A novel strategy for quantitative proteomics using isotope-coded protein labels

A critical appraisal of techniques, software packages, and standards for quantitative proteomic analysis

New methods for performing quantitative proteome analyses based on differential labeling protocols or label-free techniques are reported in the literature on an almost monthly basis. In parallel, a correspondingly vast number of software tools for the analysis of quantitative proteomics data has also been described in the literature and produced by private companies. In this article we focus on the review of some of the most popular techniques in the field and present a critical appraisal of several software packages available to process and analyze the data produced. We also describe the importance of community standards to support the wide range of software, which may assist researchers in the analysis of data using different platforms and protocols. It is intended that this review will serve bench scientists both as a useful reference and a guide to the selection and use of different pipelines to perform quantitative proteomics data analysis. We have produced a web-based tool ( http://www.proteosuite.org/?q=other_resources ) to help researchers find appropriate software for their local instrumentation, available file formats, and quantitative methodology.

Mass Spectrometry-based Proteomics and Peptidomics for Systems Biology and Biomarker Discovery

The scientific community has shown great interest in the field of mass spectrometry-based proteomics and peptidomics for its applications in biology. Proteomics technologies have evolved to produce large datasets of proteins or peptides involved in various biological and disease progression processes producing testable hypothesis for complex biological questions. This review provides an introduction and insight to relevant topics in proteomics and peptidomics including biological material selection, sample preparation, separation techniques, peptide fragmentation, post-translation modifications, quantification, bioinformatics, and biomarker discovery and validation. In addition, current literature and remaining challenges and emerging technologies for proteomics and peptidomics are presented.

Proteomics to study the diversity and dynamics of proteasome complexes: from fundamentals to the clinic

This article covers the latest contributions of proteomics to the structural and functional characterization of proteasomes and their associated proteins, but also to the detection of proteasomes as clinical biomarkers in diseases. Proteasomes are highly heterogenous supramolecular complexes and constitute important cellular proteases controlling the pool of proteins involved in key cellular functions. The comprehension of the structure/function relationship of proteasomes is therefore of major interest in biology. Numerous biochemical methods have been employed to purify proteasomes, and have led to the identification of complexes of various compositions - depending on the experimental conditions and the type of strategy used. In association with protein separation and enrichment techniques, modern mass spectrometry instruments and mass spectrometry-based quantitative methods, they have led to unprecedented breakthroughs in the in-depth analysis of the diversity and dynamics of proteasome composition and localization under various stimuli or pathological contexts. Proteasome inhibitors are now used in clinics for the treatment of cancer, and recent studies propose that the proteasome should be considered as a predictive biomarker for various pathologies.

Proteomic analysis of cerebrospinal fluid from obese women with idiopathic intracranial hypertension: a new approach for identifying new candidates in the pathogenesis of obesity

Body weight control is tightly regulated in the hypothalamus. The inaccessibility of human brain tissue can be partially solved by using cerebrospinal fluid (CSF) as a tool for assessing the central nervous system's production of orexigen and anorexigen factors. Using proteomic analysis, the present study investigated the differentially displayed proteins in human CSF from obese and non-obese subjects. We designed a case-control study conducted in a reference hospital where eight obese (cases) and eight non-obese (controls) women with idiopathic intracranial hypertension were included. Intracranial hypertension was normalised through the placement of a ventriculo- or lumboperitoneal shunt in the 12 months before their inclusion in the study. Isotope-coded protein label (for proteins > 10 kDa) and label-free liquid chromatography (for proteins < 10 kDa) associated with mass spectrometry analysis were used. Eighteen differentially expressed proteins were identified. Many of them fall into three main groups: inflammation (osteopontin, fibrinogen γ and β chain, α1 acid glycoprotein 2 and haptoglobin), neuroendocrine mediators (neurosecretory protein VGF, neuroendocrine protein 7B2, chromogranin-A and chromogranin B), and brain plasticity (testican-1, isoform 10 of fibronectin, galectin-3 binding protein and metalloproteinase inhibitor type 2). The differential production of osteopontin, neurosecretory protein VGF, chromogranin-A and fibrinogen γ chain was further confirmed by either enzyme-linked immunosorbent assay or western blotting. In conclusion, we have identified potential candidates that could be involved in the pathogenesis of obesity. Further studies aiming to investigating the precise role of these proteins in the pathogenesis of obesity and their potential therapeutic implications are needed.

