A database of mass spectrometric assays for the yeast proteome

Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry

Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up proteomics" is the prevailing strategy, in which proteins are hydrolyzed into peptides that are analyzed by mass spectrometry. Proteomics studies can be applied to diverse studies ranging from simple protein identification to studies of proteoforms, protein-protein interactions, protein structural alterations, absolute and relative protein quantification, post-translational modifications, and protein stability. To enable this range of different experiments, there are diverse strategies for proteome analysis. The nuances of how proteomic workflows differ may be challenging to understand for new practitioners. Here, we provide a comprehensive overview of different proteomics methods. We cover from biochemistry basics and protein extraction to biological interpretation and orthogonal validation. We expect this Review will serve as a handbook for researchers who are new to the field of bottom-up proteomics.

Comprehensive Overview of Bottom-Up Proteomics using Mass Spectrometry

Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up proteomics" is the prevailing strategy, in which proteins are hydrolyzed into peptides that are analyzed by mass spectrometry. Proteomics studies can be applied to diverse studies ranging from simple protein identification to studies of proteoforms, protein-protein interactions, protein structural alterations, absolute and relative protein quantification, post-translational modifications, and protein stability. To enable this range of different experiments, there are diverse strategies for proteome analysis. The nuances of how proteomic workflows differ may be challenging to understand for new practitioners. Here, we provide a comprehensive overview of different proteomics methods to aid the novice and experienced researcher. We cover from biochemistry basics and protein extraction to biological interpretation and orthogonal validation. We expect this work to serve as a basic resource for new practitioners in the field of shotgun or bottom-up proteomics.

Collision energies: Optimization strategies for bottom-up proteomics

Mass-spectrometry coupled to liquid chromatography is an indispensable tool in the field of proteomics. In the last decades, more and more complex and diverse biochemical and biomedical questions have arisen. Problems to be solved involve protein identification, quantitative analysis, screening of low abundance modifications, handling matrix effect, and concentrations differing by orders of magnitude. This led the development of more tailored protocols and problem centered proteomics workflows, including advanced choice of experimental parameters. In the most widespread bottom-up approach, the choice of collision energy in tandem mass spectrometric experiments has outstanding role. This review presents the collision energy optimization strategies in the field of proteomics which can help fully exploit the potential of MS based proteomics techniques. A systematic collection of use case studies is then presented to serve as a starting point for related further scientific work. Finally, this article discusses the issue of comparing results from different studies or obtained on different instruments, and it gives some hints on methodology transfer between laboratories based on measurement of reference species.

Proteomic identification and quantification of Clostridium perfringens enterotoxin using a stable isotope-labelled peptide via liquid chromatography-tandem mass spectrometry

PURPOSE

Detection of Clostridium perfringens enterotoxin (CPE) in human stool is critical evidence of food poisoning. However, processing patient-derived samples is difficult and very few methods exist to confirm the presence of CPE. In this study, a technique was developed using proteomic analysis to identify and quantify CPE in artificial gut fluid as an alternative.

METHODS

The standard CPE was spiked into artificial gut fluids, and effective methods were developed by employing both a stable isotope-labelled internal standard peptide and liquid chromatography-tandem mass spectrometry (LC-MS/MS).

RESULTS

Proteotypic peptide EILDLAAATER formed by tryptic digestion was selected for quantitation of CPE. The peptide was identified using product ion spectra. Although the nontoxic peptides originating from CPE showed very low detectability in extraction and tryptic digestion, they could be detected with sufficient sensitivity using the method we developed. Based on a spiked recovery test at two concentrations (50 and 200 µg/kg), the recovery values were 85 and 78%, respectively. The relative standard deviations of repeatability and within-laboratory reproducibility were less than 8 and 11%, respectively. These standard deviations satisfied the criteria of the Japanese validation guidelines for residues (MHLW 2010, Director Notice, Syoku-An No. 1224-1). The limit of quantification (LOQ) was estimated to be 50 µg/kg. The combination of the product ion spectra and relative ion ratio supported CPE identification at the LOQ level.

CONCLUSIONS

To the best of our knowledge, this is the first report of proteomic analysis of CPE using LC-MS/MS. The method would greatly help in assessing CPE reliably.

