Selected reaction monitoring for quantitative proteomics: a tutorial

Extracellular matrix bioengineering and systems biology approaches in liver disease

The extracellular matrix (ECM) in the liver as well as in many organs comprises a peripheral network linking numerous macromolecules typically classified into collagens, microfibrillar proteins, proteoglycans, chemokines, growth factors and glycoproteins. In addition to its role as an essential structural and physiological component, it plays a vital role in driving key cellular events such as cell adhesion, migration, proliferation, differentiation and survival. Any structural inherited or acquired defect and/or metabolic or pathologic alteration in the hepatic ECM may cause cellular and organ responses leading to the development or progression of liver disease. Therefore, the ECM molecules are key players in tissue engraftment and in the pathophysiology of liver disease. In this review we provide a snapshot on current efforts for understanding its role in physiological and non-physiological states, by describing how tissue engineering platforms can enhance in vitro and in vivo models of liver disease, by providing examples where bioengineered ECM can serve as systems biology approaches to study the ECM, and then by evaluating pathological protein regulatory networks in the liver using systems biology tools. These approaches hold great promise for future research.

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.

Quantification of activated NF-kappaB/RelA complexes using ssDNA aptamer affinity-stable isotope dilution-selected reaction monitoring-mass spectrometry

Nuclear Factor-κB (NF-κB) is a family of inducible transcription factors regulated by stimulus-induced protein interactions. In the cytoplasm, the NF-κB member RelA transactivator is inactivated by binding inhibitory IκBs, whereas in its activated state, the serine-phosphorylated protein binds the p300 histone acetyltransferase. Here we describe the isolation of a ssDNA aptamer (termed P028F4) that binds to the activated (IκBα-dissociated) form of RelA with a K(D) of 6.4 × 10(-10), and its application in an enrichment-mass spectrometric quantification assay. ssDNA P028F4 competes with cognate duplex high affinity NF-κB binding sites for RelA binding in vitro, binds activated RelA in eukaryotic nuclei and reduces TNFα-stimulated endogenous NF-κB dependent gene expression. Incorporation of P028F4 as an affinity isolation step enriches for serine 536 phosphorylated and p300 coactivator complexed RelA, simultaneously depleting IκBα·RelA complexes. A stable isotope dilution (SID)-selected reaction monitoring (SRM)- mass spectrometry (MS) assay for RelA was developed that produced a linear response over 1,000 fold dilution range of input protein and had a 200 amol lower limit of quantification. This multiplex SID-SRM-MS RelA assay was used to quantify activated endogenous RelA in cytokine-stimulated eukaryotic cells isolated by single-step P028F4 enrichment. The aptamer-SID-SRM-MS assay quantified the fraction of activated RelA in subcellular extracts, detecting the presence of a cytoplasmic RelA reservoir unresponsive to TNFα stimulation. We conclude that aptamer-SID-SRM-MS is a versatile tool for quantification of activated NF-κB/RelA and its associated complexes in response to pathway activation.

Liquid chromatography-mass spectrometry-based quantitative proteomics

LC-MS-based quantitative proteomics has become increasingly applied to a wide range of biological applications due to growing capabilities for broad proteome coverage and good accuracy and precision in quantification. Herein, we review the current LC-MS-based quantification methods with respect to their advantages and limitations and highlight their potential applications.

Protein phosphorylation analysis in archival clinical cancer samples by shotgun and targeted proteomics approaches

Protein phosphorylation affects most eukaryotic cellular processes and its deregulation is considered a hallmark of cancer and other diseases. Phosphoproteomics may enable monitoring of altered signaling pathways as a means of stratifying tumors and facilitating the discovery of new drugs. Unfortunately, the development of molecular tests for clinical use is constrained by the limited availability of fresh frozen, clinically annotated samples. Here we report phosphopeptide analysis in human archival formalin-fixed, paraffin-embedded (FFPE) cancer samples based on immobilized metal affinity chromatography followed by liquid chromatography coupled with tandem mass spectrometry and selected reaction monitoring techniques. Our results indicate the equivalence of detectable phosphorylation rates in archival FFPE and fresh frozen tissues. Moreover, we demonstrate the applicability of targeted assays for phosphopeptide analysis in clinical archival FFPE samples, using an experimental workflow suitable for processing and analyzing large sample series. This work paves the way for the application of shotgun and targeted phosphoproteomics approaches in clinically relevant studies using archival clinical samples.

Monitoring protein expression in whole-cell extracts by targeted label- and standard-free LC-MS/MS

Targeted quantification of proteins is a daily task in biological research but often relies on techniques such as western blotting that are only barely quantitative. Here we present a broadly applicable workflow for protein quantification from unpurified whole-cell extracts that can be completed in less than 3 d. Without prefractionation or affinity enrichment, a whole-cell extract is trypsin-digested in an acetonitrile-containing ammonium carbonate buffer and high-molecular-weight compounds are removed by filtration. A normalization strategy, which involves endogenous reference proteins, facilitates the determination of relative changes in protein expression without requiring isotope labeling or standard addition. On a triple-quadrupole mass spectrometer, we demonstrate standard-free quantification of yeast proteins present over five orders of magnitude and present at ≥500 copies per cell. Liquid chromatography/multiple reaction monitoring (LC-MRM)-based proteomics is therefore a next-generation alternative to western blotting, as it allows simultaneous and reliable quantification of multiple endogenous proteins without the need for enrichment, isotope labeling or use of antibodies.

