes, C. J. Physiol. 1972, 220, 529-545. (8) Gusman, H.; Leone, C.; Helmerhorst, E. J.; Nunn, M.; Flora, B.; Troxler, R. F.; Oppenheim, F. G. Arch. Oral Biol. 2004, 49, 11-22. (9) Dawes, C. Int. J. Chronobiol. 1974, 2, 253-279. (10) Castagnola, M.; Cabras, T.; Denotti, G.; Fadda, M. B.; Gambarini, G.; Lupi, A.; Manca, I.; Onnis, G.; Piras, V.; Soro, V.; Tambaro, S.; Messana, I. Biol. Rhythm Res. 2002, 33, 213-222. (11) Hardt, M.; Thomas, L. R.; Dixon, S. E.; Newport, G.; Prakobphol, A.; Hall, S. C.; Witkowska, H. E.; Fisher, S. J. Biochemistry 2005, 44, 2885-2899. (12) Castagnola, M.; Inzitari, R.; Rossetti, D. V.; Olmi, C.; Cabras, T.; Piras, V.; Nicolussi, P.; Sanna, M. T.; Pellegrini, M.; Giardina, B.; Messana, I. J. Biol. Chem. 2004, 279, 41436-41443.
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the global analysis of the endogenous salivary peptidome requires a methodological approach that can be applied to samples with a high degree of complexity independent of their amino acid composition. Here we demonstrate that iTRAQ stable isotope labeling chemistry, originally applied in relative protein quantitation,13 is a useful method for analyzing native peptides in biological fluids. Specifically, we used iTRAQ labeling chemistry to address the question of how diurnal variation affects the composition of the LMW peptide fraction of parotid saliva. This method, which derivatizes peptides using four isobaric mass tags, also imparts identical reversed-phase retention properties to differentially labeled peptides. Therefore, four separate peptide mixtures can be individually labeled with different mass tags, combined, and separated by reversed-phase HPLC. The labeled derivatives with identical peptide sequences coelute, allowing subsequent coselection for gas-phase fragmentation in an HPLC MS/MS experiment. The resulting spectrum contains fragment ions specific for the peptide amino acid sequence as well as a quartet of low-mass ions attributable to the different mass tags, i.e., massto-charge ratios (m/z) 114, 115, 116, and 117 Da. The relative intensities of the latter species correspond to the relative abundances of the labeled peptide under different experimental conditions, which in this study was collection time. Consequently, peptide identification, on the basis of sequence-specific fragment ions, and an estimate of relative abundance are accomplished simultaneously. Furthermore, since iTRAQ reagents derivatize primary amine groups, they tag virtually all proteins/peptides except those lacking both lysine and reactive N-terminal amino acids. This feature reduces the bias inherent in similar strategies, such as the isotope-coded affinity tag procedure, which labels peptides containing cysteine.14 Other general labeling chemistries targeting either amino or carboxyl groups have also been reported.15-21 Here we show that iTRAQ labeling chemistry is a robust method for analyzing endogenous peptides in samples of human parotid saliva that have not been digested with exogenous proteinases. Using the multiplexing capability of this method, we identified and quantified, in relative terms, components of the parotid peptidome. Application of this method allowed us to compare the composition of the LMW fraction at 3-h intervals beginning at 9 a.m. and ending at 6 p.m. The results show a complex pattern of diurnal variations in which the abundance of individual species is differentially regulated. This labeling method (13) Ross, P. L.; Huang, Y. N.; Marchese, J.; 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. (14) Gygi, S. P.; Rist, B.; Gerber, S. A.; Turecek, F.; Gelb, M. H.; Aebersold, R. Nat. Biotechnol. 1999, 17, 994-999. (15) Munchbach, M.; Quadroni, M.; Miotto, G.; James, P. Anal. Chem. 2000, 72, 4047-4057. (16) Mirgorodskaya, O. A.; Kozmin, Y. P.; Titov, M. I.; Korner, R.; Sonksen, C. P.; Roepstorff, P. Rapid Commun. Mass Spectrom. 2000, 14. (17) Chakraborty, A.; Regnier, F. E. J Chromatogr., A 2002, 949, 173-184. (18) Che, F. Y.; Fricker, L. D. Anal. Chem. 2002, 74, 3190-3198. (19) Hsu, J. L.; Huang, S. Y.; Chow, N. H.; Chen, S. H. Anal. Chem. 2003, 75, 6843-6852. (20) Mason, D. E.; Liebler, D. C. J. Proteome Res. 2003, 2, 265-272. (21) Goodlett, D. R.; Keller, A.; Watts, J. D.; Newitt, R.; Yi, E. C.; Purvine, S.; Eng, J. K.; von Haller, P.; Aebersold, R.; Kolker, E. Rapid Commun. Mass Spectrom. 2001, 15, 1214-1221.
