Stable isotope-labeling of DNA repair proteins, and their purification and characterization

Reduced DNA repair capacity is associated with increased risk for a variety of disease processes including carcinogenesis. Thus, DNA repair proteins have the potential to be used as important predictive, prognostic and therapeutic biomarkers in cancer and other diseases. The measurement of the expression level of these enzymes may be an excellent tool for this purpose. Mass spectrometry is becoming the technique of choice for the identification and quantification of proteins. However, suitable internal standards must be used to ensure the precision and accuracy of measurements. An ideal internal standard in this case would be a stable isotope-labeled analog of the analyte protein. In the present work, we over-expressed, purified and characterized two stable isotope-labeled DNA glycosylases, i.e., (15)N-labeled Escherichia coli formamidopyrimidine DNA glycosylase (Fpg) and (15)N-labeled human 8-oxoguanine-DNA glycosylase (hOGG1). DNA glycosylases are involved in the first step of the base excision repair of oxidatively induced DNA damage by removing modified DNA bases. The measurement by MALDI-ToF mass spectrometry of the molecular mass and isotopic purity proved the identity of the (15)N-labeled proteins and showed that the (15)N-labeling of both proteins was more than 99.7%. We also measured the DNA glycosylase activities using gas chromatography/mass spectrometry with isotope-dilution. The enzymic activities of both (15)N-labeled Fpg and (15)N-labeled hOGG1 were essentially identical to those of their respective unlabeled counterparts, ascertaining that the labeling did not perturb their catalytic sites. The procedures described in this work may be used for obtaining stable isotope-labeled analogs of other DNA repair proteins for mass spectrometric measurements of these proteins as disease biomarkers.     

Absolute quantification of the model biomarker prostate-specific antigen in serum by LC-Ms/MS using protein cleavage and isotope dilution mass spectrometry

Protein cleavage-isotope dilution mass spectrometry (PC-IDMS) can be used to quantify proteins, with an isotope-labeled analogue of the peptide fragment used as an internal standard. Here, we investigate use of a standard LC-MS/MS platform for quantifying a model biomarker directly from serum by this technique. We synthesized a peptide (IVGGWECEK) identical to the N-terminal tryptic fragment of PSA but with each glycine containing two 13C atoms and one 15N atom. PSA-free human serum was denatured with urea followed by the introduction of PSA standard and the stable isotope labeled internal standard peptide. The sample was then proteolyzed with trypsin and subjected to quantification using LC-MS/ MS on a triple quadrupole mass spectrometer. A linear least squares calibration curve made from five different concentrations of PSA added to serum and digested (each made in triplicate and randomly injected three times) had a mean slope of 0.973 (SE = 0.023), intercept of -0.003 (SE = 0.022), and R2 of 0.971. Recovery of calibrators ranged from 70 to 85% with a mean run-to-run CV of 13% and a mean within-run CV of 5.7%. PC-IDMS is a promising technique for quantifying proteins covering a broad range of applications from standardizing immunoassays to monitoring post-translational modifications to quantifying newly discovered biomarkers prior to the development and implementation of an immunoassay, just to name a few. Issues surrounding the application of PC-IDMS for the absolute quantification of proteins include selection of a proteolytic fragment for quantification that can be cleaved and isolated reproducibly over a broad dynamic range, stable isotope labeled synthetic peptide standards that give consistent results, and LC-MS/MS methods that provide adequate sensitivity and reproducibility without creating impractical analysis times. The results presented here show that absolute quantification can be performed on the model biomarker PSA introduced into denatured serum when analyzed by LC-MS/MS. However, concerns still exist regarding sensitivity compared to existing immunoassays as well as the reproducibility of PC-IDMS performed in different matrixes.     