Proteomic analysis in allergy and intolerance to wheat products

Owing to its extensive use in the human diet, wheat is among the most common causes of food-related allergies and intolerances. Allergies to wheat are provoked by ingestion, inhalation or contact with either the soluble or the insoluble gluten proteins in wheat. Gluten proteins, and particularly the gliadin fraction, are also the main factor triggering celiac disease, a common enteropathy induced by ingestion of wheat gluten proteins and related prolamins from oat, rye and barley in genetically susceptible individuals. The role of gliadin and of its derived peptides in eliciting the adverse reactions in celiac disease are still far from being completely explained. Owing to its unique pathogenesis, celiac disease is widely investigated as a model immunogenetic disorder. The structural characterization of the injuring agents, the gluten proteins, assumes a particular significance in order to deepen the understanding of the events that trigger this and similar diseases at the molecular level. Recent developments in proteomics have provided an important contribution to the understanding of several basic aspects of wheat protein-related diseases. These include: the identification of gluten fractions and derived peptides involved in wheat allergy and intolerance, including celiac disease, and the elucidation of their mechanism of toxicity; the development and validation of sensitive and specific methods for detecting trace amounts of gluten proteins in gluten-free foods for intolerant patients; and the formulation of completely new substitute foods and ingredients to replace the gluten-based ones. In this article, the main aspects of current and prospective applications of mass spectrometry and proteomic technologies to the structural characterization of gluten proteins and derived peptides are critically presented, with a focus on issues related to their detection, identification and quantification, which are relevant to the biochemical, immunological and toxicological aspects of wheat intolerance.

Direct quantitation of MHC-bound peptide epitopes by selected reaction monitoring

We describe a cell-free approach that employs selected reaction monitoring (SRM) in tandem mass spectrometry to identify and quantitate T-cell epitopes. This approach utilises multiple epitope-specific SRM transitions to identify known T-cell epitopes and an absolute quantitation (AQUA) peptide strategy to afford AQUA. The advantage of a mass spectrometry-based approach over more traditional cell-based assays resides in the robustness and transferability of an SRM approach between laboratories and the ability of this strategy to detect multiple peptides simultaneously without the requirement of epitope-specific reagents such as T-cell lines. Thus, the SRM strategy for epitope quantitation will find application in studies of antigen density, the link between epitope abundance and immunogenicity, the dynamic range of epitope presentation and the abundance of T-cell epitopes in disease.

Selected reaction monitoring by linear ion-trap mass spectrometry can effectively be applicable to simultaneous quantification of multiple peptides

Selected reaction monitoring (SRM) mass spectrometry (MS) is becoming a popular approach for targeted quantitative proteomics. Triple-quadrupole mass spectrometers have been historically considered as the instrument of choice for this type of quantitative analysis. Recently, however, it has been reported that the SRM MS with a linear ion-trap (LIT) mass spectrometer is rather more appropriate for quantitative analysis of large peptides than the triple-quadrupole ones. In this study, we demonstrate that the SRM MS performed with a LIT mass spectrometer can simultaneously analyze multiple peptides and can quantify specific peptides in biological specimens without the use of stable isotope (SI)-labeled standard peptides. Firstly, a mixture of 10 synthesized peptides derived from yeast proteins and bovine serum albumin (BSA) was simultaneously analyzed by the LIT SRM. The ion peak areas of the 10 peptides were linearly correlated with the input amounts between 1 fmol and 10 pmol. Furthermore, the same peptide mixture spiked into human plasma was analyzed, and a linear response was found. Next, the amount of a BSA tryptic peptide was quantified by using an SI-labeled or a non SI-labeled peptide as an external reference standard. The difference in the quantified amounts of the BSA tryptic peptide was less than 10% between the 2 methods, suggesting that the "externally pulsed" non SI-labeled standard peptides derived from another species are useful. These results indicate that the SRM MS conducted with a LIT mass spectrometer is applicable to targeted quantitative proteomics of peptides at least up to 10 in number.

Comprehensive quantitative analysis of central carbon and amino-acid metabolism in Saccharomyces cerevisiae under multiple conditions by targeted proteomics

With a targeted proteomic approach, we could quantify 90% of the enzymes involved in carbon and amino-acid metabolism in yeast, including complete isoenzyme families, throughout a set of different metabolic states.

The data, interpreted through flux balance modeling, indicate that S. cerevisiae expresses enzymes, not necessarily used in a particular metabolic condition.

For many isoenzymes our data suggest functional diversification, which might explain their parallel presence in the S. cerevisiae genome.

The metabolic network in the yeast Saccharomyces cerevisiae has been very well characterized in terms of components and topology. The adaptation of metabolism to changing nutritional conditions, in contrast, is much less well understood.

