Quantitative Mass Spectrometric Multiple Reaction Monitoring Assays for Major Plasma Proteins

Quantitative LC-MS/MS assays were designed for tryptic peptides representing 53 high and medium abundance proteins in human plasma using a multiplexed multiple reaction monitoring (MRM) approach. Of these, 47 produced acceptable quantitative data, demonstrating within-run coefficients of variation (CVs) (n = 10) of 2–22% (78% of assays had CV <10%). A number of peptides gave CVs in the range 2–7% in five experiments (10 replicate runs each) continuously measuring 137 MRMs, demonstrating the precision achievable in complex digests. Depletion of six high abundance proteins by immunosubtraction significantly improved CVs compared with whole plasma, but analytes could be detected in both sample types. Replicate digest and depletion/digest runs yielded correlation coefficients (R2) of 0.995 and 0.989, respectively. Absolute analyte specificity for each peptide was demonstrated using MRM-triggered MS/MS scans. Reliable detection of L-selectin (measured at 0.67 μg/ml) indicates that proteins down to the μg/ml level can be quantitated in plasma with minimal sample preparation, yielding a dynamic range of 4.5 orders of magnitude in a single experiment. Peptide MRM measurements in plasma digests thus provide a rapid and specific assay platform for biomarker validation, one that can be extended to lower abundance proteins by enrichment of specific target peptides (stable isotope standards and capture by anti-peptide antibodies (SISCAPA)). Quantitative LC-MS/MS assays were designed for tryptic peptides representing 53 high and medium abundance proteins in human plasma using a multiplexed multiple reaction monitoring (MRM) approach. Of these, 47 produced acceptable quantitative data, demonstrating within-run coefficients of variation (CVs) (n = 10) of 2–22% (78% of assays had CV <10%). A number of peptides gave CVs in the range 2–7% in five experiments (10 replicate runs each) continuously measuring 137 MRMs, demonstrating the precision achievable in complex digests. Depletion of six high abundance proteins by immunosubtraction significantly improved CVs compared with whole plasma, but analytes could be detected in both sample types. Replicate digest and depletion/digest runs yielded correlation coefficients (R2) of 0.995 and 0.989, respectively. Absolute analyte specificity for each peptide was demonstrated using MRM-triggered MS/MS scans. Reliable detection of L-selectin (measured at 0.67 μg/ml) indicates that proteins down to the μg/ml level can be quantitated in plasma with minimal sample preparation, yielding a dynamic range of 4.5 orders of magnitude in a single experiment. Peptide MRM measurements in plasma digests thus provide a rapid and specific assay platform for biomarker validation, one that can be extended to lower abundance proteins by enrichment of specific target peptides (stable isotope standards and capture by anti-peptide antibodies (SISCAPA)). Accurate quantitation of proteins and peptides in plasma and serum is a challenging problem because of the complexity and extreme dynamic range that characterize these samples (1Anderson N.L. Anderson N.G. The human plasma proteome: history, character, and diagnostic prospects.Mol. Cell. Proteomics. 2002; 1: 845-867Abstract Full Text Full Text PDF PubMed Scopus (3564) Google Scholar). The widely adopted separative (survey) approach to proteomics, in which an attempt is made to detect all components, has proven to be limited in sensitivity toward low abundance proteins (2Anderson N.L. Polanski M. Pieper R. Gatlin T. Tirumalai R.S. Conrads T.P. Veenstra T.D. Adkins J.N. Pounds J.G. Fagan R. Lobley A. The human plasma proteome: a non-redundant list developed by combination of four separate sources.Mol. Cell. Proteomics. 