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also allowed us to identify peptide species that were not detected in nonderivatized samples. EXPERIMENTAL SECTION Collection of Parotid Saliva and Isolation of the LMW Fraction. The protocol for collecting saliva was approved by the Committee on Human Research of the University of California San Francisco. Informed consent was obtained from the subject, a healthy 30-year-old male (blood group A, Le a+b+) taking no medications, with no overt signs of gingivitis or caries. Parotid saliva was collected for 20 min (on ice) as the ductal secretion by using a Lashley cup at four time points (9 a.m., 12 p.m., 3 p.m., 6 p.m.) on three consecutive days.22 To minimize environmental effects on sample composition, the donor was asked to eat similar foods at the same times during the sample collection period. Likewise, activity levels and the sleep/wake cycle, which were recorded, were constant. Upon collection, EDTA was added to a final concentration of 15 mM and the samples were clarified by centrifugation (12000g, 10 min), aliquoted, and stored at -20 °C. For preparation of the LMW fraction, samples were transferred to a Microcon ultrafiltration device (nominal molecular weight limit 10 000; Millipore Corp.) and centrifuged at 10000g at 4 °C for ∼90 min. The filtrate was stored at -20 °C until further analysis. Amino Acid Analysis of the e10-kDa (LMW) Fraction. Aliquots of the e10-kDa fraction that were collected at the same time points were pooled, and duplicate 100-µL portions were subjected to amino acid analysis. Briefly, the samples were vacuum-dried in borosilicate glass tubes and then hydrolyzed in the presence of 0.5 mL of 6 N HCl under an argon atmosphere at 158 °C for 45 min. Afterward, the samples were vacuum-dried a second time and then reconstituted in aqueous 0.005% (w/v) Tris potassium EDTA. Aliquots were subjected to phenylthiocarbamylamino acid analysis using the Applied Biosystems model 421 Analyzer. iTRAQ Labeling of Native Peptides. Equal volumes (100 µL) of the low-molecular-weight fractions were analyzed: 1.8 (9 a.m.), 2.2 (12 p.m.), 3.1 (3 p.m.), or 3.3 µg (6 p.m.). The aliquots were combined based on the collection time point and dried on a SpeedVac, reconstituted in 13 µL of 0.5 M triethylammonium bicarbonate buffer, and reduced with 2 mM tris(2-carboxyethyl)phosphine hydrochloride at 60 °C for 1 h. The cystine residues were then alkylated with 200 mM iodoacetamide for 10 min at room temperature. Each reaction consumed half the volume of an aliquot of the iTRAQ reagent, which according to the manufacturer is sufficient to label up to 50 µg of protein. Briefly, the reagents (Applied Biosystems) were dissolved in ethanol, and 35-µL aliquots of iTRAQ 114, 115, 116, and 117 were incubated at room temperature for 1 h with samples collected at 9 a.m., 12 p.m., 3 p.m., and 6 p.m., respectively. After labeling, the samples were combined, dried on a SpeedVac, and reconstituted in 0.1% trifluoroacetic acid (TFA) (100 µL). Then, aliquots (5 µL) were analyzed by reversed-phase high-performance liquid chromatography (HPLC), matrix-assisted laser desorption/ionization timeof-flight mass spectrometry (MALDI TOF MS), and MALDI TOF tandem mass spectrometry (MALDI TOF MS/MS). Reversed-Phase HPLC. Liquid chromatographic separations were performed on an Ultimate nanoHPLC System (Dionex/ (22) Gillece-Castro, B. L.; Prakobphol, A.; Burlingame, A. L.; Leffler, H.; Fisher, S. J. J. Biol. Chem. 1991, 266, 17358-17368.