In this study, we exploited quantitative proteomic assays based on selected reaction monitoring (SRM) mass spectrometry to comprehensively analyze the set of enzymes involved in carbon and amino-acid metabolism in yeast (Figure 1), throughout a set of different metabolic states. To elucidate how this metabolic network of proteins adapts to environmental challenges, we chose five nutritional conditions resulting in maximal difference in magnitude and direction of metabolic fluxes. We could reproducibly detect and quantify across the different conditions, 90% of the targeted metabolic proteome, including complete families of isoenzymes, sharing up to 99.5% sequence identity and multi-subunit enzyme complexes. This yielded an information-rich proteomic data set that represents a nutritionally perturbed biological system with high coverage of its components.

Interpreted through flux balance modeling, the data indicate that S. cerevisiae expresses—at least at a basal level—more proteins than are actually necessary for sustaining a given metabolic condition. One potential explanation for the presence of non-necessary proteins is that these enzymes could realize immediate basal metabolic fluxes upon a change to new environmental conditions.

Next, we asked whether our data set could contribute to unravel the function of isoenzymes in the metabolic set. Previously proposed roles for isoenzymes include redundancy to buffer against mutations, a means to gene dosage or facilitation of evolutionary innovation and functional diversification. To address the role of isoenzymes in central metabolism, we used hierarchical clustering to analyze the abundance patterns of the metabolic proteins and their relationship to different functional classes and metabolic pathways. Interestingly, while subunits of the same protein complex preferably cluster in proximate branches, members of the same isoenzyme family often clustered in distant branches (Figure 5). The data therefore suggested functional diversification within most isoenzyme families and allowed to propose different functions of divergent isoenzymes.

We expect that the comprehensive data set presented in this study will be an ideal blueprint for further developing models of yeast metabolism and for follow-up studies on the function of target metabolic proteins.

Decades of biochemical research have identified most of the enzymes that catalyze metabolic reactions in the yeast Saccharomyces cerevisiae. The adaptation of metabolism to changing nutritional conditions, in contrast, is much less well understood. As an important stepping stone toward such understanding, we exploit the power of proteomics assays based on selected reaction monitoring (SRM) mass spectrometry to quantify abundance changes of the 228 proteins that constitute the central carbon and amino-acid metabolic network in the yeast Saccharomyces cerevisiae, at five different metabolic steady states. Overall, 90% of the targeted proteins, including families of isoenzymes, were consistently detected and quantified in each sample, generating a proteomic data set that represents a nutritionally perturbed biological system at high reproducibility. The data set is near comprehensive because we detect 95–99% of all proteins that are required under a given condition. Interpreted through flux balance modeling, the data indicate that S. cerevisiae retains proteins not necessarily used in a particular environment. Further, the data suggest differential functionality for several metabolic isoenzymes.

Intracellular eukaryotic parasites have a distinct unfolded protein response

Insult to the endoplasmic reticulum (ER) activates the Unfolded Protein Response (UPR), a set of signaling pathways that protect the cell from the potential damage caused by improperly folded proteins. Accumulation of misfolded proteins in the ER lumen initiates a series of signal transduction events via activation of three transmembrane ER proteins: Ire1, Atf6 and PERK. Activation of these proteins results in the transcriptional up-regulation of the components of the folding, trafficking and degradation machinery in the ER. PERK further reduces the load on the ER via the phosphorylation of eIF2α, attenuating general protein translation. It is believed that the UPR evolved as a transcriptional response that up-regulates protein folding machinery in the ER and later gained the ability to decrease ER load by attenuating general protein translation in metazoa. However, our in silico analyses of protozoan parasites revealed an absence of proteins involved in the transcriptionally mediated UPR and the presence of both PERK and its target eIF2α. Consistent with these observations, stimulation of the UPR in Leishmania donovani identified an absence of up-regulation of the ER chaperone BiP, the canonical ER chaperone modulated by the UPR in higher eukaryotes, while exhibiting increased phosphorylation of eIF2α which has been shown to attenuate protein translation. We further observed that L. donovani is more sensitive to UPR inducing agents than host macrophages, suggesting that the less evolved stress response could provide a new avenue for therapeutic treatment of parasitic infections.

mProphet: automated data processing and statistical validation for large-scale SRM experiments

Selected reaction monitoring (SRM) is a targeted mass spectrometric method that is increasingly used in proteomics for the detection and quantification of sets of preselected proteins at high sensitivity, reproducibility and accuracy. Currently, data from SRM measurements are mostly evaluated subjectively by manual inspection on the basis of ad hoc criteria, precluding the consistent analysis of different data sets and an objective assessment of their error rates. Here we present mProphet, a fully automated system that computes accurate error rates for the identification of targeted peptides in SRM data sets and maximizes specificity and sensitivity by combining relevant features in the data into a statistical model.