2004; 3: 311-326Abstract Full Text Full Text PDF PubMed Scopus (760) Google Scholar) and typically provides limited quantitative precision. The alternative candidate-based approach, which relies on specific assays optimized for quantitative detection of selected proteins, can provide significantly increased sensitivity (into the pg/ml range) and precision (CVs 1The abbreviations used are: CV, coefficient of variation; QqQ, triple quadrupole; MRM, multiple reaction monitoring; S/N, signal-to-noise; Nat, natural sample-derived peptide; SIS, stable isotope-labeled internal standard; polySIS, polyprotein SIS; SISCAPA, stable isotope standards and capture by anti-peptide antibodies; MIDAS, multiple reaction monitoring-initiated detection and sequencing; MARS, multiple affinity removal system. < 5–10%) at the cost of restricting discovery potential toward novel proteins (3Kuhn E. Wu J. Karl J. Liao H. Zolg W. Guild B. Quantification of C-reactive protein in the serum of patients with rheumatoid arthritis using multiple reaction monitoring mass spectrometry and 13C-labeled peptide standards.Proteomics. 2004; 4: 1175-1186Crossref PubMed Scopus (370) Google Scholar). In practice, a combination of these approaches (one or more survey approaches for de novo biomarker discovery coupled with a candidate-based approach to biomarker validation in large sample sets) appears to provide an effective staged pipeline (4Anderson N.L. The roles of multiple proteomics platforms in a pipeline for new diagnostics.Mol. Cell. Proteomics. 2005; 4: 1441-1444Abstract Full Text Full Text PDF PubMed Scopus (111) Google Scholar) for generation of valid plasma biomarkers of disease, risk, and therapeutic response. Candidate-based specific assays rely on the specificity of capture or detection methods to select a specific molecule as analyte. Capture reagents such as antibodies can provide extreme specificity (particularly when two different antibodies are used as in a sandwich immunoassay) and form the basis of most existing clinical protein assays. There is intense interest in miniaturizing sets of such assays (5Joos T.O. Stoll D. Templin M.F. Miniaturised multiplexed immunoassays.Curr. Opin. Chem. Biol. 2002; 6: 76-80Crossref PubMed Scopus (94) Google Scholar, 6Haab B.B. Antibody arrays in cancer research.Mol. Cell. Proteomics. 2005; 4: 377-383Abstract Full Text Full Text PDF PubMed Scopus (215) Google Scholar) in array formats (on planar substrates, beads, etc.), although significant problems remain in the production of suitable antibodies and in the simultaneous optimization of multiple assays in one fluid volume. Mass spectrometry provides an alternative assay approach, relying on the discriminating power of mass analyzers to select a specific analyte and on ion current measurements for quantitation. In the field of analytical chemistry, many small molecule analytes (e.g. drug metabolites (7Kostiainen R. Kotiaho T. Kuuranne T. Auriola S. Liquid chromatography/atmospheric pressure ionization-mass spectrometry in drug metabolism studies.J. Mass. Spectrom. 2003; 38: 357-372Crossref PubMed Scopus (318) Google Scholar), hormones (8Tai S.S. Bunk D.M. White E.T. Welch M.J. Development and evaluation of a reference measurement procedure for the determination of total 3,3′,5-triiodothyronine in human serum using isotope-dilution liquid chromatography-tandem mass spectrometry.Anal. Chem. 2004; 76: 5092-5096Crossref PubMed Scopus (72) Google Scholar), protein degradation products (9Ahmed N. Thornalley P.J. Quantitative screening of protein biomarkers of early glycation, advanced glycation, oxidation and nitrosation in cellular and extracellular proteins by tandem mass spectrometry multiple reaction monitoring.Biochem. Soc. Trans. 2003; 31: 1417-1422Crossref PubMed Google Scholar), and pesticides (10Sannino A. Bolzoni L. Bandini M. Application of liquid chromatography with electrospray tandem mass spectrometry to the determination of a new generation of pesticides in processed fruits and vegetables.J. Chromatogr. A. 2004; 1036: 161-169Crossref PubMed Scopus (227) Google Scholar)) are routinely measured using this approach at high throughput with great precision (CV < 5%). Most such assays use electrospray ionization followed by two stages of mass selection: a first stage (MS1) selecting the mass of the intact analyte (parent ion) and, after fragmentation of the parent by collision with gas atoms, a second stage (MS2) selecting a specific fragment of the parent, collectively generating a selected reaction monitoring (plural MRM) assay. The two mass filters produce a very specific and sensitive response for the selected analyte that can be used to detect and integrate a peak in a simple one-dimensional