LC Packings) equipped with a PepMap C18 column (Dionex/ LC Packings; 75-µm i.d., 15-cm length, 100-Å pore size, 3-µm particle size), a Famos microautosampler, and a ProBot microfraction collector. The mobile-phase flow rate was 325 nL/min. The column was equilibrated at 2% solvent B for 20 min before sample injection (solvent B: 80% acetonitrile/0.04% TFA. solvent A: 2% acetonitrile/0.05% TFA). The binary gradient consisted of a 5-min isocratic wash at 2% solvent B to remove salt, a linear gradient of 2-50% solvent B over 45 min, followed by a column cleanup step of 95% solvent B for 7 min. Peptide elution was monitored at 214 and 280 nm. The column effluent was mixed online using a static micromixing tee (Upchurch Scientific) with a continuous stream (2 µL/min) of R-cyano-4-hydroxycinnamic acid (7 mg/mL in 50% acetonitrile/1% ammonium phosphate) before deposition across a 100-well stainless steel MALDI sample plate at a frequency of one spot/30 s. Mass Spectrometry. Samples were analyzed by MALDI TOF MS on a Voyager DE STR (Applied Biosystems) and by MALDI TOF/TOF MS/MS on a 4700 Proteomics Analyzer mass spectrometer (Applied Biosystems) in positive ion mode. The 4700 Proteomics Analyzer was equipped with TOF/TOF optics and a 200-Hz Nd:YAG laser. For collision-induced dissociation, the collision cell was floated at 1 kV, the resolution of the precursor selection was set to 150 fwhm, and air was used as the collision gas at 5 × 10-7 Torr. Automated acquisition of MS and MS/MS data was controlled by 4700 Explorer Software 2.0. Automated precursor ion selection and MS/MS data analysis were performed utilizing GPS Explorer software 2.0. Specifically, peptides were identified by isolating, within the mass spectrometer, a peptide ion population with a single m/z, fragmenting this population, and measuring the masses of the peptide fragment ions. The experimentally determined peptide fragment ion masses were matched, within a window of (0.1 Da, to theoretical fragment ion masses generated by in silico fragmentation of all peptides derived from human proteins within the Swiss-Prot and NCBInr databases via nonspecific digestion (i.e., “no enzyme” search) using GPS Explorer 2.0 (Applied Biosystems) and MASCOT 1.9 (Matrix Science) software. Identities of some peptides were obtained by manual de novo interpretation of MS/MS spectra. Quantification was based on the peak areas of the characteristic low-mass MS/MS fragment ions of each iTRAQ label and was performed utilizing a script provided by the manufacturer (Applied Biosystems). Quantitation was normalized to either the 9 a.m. or 6 p.m. time point. RESULTS AND DISCUSSION Our experimental strategy was designed to monitor diurnal changes in the abundance, in both absolute and relative terms, of native peptide species found in the LMW fraction of human parotid saliva. In absolute terms, the total amino acid content of the LMW fraction increased over the 9-h period we studied (Figure 1A), which is in agreement with published results regarding the effects of circadian rhythm on the protein concentration of salivary gland secretions.7 As to individual species, a total of 50 peptides were unequivocally identified by MS/MS and quantified using iTRAQ labeling chemistry. Approximate elution times of these peptides are indicated as dots above the HPLC chromatograms in Figure 1B. Predictably, many peptides coeluted or showed negligible UV absorbance; this result emphasizes the importance
Figure 1. (A) Diurnal variation in the total amino acid content of the e10-kDa fraction of human parotid saliva. The data were generated by amino acid analysis of samples collected at the four time points shown. The analysis was performed in duplicate. (B) HPLC separation of the e10-kDa fraction of human parotid saliva. Traces show the A214 of two independent separations of the same sample. The A280 chromatogram, although less sensitive, had a similar pattern (data not shown). The dots indicate the peptide elution order by retention time and position on the MALDI sample plate.