MeCAT peptide labeling for the absolute quantification of proteins by 2D-LC-ICP-MS

Metal-Coded Affinity Tags (MeCAT) reagents were devised for the absolute quantification of labeled proteins and peptides using inductively coupled plasma mass spectrometry (ICP-MS). After the recent publication of quantification approaches for digested proteins, this work presents a multidimensional strategy for the application of MeCAT to samples which require higher chromatographic resolution. Two-dimensional separations based on strong cation exchange (SCX) and reversed-phase (RP) chromatography, were used for the quantification of lysozyme, bovine serum albumin and transferrin after tryptic digestion. The elution protocols were optimized to improve the resolution of the MeCAT-labeled peptides which led to faster elutions in SCX and longer retention times in RP compared with unlabeled peptides. The optimized method provided enough resolution for the samples analyzed. Peptides losses during the whole procedure were studied. Although recoveries of greater than 90% were found in the RP dimension, important global losses in the two-dimensional offline approach forced us to use specific internal standards, in this case MeCAT-labeled standard peptides. External calibration and label-specific isotope dilution analysis (IDA) were tested and compared as possible quantification techniques. While both techniques showed accurate and precise determinations, the label-specific IDA technique resulted in more straightforward measurements and more affordable external calibrations. Finally, simultaneous quantification of three different samples labeled with different lanthanides was successfully performed demonstrating the potential of MeCAT combined with ICP-MS for multiplexing. Electrospray ionization mass spectrometry techniques provided the structural information needed for the identification of the labeled species.

Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions

Selected reaction monitoring (SRM) is a targeted mass spectrometry technique that is emerging in the field of proteomics as a complement to untargeted shotgun methods. SRM is particularly useful when predetermined sets of proteins, such as those constituting cellular networks or sets of candidate biomarkers, need to be measured across multiple samples in a consistent, reproducible and quantitatively precise manner. Here we describe how SRM is applied in proteomics, review recent advances, present selected applications and provide a perspective on the future of this powerful technology.

Quantitative proteomic Isotope-Coded Protein Label (ICPL) analysis reveals alteration of several functional processes in the glioblastoma

Glioblastoma (GB), the most frequent primary tumor of the central nervous system, remains one of the most lethal human cancers despite intensive researches. Current paradigm in the study of GB has been focused on inter-patient variability and on trying to isolate new classification elements or prognostic factors. Here, using ICPL, a technique for protein relative quantification by mass spectrometry, we investigated protein expression between the four regions of GB on clinically relevant biopsies from 5 patients. We identified 584 non-redundant proteins and 31 proteins were found to be up-regulated in the tumor region compared to the peri-tumoral brain tissue, among which, 24 proteins belong to an interaction network linked to 4 biological processes. The core of this network is mainly constituted of interactions between beta-actin (ACTB) with heat shock proteins (HSP90AA1, HSPA8) and 14-3-3 proteins (YWHAZ, YWHAG, YWHAB). A cluster of three isoforms of the sodium pump α-subunit (ATP1A1, ATP1A2, ATP1A3) was also identified outside this network. The differential expression observed for ACTB and 14-3-3γ was further validated by western blot and/or immunohistochemistry. Our study confirms the identity of previously proposed molecular targets, highlights several functional processes altered in GB such as energy metabolism and synaptic transmission and could thus provide added value to new therapeutic trails.