chromatographic separation of the sample. In principle, this MS-based approach can provide absolute structural specificity for the analyte, and in combination with appropriate stable isotope-labeled internal standards (SISs), it can provide absolute quantitation of analyte concentration. These measurements have been multiplexed to provide 30 or more specific assays in one run (11Barr D.B. Barr J.R. Maggio V.L. Whitehead Jr., R.D. Sadowski M.A. Whyatt R.M. Needham L.L. A multi-analyte method for the quantification of contemporary pesticides in human serum and plasma using high-resolution mass spectrometry.J. Chromatogr. B. Anal. Technol. Biomed. Life Sci. 2002; 778: 99-111Crossref PubMed Scopus (148) Google Scholar). Such methods are slowly gaining acceptance in the clinical laboratory for the routine measurement of endogenous metabolites (e.g. in screening newborns for a panel of inborn errors of metabolism (12Roschinger W. Olgemoller B. Fingerhut R. Liebl B. Roscher A.A. Advances in analytical mass spectrometry to improve screening for inherited metabolic diseases.Eur. J. Pediatr. 2003; 162: S67-S76Crossref PubMed Google Scholar)) and some drugs (e.g. immunosuppressants (13Streit F. Armstrong V.W. Oellerich M. Rapid liquid chromatography-tandem mass spectrometry routine method for simultaneous determination of sirolimus, everolimus, tacrolimus, and cyclosporin a in whole blood.Clin. Chem. 2002; 48: 955-958Crossref PubMed Scopus (184) Google Scholar)). Recently the MRM assay approach has been applied to the measurement of specific peptides in complex mixtures such as tryptic digests of plasma (3Kuhn E. Wu J. Karl J. Liao H. Zolg W. Guild B. Quantification of C-reactive protein in the serum of patients with rheumatoid arthritis using multiple reaction monitoring mass spectrometry and 13C-labeled peptide standards.Proteomics. 2004; 4: 1175-1186Crossref PubMed Scopus (370) Google Scholar). In this case, a specific tryptic peptide can be selected as a stoichiometric representative of the protein from which it is cleaved and quantitated against a spiked internal standard (a synthetic stable isotope-labeled peptide (14Gerber S.A. Rush J. Stemman O. Kirschner M.W. Gygi S.P. Absolute quantification of proteins and phosphoproteins from cell lysates by tandem MS.Proc. Natl. Acad. Sci. U. S. A. 2003; 100: 6940-6945Crossref PubMed Scopus (1549) Google Scholar)) to yield a measure of protein concentration. In principle, such an assay requires only knowledge of the masses of the selected peptide and its fragment ions and an ability to make the stable isotope-labeled version. C-reactive protein (3Kuhn E. Wu J. Karl J. Liao H. Zolg W. Guild B. Quantification of C-reactive protein in the serum of patients with rheumatoid arthritis using multiple reaction monitoring mass spectrometry and 13C-labeled peptide standards.Proteomics. 2004; 4: 1175-1186Crossref PubMed Scopus (370) Google Scholar), apolipoprotein A-I (15Barr J.R. Maggio V.L. Patterson Jr., D.G. Cooper G.R. Henderson L.O. Turner W.E. Smith S.J. Hannon W.H. Needham L.L. Sampson E.J. Isotope dilution-mass spectrometric quantification of specific proteins: model application with apolipoprotein A-I.Clin. Chem. 1996; 42: 1676-1682Crossref PubMed Scopus (321) Google Scholar), human growth hormone (16Wu S.L. Amato H. Biringer R. Choudhary G. Shieh P. Hancock W.S. Targeted proteomics of low-level proteins in human plasma by LC/MSn: using human growth hormone as a model system.J. Proteome Res. 2002; 1: 459-465Crossref PubMed Scopus (123) Google Scholar), and prostate-specific antigen (17Barnidge D.R. Goodmanson M.K. Klee G.G. Muddiman D.C. Absolute quantification of the model biomarker prostate-specific antigen in serum by LC-MS/MS using protein cleavage and isotope dilution mass spectrometry.J. Proteome Res. 2004; 3: 644-652Crossref PubMed Scopus (244) Google Scholar) have been measured in plasma or serum using this approach. Because the sensitivity of these assays is limited by mass spectrometer dynamic range and by the capacity and resolution of the assisting chromatography separation(s), hybrid methods have also been developed coupling MRM assays with enrichment of proteins by immunodepletion and size exclusion chromatography (18Liao H. Wu J. Kuhn E. Chin W. Chang B. Jones M.D. O'Neil S. Clauser K.R. Karl J. Hasler F. Roubenoff R. Zolg W. Guild B.C. Use of mass spectrometry to identify protein biomarkers of disease severity in the synovial fluid and serum of patients with rheumatoid arthritis.Arthritis Rheum. 