of using mass spectrometry for the detection, identification, and, in this case, quantification of protein fragments. In general, the mass spectra revealed complete amino group labeling. When peptides had multiple primary amine groups, low levels of incomplete derivatization were detected; MS/MS data for these species usually revealed that they were mixtures of all possible combinations of unlabeled sites. A detailed analysis of the underlabeled peptides is presented in Table S-1 (see Supporting Information). The same instances of incomplete labeling occurred in both analyses, suggesting that this phenomenon is likely sequence-specific rather than concentration-dependent. Furthermore, there were no differences in the labeling efficiencies among the samples obtained at the four time points studied, evidence that the concentration of the iTRAQ reagent was sufficient to circumvent any potential problems introduced due to initial differences in peptide concentrations among the samples. Only data from fully derivatized peptides were used for quantification. Analytical Chemistry, Vol. 77, No. 15, August 1, 2005
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Figure 2. MALDI TOF/TOF MS/MS spectra of peptides YQQYTF (A) and KRHHGYK (B) labeled with iTRAQ reagents. Samples collected at four time points were labeled with different isobaric tags. In an MS/MS experiment, the iTRAQ labels fragment into a quartet of unique, lowmass ions that are sample specific (see insets). The peak areas of the iTRAQ fragmentation products were used as a measure of the relative abundance of individual peptides in samples collected at the time points indicated. (A) MS/MS spectrum of peptide YQQYTF corresponding to the C-terminal portion of statherin. Peptides collected at different times carried a single iTRAQ tag that varied, after fragmentation, by 1 Da. The relative peak areas of the iTRAQ fragment ions indicated a considerable reduction in relative abundance of this peptide over the time period studied. (B) The relative abundance of peptide KRHHGYK (amino acid residues 24-30 of the histatin 3 precursor) increased from 9 a.m. to 6 p.m. In both panels, sites of iTRAQ modifications are shown by asterisks within the sequences.
Representative examples of the MS data are shown in Figure 2. The abundance of peptide YQQYTF (Figure 2A) decreased during the day, whereas peptide KRHHGYK (Figure 2B) showed the opposite pattern. In many cases, the iTRAQ label improved the overall signal-to-noise ratios of the MS/MS product ion intensities and simplified the fragmentation patterns. In addition, the N-terminal labeling of peptides devoid of internal charged amino acid residues often enhanced the formation of b-series ion. This phenomenon is illustrated by the MALDI TOF/TOF MS/MS spectrum of peptide NYLYDN before (Figure 3A) and after (Figure 3B) iTRAQ labeling. This feature of the iTRAQ chemistry was particularly valuable in analyzing native peptides that, in general, lack the uniform architecture of tryptic cleavage products, e.g., a basic C-terminal amino acid residue, making interpretation of their MS/MS spectra more challenging. Improved fragmentation patterns along with increased signal intensities 4950
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allowed the identification of many peptides that, in our previous study, were either not detected or produced MS/MS data lacking sufficient information to validate their identities.11 All peptides identified during this study are listed in Table 1. Nineteen novel peptides were identified. Peptides in parotid saliva can be grouped into five distinct categories according to the observed pattern of diurnal changes in their concentrations. Figure 4 summarizes the peptides that were up- or downregulated as well as those with concentrations that oscillated. Most peptides peaked at 12 p.m. (Figure 4B) or oscillated in concentration throughout the day (Figure 4E). Mirroring the effect of diurnal variation on the global protein concentration of saliva, the relative concentrations of six peptides peaked at 6 p.m. (Figure 4D), the last time point analyzed. Repeat labeling and analysis of a second set of samples from the same individual revealed the same set of peptides. In most cases, the
Figure 3. MALDI TOF/TOF MS/MS spectrum of peptide NYLYDN before (A) and after (B) labeling with iTRAQ reagents. Labeling improved the signal-to-noise ratio and enhanced the fragmentation pattern with regard to b-series ions.