Performance of isobaric and isotopic labeling in quantitative plant proteomics

Mass spectrometry has become indispensable for peptide and protein quantification in proteomics studies. When proteomics technologies are applied to understand the biology of plants, two-dimensional gel electrophoresis is still the prevalent method for protein fractionation, identification, and quantitation. In the present work, we have used LC-MS to compare an isotopic (ICPL) and isobaric (iTRAQ) chemical labeling technique to quantify proteins in the endosperm of Ricinus communis seeds at three developmental stages (IV, VI, and X). Endosperm proteins of each stage were trypsin-digested in-solution, and the same amount of peptides was labeled with ICPL and iTRAQ tags in two orders (forward and reverse). Each sample was submitted to nanoLC coupled to an LTQ-Orbitrap high-resolution mass spectrometer. Comparing labeling performance, iTRAQ was able to label 99.8% of all identified unique peptides, while 94.1% were labeled by ICPL. After statistical analysis, it was possible to quantify 309 (ICPL) and 321 (iTRAQ) proteins, from which 95 are specific to ICPL, 107 to iTRAQ, and 214 common to both labeling strategies. We noted that the iTRAQ quantification could be influenced by the tag. Even though the efficiency of the iTRAQ and ICPL in protein quantification depends on several parameters, both labeling methods were able to successfully quantify proteins present in the endosperm of castor bean during seed development and, when combined, increase the number of quantified proteins.

Intact proteome fractionation strategies compatible with mass spectrometry

Proteome fractionation refers to separation at the level of intact proteins. Proteome fractionation may precede sample digestion and subsequent peptide-level separation and detection (i.e., bottom-up mass spectrometry [MS]). For top-down MS, proteome fractionation acts as a stand-alone separation platform, since intact proteins are directly analyzed by the mass spectrometer. Regardless of the MS identification strategy, separation of intact proteins has clear benefits as a result of decreasing sample complexity. However, this stage of the workflow also creates considerable challenges, which are generally absent from the counterpart peptide separation experiment. For example, maintaining protein solubility is a key concern before, during and after separation. To this end, surfactants such as sodium dodecyl sulfate may be employed during fractionation, so long as they are eliminated prior to MS. In this article, current strategies for proteome fractionation in a MS-compatible format are reviewed, illustrating the challenges and outlooks on this important aspect of proteomics.

Gel-based and gel-free quantitative proteomics approaches at a glance

Two-dimensional gel electrophoresis (2-DE) is widely applied and remains the method of choice in proteomics; however, pervasive 2-DE-related concerns undermine its prospects as a dominant separation technique in proteome research. Consequently, the state-of-the-art shotgun techniques are slowly taking over and utilising the rapid expansion and advancement of mass spectrometry (MS) to provide a new toolbox of gel-free quantitative techniques. When coupled to MS, the shotgun proteomic pipeline can fuel new routes in sensitive and high-throughput profiling of proteins, leading to a high accuracy in quantification. Although label-based approaches, either chemical or metabolic, gained popularity in quantitative proteomics because of the multiplexing capacity, these approaches are not without drawbacks. The burgeoning label-free methods are tag independent and suitable for all kinds of samples. The challenges in quantitative proteomics are more prominent in plants due to difficulties in protein extraction, some protein abundance in green tissue, and the absence of well-annotated and completed genome sequences. The goal of this perspective assay is to present the balance between the strengths and weaknesses of the available gel-based and -free methods and their application to plants. The latest trends in peptide fractionation amenable to MS analysis are as well discussed.

Software tools for MS-based quantitative proteomics: a brief overview

Proteomics is turning more and more towards quantitative measurements of biological systems. This in turn has spurred the development of numerous experimental methods that enable such measurements. Vast quantities of mostly mass spectrometric data are often generated as a result which requires the use of software tools that turns raw data into useful quantitative information from which knowledge about the biological system can eventually be derived. This chapter gives a brief overview of available software tools for mass spectrometry based quantitative proteomics.

Quantitative mass spectrometry-based proteomics: an overview

In recent years, mass spectrometry has moved more than ever before into the front line of protein-centered research. After being established at the qualitative level, the more challenging question of quantification of proteins and peptides using mass spectrometry has become a focus for further development. In this chapter, we discuss and review the strategies and problems of the methods currently in use for the quantitative analysis of peptides, proteins, and finally proteomes by mass spectrometry. The common themes, the differences, and the potential pitfalls of the main approaches are presented in order to provide a survey of the emerging field of quantitative, mass spectrometry-based proteomics.

