Proteomics Analysis of Cells in Whole Saliva from Oral Cancer Patients via Value-added Three-dimensional Peptide Fractionation and Tandem Mass Spectrometry
2007; Elsevier BV; Volume: 7; Issue: 3 Linguagem: Inglês
10.1074/mcp.m700146-mcp200
ISSN1535-9484
AutoresHongwei Xie, Getiria Onsongo, Jonathan Popko, Ebbing P. de Jong, Jing Cao, John V. Carlis, Robert J. Griffin, Nelson L. Rhodus, Timothy J. Griffin,
Tópico(s)Glycosylation and Glycoproteins Research
ResumoWhole human saliva possesses tremendous potential in clinical diagnostics, particularly for conditions within the oral cavity such as oral cancer. Although many have studied the soluble fraction of whole saliva, few have taken advantage of the diagnostic potential of the cells present in saliva, and none have taken advantage of proteomics capabilities for their study. We report on a novel proteomics method with which we characterized for the first time cells contained in whole saliva from patients diagnosed with oral squamous cell carcinoma. Our method uses three dimensions of peptide fractionation, combining the following steps: preparative IEF using free flow electrophoresis, strong cation exchange step gradient chromatography, and microcapillary reverse-phase liquid chromatography. We determined that the whole saliva samples contained enough cells, mostly exfoliated epithelial cells, providing adequate amounts of total protein for proteomics analysis. From a mixture of four oral cancer patient samples, the analysis resulted in a catalogue of over 1000 human proteins, each identified from at least two peptides, including numerous proteins with a role in oral squamous cell carcinoma signaling and tumorigenesis pathways. Additionally proteins from over 30 different bacteria were identified, some of which putatively contribute to cancer development. The combination of preparative IEF followed by strong cation exchange chromatography effectively fractionated the complex peptide mixtures despite the closely related physiochemical peptide properties of these separations (pI and solution phase charge, respectively). Furthermore compared with our two-step method combining preparative IEF and reverse-phase liquid chromatography, our three-step method identified significantly more cellular proteins while retaining higher confidence protein identification enabled by peptide pI information gained through IEF. Thus, for detecting salivary markers of oral cancer and possibly other conditions of the oral cavity, the results confirm both the potential of analyzing the cells in whole saliva and doing so with our proteomics method. Whole human saliva possesses tremendous potential in clinical diagnostics, particularly for conditions within the oral cavity such as oral cancer. Although many have studied the soluble fraction of whole saliva, few have taken advantage of the diagnostic potential of the cells present in saliva, and none have taken advantage of proteomics capabilities for their study. We report on a novel proteomics method with which we characterized for the first time cells contained in whole saliva from patients diagnosed with oral squamous cell carcinoma. Our method uses three dimensions of peptide fractionation, combining the following steps: preparative IEF using free flow electrophoresis, strong cation exchange step gradient chromatography, and microcapillary reverse-phase liquid chromatography. We determined that the whole saliva samples contained enough cells, mostly exfoliated epithelial cells, providing adequate amounts of total protein for proteomics analysis. From a mixture of four oral cancer patient samples, the analysis resulted in a catalogue of over 1000 human proteins, each identified from at least two peptides, including numerous proteins with a role in oral squamous cell carcinoma signaling and tumorigenesis pathways. Additionally proteins from over 30 different bacteria were identified, some of which putatively contribute to cancer development. The combination of preparative IEF followed by strong cation exchange chromatography effectively fractionated the complex peptide mixtures despite the closely related physiochemical peptide properties of these separations (pI and solution phase charge, respectively). Furthermore compared with our two-step method combining preparative