normalized relative peptide abundances suggested good reproducibility between the two experiments. In a few cases, the relative abundances of individual peptides differed greatly. These differences can be attributed to low fragment ion statistics in the MS/MS experiments. Figure S-1 (see Supporting Information) illustrates the relationship between the peak area of the reference iTRAQ product ion and interexperimental differences in the ratios obtained. Predictably, overall variation increased as product ion intensity decreased. Nevertheless, a subpopulation of results that were based on the latter data was highly reproducible. Also contributing to this phenomenon could be slight variations in elution profiles, possibly complicated by the coelution of multiple peptides with very closely related molecular masses that cannot be resolved during the selection of precursor ions for MS/MS analyses. As we previously reported, the observed peptides correspond to sequences found in only a few parotid proteins, principally histatins 1 and 3.11 Mapping these peptides back to their precursors revealed the complex effects of diurnal variation on their generation (Figure 5). For example, peptides derived from the C-termini of the histatin precursors, which have regions of sequence similarity, are much lower in abundance at 9 a.m. than at the other time points analyzed. Interestingly, the only unique C-terminal histatin 1 peptide (DYGSNYLYDN) did not share this pattern, suggesting that synthesis, proteolysis, or both, of histatins 3 and 1 may be differentially regulated. In contrast, internal histatin 1 and 3 peptides (e.g., HEKHHSHR) were most abundant at
9 a.m., suggesting that multiple independent mechanisms are responsible for the generation of peptides from different regions of the parent molecule. This work is an initial step toward understanding the effects of diurnal variation on the peptide composition of human saliva. The multiplexing capability of iTRAQ reagents allows simultaneous identification and quantification of a large set of parotid peptides collected at different time points in a single LC MALDI MS/MS experiment. In many cases, the relative concentrations of individual peptides changed notably from one collection time to the next, often following complex patterns (e.g., see Figure 4) that did not correlate with the steady increase, from 9 a.m. to 6 p.m., in the global amino acid concentration of the e10-kDa LMW fraction (Figure 1). Our methodology differs considerably from that described in previous publications that examined the effects of circadian rhythm on the abundance of salivary components. Two groups used HPLC separation with UV detection to determine the relative concentrations of specific histatins,8,10 whereas other investigators used immunoaffinity assays to detect diurnal effects on levels of salivary leptin23 and endothelin.24 Histatins 1, 3, and 5 were most abundant in the afternoon; leptin peaked at 12 a.m., whereas endothelin levels were relatively constant. Here, we employed an (23) Randeva, H. S.; Karteris, E.; Lewandowski, K. C.; Sailesh, S.; O’Hare, P.; Hillhouse, E. W. Mol. Genet. Metab. 2003, 78, 229-235. (24) Xiang, S.; Denver, R.; Bailey, M.; Krum, H. Clin. Chem. 2003, 49, 20122019.