Validation of peptide MS/MS spectra using metabolic isotope labeling for spectral matching-based shotgun proteome analysis

We report an isotope labeling shotgun proteome analysis strategy to validate the spectrum-to-sequence assignments generated by using sequence-database searching for the construction of a more reliable MS/MS spectral library. This strategy is demonstrated in the analysis of the E. coli K12 proteome. In the workflow, E. coli cells were cultured in normal and (15)N-enriched media. The differentially labeled proteins from the cell extracts were subjected to trypsin digestion and two-dimensional liquid chromatography quadrupole time-of-flight tandem mass spectrometry (2D-LC QTOF MS/MS) analysis. The MS/MS spectra of the two samples were individually searched using Mascot against the E. coli proteome database to generate lists of peptide sequence matches. The two data sets were compared by overlaying the spectra of unlabeled and labeled matches of the same peptide sequence for validation. Two cutoff filters, one based on the number of common fragment ions and another one on the similarity of intensity patterns among the common ions, were developed and applied to the overlaid spectral pairs to reject the low quality or incorrectly assigned spectra. By examining 257,907 and 245,156 spectra acquired from the unlabeled and (15)N-labeled samples, respectively, an experimentally validated MS/MS spectral library of tryptic peptides was constructed for E. coli K12 that consisted of 9,302 unique spectra with unique sequence and charge state, representing 7,763 unique peptide sequences. This E. coli spectral library could be readily expanded, and the overall strategy should be applicable to other organisms. Even with this relatively small library, it was shown that more peptides could be identified with higher confidence using the spectral search method than by sequence-database searching.     

Automated comparative proteomics based on multiplex tandem mass spectrometry and stable isotope labeling

Comparative proteomic approaches using isotopic labeling and MS have become increasingly popular. Conventionally quantification is based on MS or extracted ion chromatogram (XIC) signals of differentially labeled peptides. However, in these MS-based experiments, the accuracy and dynamic range of quantification are limited by the high noise levels of MS/XIC data. Here we report a quantitative strategy based on multiplex (derived from multiple precursor ions) MS/MS data. One set of proteins was metabolically labeled with [13C6]lysine and [15N4]arginine; the other set was unlabeled. For peptide analysis after tryptic digestion of the labeled proteins, a wide precursor window was used to include both the light and heavy versions of each peptide for fragmentation. The multiplex MS/MS data were used for both protein identification and quantification. The use of the wide precursor window increased sensitivity, and the y ion pairs in the multiplex MS/MS spectra from peptides containing labeled and unlabeled lysine or arginine offered more information for, and thus the potential for improving, protein identification. Protein ratios were obtained by comparing intensities of y ions derived from the light and heavy peptides. Our results indicated that this method offers several advantages over the conventional XIC-based approach, including increased sensitivity for protein identification and more accurate quantification with more than a 10-fold increase in dynamic range. In addition, the quantification calculation process was fast, fully automated, and independent of instrument and data type. This method was further validated by quantitative analysis of signaling proteins in the EphB2 pathway in NG108 cells.     

Two-dimensional mass spectra generated from the analysis of 15N-labeled and unlabeled peptides for efficient protein identification and de novo peptide sequencing

Protein identification has been greatly facilitated by database searches against protein sequences derived from product ion spectra of peptides. This approach is primarily based on the use of fragment ion mass information contained in a MS/MS spectrum. Unambiguous protein identification from a spectrum with low sequence coverage or poor spectral quality can be a major challenge. We present a two-dimensional (2D) mass spectrometric method in which the numbers of nitrogen atoms in the molecular ion and the fragment ions are used to provide additional discriminating power for much improved protein identification and de novo peptide sequencing. The nitrogen number is determined by analyzing the mass difference of corresponding peak pairs in overlaid spectra of (15)N-labeled and unlabeled peptides. These peptides are produced by enzymatic or chemical cleavage of proteins from cells grown in (15)N-enriched and normal media, respectively. It is demonstrated that, using 2D information, i.e., m/z and its associated nitrogen number, this method can, not only confirm protein identification results generated by MS/MS database searching, but also identify peptides that are not possible to identify by database searching alone. Examples are presented of analyzing Escherichia coli K12 extracts that yielded relatively poor MS/MS spectra, presumably from the digests of low abundance proteins, which can still give positive protein identification using this method. Additionally, this 2D MS method can facilitate spectral interpretation for de novo peptide sequencing and identification of posttranslational or other chemical modifications. We envision that this method should be particularly useful for proteome expression profiling of organelles or cells that can be grown in (15)N-enriched media.     