2004; 50: 3792-3803Crossref PubMed Scopus (239) Google Scholar) or enrichment of peptides by antibody capture (SISCAPA (19Anderson N.L. Anderson N.G. Haines L.R. Hardie D.B. Olafson R.W. Pearson T.W. Mass spectrometric quantitation of peptides and proteins using stable isotope standards and capture by anti-peptide antibodies (SISCAPA).J. Proteome Res. 2004; 3: 235-244Crossref PubMed Scopus (696) Google Scholar)). In essence the latter approach uses the mass spectrometer as a "second antibody" that has absolute structural specificity. SISCAPA has been shown to extend the sensitivity of a peptide assay by at least 2 orders of magnitude (19Anderson N.L. Anderson N.G. Haines L.R. Hardie D.B. Olafson R.W. Pearson T.W. Mass spectrometric quantitation of peptides and proteins using stable isotope standards and capture by anti-peptide antibodies (SISCAPA).J. Proteome Res. 2004; 3: 235-244Crossref PubMed Scopus (696) Google Scholar) and with further development appears capable of extending the MRM method to cover the full known dynamic range of plasma (i.e. to the pg/ml level). There is compelling evidence that high and medium abundance plasma proteins have value as clinical biomarkers and thus that there may be applications for specific MRM assays even without antibody enrichment. One may therefore ask how many plasma proteins can be measured by quantitating their peptides in a plasma digest, and how precise could these measurements be? If the measurement strategy proves to be robust, could it be carried out using existing high throughput LC-MS/MS platforms? To address these questions we generated and tested MRM assays based on peptides from a variety of high to medium abundance plasma proteins to see how many could be measured effectively by LC-MS/MS with and without subtraction of the most abundant proteins. An understanding of the performance of MS/MS in this application could enable routine and relatively inexpensive measurement of classical plasma proteins and also provide a foundation for use of MS/MS in more sensitive anti-peptide antibody-enhanced SISCAPA assays for low abundance proteins. We developed a set of MRMs iteratively using three basic approaches: pure in silico design from sequence databases, design from available LC-MS/MS proteomic survey data, and comprehensive MRM testing of all of the candidate peptides of a protein. In our initial attempt to generate MRMs by purely in silico methods, a set of 177 proteins and protein forms was assembled that are demonstrated or have potential to be plasma markers of some aspect of cardiovascular disease (20Anderson N.L. Candidate-based proteomics in the search for biomarkers of cardiovascular disease.J. Physiol. 2005; 563: 23-60Crossref PubMed Scopus (316) Google Scholar), and a subset of 62 proteins was selected for which an estimate of normal plasma abundance was available. Predicted tryptic peptides for each of these were generated along with relevant Swiss-Prot annotations and a series of computed physicochemical parameters: e.g. amino acid composition, peptide mass, Hopp-Woods hydrophilicity (21Hopp T.P. Woods K.R. Prediction of protein antigenic determinants from amino acid sequences.Proc. Natl. Acad. Sci. U. S. A. 1981; 78: 3824-3828Crossref PubMed Scopus (2912) Google Scholar), and predicted retention time in reversed-phase (C18) chromatography (22Krokhin O.V. Craig R. Spicer V. Ens W. Standing K.G. Beavis R.C. Wilkins J.A. An improved model for prediction of retention times of tryptic peptides in ion pair reversed-phase HPLC: its application to protein peptide mapping by off-line HPLC-MALDI MS.Mol. Cell. Proteomics. 2004; 3: 908-919Abstract Full Text Full Text PDF PubMed Scopus (246) Google Scholar). An index of the likelihood of experimental detection was derived from a data set reported by Adkins et al. (23Adkins J.N. Varnum S.M. Auberry K.J. Moore R.J. Angell N.H. Smith R.D. Springer D.L. Pounds J.G. Toward a human blood serum proteome: analysis by multidimensional separation coupled with mass spectrometry.Mol. Cell. Proteomics. 