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.     

液质联用多反应监测法定量目标多肽或蛋白质

为建立优化的血浆内源性多肽提取方法,并且构建目标多肽和蛋白质的质谱定量方 法,本研究考察了超滤法、有机溶剂沉淀法和固相萃取法对血浆内源性多肽的提取效果 ,并通过Tricine-SDS-PAGE对提取效果进行比较.通过液相色谱串联质谱多反应监测 （MRM）分析,建立了多肽标准品ESAT-6定量方法,并将ESAT-6定量建立的液相色谱和质谱条件应用于蛋白质的定量,对多肽和蛋白质MRM定量的标准曲线进行了考 察.Tricine-SDS-PAGE结果表明,乙腈沉淀法是最佳的血浆内源性多肽提取方法,低分子量的多肽可以得到很好的富集,且能有效地去除高分子蛋白质的污染.液相色谱串联 质谱MRM法检测血浆内提取的多肽,标准曲线的线性较好,相关系数为0.999.另外,采 用MRM法对胶内分离的蛋白质进行定量,标准曲线的线性相关系数为0.995.综上所述, 本研究构建了一种简单有效的血浆多肽提取方法,通过液质联用MRM法成功地实现了目标多肽和蛋白质定量测定.该定量方法可以推广应用于复杂样品中的多肽和蛋白质的定 量分析.     

Accurate peptide fragment mass analysis: multiplexed peptide identification and quantification

Fourier transform-all reaction monitoring (FT-ARM) is a novel approach for the identification and quantification of peptides that relies upon the selectivity of high mass accuracy data and the specificity of peptide fragmentation patterns. An FT-ARM experiment involves continuous, data-independent, high mass accuracy MS/MS acquisition spanning a defined m/z range. Custom software was developed to search peptides against the multiplexed fragmentation spectra by comparing theoretical or empirical fragment ions against every fragmentation spectrum across the entire acquisition. A dot product score is calculated against each spectrum to generate a score chromatogram used for both identification and quantification. Chromatographic elution profile characteristics are not used to cluster precursor peptide signals to their respective fragment ions. FT-ARM identifications are demonstrated to be complementary to conventional data-dependent shotgun analysis, especially in cases where the data-dependent method fails because of fragmenting multiple overlapping precursors. The sensitivity, robustness, and specificity of FT-ARM quantification are shown to be analogous to selected reaction monitoring-based peptide quantification with the added benefit of minimal assay development. Thus, FT-ARM is demonstrated to be a novel and complementary data acquisition, identification, and quantification method for the large scale analysis of peptides.     

Introducing AAA-MS, a rapid and sensitive method for amino acid analysis using isotope dilution and high-resolution mass spectrometry

Accurate quantification of pure peptides and proteins is essential for biotechnology, clinical chemistry, proteomics, and systems biology. The reference method to quantify peptides and proteins is amino acid analysis (AAA). This consists of an acidic hydrolysis followed by chromatographic separation and spectrophotometric detection of amino acids. Although widely used, this method displays some limitations, in particular the need for large amounts of starting material. Driven by the need to quantify isotope-dilution standards used for absolute quantitative proteomics, particularly stable isotope-labeled (SIL) peptides and PSAQ proteins, we developed a new AAA assay (AAA-MS). This method requires neither derivatization nor chromatographic separation of amino acids. It is based on rapid microwave-assisted acidic hydrolysis followed by high-resolution mass spectrometry analysis of amino acids. Quantification is performed by comparing MS signals from labeled amino acids (SIL peptide- and PSAQ-derived) with those of unlabeled amino acids originating from co-hydrolyzed NIST standard reference materials. For both SIL peptides and PSAQ standards, AAA-MS quantification results were consistent with classical AAA measurements. Compared to AAA assay, AAA-MS was much faster and was 100-fold more sensitive for peptide and protein quantification. Finally, thanks to the development of a labeled protein standard, we also extended AAA-MS analysis to the quantification of unlabeled proteins.     

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.     