Relative quantification of serum proteins from pancreatic ductal adenocarcinoma patients by stable isotope dilution liquid chromatography-mass spectrometry

We report an innovative multiplexed liquidchromatography-multiple reaction monitoring/mass spectrometry (LC-MRM/MS)-based assay for rapidly measuring a large number of disease specific protein biomarkers in human serum. Furthermore, this approach uses stable isotope dilution methodology to reliably quantify candidate protein biomarkers. Human serum was diluted using a stable isotope labeled proteome (SILAP) standard prepared from the secretome of pancreatic cell lines, subjected to immunoaffinity removal of the most highly abundant proteins, trypsin digested, and analyzed by LC-MRM/MS. The method was found to be precise, linear, and specific for the relative quantification of 72 proteins when analyte response was normalized to the relevant internal standard (IS) from the SILAP. The method made it possible to determine statistically different concentrations for three proteins (cystatin M, IGF binding protein 7, and villin 2) in control and pancreatic cancer patient samples. This method proves the feasibility of using a SILAP standard in combination with stable isotope dilution LC-MRM/MS analysis of tryptic peptides to compare changes in the concentration of candidate protein biomarkers in human serum.     

Absolute multiplexed quantitative analysis of protein expression during muscle development using QconCAT

Stable isotope-labeled proteotypic peptides are used as surrogate standards for absolute quantification of proteins in proteomics. However, a stable isotope-labeled peptide has to be synthesized, at relatively high cost, for each protein to be quantified. To multiplex protein quantification, we developed a method in which gene design de novo is used to create and express artificial proteins (QconCATs) comprising a concatenation of proteotypic peptides. This permits absolute quantification of multiple proteins in a single experiment. This complete study was constructed to define the nature, sources of error, and statistical behavior of a QconCAT analysis. The QconCAT protein was designed to contain one tryptic peptide from 20 proteins present in the soluble fraction of chicken skeletal muscle. Optimized DNA sequences encoding these peptides were concatenated and inserted into a vector for high level expression in Escherichia coli. The protein was expressed in a minimal medium containing amino acids selectively labeled with stable isotopes, creating an equimolar series of uniformly labeled proteotypic peptides. The labeled QconCAT protein, purified by affinity chromatography and quantified, was added to a homogenized muscle preparation in a known amount prior to proteolytic digestion with trypsin. As anticipated, the QconCAT was completely digested at a rate far higher than the analyte proteins, confirming the applicability of such artificial proteins for multiplexed quantification. The nature of the technical variance was assessed and compared with the biological variance in a complete study. Alternative ionization and mass spectrometric approaches were investigated, particularly LC-ESI-TOF MS and MALDI-TOF MS, for analysis of proteins and tryptic peptides. QconCATs offer a new and efficient approach to precise and simultaneous absolute quantification of multiple proteins, subproteomes, or even entire proteomes.     

Relative protein quantification by isobaric SILAC with immonium ion splitting (ISIS)