IEF and reverse-phase liquid chromatography, our three-step method identified significantly more cellular proteins while retaining higher confidence protein identification enabled by peptide pI information gained through IEF. Thus, for detecting salivary markers of oral cancer and possibly other conditions of the oral cavity, the results confirm both the potential of analyzing the cells in whole saliva and doing so with our proteomics method. Whole human saliva is easily collected in the clinic in a non-invasive, on-demand manner and in relatively large, easily stored quantities, making it an optimal bodily fluid for clinical diagnostics (1Hofman L.F. Human saliva as a diagnostic specimen.J. Nutr. 2001; 131: 1621S-1625SCrossref PubMed Google Scholar, 2Lawrence H.P. Salivary markers of systemic disease: noninvasive diagnosis of disease and monitoring of general health.J. Can. Dent. Assoc. 2002; 68: 170-174PubMed Google Scholar). Diagnosis of oral cancer could benefit greatly from the development of whole saliva-based clinical tests given the physical proximity of the site of cancer development with the diagnostic fluid. In fact, oral cancer, usually diagnosed in the form of oral squamous cell carcinoma (OSCC), 1The abbreviations used are: OSCC, oral squamous cell carcinoma; FFE, free flow electrophoresis; μLC, microcapillary LC; SCX, strong cation exchange; DAPI, 4′,6-diamidino-2-phenylindole; iTRAQ, isobaric tags for relative and absolute quantitation. has not seen a drop in its 50% mortality rate over the last 30 years (3Landis S.H. Murray T. Bolden S. Wingo P.A. Cancer statistics, 1998.CA Cancer J. Clin. 1998; 48: 6-29Crossref PubMed Scopus (2456) Google Scholar), motivating the development of new and reliable, saliva-based clinical diagnostic tests for the early detection of OSCC. Such tests would lead to more informed treatment of patients and a reduction in the suffering and death caused by this cancer. To develop these tests, molecular markers that are predictive of cancer development need first to be identified within whole saliva. Many researchers have studied the soluble fraction of whole saliva as a source of these markers (4Wong D.T. Towards a simple, saliva-based test for the detection of oral cancer. 'Oral fluid (saliva), which is the mirror of the body, is a perfect medium to be explored for health and disease surveillance'.Expert Rev. Mol. Diagn. 2006; 6: 267-272Crossref PubMed Scopus (66) Google Scholar, 5Rhodus N.L. Cheng B. Myers S. Miller L. Ho V. Ondrey F. The feasibility of monitoring NF-κB associated cytokines: TNF-α, IL-1α, IL-6, and IL-8 in whole saliva for the malignant transformation of oral lichen planus.Mol. Carcinog. 2005; 44: 77-82Crossref PubMed Scopus (129) Google Scholar, 6Rhodus N.L. Ho V. Miller C.S. Myers S. Ondrey F. NF-κB dependent cytokine levels in saliva of patients with oral preneoplastic lesions and oral squamous cell carcinoma.Cancer Detect. Prev. 2005; 29: 42-45Abstract Full Text Full Text PDF PubMed Scopus (161) Google Scholar, 7Warnakulasuriya S. Soussi T. Maher R. Johnson N. Tavassoli M. Expression of p53 in oral squamous cell carcinoma is associated with the presence of IgG and IgA p53 autoantibodies in sera and saliva of the patients.J. Pathol. 2000; 192: 52-57Crossref PubMed Scopus (62) Google Scholar, 8Park N.J. Zhou X. Yu T. Brinkman B.M. Zimmermann B.G. Palanisamy V. Wong D.T. Characterization of salivary RNA by cDNA library analysis.Arch. Oral Biol. 2007; 52: 30-35Crossref PubMed Scopus (74) Google Scholar) with some of these studies using large scale mass spectrometry-based proteomics technologies to catalogue its protein components (9Guo T. Rudnick P.A. Wang W. Lee C.S. Devoe D.L. Balgley B.M. Characterization of the human salivary proteome by capillary isoelectric focusing/nanoreversed-phase liquid chromatography coupled with ESI-tandem MS.J. Proteome Res. 2006; 5: 1469-1478Crossref PubMed Scopus (125) Google Scholar, 10Hu S. Xie Y. Ramachandran P. Ogorzalek Loo R.R. Li Y. Loo J.A. Wong D.T. Large-scale identification of proteins in human salivary proteome by liquid chromatography/mass spectrometry and two-dimensional gel electrophoresis-mass spectrometry.Proteomics. 