The Application of Gaussian Mixture Models for Signal Quantification in MALDI-ToF Mass Spectrometry of Peptides

Matrix assisted laser desorption/ionization time-of-flight (MALDI-TOF) coupled with stable isotope standards (SIS) has been used to quantify native peptides. This peptide quantification by MALDI-TOF approach has difficulties quantifying samples containing peptides with ion currents in overlapping spectra. In these overlapping spectra the currents sum together, which modify the peak heights and make normal SIS estimation problematic. An approach using Gaussian mixtures based on known physical constants to model the isotopic cluster of a known compound is proposed here. The characteristics of this approach are examined for single and overlapping compounds. The approach is compared to two commonly used SIS quantification methods for single compound, namely Peak Intensity method and Riemann sum area under the curve (AUC) method. For studying the characteristics of the Gaussian mixture method, Angiotensin II, Angiotensin-2-10, and Angiotenisn-1-9 and their associated SIS peptides were used. The findings suggest, Gaussian mixture method has similar characteristics as the two methods compared for estimating the quantity of isolated isotopic clusters for single compounds. All three methods were tested using MALDI-TOF mass spectra collected for peptides of the renin-angiotensin system. The Gaussian mixture method accurately estimated the native to labeled ratio of several isolated angiotensin peptides (5.2% error in ratio estimation) with similar estimation errors to those calculated using peak intensity and Riemann sum AUC methods (5.9% and 7.7%, respectively). For overlapping angiotensin peptides, (where the other two methods are not applicable) the estimation error of the Gaussian mixture was 6.8%, which is within the acceptable range. In summary, for single compounds the Gaussian mixture method is equivalent or marginally superior compared to the existing methods of peptide quantification and is capable of quantifying overlapping (convolved) peptides within the acceptable margin of error.     

Analysis of host-cell proteins in biotherapeutic proteins by comprehensive online two-dimensional liquid chromatography/mass spectrometry

Assays for identification and quantification of host-cell proteins (HCPs) in biotherapeutic proteins over 5 orders of magnitude in concentration are presented. The HCP assays consist of two types: HCP identification using comprehensive online two-dimensional liquid chromatography coupled with high resolution mass spectrometry (2D-LC/MS), followed by high-throughput HCP quantification by liquid chromatography, multiple reaction monitoring (LC-MRM). The former is described as a “discovery” assay, the latter as a “monitoring” assay. Purified biotherapeutic proteins (e.g., monoclonal antibodies) were digested with trypsin after reduction and alkylation, and the digests were fractionated using reversed-phase (RP) chromatography at high pH (pH 10) by a step gradient in the first dimension, followed by a high-resolution separation at low pH (pH 2.5) in the second dimension. As peptides eluted from the second dimension, a quadrupole time-of-flight mass spectrometer was used to detect the peptides and their fragments simultaneously by alternating the collision cell energy between a low and an elevated energy (MSE methodology). The MSE data was used to identify and quantify the proteins in the mixture using a proven label-free quantification technique (“Hi3” method). The same data set was mined to subsequently develop target peptides and transitions for monitoring the concentration of selected HCPs on a triple quadrupole mass spectrometer in a high-throughput manner (20 min LC-MRM analysis). This analytical methodology was applied to the identification and quantification of low-abundance HCPs in six samples of PTG1, a recombinant chimeric anti-phosphotyrosine monoclonal antibody (mAb). Thirty three HCPs were identified in total from the PTG1 samples among which 21 HCP isoforms were selected for MRM monitoring. The absolute quantification of three selected HCPs was undertaken on two different LC-MRM platforms after spiking isotopically labeled peptides in the samples. Finally, the MRM quantitation results were compared with TOF-based quantification based on the Hi3 peptides, and the TOF and MRM data sets correlated reasonably well. The results show that the assays provide detailed valuable information to understand the relative contributions of purification schemes to the nature and concentrations of HCP impurities in biopharmaceutical samples, and the assays can be used as generic methods for HCP analysis in the biopharmaceutical industry.     