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Table 1. Native Peptides Identified in Parotid Salivaa position
x x
b
x x x x
b b
x x
b b
x
x x
b b
x x x x
b b b b
x
b
x x
b b
x
b
x
b
x
b
x
b
x
b
Swiss-Prot accession no.
start
end
[MH]+
P01833 P15516 P15515/P15516 P15515/P15516
604 26
609 31
P02808 P15515/P15516 P15516 P15516 P15516 P15515/P15516 P15516 P15516 P15515/P15516 P15516 P15516 P15516
57
62
37 24 25
43 30 31
36 44
43 51
24 34 35
31 42 43
P15516 P15516 P15516 P15515
43 20 24 48
51 29 32 57
P15516 P15516 P15516 P15516 P01833 P02810
42 34 35 20 604 153
51 43 44 30 615 166
P01833 P15516 P15516 P02808 P15516 P15515
598 33 34 45 20 20
609 43 44 56 31 30
P15516 P15516 P15516 P15516
32 33 20 39
43 44 32 51
P15516
31
43
P02810 P15516 P02812
148 31 170
166 44 194
736.4 797.4 801.3 844.5 845.5 847.4 888.4 893.4 925.5 953.5 962.5 1021.5 1044.5 1067.6 1081.7 1124.5 1150.6 1186.6 1207.5 1207.6 1209.6 1223.5 1243.6 1264.6 1287.6 1306.6 1335.7 1349.7 1390.7 1414.7 1416.8 1434.7 1443.7 1487.7 1491.8 1501.6 1517.7 1562.8 1590.8 1619.9 1644.7 1680.9 1718.9 1824.9 1866.9 1875.0 2434.3
poly Ig
P01833
623
648
2490.2
PRB2c
P02812
196
222
2601.2
peptide P-C (intact)
P02810
123
166
4369.2
peptide sequence
parent protein
(R) *LFAEE*K (A) (R) *HHGY*KR (K) (S) *NYLYDN () (K) *R*KFHE*K (H) (G) *D*KSRSPR (?) (Q) *YQQYTF () (R) *SNYLYDN () (K) *HHSHRGY (R) (A) **KRHHGY*K (R) (K) *RHHGY*KR (K) (R) **KFHE*KHH (S) (E) **KHHSHRGY (R) (Y) *RSNYLYDN () (F) *HE*KHHSHR (G) (A) **KRHHGY*KR (K) (F) *HE*KHHSHRG (Y) (H) *E*KHHSHRGY (R) (?) *SPPG*KPQGPPPQ (G) (G) *YRSNYLYDN () () *DSHA*KRHHGY (K) (A) **KRHHGY*KR*K (F) (G) *DYGSNYLYDN () (?) *SPPG*KPQGPPPQG (G) (R) *GYRSNYLYDN () (F) *HE*KHHSHRGY (R) (H) *E*KHHSHRGYR (S) () *DSHA*KRHHGY*K (R) (R) *LFAEE*KAVADTR (D) (Q) *GGRPQGPPQGQSPQ () (?) *SPPG*KPQGPPPQGGN (Q) (K) *AIQDPRLFAEE*K (A) (K) *FHE*KHHSHRGY (R) (F) *HE*KHHSHRGYR (S) (P) *EQPLYPQPYQPQ (Y) () *DSHA*KRHHGY*KR (K) () *DsHE*KRHHGYR (R) (R) *SPPG*KPQGPPQQEGN (?) (R) *KFHE*KHHSHRGY (R) (K) *FHE*KHHSHRGYR (S) () *DSHA*KRHHGY*KR*K (F) (H) *SHRGYRSNYLYDN () (Q) *GPPRPPQGGRPSRPPQ () (K) *R*KFHE*KHHSHRGY (R) (?) *SPPG*KPQGPPPQGGNQPQG (P) (Q) *GPPPQGGRPQGPPQGQSPQ () (K) *R*KFHE*KHHSHRGYR (S) (N) **KPQGPPPPG*KPQGPPPQ GGS*KSRSA (R) (R) *ASVDSGSSEEQGGSSRALV STLVPG (L) (R) *SPPGKPQGPPQQEGNNPQ GPPPPAGN (P) (R) *GRPQGPPQQGGHQQGPPPPPP G*KQGPPP QGGRPQGPPQGQSPQ ()
poly Ig histatin 3 histatin 1 or 3 histatin 1 or 3 multiple precursors statherin histatin 1 or 3 histatin 3 histatin 12 (intact) histatin 3 histatin 1 or 3 histatin 3 histatin 3 histatin 1 or 3 histatin 11 (intact) histatin 3 histatin 3 multiple precursors histatin 3 histatin 3 histatin 3 histatin 1 multiple precursors histatin 3 histatin 3 histatin 3 histatin 3 poly Ig peptide P-C multiple precursors poly Ig histatin 3 histatin 3 statherin histatin 3 histatin 1 multiple precursors histatin 8 (intact) histatin 3 histatin 3 histatin 3 multiple precursors histatin 7 (intact) multiple precursors PRP Cb histatin 9 (intact) peptide P-F
a Novel peptides are indicated by b; peptides that were identified only after labeling with iTRAQ reagents are indicated by x; sites of iTRAQ modifications are identified by an asterisk within the sequence. b PRP C, salivary acidic proline-rich phosphoprotein 1/2. c PRB2, basic salivary proline-rich protein 2.