ATAQS: A computational software tool for high throughput transition optimization and validation for selected reaction monitoring mass spectrometry

BACKGROUND

Since its inception, proteomics has essentially operated in a discovery mode with the goal of identifying and quantifying the maximal number of proteins in a sample. Increasingly, proteomic measurements are also supporting hypothesis-driven studies, in which a predetermined set of proteins is consistently detected and quantified in multiple samples. Selected reaction monitoring (SRM) is a targeted mass spectrometric technique that supports the detection and quantification of specific proteins in complex samples at high sensitivity and reproducibility. Here, we describe ATAQS, an integrated software platform that supports all stages of targeted, SRM-based proteomics experiments including target selection, transition optimization and post acquisition data analysis. This software will significantly facilitate the use of targeted proteomic techniques and contribute to the generation of highly sensitive, reproducible and complete datasets that are particularly critical for the discovery and validation of targets in hypothesis-driven studies in systems biology.

RESULT

We introduce a new open source software pipeline, ATAQS (Automated and Targeted Analysis with Quantitative SRM), which consists of a number of modules that collectively support the SRM assay development workflow for targeted proteomic experiments (project management and generation of protein, peptide and transitions and the validation of peptide detection by SRM). ATAQS provides a flexible pipeline for end-users by allowing the workflow to start or end at any point of the pipeline, and for computational biologists, by enabling the easy extension of java algorithm classes for their own algorithm plug-in or connection via an external web site.This integrated system supports all steps in a SRM-based experiment and provides a user-friendly GUI that can be run by any operating system that allows the installation of the Mozilla Firefox web browser.

CONCLUSIONS

Targeted proteomics via SRM is a powerful new technique that enables the reproducible and accurate identification and quantification of sets of proteins of interest. ATAQS is the first open-source software that supports all steps of the targeted proteomics workflow. ATAQS also provides software API (Application Program Interface) documentation that enables the addition of new algorithms to each of the workflow steps. The software, installation guide and sample dataset can be found in http://tools.proteomecenter.org/ATAQS/ATAQS.html.

Towards the profiling of the Arabidopsis thaliana plasma membrane transportome by targeted proteomics

Plant membranes bear a variety of transporters belonging to multigene families that are affected by environmental and nutritional conditions. In addition, they often display high-sequence identity, making difficult in-depth investigation by current shot-gun strategies. In this study, we set up a targeted proteomics approach aimed at identifying and quantifying within single experiments the five major proton pumps of the autoinhibited H(+) ATPases (AHA) family, the 13 plasma membrane intrinsic proteins (PIP) water channels (PIPs), and ten members of ammonium transporters (AMTs) and nitrate transporter (NRT) families. Proteotypic peptides were selected and isotopically labeled heavy versions were used for technical optimization and for quantification of the corresponding light version in biological samples. This approach allowed to quantify simultaneously nine PIPs in leaf membranes and 13 PIPs together with three autoinhibited H(+) ATPases, two ammonium transporters, and two NRTs in root membranes. Similarly, it was used to investigate the effect of a salt stress on the expression of these latter 20 transporters in roots. These novel isoform-specific data were compared with published transcriptome information and revealed a close correlation between PIP isoforms and transcripts levels. The obtained resource is reusable and can be expanded to other transporter families for large-scale profiling of membrane transporters.

Peptide and protein drug analysis by MS: challenges and opportunities for the discovery environment

Straightforward assay development using MS has become commonplace in most modern pharmaceutical laboratories. In particular, MS is an invaluable tool in the discovery environment of this industry, making it possible to characterize the structures of target drugs and to screen large numbers of potential drug candidates in metabolism and pharmacokinetics studies, and much more. Furthermore, as drug portfolios expand to include biotherapeutic species, such as peptides and proteins, MS is there to meet any analytical challenges. In this article, general aspects of MS in the discovery environment are discussed, as well as what the future might hold.

Selected reaction monitoring applied to proteomics

Selected reaction monitoring (SRM) performed on triple quadrupole mass spectrometers has been the reference quantitative technique to analyze small molecules for several decades. It is now emerging in proteomics as the ideal tool to complement shotgun qualitative studies; targeted SRM quantitative analysis offers high selectivity, sensitivity and a wide dynamic range. However, SRM applied to proteomics presents singularities that distinguish it from small molecules analysis. This review is an overview of SRM technology and describes the specificities and the technical aspects of proteomics experiments. Ongoing developments aiming at increasing multiplexing capabilities of SRM are discussed; they dramatically improve its throughput and extend its field of application to directed or supervised discovery experiments.

Regulation of the DNA damage response and gene expression by the Dot1L histone methyltransferase and the 53Bp1 tumour suppressor

Background

Dot1L, a histone methyltransferase that targets histone H3 lysine 79 (H3K79), has been implicated in gene regulation and the DNA damage response although its functions in these processes remain poorly defined.

Methodology/Principal Findings

Using the chicken DT40 model system, we generated cells in which the Dot1L gene is disrupted to examine the function and focal recruitment of the 53Bp1 DNA damage response protein. Detailed kinetic and dose response assays demonstrate that, despite the absence of H3K79 methylation demonstrated by mass spectrometry, 53Bp1 focal recruitment is not compromised in these cells. We also describe, for the first time, the phenotypes of a cell line lacking both Dot1L and 53Bp1. Dot1L^−/− and wild type cells are equally resistant to ionising radiation, whereas 53Bp1^−/−/Dot1L^−/− cells display a striking DNA damage resistance phenotype. Dot1L and 53Bp1 also affect the expression of many genes. Loss of Dot1L activity dramatically alters the mRNA levels of over 1200 genes involved in diverse biological functions. These results, combined with the previously reported list of differentially expressed genes in mouse ES cells knocked down for Dot1L, demonstrates surprising cell type and species conservation of Dot1L-dependent gene expression. In 53Bp1^−/− cells, over 300 genes, many with functions in immune responses and apoptosis, were differentially expressed. To date, this is the first global analysis of gene expression in a 53Bp1-deficient cell line.