Metabolic labeling techniques have recently become popular tools for the quantitative profiling of proteomes. Classical stable isotope labeling with amino acids in cell cultures (SILAC) uses pairs of heavy/light isotopic forms of amino acids to introduce predictable mass differences in protein samples to be compared. After proteolysis, pairs of cognate precursor peptides can be correlated, and their intensities can be used for mass spectrometry-based relative protein quantification. We present an alternative SILAC approach by which two cell cultures are grown in media containing isobaric forms of amino acids, labeled either with 13C on the carbonyl (C-1) carbon or 15N on backbone nitrogen. Labeled peptides from both samples have the same nominal mass and nearly identical MS/MS spectra but generate upon fragmentation distinct immonium ions separated by 1 amu. When labeled protein samples are mixed, the intensities of these immonium ions can be used for the relative quantification of the parent proteins. We validated the labeling of cellular proteins with valine, isoleucine, and leucine with coverage of 97% of all tryptic peptides. We improved the sensitivity for the detection of the quantification ions on a pulsing instrument by using a specific fast scan event. The analysis of a protein mixture with a known heavy/light ratio showed reliable quantification. Finally the application of the technique to the analysis of two melanoma cell lines yielded quantitative data consistent with those obtained by a classical two-dimensional DIGE analysis of the same samples. Our method combines the features of the SILAC technique with the advantages of isobaric labeling schemes like iTRAQ. We discuss advantages and disadvantages of isobaric SILAC with immonium ion splitting as well as possible ways to improve it.     

Perfluorooctanoic acid for shotgun proteomics

Here, we describe the novel use of a volatile surfactant, perfluorooctanoic acid (PFOA), for shotgun proteomics. PFOA was found to solubilize membrane proteins as effectively as sodium dodecyl sulfate (SDS). PFOA concentrations up to 0.5% (w/v) did not significantly inhibit trypsin activity. The unique features of PFOA allowed us to develop a single-tube shotgun proteomics method that used all volatile chemicals that could easily be removed by evaporation prior to mass spectrometry analysis. The experimental procedures involved: 1) extraction of proteins in 2% PFOA; 2) reduction of cystine residues with triethyl phosphine and their S-alkylation with iodoethanol; 3) trypsin digestion of proteins in 0.5% PFOA; 4) removal of PFOA by evaporation; and 5) LC-MS/MS analysis of the resulting peptides. The general applicability of the method was demonstrated with the membrane preparation of photoreceptor outer segments. We identified 75 proteins from 1 μg of the tryptic peptides in a single, 1-hour, LC-MS/MS run. About 67% of the proteins identified were classified as membrane proteins. We also demonstrate that a proteolytic (18)O labeling procedure can be incorporated after the PFOA removal step for quantitative proteomic experiments. The present method does not require sample clean-up devices such as solid-phase extractions and membrane filters, so no proteins/peptides are lost in any experimental steps. Thus, this single-tube shotgun proteomics method overcomes the major drawbacks of surfactant use in proteomic experiments.     

Addressing trypsin bias in large scale (phospho)proteome analysis by size exclusion chromatography and secondary digestion of large post-trypsin peptides

In the vast majority of bottom-up proteomics studies, protein digestion is performed using only mammalian trypsin. Although it is clearly the best enzyme available, the sole use of trypsin rarely leads to complete sequence coverage, even for abundant proteins. It is commonly assumed that this is because many tryptic peptides are either too short or too long to be identified by RPLC-MS/MS. We show through in silico analysis that 20-30% of the total sequence of three proteomes (Schizosaccharomyces pombe, Saccharomyces cerevisiae, and Homo sapiens) is expected to be covered by Large post-Trypsin Peptides (LpTPs) with M(r) above 3000 Da. We then established size exclusion chromatography to fractionate complex yeast tryptic digests into pools of peptides based on size. We found that secondary digestion of LpTPs followed by LC-MS/MS analysis leads to a significant increase in identified proteins and a 32-50% relative increase in average sequence coverage compared to trypsin digestion alone. Application of the developed strategy to analyze the phosphoproteomes of S. pombe and of a human cell line identified a significant fraction of novel phosphosites. Overall our data indicate that specific targeting of LpTPs can complement standard bottom-up workflows to reveal a largely neglected portion of the proteome.     