Absolute quantification of proteins using standard peptides and multiple reaction monitoring

Mass spectrometry (MS) is a powerful tool for protein identification and has therefore become indispensable for proteome studies. In recent years, simple protein identification by MS has become routine, and more attention has been devoted to the MS-based investigation of posttranslational modifications and the quantification of proteins and peptides. Numerous methods and techniques for relative quantification of proteins by MS have emerged and have been applied successfully to answer various questions of protein abundance. Absolute quantification is often applied in clinical research and biomarker discovery, but has also been used to determine protein stoichiometries in protein complexes. However, the number of methods available for absolute quantification is still restricted and often requires the generation of standard peptides containing amino acids labeled with stable isotopes, although label-free approaches are also gaining importance. Complete hydrolysis of the proteins to be quantified is known to be one of the prerequisites for reliable absolute quantification, and selection and suitability of the standard peptides are critical factors in the planning of a quantitative study. Along the different methods to read out quantitative signals by MS, multiple reaction monitoring (MRM) has proven to be most suitable, with a wide linear range. However, analysis by MRM is a targeted approach and each case requires the individual design of suitable assays, which is a time-consuming step during the preliminary analysis. In this chapter, we present various protocols for in-solution hydrolysis, manual selection of suitable standard peptides, and design of MRM transitions.

Application of subproteomics in the characterization of Gram-positive bacteria

Gram-positive bacteria cause a series of diseases in human, animals and plants. There has been increasing interest in efforts to investigate pathogenesis of bacteria using multiple "omic" strategies including proteomics. Proteins in different cell fractions of bacteria may play different vital roles in various physiological processes, such as adhesion, invasion, internalization, sensing, respiration, oxidative stress protection and pathogenicity. Subproteomics specifically focuses on the pre-fractionated cellular proteins and thus may be able to characterize more low-abundance molecules that are usually overlooked by the traditional whole-cell proteomics, providing comprehensive information for further investigations. This review intends to outline the current progress, challenges and future development of subproteomics in the characterization of Gram-positive bacteria. This article is part of a Special Issue entitled: Proteomics: The clinical link.

The "Alzheimer's disease signature": potential perspectives for novel biomarkers

Alzheimer's disease is a progressive and neurodegenerative disorder which involves multiple molecular mechanisms. Intense research during the last years has accumulated a large body of data and the search for sensitive and specific biomarkers has undergone a rapid evolution. However, the diagnosis remains problematic and the current tests do not accurately detect the process leading to neurodegeneration. Biomarkers discovery and validation are considered the key aspects to support clinical diagnosis and provide discriminatory power between different stages of the disorder. A considerable challenge is to integrate different types of data from new potent approach to reach a common interpretation and replicate the findings across studies and populations. Furthermore, long-term clinical follow-up and combined analysis of several biomarkers are among the most promising perspectives to diagnose and manage the disease. The present review will focus on the recent published data providing an updated overview of the main achievements in the genetic and biochemical research of the Alzheimer's disease. We also discuss the latest and most significant results that will help to define a specific disease signature whose validity might be clinically relevant for future AD diagnosis.

OMICS-strategies and methods in the fight against doping

During the past decade OMICS-methods not only continued to have their impact on research strategies in life sciences and in particular molecular biology, but also started to be used for anti-doping control purposes. Research activities were mainly reasoned by the fact that several substances and methods, which were prohibited by the World Anti-Doping Agency (WADA), were or still are difficult to detect by direct methods. Transcriptomics, proteomics, and metabolomics in theory offer ideal platforms for the discovery of biomarkers for the indirect detection of the abuse of these substances and methods. Traditionally, the main focus of transcriptomics and proteomics projects has been on the prolonged detection of the misuse of human growth hormone (hGH), recombinant erythropoietin (rhEpo), and autologous blood transfusion. An additional benefit of the indirect or marker approach would also be that similarly acting substances might then be detected by a single method, without being forced to develop new direct detection methods for new but comparable prohibited substances (as has been the case, e.g. for the various forms of Epo analogs and biosimilars). While several non-OMICS-derived parameters for the indirect detection of doping are currently in use, for example the blood parameters of the hematological module of the athlete's biological passport, the outcome of most non-targeted OMICS-projects led to no direct application in routine doping control so far. The main reason is the inherent complexity of human transcriptomes, proteomes, and metabolomes and their inter-individual variability. The article reviews previous and recent research projects and their results and discusses future strategies for a more efficient application of OMICS-methods in doping control.