A Probabilistic Framework for Peptide and Protein Quantification from Data-Dependent and Data-Independent LC-MS Proteomics Experiments

Abstract A probability-based quantification framework is presented for the calculation of relative peptide and protein abundance in label-free and label-dependent LC-MS proteomics data. The results are accompanied by credible intervals and regulation probabilities. The algorithm takes into account data uncertainties via Poisson statistics modified by a noise contribution that is determined automatically during an initial normalization stage. Protein quantification relies on assignments of component peptides to the acquired data. These assignments are generally of variable reliability and may not be present across all of the experiments comprising an analysis. It is also possible for a peptide to be identified to more than one protein in a given mixture. For these reasons the algorithm accepts a prior probability of peptide assignment for each intensity measurement. The model is constructed in such a way that outliers of any type can be automatically reweighted. Two discrete normalization methods can be employed. The first method is based on a user-defined subset of peptides, while the second method relies on the presence of a dominant background of endogenous peptides for which the concentration is assumed to be unaffected. Normalization is performed using the same computational and statistical procedures employed by the main quantification algorithm. The performance of the algorithm will be illustrated on example data sets, and its utility demonstrated for typical proteomics applications. The quantification algorithm supports relative protein quantification based on precursor and product ion intensities acquired by means of data-dependent methods, originating from all common isotopically-labeled approaches, as well as label-free ion intensity-based data-independent methods.     

A metal-coded affinity tag approach to quantitative proteomics

The quantitative analysis of protein mixtures is pivotal for the understanding of variations in the proteome of living systems. Therefore, approaches have been recently devised that generally allow the relative quantitative analysis of peptides and proteins. Here we present proof of concept of the new metal-coded affinity tag (MeCAT) technique, which allowed the quantitative determination of peptides and proteins. A macrocyclic metal chelate complex (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA)) loaded with different lanthanides (metal(III) ions) was the essential part of the tag. The combination of DOTA with an affinity anchor for purification and a reactive group for reaction with amino acids constituted a reagent that allowed quantification of peptides and proteins in an absolute fashion. For the quantitative determination, the tagged peptides and proteins were analyzed using flow injection inductively coupled plasma MS, a technique that allowed detection of metals with high precision and low detection limits. The metal chelate complexes were attached to the cysteine residues, and the course of the labeling reaction was followed using SDS-PAGE and MALDI-TOF MS, ESI MS, and inductively coupled plasma MS. To limit the width in isotopic signal spread and to increase the sensitivity for ESI analysis, we used the monoisotopic lanthanide macrocycle complexes. Peptides tagged with the reagent loaded with different metals coelute in liquid chromatography. In first applications with proteins, the calculated detection limit for bovine serum albumin for example was 110 amol, and we have used MeCAT to analyze proteins of the Sus scrofa eye lens as a model system. These data showed that MeCAT allowed quantification not only of peptides but also of proteins in an absolute fashion at low concentrations and in complex mixtures.     

A paired ions scoring algorithm based on Morpheus for simultaneous identification and quantification of proteome samples prepared by isobaric peptide termini labeling strategies

The isobaric peptide termini labeling (IPTL) method is a promising strategy in quantitative proteomics for its high accuracy, while the increased complexity of MS2 spectra originated from the paired b, y ions has adverse effect on the identification and the coverage of quantification. Here, a paired ions scoring algorithm (PISA) based on Morpheus, a database searching algorithm specifically designed for high‐resolution MS2 spectra, was proposed to address this issue. PISA was first tested on two 1:1 mixed IPTL datasets, and increases in peptide to spectrum matchings, distinct peptides and protein groups compared to Morpheus itself and MASCOT were shown. Furthermore, the quantification is simultaneously performed and 100% quantification coverage is achieved by PISA since each of the identified peptide to spectrum matchings has several pairs of fragment ions which could be used for quantification. Then the PISA was applied to the relative quantification of human hepatocellular carcinoma cell lines with high and low metastatic potentials prepared by an IPTL strategy.     