2002; 1: 947-955Abstract Full Text Full Text PDF PubMed Scopus (719) Google Scholar) by counting the number of separate "hits" for the peptide in the data set divided by the number of hits for the most frequently detected peptide from the same protein. An overall index of peptide quality was generated according to a formula that gave positive weights to Pro, KP, RP, and DP content and negative weights to Cys, Trp, Met, chymotrypsin sites, certain Swiss-Prot features (carbohydrate attachment, modified residues, sequence conflicts, or genetic variants), and mass less than 800 or greater than 2000. The 3619 tryptic peptides predicted for the 62 protein marker candidates (6–497 peptides per target) ranged in length from 1 to 285 amino acids. Within the useful range of 8–24 amino acids, 721 peptides had a C-terminal Lys and 690 had a C-terminal Arg. In this report, peptides from 30 of these target proteins ending in C-terminal Lys were selected for further study. We also selected peptides based on two types of direct proteomic survey experiments. In the first case we carried out classical LC-MS/MS analysis of plasma digests in which the major ions observed were subjected to MS/MS using the ion trap capabilities of the 4000 Q TRAP instrument. The identified peptides showing the best signal intensity and chromatographic peak shape for a given parent protein were selected. In addition, we used the Global Proteome Machine database of Craig et al. (24Craig R. Cortens J.P. Beavis R.C. Open source system for analyzing, validating, and storing protein identification data.J. Proteome Res. 2004; 3: 1234-1242Crossref PubMed Scopus (578) Google Scholar) to select peptides from target proteins that were frequently detected (multiple experiments). Finally we used an adaptation of the MIDAS workflow, described previously for discovering post-translational modifications (25Unwin R.D. Griffiths J.R. Leverentz M.K. Grallert A. Hagan I.M. Whetton A.D. Multiple reaction monitoring to identify sites of protein phosphorylation with high sensitivity.Mol. Cell. Proteomics. 2005; 4: 1134-1144Abstract Full Text Full Text PDF PubMed Scopus (188) Google Scholar, 26Cox D.M. Zhong F. Du M. Duchoslav E. Sakuma T. McDermott J.C. Multiple reaction monitoring as a method for identifying protein posttranslational modifications.J. Biomol. Tech. 2005; 16: 83-90PubMed Google Scholar), to look for measurable tryptic peptides from a variety of plasma proteins. In this approach, the protein sequence is digested in silico, likely y-ion fragments are predicted, and theoretical MRMs are generated for all the peptides in an acceptable size window. These MRMs are then used as a survey scan in a data-dependent experiment to detect specific peptide peaks, and each resulting MRM peak is examined by full scan MS/MS to obtain sequence verification of the hypothesized peptide. To verify peptide specificity in designated protein targets, selected peptides were searched with BLASTP for exact matches against the genome-derived human, mouse, and rat Ensembl peptides using Ensembl Blastview (www.ensembl.org/Homo_sapiens/blastview). Two approaches were used to generate pseudorandom MRMs. In the first case we used 100 MS1 values distributed randomly (by the Excel RAND function) between 408.5 and 1290.2 (the maximum and minimum of an early set of real MRMs we tested) paired with MS2 values chosen randomly between this MS1 and the maximum of the real MRMs (1495.6), thus mimicking the properties of our real MRMs (which are generally +2 charge state peptides and +1 charge fragments). In a second set we paired 131 MS1 values chosen randomly from among MS1 values in a large table of real MRMs with MS2 values chosen randomly from the real MS2 values of the same list, imposing only the constraint that each MS2 had to be between 1 and 2 times the paired MS1 mass (to approximate our selection criteria for real MRMs). Peaks detected in these MRMs were examined by triggering MS/MS (the MIDAS workflow). The following chemicals were used: trypsin (Promega), sodium dodecyl sulfate (Bio-Rad), iodoacetamide (Sigma), formic acid (Sigma), tris-(2-carboxyethyl)phosphine (Sigma), and acetonitrile (Burdick and Jackson). All experiments were performed on aliquots of a single human