Impact of clostridial glucosylating toxins on the proteome of colonic cells determined by isotope-coded protein labeling and LC-MALDI

Background

The anaerobe Clostridium difficile produces two major virulence factors toxin A and B that inactivate Rho proteins by glucosylation of a pivotal threonine residue. Purified toxins induce reorganization of the cytoskeleton and cell death in colonic cells. Whether all toxin effects on target cells depend on catalytic glucosyltransferase activity is unclear at present. Thus, we conducted a proteome approach to compare the protein profile of target cells treated either with wild type toxin A (rTcdA wt) or with a catalytically inactive mutant toxin A (mutant rTcdA). Relative protein quantification was feasible using isotope-coded protein labeling techniques (ICPL) and mass spectrometry (LC-MALDI).

Results

Altogether we found a significant differential expression of thirty proteins after treatment with rTcdA wt or mutant rTcdA. Mutant rTcdA caused up-regulation of seven proteins and sixteen proteins were responsive to rTcdA wt after 5 h. Long-term effect of rTcdA wt on protein expression was the down-regulation of eleven proteins. Up- or down-regulation of several proteins was verified by western blot analysis confirming the MS results.

Conclusion

Our results indicate incubation time-dependent effects of the clostridial glucosylating toxin A on colonic cells. The rTcdA wt impact more cellular functions than actin cytoskeleton reorganization and apoptosis. Furthermore, these data give insight into glucosyltransferase independent effects of clostridial glucosylating toxins on target cells after short incubation time. Additionally, our data reveal pro-inflammatory and proliferative effects of mutant rTcdA after short-term incubation.

Integration of high accuracy N-terminus identification in peptide sequencing and comparative protein analysis via isothiocyanate-based isotope labeling reagent with ESI ion-trap TOF MS

A multifunctional isothiocyanate-based isotope labeling reagent, [d (0)]-/[d (6)]-4,6-dimethoxy pyrimidine-2-isothiocyanate (DMPITC), has been developed for accurate N-terminus identification in peptide sequencing and comparative protein analysis by ESI Ion-trap TOF mass spectrometry. In contrast with the conventional labeling reagent phenyl isothiocyanate (PITC), DMPITC showed more desirable properties such as rapid labeling, sensitivity enhancement, and facilitating peptide sequencing. More significantly, DMPITC-based labeling strategy possessed the capacity of higher reliable N-terminus identification owning to the high-yield b(1) ion combined with the isotope validation of 6 Da. Meanwhile, it also showed potential in differentiating isomeric residues of leucine and isoleucine at N-terminus on the basis of the relative abundance ratios between the fragment ions of their respective b(1) ions. The strategy not only allows accurate interpretation for peptide but also ensures rapid and sensitive comparative analysis for protein by direct MS analysis. Using trypsin-digested bovine serum albumin (BSA), both peptide N-terminus identification and quantitative analysis were accomplished with high accuracy, efficiency, and reproducibility. The application of DMPITC-based labeling strategy is expected to serve as a promising tool for proteome research.

Inverse regulation in the metabolic genes pckA and metE revealed by proteomic analysis of the Salmonella RcsCDB regulon

The RcsC, RcsD, and RcsB proteins compose a system used by enteric bacteria to sense envelope stress. Signal transmission occurs from the sensor RcsC to the transcriptional regulator RcsB. Accessory proteins, such as IgaA, are known to adjust the response level. In a previous transcriptomic study, we uncovered 85 genes differentially expressed in Salmonella enterica serovar Typhimurium igaA mutants. Here, we extended these observations to proteomics by performing differential isotope-coded protein labeling (ICPL) followed by liquid chromatography-electrospray ionization tandem mass spectrometry. Five-hundred five proteins were identified and quantified, with 75 of them displaying significant changes in response to alterations in the RcsCDB system. Divergent expression at the RNA and protein level was observed for the metabolic genes pckA and metE, involved in gluconeogenesis and methionine synthesis, respectively. When analyzed in diverse environmental conditions, including the intracellular niche of eukaryotic cells, inverse regulation was more evident for metE and in bacteria growing in defined minimal medium or to stationary phase. The RcsCDB system was also shown to repress the synthesis of the small RNA FnrS, previously reported to modulate metE expression. Collectively, these findings provide new insights into post-transcriptional regulatory mechanisms involving the RcsCDB system and its control over metabolic functions.