Quantitative analysis of human cerebrospinal fluid proteins using a combination of cysteine tagging and amine-reactive isobaric labeling

Highly complex and dynamic protein mixtures are hardly comprehensively resolved by direct shotgun proteomic analysis. As many proteins of biological interest are of low abundance, numerous analytical methodologies have been developed to reduce sample complexity and go deeper into proteomes. The present work describes an analytical strategy to perform cysteinyl-peptide subset enrichment and relative quantification through successive cysteine and amine-isobaric tagging. A cysteine-reactive covalent capture tag (C3T) allowed derivatization of cysteines and specific isolation on a covalent capture (CC) resin. The 6-plex amine-reactive tandem mass tags (TMT) served for relative quantification of the targeted peptides. The strategy was first evaluated on a model protein mixture with increasing concentrations to assess the specificity of the enrichment and the quantitative performances of the workflow. It was then applied to human cerebrospinal fluid (CSF) from post-mortem and ante-mortem samples. These studies confirmed the specificity of the C3T and the CC technique to cysteine-containing peptides. The model protein mixture analysis showed high precision and accuracy of the quantification with coefficients of variation and mean absolute errors of less than 10% on average. The CSF experiments demonstrated the potential of the strategy to study complex biological samples and identify differential brain-related proteins. In addition, the quantification data were highly correlated with a classical TMT experiment (i.e., without C3T cysteine-tagging and enrichment steps). Altogether, these results legitimate the use of this quantitative C3T strategy to enrich and relatively quantify cysteine-containing peptides in complex mixtures.     

Assessment and Refinement of Sample Preparation Methods for Deep and Quantitative Plant Proteome Profiling

A major challenge in the field of proteomics is obtaining high‐quality peptides for comprehensive proteome profiling by LC–MS. Here, evaluation and modification of a range of sample preparation methods using photosynthetically active Arabidopsis leaf tissue are done. It was found that inclusion of filter‐aided sample preparation (FASP) based on filter digestion improves all protein extraction methods tested. Ultimately, a detergent‐free urea‐FASP approach that enables deep and robust quantification of leaf and root proteomes is shown. For example, from 4‐day‐old leaf tissue, up to 11 690 proteins were profiled from a single sample replicate. This method should be broadly applicable to researchers working with difficult to process plant samples.     

Mass spectrometry-based absolute protein quantification: PSAQ™ strategy makes use of "noncanonical" proteotypic peptides

Absolute quantification of proteins using isotope dilution mass spectrometry requires the selection of proteotypic peptides. When choosing these peptides, a certain number of rules must be respected. Several of these were established to safeguard against quantification errors resulting from the isotopically labeled standard peptides not behaving in the same way as the peptides to be quantified. Of all absolute quantification methods using isotope dilution, Protein Standard for Absolute Quantification (PSAQ(TM) ) offers the maximal protein sequence coverage. In the present study, we show that the PSAQ method presents a previously unreported advantage for protein quantification as it makes use of Met/Cys-containing peptides and peptides-containing miscleavages in addition to proteotypic peptides. By increasing the total number of peptides that can be considered, robustness of quantification is improved, paving the way for a facilitated quantification of low abundant and/or low-molecular-weight proteins.     

The importance of the digest: proteolysis and absolute quantification in proteomics

Virtually all mass spectrometric-based methods for quantitative proteomics are at the peptide level, whether label-mediated or label-free. Absolute quantification in particular is based on the measurement of limit peptides, defined as those peptides that cannot be further fragmented by the protease in use. Complete release of analyte and (stable isotope labelled) standard ensures that the most reliable quantification data are recovered, especially when the standard peptides are in a different primary sequence context, such as sometimes occurs in the QconCAT methodology. Moreover, in label-free methods, incomplete digestion would diminish the ion current attributable to limit peptides and lead to artifactually low quantification data. It follows that an essential requirement for peptide-based absolute quantification in proteomics is complete and consistent proteolysis to limit peptides. In this paper we describe strategies to assess completeness of proteolysis and discuss the potential for variance in digestion efficiency to compromise the ensuing quantification data. We examine the potential for kinetically favoured routes of proteolysis, particularly at the last stages of the digestion, to direct products into ‘dead-end’ mis-cleaved products.     