plasma sample from a normal volunteer. The six highest abundance proteins were depleted from plasma using the multiple affinity removal system ("MARS"; Agilent Technologies spin columns) according to the manufacturer's protocol. Depleted sample was then exchanged into 50 mM ammonium bicarbonate using a VivaSpin concentrator (5000 molecular weight cutoff, VivaScience). Undepleted plasma was also desalted before digestion. Both depleted or undepleted plasma samples were denatured and reduced by incubating proteins in 0.05% SDS and 5 mM tris-(2-carboxyethyl)phosphine at 60 °C for 15 min. The sample was then adjusted to 10 mM with iodoacetamide and incubated for 15 min at 25 °C in the dark. Trypsin was added in one aliquot (protease:protein ratio of 1:20) and incubated for 5 h at 37 °C. A series of SIS peptides was added to samples in selected experiments by spiking with the tryptic digest of a "polySIS" polyprotein. 2L. Anderson and C. L. Hunter, manuscript in preparation. Briefly this protein was produced by cell-free transcription and translation of a synthetic gene coding for 30 concatenated tryptic peptide sequences (derived from 30 plasma proteins) in the presence of U-13C6,U-15N2-labeled lysine (a total mass increment of 8 amu compared with the natural peptide). The 30 peptides were selected based on our initial in silico MRM design approaches and are thus not fully optimized using experimental data. Of these peptides, 13 were used in the present studies (the remainder were not reproducibly detected in digested plasma with peak area >1E+04). The positioning of the label atoms at the extreme C terminus of each peptide has the effect that all fragments that contain the C terminus (i.e. the y-ions) will show the mass shift due to the label, whereas all the fragments that contain the N terminus (and hence have lost one of more C-terminal residues: the b-series ions) will have the same masses as the corresponding fragments from the natural (sample-derived) target protein. These features (shifted y-ions and normal b-ions) provide a simplification in interpreting the fragmentation patterns of the SIS peptides in comparison with the similar QCAT concept described recently by Beynon et al. (27Beynon R.J. Doherty M.K. Pratt J.M. Gaskell S.J. Multiplexed absolute quantification in proteomics using artificial QCAT proteins of concatenated signature peptides.Nat. Methods. 2005; 2: 587-589Crossref PubMed Scopus (395) Google Scholar). To determine the absolute concentration of polySIS protein, an aliquot was diluted with 1 M urea, 0.05% SDS, and 50 mM Tris, pH 8 and subjected to N-terminal Edman sequencing, yielding an initial concentration of 5 ± 1 pmol/μl. A tryptic digest of the polySIS protein was spiked into whole and depleted human plasma digests at the final concentrations shown in Table I.Table ISummary design of data sets (experiments A–F)ExperimentReplicate runsSampleLC systemEquivalent plasma volume loadedLoad factorPolySIS spikeTotal proteinNon-depleted proteinsμlfmolA10Depleted plasma digestLC Packings0.01111.3B10Whole plasma digestLC Packings0.011011.3C10Whole plasma digestEksigent0.00160.12.0D10Depleted plasma digestEksigent0.010.612.0E10Depleted plasma digestEksigent0.0333.33.36.0F1_14Depletion 1, digest 1Eksigent0.0111F1_24Depletion 1, digest 2Eksigent0.0111F2_14Depletion 2, digest 1Eksigent0.0111F2_24Depletion 2, digest 2Eksigent0.0111 Open table in a new tab Plasma digests with and without added polySIS peptides were analyzed by electrospray LC-MS/MS using LC Packings (a division of Dionex, Synnyvale, CA) or Eksigent nanoflow LC systems (Table I) with 75-μm-diameter C18 PepMap reversed-phase columns (LC Packings) and eluted with gradients of 3–30% acetonitrile with 0.1% formic acid. A column oven (Keystone Scientific, Inc.) was used to maintain the column temperature at 35 °C. Electrospray MS data were collected using the NanoSpray® source on a 4000 Q TRAP hybrid triple quadrupole/linear ion trap instrument (Applied Biosystems/MDS Sciex), and the peaks were integrated using quantitation procedures in the Analyst software 1.4.1 (IntelliQuan algorithm). MRM transitions were acquired at unit resolution in both the Q1 and Q3 quadrupoles to maximize specificity. In an initial approach to the selection of