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.     

SVM model for quality assessment of medium resolution mass spectra from 18O-water labeling experiments

We describe a method for assessing the quality of mass spectra and improving reliability of relative ratio estimations from (18)O-water labeling experiments acquired from low resolution mass spectrometers. The mass profiles of heavy and light peptide pairs are often affected by artifacts, including coeluting contaminant species, noise signal, instrumental fluctuations in measuring ion position and abundance levels. Such artifacts distort the profiles, leading to erroneous ratio estimations, thus reducing the reliability of ratio estimations in high throughput quantification experiments. We used support vector machines (SVMs) to filter out mass spectra that deviated significantly from expected theoretical isotope distributions. We built an SVM classifier with a decision function that assigns a score to every mass profile based on such spectral features as mass accuracy, signal-to-noise ratio, and differences between experimental and theoretical isotopic distributions. The classifier was trained using a data set obtained from samples of mouse renal cortex. We then tested it on protein samples (bovine serum albumin) mixed in five different ratios of labeled and unlabeled species. We demonstrated that filtering the data using our SVM classifier results in as much as a 9-fold reduction in the coefficient of variance of peptide ratios, thus significantly improving the reliability of ratio estimations.     

UNiquant, a program for quantitative proteomics analysis using stable isotope labeling

Stable isotope labeling (SIL) methods coupled with nanoscale liquid chromatography and high resolution tandem mass spectrometry are increasingly useful for elucidation of the proteome-wide differences between multiple biological samples. Development of more effective programs for the sensitive identification of peptide pairs and accurate measurement of the relative peptide/protein abundance are essential for quantitative proteomic analysis. We developed and evaluated the performance of a new program, termed UNiquant, for analyzing quantitative proteomics data using stable isotope labeling. UNiquant was compared with two other programs, MaxQuant and Mascot Distiller, using SILAC-labeled complex proteome mixtures having either known or unknown heavy/light ratios. For the SILAC-labeled Jeko-1 cell proteome digests with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10), UNiquant quantified a similar number of peptide pairs as MaxQuant for the H/L = 1:1 and 1:5 mixtures. In addition, UNiquant quantified significantly more peptides than MaxQuant and Mascot Distiller in the H/L = 1:10 mixtures. UNiquant accurately measured relative peptide/protein abundance without the need for postmeasurement normalization of peptide ratios, which is required by the other programs.     

Key issues in the acquisition and analysis of qualitative and quantitative mass spectrometry data for peptide-centric proteomic experiments

Proteomic technologies have matured to a level enabling accurate and reproducible quantitation of peptides and proteins from complex biological matrices. Analysis of samples as diverse as assembled protein complexes, whole cell lysates or sub-cellular proteomes from cell cultures, and direct analysis of animal and human tissues and fluids demonstrate the incredible versatility of the fundamental nature of the technique that forms the basis of most proteomic applications today (mass spectrometry). Determining the mass of biomolecules and their fragments or related products with high accuracy can convey a highly specific assay for detection and identification. Importantly, ion currents representative of these specifically identified analytes can be accurately quantified with the correct application of smart isobaric tagging chemistries, heavy and light isotopically derivatised samples or standards, or by careful application of workflows to compare unlabelled samples in so-called 'label-free' and targeted selected reaction monitoring experiments. In terms of exploring biology, a myriad of protein changes and modifications are being increasingly probed and quantified, including diverse chemical changes from relatively decisive modifications such as protein splicing and truncation, to more transient dynamic modifications such as phosphorylation, acetylation and ubiquitination. Proteomic workflows can be complex beasts and several key considerations to ensure effective applications have been outlined in the recent literature. The past year has witnessed the publication of several excellent reviews that thoroughly describe the fundamental principles underlying the state of the art. This review further elaborates on specific critical issues introduced by these publications and raises other important unaddressed considerations and new developments that directly impact on the effectiveness of proteomic technologies, in particular for, but not necessarily exclusive to peptide-centric experiments. These factors are discussed both in terms of qualitative analyses, including dynamic range and sampling issues, and developments to improve the translation of peptide fragmentation data into peptide and protein identities, as well as quantitative analyses, including data normalisation and the utility of ontology or functional annotation, the effects of modified peptides, and considered experimental design to facilitate the use of robust statistical methods.     