Label-free mass spectrometry-based relative quantification of proteins separated by one-dimensional gel electrophoresis

Here we present a matrix-assisted laser desorption/ionization tandem time-of-flight (MALDI–TOF/TOF)-based label-free relative protein quantification strategy that involves sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS–PAGE) separation of proteins followed by in-gel trypsin digestion. The main problem encountered in gel-based protein quantification is the difficulty in achieving complete and consistent proteolytic digestion. To solve this problem, we developed a high-pressure-assisted in-gel trypsin digestion method that is based on pressure cycling technology (PCT). The PCT approach performed at least as well as the conventional overnight in-gel trypsin digestion approach in parameters such as number of peaks detected, number of peptides identified, and sequence coverage, and the digestion time was reduced to 45 min. The gel/mass spectrometry (MS)-based label-free protein quantification method presented in this work proved the applicability of the signal response factor concept for relative protein quantification previously demonstrated by other groups using the liquid chromatography (LC)/MS platform. By normalizing the average signal intensities of the three most intense peptides of each protein with the average intensities of spiked synthetic catalase tryptic peptides, which we used as an internal standard, we observed spot-to-spot and lane-to-lane coefficients of variation of less than 10 and 20%, respectively. We also demonstrated that the method can be used for determining the relative quantities of proteins comigrating during electrophoretic separation.     

Computational approach for identification and characterization of GPI-anchored peptides in proteomics experiments

Genes that encode glycosylphosphatidylinositol anchored proteins (GPI-APs) constitute an estimated 1-2% of eukaryote genomes. Current computational methods for the prediction of GPI-APs are sensitive and specific; however, the analysis of the processing site (omega- or omega-site) of GPI-APs is still challenging. Only 10% of the proteins that are annotated as GPI-APs have the omega-site experimentally verified. We describe an integrated computational and experimental proteomics approach for the identification and characterization of GPI-APs that provides the means to identify GPI-APs and the derived GPI-anchored peptides in LC-MS/MS data sets. The method takes advantage of sequence features of GPI-APs and the known core structure of the GPI-anchor. The first stage of the analysis encompasses LC-MS/MS based protein identification. The second stage involves prediction of the processing sites of the identified GPI-APs and prediction of the corresponding terminal tryptic peptides. The third stage calculates possible GPI structures on the peptides from stage two. The fourth stage calculates the scores by comparing the theoretical spectra of the predicted GPI-peptides against the observed MS/MS spectra. Automated identification of C-terminal GPI-peptides from porcine membrane dipeptidase, folate receptor and CD59 in complex LC-MS/MS data sets demonstrates the sensitivity and specificity of this integrated computational and experimental approach.     

A systematical analysis of tryptic peptide identification with reverse phase liquid chromatography and electrospray ion trap mass spectrometry

In this study we systematically analyzed the elution condition of tryptic peptides and the characteristics of identified peptides in reverse phase liquid chromatography and electrospray tandem mass spectrometry (RPLC-MS/MS) analysis. Following protein digestion with trypsin, the peptide mixture was analyzed by on-line RPLC-MS/MS. Bovine serum albumin (BSA) was used to optimize acetonitrile (ACN) elution gradient for tryptic peptides, and Cytochrome C was used to retest the gradient and the sensitivity of LC-MS/MS. The characteristics of identified peptides were also analyzed. In our experiments, the suitable ACN gradient is 5% to 30% for tryptic peptide elution and the sensitivity of LC-MS/MS is 50 fmol.Analysis of the tryptic peptides demonstrated that longer (more than 10 amino acids) and multi-charge state ( 2, 3) peptides are likely to be identified, and the hydropathicity of the peptides might not be related to whether it is more likely to be identified or not. The number of identified peptides for a protein might be used to estimate its loading amount under the same sample background. Moreover, in this study the identified peptides present three types of redundancy, namely identification, charge, and sequence redundancy, which may repress low abundance protein identification.     