Nutriproteomics: technologies and applications for identification and quantification of biomarkers and ingredients

Nutrition refers to the process by which a living organism ingests and digests food and uses the nutrients therein for growth, tissue maintenance and all other functions essential to life. Food components interact with our body at molecular, cellular, organ and system level. Nutrients come in complex mixtures, in which the presence and concentration of single compounds as well as their interactions with other compounds and the food matrix influence their bioavailability and bioefficacy. Traditionally, nutrition research mainly concentrated on supplying nutrients of quality to nourish populations and on preventing specific nutrient deficiencies. More recently, it investigates health-related aspects of individual ingredients or of complete diets, in view of health promotion, performance optimisation, disease prevention and risk assessment. This review focuses on proteins and peptides, their role as nutrients and biomarkers and on the technologies developed for their analysis. In the first part of this review, we provide insights into the way proteins are currently characterised and analysed using classical and emerging proteomic approaches. The scope of the second part is to review major applications of proteomics to nutrition, from characterisation of food proteins and peptides, via investigation of health-related food benefits to understanding disease-related mechanisms.

Identification and characterization of human leukocyte antigen class I ligands in renal cell carcinoma cells

The presentation of tumor antigen-derived peptides by human leukocyte antigen (HLA) class I surface antigens on tumor cells is a key prerequisite to trigger effective T-cell responses in cancer patients. Multiple complementary strategies like cDNA and serological expression cloning, reverse immunology and different 'ome'-based methods have been employed to identify potential T-cell targets. This report focuses on a ligandomic profiling approach leading to the identification of 49 naturally processed HLA class I peptide ligands presented on the cell surface of renal cell carcinoma (RCC) cells. The source proteins of the defined HLA ligands are classified according to their biological function and subcellular localization. Previously established cDNA microarray data of paired tissue specimen of RCC and renal epithelium assessed the transcriptional regulation for 28 source proteins. In addition, HLA-A2-restricted, peptide-specific T cells directed against a HLA ligand derived from sulfiredoxin-1 (SRXN1) were generated, which were able to recognize and lyse ligand-presenting target cells in a HLA class I-restricted manner. Furthermore, tumor-infiltrating T cells isolated from a RCC patient were also able to kill SRXN1 expressing tumor cells. Thus, this experimental strategy might be suited to define potential candidate biomarkers and novel targets for T-cell-based immunotherapies of this disease.

General statistical modeling of data from protein relative expression isobaric tags

Quantitative comparison of the protein content of biological samples is a fundamental tool of research. The TMT and iTRAQ isobaric labeling technologies allow the comparison of 2, 4, 6, or 8 samples in one mass spectrometric analysis. Sound statistical models that scale with the most advanced mass spectrometry (MS) instruments are essential for their efficient use. Through the application of robust statistical methods, we developed models that capture variability from individual spectra to biological samples. Classical experimental designs with a distinct sample in each channel as well as the use of replicates in multiple channels are integrated into a single statistical framework. We have prepared complex test samples including controlled ratios ranging from 100:1 to 1:100 to characterize the performance of our method. We demonstrate its application to actual biological data sets originating from three different laboratories and MS platforms. Finally, test data and an R package, named isobar, which can read Mascot, Phenyx, and mzIdentML files, are made available. The isobar package can also be used as an independent software that requires very little or no R programming skills.

Insights into MHC class I antigen processing gained from large-scale analysis of class I ligands

Short peptides derived from intracellular proteins and presented on MHC class I molecules on the cell surface serve as a showcase for the immune system to detect pathogenic or malignant alterations inside the cell, and the sequencing and analysis of the presented peptide pool has received considerable attention over the last two decades. In this review, we give a comprehensive presentation of the methods employed for the large-scale qualitative and quantitative analysis of the MHC class I ligandome. Furthermore, we focus on insights gained into the underlying processing pathway, especially involving the roles of the proteasome, the TAP complex, and the peptide specificities and motifs of MHC molecules. The identification of post-translational modifications in MHC ligands and their implications for processing are also considered. Finally, we review the correlations of the ligandome to the proteome and the transcriptome.