Conclusions/Significance

Taken together, our results uncover a negative role for Dot1L and H3K79 methylation in the DNA damage response in the absence of 53Bp1. They also enlighten the roles of Dot1L and 53Bp1 in gene expression and the control of DNA double-strand repair pathways in the context of chromatin.

Pulsed multiple reaction monitoring approach to enhancing sensitivity of a tandem quadrupole mass spectrometer

Liquid chromatography (LC)-triple quadrupole mass spectrometers operating in a multiple reaction monitoring (MRM) mode are increasingly used for quantitative analysis of low-abundance analytes in highly complex biochemical matrixes. After development and selection of optimum MRM transitions, sensitivity and data quality limitations are largely related to mass spectral peak interferences from sample or matrix constituents and statistical limitations at low number of ions reaching the detector. Herein, we report on a new approach to enhancing MRM sensitivity by converting the continuous stream of ions from the ion source into a pulsed ion beam through the use of an ion funnel trap (IFT). Evaluation of the pulsed MRM approach was performed with a tryptic digest of Shewanella oneidensis strain MR-1 spiked with several model peptides. The sensitivity improvement observed with the IFT coupled in to the triple quadrupole instrument is based on several unique features. First, ion accumulation radio frequency (rf) ion trap facilitates improved droplet desolvation, which is manifested in the reduced background ion noise at the detector. Second, signal amplitude for a given transition is enhanced because of an order-of-magnitude increase in the ion charge density compared to a continuous mode of operation. Third, signal detection at the full duty cycle is obtained, as the trap use eliminates dead times between transitions, which are inevitable with continuous ion streams. In comparison with the conventional approach, the pulsed MRM signals showed 5-fold enhanced peak amplitude and 2-3-fold reduced chemical background, resulting in an improvement in the limit of detection (LOD) by a factor of ∼4-8.

A global analysis of peptide fragmentation variability

Understanding the fragmentation process in MS/MS experiments is vital when trying to validate the results of such experiments, and one way of improving our understanding is to analyze existing data. We here present our findings from an analysis of a large and diverse data set of MS/MS-based peptide identifications, in which each peptide has been identified from multiple spectra, recorded on two commonly used types of electrospray instruments. By analyzing these data we were able to study fragmentation variability on three levels: (i) variation in detection rates and intensities for fragment ions from the same peptide sequence measured multiple times on a single instrument; (ii) consistency of rank-based fragmentation patterns; and (iii) a set of general observations on fragment ion occurrence in MS/MS experiments, regardless of sequence. Our results confirm that substantial variation can be found at all levels, even when high-quality identifications are used and the experimental conditions as well as the peptide sequences are kept constant. Finally, we discuss the observed variability in light of ongoing efforts to create spectral libraries and predictive software for target selection in targeted proteomics.

Effective representation and storage of mass spectrometry-based proteomic data sets for the scientific community

Mass spectrometry-based proteomics has emerged as a technology of choice for global analysis of cell signaling networks. However, reporting and sharing of MS data are often haphazard, limiting the usefulness of proteomics to the signaling community. We argue that raw data should always be provided with proteomics studies together with detailed peptide and protein identification and quantification information. Statistical criteria for peptide identification and their posttranslational modifications have largely been established for individual projects. However, the current practice of indiscriminately incorporating these individual results into databases such as UniProt is problematic. Because of the vast differences in underlying data quality, we advocate a differentiated annotation of data by level of reliability. Requirements for the reporting of quantitative data are being developed, but there are few mechanisms for community-wide sharing of these data.

Moving towards high density clinical signature studies with a human proteome catalogue developing multiplexing mass spectrometry assay panels

A perspective overview is given describing the current development of multiplex mass spectrometry assay technology platforms utilized for high throughput clinical sample analysis. The development of targeted therapies with novel personalized medicine drugs will require new tools for monitoring efficacy and outcome that will rely on both the quantification of disease progression related biomarkers as well as the measurement of disease specific pathway/signaling proteins.The bioinformatics developments play a key central role in the area of clinical proteomics where targeted peptide expressions in health and disease are investigated in small-, medium- and large-scaled clinical studies.An outline is presented describing applications of the selected reaction monitoring (SRM) mass spectrometry assay principle. This assay form enables the simultaneous description of multiple protein biomarkers and is an area under a fast and progressive development throughout the community. The Human Proteome Organization, HUPO, recently launched the Human Proteome Project (HPP) that will map the organization of proteins on specific chromosomes, on a chromosome-by-chromosome basis utilizing the SRM technology platform. Specific examples of an SRM-multiplex quantitative assay platform dedicated to the cardiovascular disease area, screening Apo A1, Apo A4, Apo B, Apo CI, Apo CII, Apo CIII, Apo D, Apo E, Apo H, and CRP biomarkers used in daily diagnosis routines in clinical hospitals globally, are presented. We also provide data on prostate cancer studies that have identified a variety of PSA isoforms characterized by high-resolution separation interfaced to mass spectrometry.