experimental strategy that allows a more comprehensive analysis of the salivary peptidome without any obvious constraints on the number of peptides monitored or their amino acid composition or sequence. iTRAQ labeling followed by MS analysis of the products avoids the pitfalls of UV detection: an inability to distinguish coeluting peptides and to detect species lacking aromatic amino acid residues. Furthermore, this method requires no preexisting knowledge about the amino acid composition of the peptide mixture. The inherent lack of bias in this approach, which allows the detection of many more species compared with previous studies of the effect of circadian rhythm or diurnal 4952 Analytical Chemistry, Vol. 77, No. 15, August 1, 2005
variation on the concentration of salivary peptides,8,10 will prove equally valuable in the analysis of other body fluids. At the same time, quantification was accomplished by directly correlating the relative peak areas of diagnostic tag ions to that of the peptide selected for MS/MS fragmentation, greatly enhancing the information content of a single experiment. Furthermore, iTRAQ labeling often increased the efficiency of MS/MS fragmentation, enabling the identification of 19 novel parotid peptides. For example, four species devoid of basic amino acid residues (NYLYDN, SNYLYDN, YQQYTF, DYGSNYLYDN) displayed considerably enhanced b-series ions after iTRAQ derivatization,
Figure 4. Relative peptide abundance in the e10-kDa fraction of parotid saliva at four time points. Several patterns were noted. Peptide abundance decreased over time (A), peaked at 12 p.m. (B), 3 p.m. or (C) 6 p.m. (D). Peptides showing other oscillatory patterns are shown in (E). Asterisks denote sites of iTRAQ modifications within the sequences. Identical samples were derivatized and analyzed twice, and the average is shown.
thus allowing the unambiguous interpretation of their MS/MS spectra (Figure 3). The results reported here demonstrate diurnal trends, i.e., changes in the relative concentrations of individual peptide species rather than absolute quantitation. Other investigators have reported that concentrations of different peptides derived from the same precursor can vary dramatically. For example, the C-terminal histatin peptides SNYLYDN and NYLYDN were reported at 1.4 and 2.6 nM, respectively, whereas the concentration of HEKSHHRGY, which corresponds to an internal sequence, was ∼10-fold higher.25
With time as the principal variable, the composition of the parotid peptidome shows a complex pattern of regulation. As we reported previously,11 the majority of native peptides originate from a limited number of proteins that in turn belong to particular families. Specifically, peptides derived from R-amylase, the most abundant protein in parotid saliva, were conspicuously absent, while peptides from histatins and proline-rich proteins were abundant. In toto, the amino acid content of the parotid peptidome increased during the day, a finding that mirrors changes in the (25) Perinpanayagam, H. E.; Van Wuyckhuyse, B. C.; Ji, Z. S.; Tabak, L. A. J. Dent. Res. 1995, 74, 345-350.
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Figure 5. Peptide fragments mapped back to histatins 1 and 3. Peptide fragments that could have been derived from either sequence are shown in italics. Quantitation was normalized to the 9 a.m. or 6 p.m. time point; the y-scale of each plot, which reflects the highest concentration of each peptide, varies slightly among the plots.
from our past work on the peptidome of human parotid saliva, we know that ultrafiltration in the presence of up to 20% acetonitrile does not substantially alter the peptidome repertoire (unpublished results). This finding is in accord with the lack of published evidence that salivary protein complexes include peptides. Finally, we have purified and conducted detailed MS-based analyses of four of the major salivary proteins MG1,31 MG2,32 the prolinerich glycoprotein,22 and the salivary agglutinin.33 We know from this experience that the relative abundance of these components does not show diurnal variations, a possibility that could also confound interpretation of our results. If proteolytic processing generates the parotid peptide repertoire, then it seems plausible that multiple, yet to be identified proteinases with the same diurnal expression or activation patterns as their products are involved. There is a precedent for this type of regulation: circadian rhythm influences the secretion of some salivary components with important enzymatic activities, most notably R-amylase,34 but not others, such as lysozyme35 and kallikrein.34
global protein content of parotid saliva.7 Individually, the relative concentrations of native peptides showed several complex patterns of regulation (Figure 4). The results of previous studies support our finding of a high degree of variability in the relative concentrations of individual salivary peptides during the day. Notably, histatins 1, 3, and 5 show an acrophase in the late afternoon synchronous with the flow rate of whole saliva, whereas the concentration of statherin does not change.8,10 Although the cause of these differences is not clear, it is reasonable to hypothesize that they are related to the specialized functions or generative mechanisms of peptides in different groupings. As yet, the exact mechanism(s) that produce(s) the diverse repertoire of parotid peptides is unknown. Since many of the observed peptides are likely derived from larger precursor molecules, proteolytic processing is a prime candidate. Previous studies suggest that histatins,12,25,26 statherins,27 proline-rich proteins,28,29 cystatins,30 and endothelin24 are proteinase substrates. When the peptides derived from histatins 1 and 3 are mapped back to the full-length molecules (Figure 5), it is evident that multiple processing steps are required to create the observed fragments. With regard to timing, the relative concentrations of the smaller C-terminal peptides were very low at 9 a.m., but no other obvious patterns were observed. Unexpectedly, we did not detect intact histatins, i.e., the putative precursors of the observed peptide fragments. Therefore, we were not able to correlate the concentrations of the substrates with the products. We cannot exclude the possibility that some peptides might be trapped in protein complexes with larger molecules. However,
CONCLUSIONS We used an innovative fourplex labeling method to study the effects of diurnal variation on the parotid peptidome and in doing so discovered additional novel endogenous peptides. Our results highlight the difficulties involved in establishing normal values of salivary components, because common variables, such as time of day the sample is collected, dramatically affect the relative abundance of individual components. Similar to other parameters that influence salivary composition, e.g., hormonal regulation36 and method of sample collection,24 diurnal variation is an important variable that future research on salivary biomarkers must take into consideration. Whether or not similar phenomena occur in other body fluids is an interesting question that can be rapidly addressed using the novel labeling and MS-based analysis strategy we employed.