representative peptides for MRM assays, a single peptide of 8–18 amino acids was chosen from each of 30 proteins spanning a broad range of plasma concentrations (6.6 × 108 down to 1 fmol/ml normal concentration) based on computed characteristics alone (19Anderson N.L. Anderson N.G. Haines L.R. Hardie D.B. Olafson R.W. Pearson T.W. Mass spectrometric quantitation of peptides and proteins using stable isotope standards and capture by anti-peptide antibodies (SISCAPA).J. Proteome Res. 2004; 3: 235-244Crossref PubMed Scopus (696) Google Scholar). MRMs were designed assuming doubly charged peptide ions and using fragments selected as likely y-ions above the m/z of the 2+ parent ion with collision energies assigned by a generic formula (CE = 0.05 × m/z + 5), and the peptides were expressed as a concatamer polySIS protein containing single copies of each peptide labeled with [U-13C6,U-15N2]lysine. When a tryptic digest of the polySIS was analyzed, all 30 peptides were detected by MRMs. When a digest of whole human plasma was added to the polySIS peptides, 19 of the labeled polySIS peptides were still detected by the same MRMs, but only 11 of the plasma digest-derived unlabeled cognate peptides were detected (by the same MRMs adjusted for isotope label masses). Because different peptides from a single protein can vary widely in detectability by ESI-MS, we attempted to improve upon the in silico approach to MRM design using experimental data from a conventional peptide survey scan of a human plasma digest and applying the selection criteria to peptides with demonstrated detectability. Using a 3-h LC gradient, MS/MS scans were collected for the major doubly or triply charged ions across the separation using information-dependent data acquisition, and a second run was performed using time-filtered exclusions of the peptide ions detected in the first run. The combined results identified 54 plasma proteins ranging in abundance from albumin down to fibronectin (normal plasma concentration of ∼300 μg/ml). This experimental MS/MS data provided explicit information for peptide selection, charge state, and most abundant y-ion m/z value under the specific conditions used (i.e. electrospray ionization with collisional peptide fragmentation), allowing improved design of MRMs. When these MRMs were then used to analyze the same sample in a subsequent run, triggering MS/MS scans at any MRM signal, most of the peptides were detected as peaks in the chromatogram and identified by database search as expected. In most of these MRM chromatograms, only a single peak was detected. Because peptide detection sensitivity using MRM is expected to be greater than that achieved in a full scan MS survey approach, a comprehensive de novo MRM design method was explored for those proteins not detected in the above survey experiment. Using a novel software tool, a large set of MRMs was generated for each of a series of target proteins by selecting all predicted tryptic peptides in a useful size range together with multiple high mass y-ion fragments of each (the "MIDAS" workflow (25Unwin R.D. Griffiths J.R. Leverentz M.K. Grallert A. Hagan I.M. Whetton A.D. Multiple reaction monitoring to identify sites of protein phosphorylation with high sensitivity.Mol. Cell. Proteomics. 2005; 4: 1134-1144Abstract Full Text Full Text PDF PubMed Scopus (188) Google Scholar, 26Cox D.M. Zhong F. Du M. Duchoslav E. Sakuma T. McDermott J.C. Multiple reaction monitoring as a method for identifying protein posttranslational modifications.J. Biomol. Tech. 2005; 16: 83-90PubMed Google Scholar)). These MRMs were then tested in LC-MS/MS runs of the unfractionated plasma digest, grouped in panels that included all the predicted tryptic peptides of one or two proteins at a time (50–100 MRMs per run), with MS/MS scans triggered on any peaks observed. Of 12 proteins examined, nine produced at least one usable MRM (signal-to-noise (S/N) ratio >20). MRM results from the above approaches were pooled, and a set of optimized MRMs was assembled that covered a total of 60 peptides representing 53 proteins in human plasma (Table II; seven proteins were represented by two peptides). This set includes 18 peptides selected by the in silico approach (indicated by an X in the SIS column of Table II):