A multimodal metabolomics approach using imaging mass spectrometry and liquid chromatography-tandem mass spectrometry for spatially characterizing monoterpene indole alkaloids secreted from roots

Plants release specialized (secondary) metabolites from their roots to communicate with other organisms, including soil microorganisms. The spatial behavior of such metabolites around these roots can help us understand roles for the communication; however, currently, they are unclear because soil-based studies are complex. Here, we established a multimodal metabolomics approach using imaging mass spectrometry (IMS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) to spatially assign metabolites under laboratory conditions using agar. In a case study using Catharanthus roseus, we showed that 58 nitrogen (N)-containing metabolites are released from the roots into the agar. For the metabolite assignment, we used ¹⁵N-labeled and non-labeled LC-MS/MS data, previously reported. Four metabolite ions were identified using authentic standard compounds as derived from monoterpene indole alkaloids (MIAs) such as ajmalicine, catharanthine, serpentine, and yohimbine. An alkaloid network analysis using dot products and spinglass methods characterized five clusters to which the 58 ions belong. The analysis clustered ions from the indolic skeleton-type MIAs to a cluster, suggesting that other communities may represent distinct metabolite groups. For future chemical assignments of the serpentine community, key fragmentation patterns were characterized using the ¹⁵N-labeled and non-labeled MS/MS spectra.     

High sequence coverage by in-capillary proteolysis of native proteins and simultaneous analysis of the resulting peptides by nanoelectrospray ionization-mass spectrometry and tandem mass spectrometry

Losses of proteolytic peptides during extraction and/or purification procedures succeeding in-gel or in-solution digests of proteins frequently occur in the course of protein identification investigations. In order to overcome this disadvantage, the method of in-capillary digest was developed: native proteins were incubated in the presence of endoproteases in the electrospray capillary and the resulting peptides were analyzed by nanoelectrospray-mass spectrometry during the ongoing proteolysis. In-capillary digest of apomyglobin by use of trypsin in a molar ratio of 25:1 yielded complete degradation already after 15 min. The sequence coverage based on formation of molecular ions was 100% and peptide ions could be fragmented by collision-induced dissociation and sequenced. When myoglobin was incubated in the electrospray capillary with trypsin in a molar ratio of 500:1, a clear shift from molecular ions and miscleaved peptide ions to the expected final tryptic peptide ions was observed over a 2 h period. The peptide spectra obtained from tryptic in-capillary proteolysis of bovine serum albumin and apotransferrin, respectively, gave rise to sequence coverages of more than 40% for both proteins. The data obtained from the peptide maps as well as from collision-induced dissociation (CID) of selected peptides were more than sufficient for protein identification by database searches. An elephant milk protein preparation was used to demonstrate the application of in-capillary proteolysis on protein mixtures. Tryptic digest, simultaneous analysis of the proteolytic peptides by use of CID, and subsequent sequencing allowed the identification of lactoferrin, alphas1-casein, beta-casein, delta-casein, and kappa-casein by homology search.     

Mass spectrometry-based glycoproteomic approach involving lysine derivatization for structural characterization of recombinant human erythropoietin

Lysine-containing peptides comprising glycosylation sites derived from recombinant human erythropoietin (rHuEPO) by trypsin or Lys-C and PNGase F dual digestion were derivatized with 2-methoxy-4,5-dihydro-1H-imidazole and its deuterated analogues. In the same reaction, under reducing conditions (beta-mercaptoethanol), cysteines were converted into methyl-cysteines and lysines into Lys-4,5-dihydro-1H-imidazole. Both modifications on cysteines and lysines simplified the CID-MS/MS spectra, while preserving the structural information by yielding y-series ions and improved the mass spectral signal intensity up to 25 times. Moreover, by this approach, the N-glycan occupation sites were unambiguously determined. O-Glycosylation sites as well as O-glycan structures were determined by a LC-MS/MS experiment carried out on dually digested rHuEPO. N-Glycan mixture purified on a graphitized carbon column using a newly developed method that extracted only sialylated carbohydrates was analyzed first using MALDI-TOF in negative linear ion mode with low mass accuracy but without interferences and metastabile ions and then a reflectron with high mass accuracy. After defining the precursor ions, we performed the nanoESI QTOF MS/MS analysis on N-glycans, mainly targeting the distinction between carbohydrates with sialylated antennae and those lacking sialic acid moieties.     