2005; 5: 1714-1728Crossref PubMed Scopus (302) Google Scholar, 11Xie H. Rhodus N.L. Griffin R.J. Carlis J.V. Griffin T.J. Catalogue of human saliva proteins identified by free flow electrophoresis-based peptide separation and tandem mass spectrometry.Mol. Cell. Proteomics. 2005; 4: 1826-1830Abstract Full Text Full Text PDF PubMed Scopus (149) Google Scholar, 12Wilmarth P.A. Riviere M.A. Rustvold D.L. Lauten J.D. Madden T.E. David L.L. Two-dimensional liquid chromatography study of the human whole saliva proteome.J. Proteome Res. 2004; 3: 1017-1023Crossref PubMed Scopus (122) Google Scholar, 13Ghafouri B. Tagesson C. Lindahl M. Mapping of proteins in human saliva using two-dimensional gel electrophoresis and peptide mass fingerprinting.Proteomics. 2003; 3: 1003-1015Crossref PubMed Scopus (119) Google Scholar, 14Vitorino R. Lobo M.J. Ferrer-Correira A.J. Dubin J.R. Tomer K.B. Domingues P.M. Amado F.M. Identification of human whole saliva protein components using proteomics.Proteomics. 2004; 4: 1109-1115Crossref PubMed Scopus (240) Google Scholar). Fewer researchers, however, have investigated using the cells found in whole human saliva for oral cancer diagnostics, and none have used proteomics methods to identify cellular protein markers for potential OSCC detection. Instead these studies have concentrated on detecting genetic or pathological changes associated with OSCC in these cells (15Cheng B. Rhodus N.L. Williams B. Griffin R.J. Detection of apoptotic cells in whole saliva of patients with oral premalignant and malignant lesions: a preliminary study.Oral Surg. Oral Med. Oral Pathol. Oral Radiol. Endod. 2004; 97: 465-470Abstract Full Text Full Text PDF PubMed Scopus (38) Google Scholar, 16Casartelli G. Bonatti S. De Ferrari M. Scala M. Mereu P. Margarino G. Abbondandolo A. Micronucleus frequencies in exfoliated buccal cells in normal mucosa, precancerous lesions and squamous cell carcinoma.Anal. Quant. Cytol. Histol. 2000; 22: 486-492PubMed Google Scholar, 17Nunes D.N. Kowalski L.P. Simpson A.J. Detection of oral and oropharyngeal cancer by microsatellite analysis in mouth washes and lesion brushings.Oral Oncol. 2000; 36: 525-528Crossref PubMed Scopus (42) Google Scholar). To catalogue proteins from complicated biological samples using mass spectrometry, peptide fractionation methods are commonly used. Complex proteolytic protein digests are divided into less complex subsets of peptide fractions from which lower abundance proteins can be detected by the mass spectrometer. Generally these methods combine multiple different chromatography or electrophoresis steps that fractionate peptide sequences using different physiochemical properties (18Link A.J. Multidimensional peptide separations in proteomics.Trends Biotechnol. 2002; 20: S8-13Abstract Full Text Full Text PDF PubMed Google Scholar, 19Issaq H.J. Chan K.C. Janini G.M. Conrads T.P. Veenstra T.D. Multidimensional separation of peptides for effective proteomic analysis.J. Chromatogr. B Anal. Technol. Biomed. Life Sci. 2005; 817: 35-47Crossref PubMed Scopus (172) Google Scholar). For historical reasons (20Giddings J.C. Two-dimensional separations: concept and promise.Anal. Chem. 1984; 56 (1264A): 1258A-1260ACrossref PubMed Scopus (535) Google Scholar), the different fractionation steps used are commonly thought of as being "orthogonal" to each other, leading to the generally used description of these methods as "multidimensional" separations. However, because for the case of modern proteomics applications, spatial dimensionality no longer holds for the fractionation steps comprising these methods, these are more accurately termed "multistep" peptide fractionation methods. Two-step peptide fractionation using a first step of strong cation exchange (SCX) chromatography followed by a second step of microcapillary reverse-phase liquid chromatography (μLC) on line with ESI-MS/MS has become a standard for proteomics analysis (18Link A.J. Multidimensional peptide separations in proteomics.Trends Biotechnol. 2002; 20: S8-13Abstract Full Text Full Text PDF PubMed Google Scholar, 21Link A.J. Eng J. Schieltz D.M. Carmack E. Mize G.J. Morris D.R. Garvik B.M. Yates III, J.R. Direct analysis of protein complexes using mass spectrometry.Nat. Biotechnol. 1999; 17: 676-682Crossref PubMed Scopus (2075) Google Scholar, 22Peng J. Elias J.E. Thoreen C.C. Licklider L.J. Gygi S.P. Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: the yeast proteome.J. Proteome Res. 2003; 2: 43-50Crossref PubMed Scopus (1388) Google Scholar). With increasing popularity, an alternative two-step method using preparative peptide IEF followed by μLC-ESI-MS/MS for sensitive analysis of complex protein mixtures is being used as described by our group (11Xie H. Rhodus N.L. Griffin R.J. Carlis J.V. Griffin T.J. Catalogue of human saliva proteins identified by free flow electrophoresis-based peptide separation and tandem mass spectrometry.Mol. Cell. Proteomics. 2005; 4: 1826-1830Abstract Full Text Full Text PDF PubMed Scopus (149) Google Scholar, 23Xie H. Bandhakavi S. Griffin T.J. Evaluating preparative isoelectric focusing of complex peptide mixtures for tandem mass spectrometry-based proteomics: a case study in profiling chromatin-enriched subcellular fractions in Saccharomyces cerevisiae.Anal. Chem. 2005; 77: 3198-3207Crossref PubMed Scopus (56) Google Scholar) and others (9Guo T. Rudnick P.A. Wang W. Lee C.S. Devoe D.L. Balgley B.M. Characterization of the human salivary proteome by capillary isoelectric focusing/nanoreversed-phase liquid chromatography coupled with ESI-tandem MS.J. Proteome Res. 2006; 5: 1469-1478Crossref PubMed Scopus (125) Google Scholar, 24Malmstrom J. Lee H. Nesvizhskii A.I. Shteynberg D. Mohanty S. Brunner E. Ye M. Weber G. Eckerskorn C. Aebersold R. Optimized peptide separation and identification for mass spectrometry based proteomics via free-flow electrophoresis.J. Proteome Res. 2006; 5: 2241-2249Crossref PubMed Scopus (80) Google Scholar, 25Cargile B.J. Bundy J.L. Freeman T.W. Stephenson Jr., J.L. Gel based isoelectric focusing of peptides and the utility of isoelectric point in protein identification.J. Proteome Res. 2004; 3: 112-119Crossref PubMed Scopus (120) Google Scholar, 26Krijgsveld J. Gauci S. Dormeyer W. Heck A.J. In-gel isoelectric focusing of peptides as a tool for improved protein identification.J. Proteome Res. 2006; 5: 1721-1730Crossref PubMed Scopus (94) Google Scholar, 27Heller M. Ye M. Michel P.E. Morier P. Stalder D. Junger M.A. Aebersold R. Reymond F. Rossier J.S. Added value for tandem mass spectrometry shotgun proteomics data validation through isoelectric focusing of peptides.J. Proteome Res. 2005; 4: 2273-2282Crossref PubMed Scopus (95) Google Scholar, 28Horth P. Miller C.A. Preckel T. Wenz C. Efficient fractionation and improved protein identification by peptide OFFGEL electrophoresis.Mol. Cell. Proteomics. 2006; 5: 1968-1974Abstract Full Text Full Text PDF PubMed Scopus (201) Google Scholar, 29An Y. Fu Z. Gutierrez P. Fenselau C. Solution isoelectric focusing for peptide analysis: comparative investigation of an insoluble nuclear protein fraction.J. Proteome Res. 2005; 4: 2126-2132Crossref PubMed Scopus (23) Google Scholar). This alternative gets valuable peptide pI information from the IEF fractionation that aids in the high confidence identification of peptide sequence matches determined by sequence database searching of the MS/MS data. One group has also demonstrated the effectiveness of a three-step, LC-based peptide fractionation method for increasing the number of proteins identified by MS/MS (30Wei J. Sun J. Yu W. Jones A. Oeller P. Keller M. Woodnutt G. Short J.M. Global proteome discovery using an online three-dimensional LC-MS/MS.J. Proteome Res. 2005; 4: 801-808Crossref PubMed Scopus (86) Google Scholar), although none have described a three-step method using preparative IEF as one of the steps. Here we introduce a novel three-step peptide fractionation method and demonstrate its effectiveness for proteomics cataloguing of cells found in whole saliva from patients with diagnosed OSCC lesions. Furthermore we show that whole saliva contains reliable amounts of cells, mainly exfoliated from the oral epithelium, which provide adequate amounts of protein for proteomics studies using mass spectrometry. The steps of our three-step method are: 1) preparative IEF using free flow electrophoresis (FFE), 2) SCX chromatography, and 3) μLC on line with ESI-MS/MS. We show that our method effectively fractionates complex peptide mixtures and increases significantly the number of proteins identified compared with our earlier described two-step method while retaining the benefits of peptide pI for high confidence protein identification (25Cargile B.J. Bundy J.L. Freeman T.W. Stephenson Jr., J.L. Gel based isoelectric focusing of peptides and the utility of isoelectric point in protein identification.J. Proteome Res. 2004; 3: 112-119Crossref PubMed Scopus (120) Google Scholar, 26Krijgsveld J. Gauci S. Dormeyer W. Heck A.J. In-gel isoelectric focusing of peptides as a tool for improved protein identification.J. Proteome Res. 2006; 5: 1721-1730Crossref PubMed Scopus (94) Google Scholar, 31Xie H. Griffin T.J. Trade-off between high sensitivity and increased potential for false positive peptide sequence matches using a two-dimensional linear ion trap for tandem mass spectrometry-based proteomics.J. Proteome Res. 2006; 5: 1003-1009Crossref PubMed Scopus (43) Google Scholar). We identified over 1000 human proteins (each matched by at least two peptides) from the cells in whole saliva from OSCC patients, with a number of these being low abundance proteins having a previously described association in oral cancer progression, and identified for the first time directly from whole saliva. We also identified proteins from over 30 different bacteria, many of which have not been described previously in whole human saliva and several of which have possible links to cancer. These results provide the first description of the potential for using cells in whole human saliva to identify protein markers of oral cancer progression and the effectiveness of our proteomics method for such studies. The study was conducted with approval by the Institutional Review Board of the School of Dentistry, University of Minnesota. Saliva was collected from four subjects with clinically diagnosed and histopathologically confirmed primary OSCC ulcerative lesions located on the tongue. Unstimulated whole saliva was obtained using a standard, controlled protocol (6Rhodus N.L. Ho V. Miller C.S. Myers S. Ondrey F. NF-κB dependent cytokine levels in saliva of patients with oral preneoplastic lesions and oral squamous cell carcinoma.Cancer Detect. Prev. 2005; 29: 42-45Abstract Full Text Full Text PDF PubMed Scopus (161) Google Scholar) by first having each subject swallow and then expectorate continuously into a 50-ml sterile, polypropylene conical tube for a period of 5 min. This resulted in ∼4 ml or more of total saliva from each subject. Following collection, the samples were immediately placed on ice and stored at −70 °C until further processing. 1 ml of whole saliva from each of the four different subjects was separately centrifuged at 1500 × g at 4 °C for 10 min, and each was processed identically in parallel. After carefully discarding the supernatant, the insoluble cell pellet was washed twice using ice-cold PBS buffer (Invitrogen), and the cells were resuspended into 1 ml of ice-cold PBS. Next 100 μl was removed, and the cells were stained with trypan blue followed by counting using a light microscope (Nikon). The remaining 900 μl of solution containing cells was again pelleted by centrifugation, the supernatant was removed, and the cells were lysed using radioimmune precipitation assay buffer containing Triton X-100 (Boston BioProducts, Worcester, MA) and a protease inhibitor mixture (Roche Applied Science). The protein concentration was determined by the BCA protein assay (Pierce). For these experiments, 500 μl of whole saliva from each of the four subject saliva samples was combined together, and the cell pellet was isolated by centrifugation as described above. Immunostaining of the cells was carried out following a previously described protocol (32Glogovac J.K. Porter P.L. Banker D.E. Rabinovitch P.S. Cytokeratin labeling of breast cancer cells extracted from paraffin-embedded tissue for bivariate flow cytometric analysis.Cytometry. 