Quantitative neuroproteomics: classical and novel tools for studying neural differentiation and function

Mechanisms underlying neural stem cell proliferation, differentiation and maturation play a critical role in the formation and wiring of neuronal connections. This process involves the activation of multiple serial events, which guide the undifferentiated cells to different lineages via distinctive developmental programs, forming neuronal circuits and thus shaping the adult nervous system. Furthermore, alterations within these strictly regulated pathways can lead to severe neurological and psychiatric diseases. In this framework, the investigation of the high dynamic protein expression changes and other factors affecting protein functions, for example post-translational modifications, the alterations of protein interaction networks, is of pivotal importance for the understanding of the molecular mechanisms responsible for cell differentiation. More recently, proteomic studies in neuroscience ("neuroproteomics") are receiving increased interest for the primary understanding of the regulatory networks underlying neuronal differentiation processes. Besides the classical two-dimensional-based proteomic strategies, the emerging platforms for LC-MS shotgun proteomic analysis hold great promise in unraveling the molecular basis of neural stem cell differentiation. In this review, recent advancements in label-free LC-MS quantitative neuroproteomics are highlighted as a new tool for the study of neural differentiation and functions, in comparison to mass spectrometry-based labeling approaches. The more commonly used protein profiling strategies and model systems for the analysis of neural differentiation are also discussed, along with the challenging proteomic approaches aimed to analyze the nervous system-specific organelles, the neural cells secretome and the specific protein interaction networks.

Unraveling the dynamics of protein interactions with quantitative mass spectrometry

Knowledge of structure and dynamics of proteins and protein complexes is important to unveil the molecular basis and mechanisms involved in most biological processes. Protein complex dynamics can be defined as the changes in the composition of a protein complex during a cellular process. Protein dynamics can be defined as conformational changes in a protein during enzyme activation, for example, when a protein binds to a ligand or when a protein binds to another protein. Mass spectrometry (MS) combined with affinity purification has become the analytical tool of choice for mapping protein-protein interaction networks and the recent developments in the quantitative proteomics field has made it possible to identify dynamically interacting proteins. Furthermore, hydrogen/deuterium exchange MS is emerging as a powerful technique to study structure and conformational dynamics of proteins or protein assemblies in solution. Methods have been developed and applied for the identification of transient and/or weak dynamic interaction partners and for the analysis of conformational dynamics of proteins or protein complexes. This review is an overview of existing and recent developments in studying the overall dynamics of in vivo protein interaction networks and protein complexes using MS-based methods.

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.

Catch me if you can: mass spectrometry-based phosphoproteomics and quantification strategies

Phosphorylation of proteins is one of the most prominent PTMs and for instance a key regulator of signal transduction. In order to improve our understanding of cellular phosphorylation events, considerable effort has been devoted to improving the analysis of phosphorylation by MS-based proteomics. Different enrichment strategies for phosphorylated peptides/proteins, such as immunoaffinity chromatography (IMAC) or titanium dioxide, have been established and constantly optimized for subsequent MS analysis. Concurrently, specific MS techniques were developed for more confident identification and phosphorylation site localization. In addition, more attention is paid to the LC-MS instrumentation to avoid premature loss of phosphorylated peptides within the analytical system. Despite major advances in all of these fields, the analysis of phosphopeptides still remains far from being routine in proteomics. However, to reveal cellular regulation by phosphorylation events, not only qualitative information about the phosphorylation status of proteins but also, in particular, quantitative information about distinct changes in phosphorylation patterns upon specific stimulation is mandatory. Thus, yielded insights are of outstanding importance for the emerging field of systems biology. In this review, we will give an insight into the historical development of phosphoproteome analysis and discuss its recent progress particularly regarding phosphopeptide quantification and assessment of phosphorylation stoichiometry.