Cancer genetics-guided discovery of serum biomarker signatures for diagnosis and prognosis of prostate cancer

A key barrier to the realization of personalized medicine for cancer is the identification of biomarkers. Here we describe a two-stage strategy for the discovery of serum biomarker signatures corresponding to specific cancer-causing mutations and its application to prostate cancer (PCa) in the context of the commonly occurring phosphatase and tensin homolog (PTEN) tumor-suppressor gene inactivation. In the first stage of our approach, we identified 775 N-linked glycoproteins from sera and prostate tissue of wild-type and Pten-null mice. Using label-free quantitative proteomics, we showed that Pten inactivation leads to measurable perturbations in the murine prostate and serum glycoproteome. Following bioinformatic prioritization, in a second stage we applied targeted proteomics to detect and quantify 39 human ortholog candidate biomarkers in the sera of PCa patients and control individuals. The resulting proteomic profiles were analyzed by machine learning to build predictive regression models for tissue PTEN status and diagnosis and grading of PCa. Our approach suggests a general path to rational cancer biomarker discovery and initial validation guided by cancer genetics and based on the integration of experimental mouse models, proteomics-based technologies, and computational modeling.

Clinical proteomics: current status, challenges, and future perspectives

This account will give an overview and evaluation of the current advances in mass spectrometry (MS)-based proteomics platforms and technology. A general review of some background information concerning the application of these methods in the characterization of molecular sizes and related protein expression profiles associated with different types of cells under varied experimental conditions will be presented. It is intended to provide a concise and succinct overview to those clinical researchers first exposed to this foremost powerful methodology in modern life sciences of postgenomic era. Proteomic characterization using highly sophisticated and expensive instrumentation of MS has been used to characterize biological samples of complex protein mixtures with vastly different protein structure and composition. These systems are then used to highlight the versatility and potential of the MS-based proteomic strategies for facilitating protein expression analysis of various disease-related organisms or tissues of interest. Major MS-based strategies reviewed herein include (1) matrix-assisted laser desorption ionization-MS and electron-spray ionization proteomics; (2) one-dimensional or two-dimensional gel-based proteomics; (3) gel-free shotgun proteomics in conjunction with liquid chromatography/tandem MS; (4) Multiple reaction monitoring coupled tandem MS quantitative proteomics and; (5) Phosphoproteomics based on immobilized metal affinity chromatography and liquid chromatography-MS/MS.

pep2pro: a new tool for comprehensive proteome data analysis to reveal information about organ-specific proteomes in Arabidopsis thaliana

pep2pro is a comprehensive proteome analysis database specifically suitable for flexible proteome data analysis. The pep2pro database schema offers solutions to the various challenges of developing a proteome data analysis database and because data integrated in pep2pro are in relational format, it enables flexible and detailed data analysis. The information provided here will facilitate building proteome data analysis databases for other organisms or applications. The capacity of the pep2pro database for the integration and analysis of large proteome datasets was demonstrated by creating the pep2pro dataset, which is an organ-specific characterisation of the Arabidopsis thaliana proteome containing 14 522 identified proteins based on 2.6 million peptide spectrum assignments. This dataset provides evidence of protein expression and reveals organ-specific processes. The high coverage and density of the dataset are essential for protein quantification by normalised spectral counting and allowed us to extract information that is usually not accessible in low-coverage datasets. With this quantitative protein information we analysed organ- and organelle-specific sub-proteomes. In addition we matched spectra to regions in the genome that were not predicted to have protein coding capacity and provide PCR validation for selected revised gene models. Furthermore, we analysed the peptide features that distinguish detected from non-detected peptides and found substantial disagreement between predicted and detected proteotypic peptides, suggesting that large-scale proteomics data are essential for efficient selection of proteotypic peptides in targeted proteomics surveys. The pep2pro dataset is available as a resource for plant systems biology at www.pep2pro.ethz.ch.

Evaluation of large scale quantitative proteomic assay development using peptide affinity-based mass spectrometry

Stable isotope standards and capture by antipeptide antibodies (SISCAPA) couples affinity enrichment of peptides with stable isotope dilution and detection by multiple reaction monitoring mass spectrometry to provide quantitative measurement of peptides as surrogates for their respective proteins. In this report, we describe a feasibility study to determine the success rate for production of suitable antibodies for SISCAPA assays in order to inform strategies for large-scale assay development. A workflow was designed that included a multiplex immunization strategy in which up to five proteotypic peptides from a single protein target were used to immunize individual rabbits. A total of 403 proteotypic tryptic peptides representing 89 protein targets were used as immunogens. Antipeptide antibody titers were measured by ELISA and 220 antipeptide antibodies representing 89 proteins were chosen for affinity purification. These antibodies were characterized with respect to their performance in SISCAPA-multiple reaction monitoring assays using trypsin-digested human plasma matrix. More than half of the assays generated were capable of detecting the target peptide at concentrations of less than 0.5 fmol/μl in human plasma, corresponding to protein concentrations of less than 100 ng/ml. The strategy of multiplexing five peptide immunogens was successful in generating a working assay for 100% of the targeted proteins in this evaluation study. These results indicate it is feasible for a single laboratory to develop hundreds of assays per year and allow planning for cost-effective generation of SISCAPA assays.