Differentially isotope-coded N-terminal protein sulphonation: combining protein identification and quantification

Most proteomic labelling technologies intend to improve protein quantification and/or facilitate (de novo) peptide sequencing. We present here a novel stable-isotope labelling method to simultaneously identify and quantify protein components in complex mixtures by specifically derivatizing the N-terminus of proteins with 4-sulphophenyl isothiocyanate (SPITC). Our approach combines protein identification with quantification through differential isotope-coded labelling at the protein N-terminus prior to digestion. The isotope spacing of 6 Da (unlabelled vs. six-fold 13C-labelled tag) between derivatized peptide pairs enables the detection on different MS platforms (MALDI and ESI). Optimisation of the reaction conditions using SPITC was performed on three model proteins. Improved detection of the N-terminally derivatized peptide compared to the native analogue was observed in negative-ion MALDI-MS. Simpler fragmentation patterns compared to native peptides facilitated protein identification. The 13C-labelled SPITC resulted in convenient peptide pair spacing without isotopic overlap and hence facilitated relative quantification by MALDI-TOF/TOF and LC-ESI-MS/MS. The combination of facilitated identification and quantification achieved by differentially isotope-coded N-terminal protein tagging with light/heavy SPITC represents, to our knowledge, a new approach to quantitative proteomics.     

Database independent detection of isotopically labeled MS/MS spectrum peptide pairs

Mass spectrometry data generated in differential profiling of complex protein samples are classically exploited using database searches. In addition, quantitative profiling is performed by various methods, one of them using isotopically coded affinity tags, where one typically uses a light and a heavy tag. Here, we present a new algorithm, ICATcher, which detects pairs of light/heavy peptide MS/MS spectra independent of sequence databases. The method can be used for de novo sequencing and detection of posttranslational modifications. ICATcher is distributed as open source software.     

Prevention of amino acid conversion in SILAC experiments with embryonic stem cells

Recent studies using stable isotope labeling with amino acids in culture (SILAC) in quantitative proteomics have made mention of the problematic conversion of isotope-coded arginine to proline in cells. The resulting converted proline peptide divides the heavy peptide ion signal causing inaccuracy when compared with the light peptide ion signal. This is of particular concern as it can effect up to half of all peptides in a proteomic experiment. Strategies to both compensate for and limit the inadvertent conversion have been demonstrated, but none have been shown to prevent it. Additionally, these methods combined with SILAC labeling in general have proven problematic in their large scale application to sensitive cell types including embryonic stem cells (ESCs) from the mouse and human. Here, we show that by providing as little as 200 mg/liter L-proline in SILAC media, the conversion of arginine to proline can be rendered completely undetectable. At the same time, there was no compromise in labeling with isotope-coded arginine, indicating there is no observable back conversion from the proline supplement. As a result, when supplemented with proline, correct interpretation of "light" and "heavy" peptide ratios could be achieved even in the worst cases of conversion. By extending these principles to ESC culture protocols and reagents we were able to routinely SILAC label both mouse and human ESCs in the absence of feeder cells and without compromising the pluripotent phenotype. This study provides the simplest protocol to prevent proline artifacts in SILAC labeling experiments with arginine. Moreover, it presents a robust, feeder cell-free, protocol for performing SILAC experiments on ESCs from both the mouse and the human.     

The NISTmAb tryptic peptide spectral library for monoclonal antibody characterization