1996; 24: 260-267Crossref PubMed Scopus (37) Google Scholar). After washing the cell pellet with ice-cold PBS buffer, it was redissolved in 1 ml of PBA (0.1% BSA in 1× PBS buffer), and an equal volume of 0.2% Triton X-100 in PBS was added. The solution was incubated for 3 min on ice and then centrifuged at 500 × g for 10 min, and the supernatant was removed. The cells were redissolved with 1 ml of PBA and transferred to a 1.5-ml microcentrifuge tube with protection from light, and 5 μl of FITC-labeled anti-cytokeratin mouse monoclonal antibody was added (Abcam, Cambridge, MA) followed by gentle shaking for 30 min at room temperature. The cells were then centrifuged, washed with ice-cold PBS, redissolved in 1 ml PBS, and then stained with DAPI DNA stain (Fisher Scientific) by adding 3 μl of a 3 mg/ml DAPI stock solution in water with gentle shaking for 12 min at room temperature. The cells were again centrifuged, washed with ice-cold PBS, redissolved in 300 μl of PBS, and counted using a fluorescence microscope (BX60, Olympus, New York, NY). For proteomics studies, new 2-ml aliquots of whole saliva from each of the four subjects were combined, the cell pellet was isolated by centrifugation, the cells were lysed as described above, and total protein was measured using the BCA method. From this mixture, 200 μg of total protein was exchanged into a buffer containing 50 mm Tris-HCl, 100 mm NaCl, and 1% SDS using an Amicon ultracentrifugal filter device (5-kDa molecular mass cutoff, Millipore, Billerica, MA). The sample was boiled briefly to denature proteins, and additional Tris/NaCl buffer was added to achieve a final buffer consisting of 50 mm Tris-HCl, 100 mm NaCl, 0.1% SDS, pH 7.5. Tris(2-carboxyethyl)phosphine reducing agent (Pierce) was added to reach a final concentration of 5 mm, 20 μg of modified trypsin (Promega, Madison, WI) was added, and the mixture was incubated overnight at 37 °C. The resulting peptides were desalted using a mixed mode cation exchange cartridge (Waters, Milford, MA) and concentrated by vacuum centrifugation. The peptides were labeled with the iTRAQ reagent (33Ross 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. Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents.Mol. Cell. Proteomics. 2004; 3: 1154-1169Abstract Full Text Full Text PDF PubMed Scopus (3721) Google Scholar) (Applied Biosystems) using the manufacturer's protocol. Although the objective of this study was not to gain quantitative information, these samples were labeled with the iTRAQ reagent to test the amenability of labeled peptides to our three-step peptide fractionation method for its potential use in future quantitative studies. After labeling, the peptides were desalted again by mixed mode cation exchange cartridge chromatography and dried by vacuum centrifugation. The overall proteomics method used for peptide fractionation and protein identification is summarized in Fig. 2 and described under "Results." Here we provide the relevant experimental details that go with this figure and description. The peptides (200 μg) were redissolved in 250 μl of FFE buffer (pH ∼8.5) and fractionated using an FFE system (BD Biosciences) enabling preparative IEF of peptides and collection into a 96-deepwell microtiter plate as we have described previously (11Xie H. Rhodus N.L. Griffin R.J. Carlis J.V. Griffin T.J. Catalogue of human saliva proteins identified by free flow electrophoresis-based peptide separation and tandem mass spectrometry.Mol. Cell. Proteomics. 2005; 4: 1826-1830Abstract Full Text Full Text PDF PubMed Scopus (149) Google Scholar, 23Xie H. Bandhakavi S. Griffin T.J. Evaluating preparative isoelectric focusing of complex peptide mixtures for tandem mass spectrometry-based proteomics: a case study in profiling chromatin-enriched subcellular fractions in Saccharomyces cerevisiae.Anal. Chem. 2005; 77: 3198-3207Crossref PubMed Scopus (56) Google Scholar). Initially a 50-μl aliquot (∼10% of total) was taken from each of the FFE fractions and processed using an Amicon Ultrafree-MC centrifugal filter device (5-kDa molecular mass cutoff, Millipore) to remove high molecular weight hydroxypropylmethylcellulose polymer as described previously (23Xie H. Bandhakavi S. Griffin T.J. Evaluating preparative isoelectric focusing of complex peptide mixtures for tandem mass spectrometry-based proteomics: a case study in profiling chromatin-enriched subcellular fractions in Saccharomyces cerevisiae.Anal. Chem. 2005; 77: 3198-3207Crossref PubMed Scopus (56) Google Scholar). The flow-through from the centrifugal device, containing purified peptides, was dried by vacuum centrifugation and reconstituted in 30 μl of HPLC load buffer (0.1% formic acid, 2% acetonitrile in water). Each sample was analyzed by μLC-MS/MS analysis (as described below) to obtain an initial profile of the peptide distribution across the microtiter plate