Quantitative Mass Spectrometry-Based Proteomics: An Overview

In recent decades, 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 actual strategies and problems of the methods 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.

Development of an alternative approach for detecting botulinum neurotoxin type A in honey: Analysis of non-toxic peptides with a reference labelled protein via liquid chromatography-tandem mass spectrometry

In this study, we developed a reference labelled protein containing the partial amino acid sequence of botulinum neurotoxin type A (BoNTA). We also applied it as an internal standard to detect specific and non-toxic peptides originated from BoNTA in honey with the use of liquid chromatography-tandem mass spectrometry (LC-MS/MS). Original proteins in the honey sample were collected through a two-step process that included solubilisation and trichloroacetic acid (TCA) precipitation. Solubilisation by adding water enabled processing of proteins in honey. TCA precipitation collected proteins without specific binding. The combination of protein alkylation and an appropriate enzyme-to-protein ratio ensured feasibility of tryptic digestion. A desalting process eliminated a large amount of salts and other tryptic peptides in the honey sample. The use of the reference labelled protein enabled compensation for tryptic digestion efficiency and electrospray ionisation efficiency based on LC-MS/MS measurement. After the peptide selection and protein BlastP analysis, five unique peptides were chosen. The non-toxic peptides originating from BoNTA were reliably detected using LC-MS/MS based on a multiple-reaction monitoring mode. Detection of several peptides ensured screening of BoNTA in honey samples. Based on the responses, the proteotypic peptide LYGIAINPNR was selected as the quantitative peptide. Due to maintaining the relative ion ratios, the selective transition completely identified the non-toxic peptides. The intensity of the transitions established a detection limit of BoNTA estimated to be 9.4 ng mL^-1. Although extraction efficiency was not evaluated using the BoNTA standard, the results suggested this method may be used for quantification of BoNTA in honey. The method was applied to 19 honey samples purchased in Tokyo; none of them was found to contain the target toxin. Overall, the method is expected to accelerate BoNTA monitoring for food safety.

Quantification of staphylococcal enterotoxin type A in cow milk by using a stable isotope-labelled peptide via liquid chromatography-tandem mass spectrometry

In this study, the staphylococcal enterotoxin type A (SEA) contaminant was quantified in cow milk by liquid chromatography-tandem mass spectrometry (LC-MS/MS) with the use of a stable isotope-labelled peptide of SEA as an internal standard. SEA was cleaned up in a two-step process that included pH control and trichloroacetic acid (TCA) precipitation. The pH control phase eliminated other proteins. TCA precipitation cleaned up SEA without special equipment. An appropriate enzyme-to-protein ratio maximised tryptic digestion. A desalting process guaranteed the stable retention of SEA-digested peptides. The coverage of amino-acid sequences (>10%) clearly identified the toxin's presence. SEA was accurately quantified using LC-MS/MS based on a multiple-reaction monitoring mode. The developed method was validated based on spiked recovery tests at 50 and 100 µg kg^-1 conducted with two samples collected on a daily basis for five days based on Japanese validation guidelines. The new method exhibited good accuracy which ranged from 80% to 82%. The relative standard deviations of repeatability were 13-14% and the relative standard deviations of within-laboratory reproducibility were 13-18%. These standard deviations satisfied the criteria of the Japanese validation guidelines. The quantification limit was estimated to be 10 µg kg^-1.

Peptide barcoding for establishment of new types of genotype-phenotype linkages

Measuring binding properties of binders (e.g., antibodies) is essential for developing useful experimental reagents, diagnostics, and pharmaceuticals. Display technologies can evaluate a large number of binders in a high-throughput manner, but the immobilization effect and the avidity effect prohibit the precise evaluation of binding properties. In this paper, we propose a novel methodology, peptide barcoding, to quantitatively measure the binding properties of multiple binders without immobilization. In the experimental scheme, unique peptide barcodes are fused with each binder, and they represent genotype information. These peptide barcodes are designed to have high detectability for mass spectrometry, leading to low identification bias and a high identification rate. A mixture of different peptide-barcoded nanobodies is reacted with antigen-coated magnetic beads in one pot. Peptide barcodes of functional nanobodies are cleaved on beads by a specific protease, and identified by selected reaction monitoring using triple quadrupole mass spectrometry. To demonstrate proof-of-principle for peptide barcoding, we generated peptide-barcoded anti-CD4 nanobody and anti-GFP nanobody, and determined whether we could simultaneously quantify their binding activities. We showed that peptide barcoding did not affect the properties of the nanobodies, and succeeded in measuring the binding activities of these nanobodies in one shot. The results demonstrate the advantages of peptide barcoding, new types of genotype–phenotype linkages.