Less label, more free: approaches in label-free quantitative mass spectrometry

In this review we examine techniques, software, and statistical analyses used in label-free quantitative proteomics studies for area under the curve and spectral counting approaches. Recent advances in the field are discussed in an order that reflects a logical workflow design. Examples of studies that follow this design are presented to highlight the requirement for statistical assessment and further experiments to validate results from label-free quantitation. Limitations of label-free approaches are considered, label-free approaches are compared with labelling techniques, and forward-looking applications for label-free quantitative data are presented. We conclude that label-free quantitative proteomics is a reliable, versatile, and cost-effective alternative to labelled quantitation.

Bioinformatics challenges in the proteomic analysis of human plasma

Mass spectrometry has become the method of choice for studying proteins in complex mixtures in a qualitative and quantitative fashion. The application of mass spectrometry-based proteomics analyses on plasma has correspondingly been established as an important method for disease-associated biomarker discovery and validation. Yet despite being a readily available human sample, plasma poses several important challenges to the proteomics researcher. With a focus on bioinformatics aspects, this chapter will discuss the problems involved in analyzing plasma proteomics data, along with the scope of solutions available through specialised tools and sophisticated analysis methods.

Phosphoproteome resource for systems biology research

PhospoPep version 2.0 is a project to support systems biology signaling research by providing interactive interrogation of MS-derived phosphorylation data from four different organisms. Currently the database hosts phosphorylation data from the fly (Drosophila melanogaster), human (Homo sapiens), worm (Caenorhabditis elegans), and yeast (Saccharomyces cerevisiae). The following will give an overview of the content and usage of the PhosphoPep database.

Mass spectrometry-driven proteomics: an introduction

Proteins are reckoned to be the key actors in a living organism. By studying proteins, one engages into deciphering a complex series of events occurring during a protein's life span. This starts at the creation of a protein, which is tightly controlled on both a transcriptional (Williams and Tyler, 2007, Curr Opin Genet Dev 17, 88-93) and a translational level (Van Der Kelen et al., 2009, Crit Rev Biochem Mol Biol 44, 143-168). During translation, a primary strand of amino acids undergoes a complex folding process in order to obtain a native three-dimensional protein structure (Gross et al., 2003, Cell 115, 739-750). Proteins take on a plethora of functions, such as complex formation, receptor activity, and signal transduction, which ultimately adds up to a cellular phenotype. Consequently, protein analysis is of major interest in molecular biology and involves annotating their presence and localization, as well as their modification state and biochemical context. To accomplish this, many methods have been developed over the last decades, and their general principles and important recent advances in large-scale protein analysis or proteomics are discussed in this review.

Quantifying attomole amounts of proteins from complex samples by nano-LC and selected reaction monitoring

Selected reaction monitoring (SRM) is one of the most powerful techniques for the relative and absolute quantification of proteins from complex protein mixtures. In contrast to traditional protein quantification methods such as ELISAs or RIAs, the SRM method uses mass spectrometry for detection. Further benefits of SRM are as follows: (1) high specificity and sensitivity; (2) large linear dynamic range of at least three orders of magnitude; and (3) the possibility to quantify multiple proteins simultaneously in a single MS run from an individual sample. To perform SRM-based protein quantification reliably, a careful design of the assay is essential, and several pitfalls must be avoided. The aim of this chapter is to help SRM newcomers to establish SRM-based protein quantification assays and discuss an overview of typical work flows that are applied during SRM assay development.

Bioinformatics challenges in mass spectrometry-driven proteomics

Mass spectrometry-based proteomics has become an essential part of the analytical toolbox of the life sciences. With the ability to identify and quantify hundreds to thousands of proteins in high throughput, the field has contributed its fair share to the data avalanche coming from the so-called omics fields. As a result, the challenges involved in processing and managing this flood of data have grown as well. This chapter will point out and discuss these challenges, starting from the processing of raw mass spectrometry data into peaks, over the identification of peptides and proteins, to the quantification of the identified molecules. Finally, the informatics aspects of the nascent field of targeted proteomics are outlined as well.