基于液相色谱质谱联用的蛋白质组非标记定量研究策略的建立及应用

定量蛋白质组研究是蛋白质组研究的热点和难点,而液相色谱质谱技术已经被广泛地应用于蛋白质的定性和定量研究.该研究建立和优化了一种基于液相色谱质谱联用技术的蛋白质组非标记定量方法,并对两种肽段质谱检测计数的归一化算法进行了比较,结果发现ASC法要优于Rsc法.最后,将建立的方法应用于肝癌细胞模型HepG2和HepG2-HBx细胞系的差异蛋白质组表达研究.质谱鉴定结果用聚类分析软件cluster3.0进行分析,最后鉴定出107个重叠蛋白,其中9个蛋白质表达上调(Ratio>1.75),6个蛋白质表达下调(Ratio<0.5),这些蛋白质均与肝癌发生和恶化密切相关.结果表明,该技术操作简单、方便,具有较高的灵敏度和动态范围,利用该方法进行差异蛋白质组研究和发现生物标志物在理论和临床上具有十分重要的意义.     

Quantification of C-reactive protein in the serum of patients with rheumatoid arthritis using multiple reaction monitoring mass spectrometry and 13C-labeled peptide standards

A general method for the quantification of proteins in human serum was developed using mass spectrometry (MS) and stable isotope-labeled synthetic peptides as internal standards. Using this approach, C-reactive protein (CRP), a diagnostic marker of rheumatoid arthritis (RA), was detected in serum samples taken from patients with either erosive or nonerosive RA and compared to healthy individuals. Small volumes of serum samples were enriched for low-abundance proteins through the selective removal of human serum albumin (HSA), immunoglobulin G (IgG), and haptoglobin. After depletion of abundant proteins, the complexity of the protein mixture was further simplified using size exclusion chromatography (SEC) to fractionate denatured proteins into discrete molecular weight ranges. Fractions of interest containing CRP, M(r) = 25 000, were pooled, digested with trypsin, and then fixed quantities of the synthetic peptides were added to the mixture. The mixture of tryptic peptides was subsequently analyzed by nanoflow chromatography-tandem MS (nanoLC-MS/MS) using multiple-reaction monitoring (MRM) on a triple quadrupole mass spectrometer (TQ-MS). The ratio of transition ions derived from the endogenous and isotope-labeled peptides provided a quantitative measure of CRP in the original samples as assessed by independent measurement of CRP in the same patient samples using an immunoassay. The use of isotope-labeled synthetic peptides and MRM is a powerful analytical method for the prescreening of candidate protein biomarkers in human serum prior to antibody and immunoassay development.     

The importance of peptide detectability for protein identification, quantification, and experiment design in MS/MS proteomics

Peptide detectability is defined as the probability that a peptide is identified in an LC-MS/MS experiment and has been useful in providing solutions to protein inference and label-free quantification. Previously, predictors for peptide detectability trained on standard or complex samples were proposed. Although the models trained on complex samples may benefit from the large training data sets, it is unclear to what extent they are affected by the unequal abundances of identified proteins. To address this challenge and improve detectability prediction, we present a new algorithm for the iterative learning of peptide detectability from complex mixtures. We provide evidence that the new method approximates detectability with useful accuracy and, based on its design, can be used to interpret the outcome of other learning strategies. We studied the properties of peptides from the bacterium Deinococcus radiodurans and found that at standard quantities, its tryptic peptides can be roughly classified as either detectable or undetectable, with a relatively small fraction having medium detectability. We extend the concept of detectability from peptides to proteins and apply the model to predict the behavior of a replicate LC-MS/MS experiment from a single analysis. Finally, our study summarizes a theoretical framework for peptide/protein identification and label-free quantification.