Index-ion triggered MS2 ion quantification: a novel proteomics approach for reproducible detection and quantification of targeted proteins in complex mixtures

Biomedical research requires protein detection technology that is not only sensitive and quantitative, but that can reproducibly measure any set of proteins in a biological system in a high throughput manner. Here we report the development and application of a targeted proteomics platform termed index-ion triggered MS2 ion quantification (iMSTIQ) that allows reproducible and accurate peptide quantification in complex mixtures. The key feature of iMSTIQ is an approach called index-ion triggered analysis (ITA) that permits the reproducible acquisition of full MS2 spectra of targeted peptides independent of their ion intensities. Accurate quantification is achieved by comparing the relative intensities of multiple pairs of fragment ions derived from isobaric targeted peptides during MS2 analysis. Importantly, the method takes advantage of the favorable performance characteristics of the LTQ-Orbitrap, which include high mass accuracy, resolution, and throughput. As such it provides an attractive targeted proteomics tool to meet the demands of systems biology research and biomarker studies.     

Absolute quantification of allergens from complex mixtures: a new sensitive tool for standardization of allergen extracts for specific immunotherapy

Products for specific diagnosis and immunotherapy of IgE-mediated allergies are currently based on natural extracts. Quantification of major allergen content is an important aspect of standardization as important allergens particularly impact vaccine potency. The aim of the study was to develop a mass spectrometry (MS) based assay for absolute quantification of Timothy (Phleum pratense) pollen allergens Phl p 1 and Phl p 5 in P. pratense extract. High-resolution and accurate mass (HRAM) MS was selected for its ability to detect peptides with high selectivity and mass accuracy (<3 ppm). Isotope labeled heavy peptides were used for absolute quantification of specific isoallergens of Phl p 1 and Phl p 5 at low femtomole level in P. pratense extract. Robustness and linearity of the method was demonstrated with intra day precision ≤ 5% (n = 3). Phl p 1b was shown to be 5 times less abundant than its variant Phl p 1a and Phl p 5b was shown to be 9 times more abundant than the Phl p 5a. The present study shows that allergen, and/or isoallergen specific, surrogate signature peptides analyzed with HRAM MS is a sensitive and accurate tool for identification and quantification of allergens from complex allergen sources.     

Analysis of host-cell proteins in biotherapeutic proteins by comprehensive online two-dimensional liquid chromatography/mass spectrometry

Assays for identification and quantification of host-cell proteins (HCPs) in biotherapeutic proteins over 5 orders of magnitude in concentration are presented. The HCP assays consist of two types: HCP identification using comprehensive online two-dimensional liquid chromatography coupled with high resolution mass spectrometry (2D-LC/MS), followed by high-throughput HCP quantification by liquid chromatography, multiple reaction monitoring (LC-MRM). The former is described as a “discovery” assay, the latter as a “monitoring” assay. Purified biotherapeutic proteins (e.g., monoclonal antibodies) were digested with trypsin after reduction and alkylation, and the digests were fractionated using reversed-phase (RP) chromatography at high pH (pH 10) by a step gradient in the first dimension, followed by a high-resolution separation at low pH (pH 2.5) in the second dimension. As peptides eluted from the second dimension, a quadrupole time-of-flight mass spectrometer was used to detect the peptides and their fragments simultaneously by alternating the collision cell energy between a low and an elevated energy (MS^E methodology). The MS^E data was used to identify and quantify the proteins in the mixture using a proven label-free quantification technique (“Hi3” method). The same data set was mined to subsequently develop target peptides and transitions for monitoring the concentration of selected HCPs on a triple quadrupole mass spectrometer in a high-throughput manner (20 min LC-MRM analysis). This analytical methodology was applied to the identification and quantification of low-abundance HCPs in six samples of PTG1, a recombinant chimeric anti-phosphotyrosine monoclonal antibody (mAb). Thirty three HCPs were identified in total from the PTG1 samples among which 21 HCP isoforms were selected for MRM monitoring. The absolute quantification of three selected HCPs was undertaken on two different LC-MRM platforms after spiking isotopically labeled peptides in the samples. Finally, the MRM quantitation results were compared with TOF-based quantification based on the Hi3 peptides, and the TOF and MRM data sets correlated reasonably well. The results show that the assays provide detailed valuable information to understand the relative contributions of purification schemes to the nature and concentrations of HCP impurities in biopharmaceutical samples, and the assays can be used as generic methods for HCP analysis in the biopharmaceutical industry.Key words: host cell proteins, protein quantification, biotherapeutic proteins, mAbs, HCP     