We describe the creation of a mass spectral library composed of all identifiable spectra derived from the tryptic digest of the NISTmAb IgG1κ. The library is a unique reference spectral collection developed from over six million peptide-spectrum matches acquired by liquid chromatography-mass spectrometry (LC-MS) over a wide range of collision energy. Conventional one-dimensional (1D) LC-MS was used for various digestion conditions and 20- and 24-fraction two-dimensional (2D) LC-MS studies permitted in-depth analyses of single digests. Computer methods were developed for automated analysis of LC-MS isotopic clusters to determine the attributes for all ions detected in the 1D and 2D studies. The library contains a selection of over 12,600 high-quality tandem spectra of more than 3,300 peptide ions identified and validated by accurate mass, differential elution pattern, and expected peptide classes in peptide map experiments. These include a variety of biologically modified peptide spectra involving glycosylated, oxidized, deamidated, glycated, and N/C-terminal modified peptides, as well as artifacts. A complete glycation profile was obtained for the NISTmAb with spectra for 58% and 100% of all possible glycation sites in the heavy and light chains, respectively. The site-specific quantification of methionine oxidation in the protein is described. The utility of this reference library is demonstrated by the analysis of a commercial monoclonal antibody (adalimumab, Humira®), where 691 peptide ion spectra are identifiable in the constant regions, accounting for 60% coverage for both heavy and light chains. The NIST reference library platform may be used as a tool for facile identification of the primary sequence and post-translational modifications, as well as the recognition of LC-MS method-induced artifacts for human and recombinant IgG antibodies. Its development also provides a general method for creating comprehensive peptide libraries of individual proteins.     

Quantitative Proteomics Using Reductive Dimethylation for Stable Isotope Labeling

Stable isotope labeling of peptides by reductive dimethylation (ReDi labeling) is a method to accurately quantify protein expression differences between samples using mass spectrometry. ReDi labeling is performed using either regular (light) or deuterated (heavy) forms of formaldehyde and sodium cyanoborohydride to add two methyl groups to each free amine. Here we demonstrate a robust protocol for ReDi labeling and quantitative comparison of complex protein mixtures. Protein samples for comparison are digested into peptides, labeled to carry either light or heavy methyl tags, mixed, and co-analyzed by LC-MS/MS. Relative protein abundances are quantified by comparing the ion chromatogram peak areas of heavy and light labeled versions of the constituent peptide extracted from the full MS spectra. The method described here includes sample preparation by reversed-phase solid phase extraction, on-column ReDi labeling of peptides, peptide fractionation by basic pH reversed-phase (BPRP) chromatography, and StageTip peptide purification. We discuss advantages and limitations of ReDi labeling with respect to other methods for stable isotope incorporation. We highlight novel applications using ReDi labeling as a fast, inexpensive, and accurate method to compare protein abundances in nearly any type of sample.     

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.     

Regression analysis for comparing protein samples with 16O/18O stable-isotope labeled mass spectrometry

MOTIVATION: Using stable isotopes in global proteome scans, labeled molecules from one sample are pooled with unlabeled molecules from another sample and subsequently subjected to mass-spectral analysis. Stable-isotope methodologies make use of the fact that identical molecules of different stable-isotope compositions are differentiated in a mass spectrometer and are represented in a mass spectrum as distinct isotopic clusters with a known mass shift. We describe two multivariable linear regression models for (16)O/(18)O stable-isotope labeled data that jointly model pairs of resolved isotopic clusters from the same peptide and quantify the abundance present in each of the two biological samples while concurrently accounting for peptide-specific incorporation rates of the heavy isotope. The abundance measure for each peptide from the two biological samples is then used in down-stream statistical analyses, e.g. differential expression analysis. Because the multivariable regression models are able to correct for the abundance of the labeled peptide that appear as an unlabeled peptide due to the inability to exchange the natural C-terminal oxygen for the heavy isotope, they are particularly advantageous for a two-step digestion/labeling procedure. We discuss how estimates from the regression model are used to quantify the variability of the estimated abundance measures for the paired samples. Although discussed in the context of (16)O/(18)O stable-isotope labeled data, the multivariable regression models are generalizable to other stable-isotope labeled technologies.     

细胞培养稳定同位素标记技术在蛋白质组学中的应用与进展

细胞培养稳定同位素标记技术（SILAC）是在细胞培养过程中,利用稳定同位素标记的氨基酸结合质谱技术,对蛋白表达进行定量分析的一种新技术。它不仅可以对蛋白质进行定性分析,还可通过质谱图上一对轻-重稳定同位素峰的比例来反映对应蛋白在不同状态下的表达水平,实现对蛋白质的精确定量。SILAC结合质谱技术在定量蛋白质组学中发挥了巨大的作用,其应用范围从细胞系扩展到亚细胞器、组织与动物整体水平,具体的应用策略也在不断完善发展。我们总结评述了SILAC技术在差异表达蛋白质组、蛋白质翻译后修饰、药物蛋白质组和蛋白质相互作用等方面的应用与进展。     