MASCP Gator: an aggregation portal for the visualization of Arabidopsis proteomics data

Proteomics has become a critical tool in the functional understanding of plant processes at the molecular level. Proteomics-based studies have also contributed to the ever-expanding array of data in modern biology, with many generating Web portals and online resources that contain incrementally expanding and updated information. Many of these resources reflect specialist research areas with significant and novel information that is not currently captured by centralized repositories. The Arabidopsis (Arabidopsis thaliana) community is well served by a number of online proteomics resources that hold an abundance of functional information. These sites can be difficult to locate among a multitude of online resources. Furthermore, they can be difficult to navigate in order to identify specific features of interest without significant technical knowledge. Recently, members of the Arabidopsis proteomics community involved in developing many of these resources decided to develop a summary aggregation portal that is capable of retrieving proteomics data from a series of online resources on the fly. The Web portal is known as the MASCP Gator and can be accessed at the following address: http://gator.masc-proteomics.org/. Significantly, proteomics data displayed at this site retrieve information from the data repositories upon each request. This means that information is always up to date and displays the latest data sets. The site also provides hyperlinks back to the source information hosted at each of the curated databases to facilitate more in-depth analysis of the primary data.

Production and use of stable isotope-labeled proteins for absolute quantitative proteomics

In the field of analytical chemistry, stable isotope dilution assays are extensively used in combination with liquid chromatography-mass spectrometry (LC-MS) to provide confident quantification results. Over the last decade, the principle of isotope dilution has been adopted by the proteomic community in order to accurately quantify proteins in biological samples. In these experiments, a protein's concentration is deduced from the ratio between the MS signal of a tryptic peptide and that of a stable isotope-labeled analog, which serves as an internal standard. The first isotope dilution standards introduced in proteomics were chemically synthesized peptides incorporating a stable isotope-tagged amino acid. These isotopically labeled peptide standards, which are currently widely used, are generally added to samples after protein isolation and digestion. Thus, if protein enrichment is necessary, they do not allow correction for protein losses that may occur during sample pre-fractionation, nor do they allow the tryptic digestion yield to be taken into account. To reduce these limitations we have developed the PSAQ (Protein Standard Absolute Quantification) strategy using full-length stable isotope-labeled proteins as quantification standards. These standards and the target proteins share identical biochemical properties. This allows standards to be spiked into samples at an early stage of the analytical process. Thanks to this possibility, the PSAQ method provides highly accurate quantification results, including for samples requiring extensive biochemical pre-fractionation. In this chapter, we describe the production of full-length stable isotope-labeled proteins (PSAQ standards) using cell-free expression devices. The purification and quality control of protein standards, crucial for good-quality and accurate measurements, are also detailed. Finally, application of the PSAQ method to a typical protein quantification assay is presented.

Is a gene-centric human proteome project the best way for proteomics to serve biology?

With the recent developments in proteomic technologies, a complete human proteome project (HPP) appears feasible for the first time. However, there is still debate as to how it should be designed and what it should encompass. In "proteomics speak", the debate revolves around the central question as to whether a gene-centric or a protein-centric proteomics approach is the most appropriate way forward. In this paper, we try to shed light on what these definitions mean, how large-scale proteomics such as a HPP can insert into the larger omics chorus, and what we can reasonably expect from a HPP in the way it has been proposed so far.

Improving N-glycosylation efficiency in Escherichia coli using shotgun proteomics, metabolic network analysis, and selective reaction monitoring

Recently, the prospect of using Escherichia coli as a host for human glycoprotein production has increased due to detailed characterization of the prokaryotic N-glycosylation process and the ability to transfer the system into this bacterium. Although functionality of the native Campylobacter jejuni N-glycosylation system in E. coli has been demonstrated, the efficiency of the process using the well-characterized C. jejuni glycoprotein AcrA, was found to be low at 13.4±0.9% of total extracted protein. A combined approach using isobaric labeling of peptides and probability-based network analysis of metabolic changes was applied to forward engineer E. coli to improve glycosylation efficiency of AcrA. Enhancing flux through the glyoxylate cycle was identified as a potential metabolic manipulation to improve modification efficiency and was achieved by increasing the expression of isocitrate lyase. While the overall recombinant protein titre did not change significantly, the amount of glycosylated protein increased by approximately 300%.

Phosphoproteomic analysis reveals interconnected system-wide responses to perturbations of kinases and phosphatases in yeast

The phosphorylation and dephosphorylation of proteins by kinases and phosphatases constitute an essential regulatory network in eukaryotic cells. This network supports the flow of information from sensors through signaling systems to effector molecules and ultimately drives the phenotype and function of cells, tissues, and organisms. Dysregulation of this process has severe consequences and is one of the main factors in the emergence and progression of diseases, including cancer. Thus, major efforts have been invested in developing specific inhibitors that modulate the activity of individual kinases or phosphatases; however, it has been difficult to assess how such pharmacological interventions would affect the cellular signaling network as a whole. Here, we used label-free, quantitative phosphoproteomics in a systematically perturbed model organism (Saccharomyces cerevisiae) to determine the relationships between 97 kinases, 27 phosphatases, and more than 1000 phosphoproteins. We identified 8814 regulated phosphorylation events, describing the first system-wide protein phosphorylation network in vivo. Our results show that, at steady state, inactivation of most kinases and phosphatases affected large parts of the phosphorylation-modulated signal transduction machinery-and not only the immediate downstream targets. The observed cellular growth phenotype was often well maintained despite the perturbations, arguing for considerable robustness in the system. Our results serve to constrain future models of cellular signaling and reinforce the idea that simple linear representations of signaling pathways might be insufficient for drug development and for describing organismal homeostasis.