Quantification of proteins in the subnanogram and nanogram range: comparison of the AuroDye, FerriDye, and India ink staining methods

The usefulness of three sensitive dyes, AuroDye, FerriDye, and India ink, for the quantification of proteins and peptides bound to nitrocellulose paper has been assessed. In general, the staining intensity varies linearly with the logarithm of protein concentrations. The detection limit of small peptides (Mr less than 5000) is higher than that of large peptides and proteins, but the sensitivity is independent of the molecular weight. Oligopeptides of four or less amino acids either stain with very high detection limits or do not stain at all. The detection limit of proteins stained by AuroDye is approximately 1 ng, and in a number of cases even lower. The useful range for quantification of proteins extends to around 100 ng. The FerriDye and India ink staining methods are less sensitive and can be used to quantify proteins over a wide nanogram range. Among the methods tested, the India ink staining method has the highest protein to protein variation in sensitivity.     

Amine-reactive isobaric tagging reagents: requirements for absolute quantification of proteins and peptides

Amine-reactive isobaric tagging reagents such as iTRAQ (isobaric tags for relative and absolute quantitation) have recently become increasing popular for relative protein quantification, cell expression profiling, and biomarker discovery. This is due mainly to the possibility of simultaneously identifying and quantifying multiple samples. The principles of iTRAQ may also be applied to absolute protein quantification with the use of synthetic peptides as standards. The prerequisites that must be fulfilled to perform absolute quantification of proteins by iTRAQ have been investigated and are described here. Three samples of somatropin were quantified using iTRAQ and synthetic peptides as standards, corresponding to a portion of the protein sequence. The results were compared with those obtained by quantification of the same protein solutions using double exact matching isotope dilution mass spectrometry (IDMS). To obtain reliable results, the appropriate standard peptides needed to be selected carefully and enzymatic digestion needed to be optimized to ensure complete release of the peptides from the protein. The kinetics and efficiency of the iTRAQ derivatization reaction of the standard peptides and digested proteins with isobaric tagging reagents were studied using a mixture of seven synthetic peptides and their corresponding labeled peptides. The implications of incomplete derivatization are also presented.     

Absolute quantification of the glycolytic pathway in yeast: deployment of a complete QconCAT approach

The availability of label-free data derived from yeast cells (based on the summed intensity of the three strongest, isoform-specific peptides) permitted a preliminary assessment of protein abundances for glycolytic proteins. Following this analysis, we demonstrate successful application of the QconCAT technology, which uses recombinant DNA techniques to generate artificial concatamers of large numbers of internal standard peptides, to the quantification of enzymes of the glycolysis pathway in the yeast Saccharomyces cerevisiae. A QconCAT of 88 kDa (59 tryptic peptides) corresponding to 27 isoenzymes was designed and built to encode two or three analyte peptides per protein, and after stable isotope labeling of the standard in vivo, protein levels were determined by LC-MS, using ultra high performance liquid chromatography-coupled mass spectrometry. We were able to determine absolute protein concentrations between 14,000 and 10 million molecules/cell. Issues such as efficiency of extraction and completeness of proteolysis are addressed, as well as generic factors such as optimal quantotypic peptide selection and expression. In addition, the same proteins were quantified by intensity-based label-free analysis, and both sets of data were compared with other quantification methods.