Quantitative proteomics using 16O/18O labeling and linear ion trap mass spectrometry

Quantitative proteomics using stable isotopic 16O/18O labeling has emerged as a very powerful tool, since it has a number of advantages over other methods, including the simplicity of chemistry, the constant mass tag at the C termini and its general applicability. However, due to the small mass difference between labeled and unlabeled peptide species, this approach has usually been restricted to high-resolution mass spectrometers. In this study we explored whether the high-resolution scanning mode, together with the extremely high scanning speed of the linear IT allows the 16O/18O-labeling method to be used for accurate, large-scale quantitative analysis of proteomes. A protocol, including digestion, desalting, labeling, MS and quantitative analysis was developed and tested using protein standards and whole proteome extracts. Using this method we were able to identify and quantify 140 proteins from only 10 mug of a proteome extract from mesenchymal stem cells. Relative expression changes larger than twofold can be identified with this method at the 95% confidence level. Our results demonstrate that accurate quantitative analysis using 16O/18O labeling can be performed in the practice using linear IT MS, without compromising large-scale peptide identification efficiency.     

Mascot file parsing and quantification (MFPaQ), a new software to parse, validate, and quantify proteomics data generated by ICAT and SILAC mass spectrometric analyses: application to the proteomics study of membrane proteins from primary human endothelial cells

Proteomics strategies based on nanoflow (nano-) LC-MS/MS allow the identification of hundreds to thousands of proteins in complex mixtures. When combined with protein isotopic labeling, quantitative comparison of the proteome from different samples can be achieved using these approaches. However, bioinformatics analysis of the data remains a bottleneck in large scale quantitative proteomics studies. Here we present a new software named Mascot File Parsing and Quantification (MFPaQ) that easily processes the results of the Mascot search engine and performs protein quantification in the case of isotopic labeling experiments using either the ICAT or SILAC (stable isotope labeling with amino acids in cell culture) method. This new tool provides a convenient interface to retrieve Mascot protein lists; sort them according to Mascot scoring or to user-defined criteria based on the number, the score, and the rank of identified peptides; and to validate the results. Moreover the software extracts quantitative data from raw files obtained by nano-LC-MS/MS, calculates peptide ratios, and generates a non-redundant list of proteins identified in a multisearch experiment with their calculated averaged and normalized ratio. Here we apply this software to the proteomics analysis of membrane proteins from primary human endothelial cells (ECs), a cell type involved in many physiological and pathological processes including chronic inflammatory diseases such as rheumatoid arthritis. We analyzed the EC membrane proteome and set up methods for quantitative analysis of this proteome by ICAT labeling. EC microsomal proteins were fractionated and analyzed by nano-LC-MS/MS, and database searches were performed with Mascot. Data validation and clustering of proteins were performed with MFPaQ, which allowed identification of more than 600 unique proteins. The software was also successfully used in a quantitative differential proteomics analysis of the EC membrane proteome after stimulation with a combination of proinflammatory mediators (tumor necrosis factor-alpha, interferon-gamma, and lymphotoxin alpha/beta) that resulted in the identification of a full spectrum of EC membrane proteins regulated by inflammation.     

A novel strategy using MASCOT Distiller for analysis of cleavable isotope-coded affinity tag data to quantify protein changes in plasma

A novel strategy consisting of cleavable Isotope-Coded Affinity Tag (cICAT) combined with MASCOT Distiller was evaluated as a tool for the quantification of proteins in "abnormal" patient plasma, prepared by pooling samples from patients with acute stroke. Quantification of all light and heavy cICAT-labelled peptide ion pairs was obtained using MASCOT Distiller combined with a proprietary software. Peptides displaying differences were selected for identification by MS. These preliminary results show the promise of our approach to identify potential biomarkers.     