(26) Xu, L.; Lal, K.; Santarpia, R. P., 3rd; Pollock, J. J. Arch. Oral Biol. 1993, 38, 277-283. (27) Jensen, J. L.; Lamkin, M. S.; Troxler, R. F.; Oppenheim, F. G. Arch. Oral Biol. 1991, 36, 529-534. (28) Ayad, M.; Van Wuyckhuyse, B. C.; Minaguchi, K.; Raubertas, R. F.; Bedi, G. S.; Billings, R. J.; Bowen, W. H.; Tabak, L. A. J. Dent. Res. 2000, 79, 976-982. (29) Messana, I.; Cabras, T.; Inzitari, R.; Lupi, A.; Zuppi, C.; Olmi, C.; Fadda, M. B.; Cordaro, M.; Giardina, B.; Castagnola, M. J. Proteome Res. 2004, 3, 792-800. (30) Lupi, A.; Messana, I.; Denotti, G.; Schinina, M. E.; Gambarini, G.; Fadda, M. B.; Vitali, A.; Cabras, T.; Piras, V.; Patamia, M.; Cordaro, M.; Giardina, B.; Castagnola, M. Proteomics 2003, 3, 461-467.
(31) Thomsson, K. A.; Prakobphol, A.; Leffler, H.; Reddy, M. S.; Levine, M. J.; Fisher, S. J.; Hansson, G. C. Glycobiology 2002, 12, 1-14. (32) Prakobphol, A.; Thomsson, K. A.; Hansson, G. C.; Rosen, S. D.; Singer, M. S.; Phillips, N. J.; Medzihradszky, K. F.; Burlingame, A. L.; Leffler, H.; Fisher, S. J. Biochemistry 1998, 37, 4916-4927. (33) Prakobphol, A.; Xu, F.; Hoang, V. M.; Larsson, T.; Bergstrom, J.; Johansson, I.; Frangsmyr, L.; Holmskov, U.; Leffler, H.; Nilsson, C.; Boren, T.; Wright, J. R.; Stromberg, N.; Fisher, S. J. J. Biol. Chem. 2000, 275, 39860-39866. (34) Jenzano, J. W.; Brown, C. K.; Mauriello, S. M. Arch. Oral Biol. 1987, 32, 757-759. (35) Richter, J.; Kral, V.; Zucov, I.; Subrt, P.; Rahm, J. Czech. Med. 1980, 3, 249-254. (36) Mandel, I. D.; Wotman, S. Oral Sci. Rev. 1976, 25-47.
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ACKNOWLEDGMENT We thank Drs. David R. Dupont, Katherine E. Williams, and Arnold Falick for technical assistance.This work was supported by a NIDCR NRSA Training Grant (T21 07204), U01 DE016274, R37 DE07244, and the Sandler New Technology Fund. SUPPORTING INFORMATION AVAILABLE Additional information as noted in text. This material is available free of charge via the Internet at http//pubs.acs.org. Received for review January 26, 2005. Accepted May 3, 2005. AC050161R