Deuterium isobaric amine-reactive tags for quantitative proteomics

This paper demonstrates the applications of a novel isobaric reagent, named deuterium ((2)H) isobaric amine-reactive tag (DiART), for quantitative proteomics. Peptides labeled with DiART were analyzed using an electrospray ionization (ESI)-based LTQ-Orbitrap mass spectrometer. Our data showed that (2)H-associated isotope effects, such as partial loss of (2)H labels during tandem mass spectrometry (MS/MS) and (2)H-related chromatographic shift, were either not observed or negligible. With the use of a hybrid collision-induced dissociation (CID)-higher energy C-trap dissociation (HCD) acquisition method, we were able to identify DiART-labeled peptides with high confidence and quantify them with high accuracy. Furthermore, we adopted a hybrid electron-transfer dissociation (ETD)-HCD acquisition protocol and developed a novel data analysis approach to measure phosphorylation of peptides. Our results showed DiART had excellent performance on LTQ-Orbitrap instruments and provided a cost-effective technique for large-scale quantitative proteomics measurements.

Complete chemical modification of amine and acid functional groups of peptides and small proteins

The chemical modification of protein thiols by reduction and alkylation is common in the preparation of proteomic samples for analysis by mass spectrometry (MS). Modification at other functional groups has received less attention in MS-based proteomics. Amine modification (Lys, N-termini) by reductive dimethylation or by acylation (e.g., iTRAQ labeling) has recently gained some popularity in peptide-based approaches (bottom-up MS). Modification at acidic groups (Asp, Glu, C-termini) has been explored very minimally. Here, we describe a sequential labeling strategy that enables complete modification of thiols, amines, and acids on peptides or small intact proteins. This method includes (1) the reduction and alkylation of thiols, (2) the reductive dimethylation of amines, and (3) the amidation of acids with any of several amines. This chemical modification scheme offers several options both for the incorporation of stable isotopes for relative quantification and for improving peptides or proteins as MS analytes.

Dynamic proteome signatures in gametes, embryos and their maternal environment

Comprehensive molecular analysis at the level of proteins represents a technically demanding, but indispensable, task since several post-transcriptional regulation mechanisms disable a valid prediction of quantitative protein expression profiles from transcriptome analysis. In crucial steps of gamete and early embryo development, de novo transcription is silenced, meaning that almost all macromolecular events take place at the level of proteins. In this review, we describe selected examples of dynamic proteome signatures addressing capacitation of spermatozoa, in vitro maturation of oocytes, effect of oestrous cycle on oviduct epithelial cells and embryo-induced alterations to the maternal environment. We also present details of the experimental strategies applied and the experiments performed to verify quantitative proteomic data. Far from being comprehensive, examples were selected to cover several mammalian species as well as the most powerful proteomic techniques currently applied. To enable non-experts in the field of proteomics to appraise published proteomic data, our examples are preceded by a customised description of quantitative proteomic methods, covering 2D difference gel electrophoresis (2D-DIGE), nano-liquid chromatography combined with tandem mass spectrometry, and label-free as well as stable-isotope labelling strategies for mass spectrometry-based quantifications.

ICPL labeling strategies for proteome research

Stable isotope labeling in combination with mass spectrometry has emerged as a powerful tool to identify and quantify thousands of proteins within complex protein mixtures. Isotope-coded protein label (ICPL) is capable of high-throughput quantitative proteome profiling on a global scale. Since ICPL is based on stable isotope tagging at the free amino groups of intact proteins, it is applicable to any protein sample, including extracts from tissues or body fluids. After labeling of up to four different proteome states, the samples can be combined and the complexity reduced by any separation method currently employed in protein chemistry. After enzymatic cleavage of the protein fractions the ratios of peptides in the different proteome states can be calculated by simple MS-based mass spectrometric analyses. Only peptides that exhibit regulations in the different proteome states are further investigated for identification by tandem-mass spectrometry. The quantification of multiplexed ICPL experiments is greatly facilitated by the recently published ICPLQuant software, which was especially designed to cover the whole ICPL workflow. The method shows highly accurate and reproducible quantification of proteins, yields high sequence coverage, and is indispensable for the comprehensive detection of posttranslational modifications and protein isoforms.