fractions and to identify those fractions containing the most complex peptide mixtures, necessitating their further fractionation by SCX as described below. For those FFE fractions containing relatively large numbers of peptides, a second step of fractionation was performed using a PolySULFOETHYL SCX guard column (Javelin guard column, 1.0-mm inner diameter × 10 mm, 5 μm, 300 Å, PolyLC, Inc.) using an automated syringe pump capable of highly accurate sub-μl/min flow rates (Harvard Apparatus Inc.). For SCX fractionation, a 250-μl aliquot was removed from each acidic FFE fraction (pH range 3.5–6, 10 FFE fractions total) as these contained the most abundant numbers of peptides, consistent with our previous descriptions of peptide fractionation by FFE (23Xie H. Bandhakavi S. Griffin T.J. Evaluating preparative isoelectric focusing of complex peptide mixtures for tandem mass spectrometry-based proteomics: a case study in profiling chromatin-enriched subcellular fractions in Saccharomyces cerevisiae.Anal. Chem. 2005; 77: 3198-3207Crossref PubMed Scopus (56) Google Scholar). For the other neutral and basic fractions, two 125-μl aliquots were combined from each adjacent FFE fraction as these were determined to contain lower numbers of peptides in initial screening experiments. Combining these fractions resulted in an additional 10 fractions. Each of the 250-μl aliquots was subjected to ultrafiltration as described above to remove the high molecular weight hydroxypropylmethylcellulose polymer, and the filtrate was then desalted using a Sep-Pak C18 cartridge (Waters) followed by concentration by vacuum centrifugation. Each peptide fraction was then redissolved in 200 μl of SCX loading buffer (10 mm KH2PO3 containing 20% acetonitrile, pH = 3.0) and loaded onto a preconditioned SCX column at a flow rate of 50 μl/min. After washing with loading buffer and the loading buffer containing 15 mm KCl (to remove loosely retained contaminants), peptides were eluted using step gradient chromatography, using steps with increasing KCl concentration, at a flow rate of 50 μl/min. For the acidic fractions, steps of 20, 25, 50, and 200 mm KCl in loading buffer were collected (200-μl total volume); for neutral and basic samples, slightly adjusted steps of 20, 25, 100, and 200 mm KCl were collected, accounting for the expected presence of more highly charged peptides with more basic peptide pI values compared with the acidic peptides. Each collected fraction was concentrated by vacuum centrifugation and reconstituted in 30 μl of HPLC load buffer. All on-line μLC separations were done on an automated Paradigm MS4 system (Michrom Bioresources, Inc., Auburn, CA). Each processed FFE/SCX fraction was automatically loaded across a Paradigm Platinum Peptide Nanotrap (Michrom Bioresources, Inc.) precolumn (0.15 × 50 mm, 400-μl volume) for sample concentrating and desalting at a flow rate of 50 μl/min in HPLC buffer A (0.1% formic acid in a solution of 5% acetonitrile and 95% water). The in-line analytical capillary column (75 μm × 12 cm) was home-packed using C18 resin (5 μm, 200-Å Magic C18AG, Michrom Bioresources, Inc.) with the exception that the electrospray tip was made with a hand-held torch. Peptides were eluted using a linear gradient of 10–35% HPLC buffer B (0.1% formic acid in a solution of 95% acetonitrile and 5% water) over 60 min followed by isocratic elution at 80% buffer B for 5 min with a flow rate of 0.25 μl/min across the capillary column. All mass spectrometry was done on an LTQ linear ion trap mass spectrometer (Thermo Fisher, Inc.) using Xcalibur version 2.0 operating software. Ionized peptides eluting from the capillary column were automatically selected for MS/MS using a data-dependent procedure that alternated between one MS scan followed by four MS/MS scans for the four most abundant precursor ions in the MS survey scan. Those m/z values selected for MS/MS were dynamically excluded for 30 s using a repeat count of 2. The electrospray voltage applied was 2.0 kV. MS and MS/MS spectra were acquired with a maximum fill time of 50 and 100 ms for MS and MS/MS analysis, respectively. MS spectra were acquired from a single microscan, whereas MS/MS spectra were acquired using two microscans. For MS scans, the m/z
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