MassChroQ: a versatile tool for mass spectrometry quantification

Recently, many software tools have been developed to perform quantification in LC-MS analyses. However, most of them are specific to either a quantification strategy (e.g. label-free or isotopic labelling) or a mass-spectrometry system (e.g. high or low resolution). In this context, we have developed MassChroQ (Mass Chromatogram Quantification), a versatile software that performs LC-MS data alignment and peptide quantification by peak area integration on extracted ion chromatograms. MassChroQ is suitable for quantification with or without labelling and is not limited to high-resolution systems. Peptides of interest (for example all the identified peptides) can be determined automatically, or manually by providing targeted m/z and retention time values. It can handle large experiments that include protein or peptide fractionation (as SDS-PAGE, 2-D LC). It is fully configurable. Every processing step is traceable, the produced data are in open standard formats and its modularity allows easy integration into proteomic pipelines. The output results are ready for use in statistical analyses. Evaluation of MassChroQ on complex label-free data obtained from low and high-resolution mass spectrometers showed low CVs for technical reproducibility (1.4%) and high coefficients of correlation to protein quantity (0.98). MassChroQ is freely available under the GNU General Public Licence v3.0 at http://pappso.inra.fr/bioinfo/masschroq/.     

The use of a novel quantitation strategy based on Reductive Isotopic Di-Ethylation (RIDE) to evaluate the effect of glufosinate on the unicellular algae Ostreococcus tauri

We report a novel stable-isotope labeling strategy for quantitative proteomics analysis. The method consists of labeling N-termini and lysine ε-amino groups through reductive amination using acetaldehyde. This allows isotope labeling using pairs of either 2H/1H or 13C/12C without mass spectrum overlap. Our labeling procedure, which is significantly different than that developed for dimethylation, can be completed with little trace of partial ethylation; non-labeled peptides represent less than 0.05% of all peptides. Co-elution of both isotopic 13C/12C peptide pairs was observed in all cases, simplifying data analysis, which can be performed using standard commercial software such as Mascot Distiller. A 13C/12C labeled mix in a 1:1 ratio from a complex extract digest of the unicellular algae Ostreococcus tauri, showed a relative standard deviation of less than 14%. This quantitative method was used to characterize O. tauri in the presence of glufosinate, an herbicide which inhibits glutamine synthetase. Blocking glutamine synthetase significantly reduced the expression of several enzymes and transporters involved in nitrogen assimilation and the expression of a number of proteins involved in various stresses including oxidative damage response were up-regulated.     

Surrobodies with Functional Tails

Surrobodies² are a unique type of binding protein based on the pre-B-cell receptor (pre-BCR). The pre-BCR is transiently expressed during development of the antibody repertoire. Unlike heterotetrameric canonical antibodies that are composed of identical pairs of heavy and light chains, the pre-BCR is a heterohexameric complex composed of identical pairs of heavy chains that are each paired with a two-subunit surrogate light chain (SLC). The SLC contains nonimmunoglobulin-like peptide extensions on each of the two SLC components. This arrangement provides unique opportunities for protein engineering by functional derivatization of these nonimmunoglobulin-like tails. Here we report recombinant fusions to these tails with either a fully active cytokine or with single-chain variable fragment (scFv) domains to generate Surrobodies with unique functions or Surrobodies that are bispecific with respect to targeted binding.     

Evaluation of absolute peptide quantitation strategies using selected reaction monitoring

The use of internal peptide standards in selected reaction monitoring experiments enables absolute quantitation. Here, we describe three approaches addressing calibration of peptide concentrations in complex matrices and assess their performance in terms of trueness and precision. The simplest approach described is single reference point quantitation where a heavy peptide is spiked into test samples and the endogenous analyte quantified relative to the heavy peptide internal standard. We refer to the second approach as normal curve quantitation. Here, a constant amount of heavy peptide and a varying amount of light peptide are spiked into matrix to construct a calibration curve. This accounts for matrix effects but due to the presence of endogenous analyte, it is usually not possible to determine the lower LOQ. We refer to the third method as reverse curve quantitation. Here, a constant amount of light peptide and a varying amount of heavy peptide are spiked into matrix to construct a calibration curve. Because there is no contribution to the heavy peptide signal from endogenous analyte, it is possible to measure the equivalent of a blank sample and determine LOQ. These approaches are applied to human plasma samples and used to assay peptides of a set of apolipoproteins.