Artificial Intelligence Understands Peptide Observability and Assists With Absolute Protein Quantification

Targeted mass spectrometry has become the method of choice to gain absolute quantification information of high quality, which is essential for a quantitative understanding of biological systems. However, the design of absolute protein quantification assays remains challenging due to variations in peptide observability and incomplete knowledge about factors influencing peptide detectability. Here, we present a deep learning algorithm for peptide detectability prediction, d::pPop, which allows the informed selection of synthetic proteotypic peptides for the successful design of targeted proteomics quantification assays. The deep neural network is able to learn a regression model that relates the physicochemical properties of a peptide to its ion intensity detected by mass spectrometry. The approach makes use of experimentally detected deviations from the assumed equimolar abundance of all peptides derived from a given protein. Trained on extensive proteomics datasets, d::pPop's plant and non-plant specific models can predict the quality of proteotypic peptides for not yet experimentally identified proteins. Interrogating the deep neural network after learning from ~76,000 peptides per model organism allows to investigate the impact of different physicochemical properties on the observability of a peptide, thus providing insights into peptide observability as a multifaceted process. Empirical evaluation with rank accuracy metrics showed that our prediction approach outperforms existing algorithms. We circumvent the delicate step of selecting positive and negative training sets and at the same time also more closely reflect the need for selecting the top most promising peptides for targeting a protein of interest. Further, we used an artificial QconCAT protein to experimentally validate the observability prediction. Our proteotypic peptide prediction approach not only facilitates the design of absolute protein quantification assays via a user-friendly web interface but also enables the selection of proteotypic peptides for not yet observed proteins, hence rendering the tool especially useful for plant research.

Standardization approaches in absolute quantitative proteomics with mass spectrometry

Mass spectrometry-based approaches have enabled important breakthroughs in quantitative proteomics in the last decades. This development is reflected in the better quantitative assessment of protein levels as well as to understand post-translational modifications and protein complexes and networks. Nowadays, the focus of quantitative proteomics shifted from the relative determination of proteins (ie, differential expression between two or more cellular states) to absolute quantity determination, required for a more-thorough characterization of biological models and comprehension of the proteome dynamism, as well as for the search and validation of novel protein biomarkers. However, the physico-chemical environment of the analyte species affects strongly the ionization efficiency in most mass spectrometry (MS) types, which thereby require the use of specially designed standardization approaches to provide absolute quantifications. Most common of such approaches nowadays include (i) the use of stable isotope-labeled peptide standards, isotopologues to the target proteotypic peptides expected after tryptic digestion of the target protein; (ii) use of stable isotope-labeled protein standards to compensate for sample preparation, sample loss, and proteolysis steps; (iii) isobaric reagents, which after fragmentation in the MS/MS analysis provide a final detectable mass shift, can be used to tag both analyte and standard samples; (iv) label-free approaches in which the absolute quantitative data are not obtained through the use of any kind of labeling, but from computational normalization of the raw data and adequate standards; (v) elemental mass spectrometry-based workflows able to provide directly absolute quantification of peptides/proteins that contain an ICP-detectable element. A critical insight from the Analytical Chemistry perspective of the different standardization approaches and their combinations used so far for absolute quantitative MS-based (molecular and elemental) proteomics is provided in this review.

Streamlined microfluidic analysis of phosphopeptides using stable isotope-labeled synthetic peptides and MRM-MS detection

Modern high-throughput and high-content biological research is performed with advanced instrumentation and complex and time-consuming protocols, which, as a whole, pose a challenge for routine implementation in a research laboratory. In support of a "bioanalytical toolbox" with potential utility for exploring cellular functions mediated via protein phosphorylation-a post-translational modification (PTM) with essential regulatory roles in a variety of cellular processes-in this work, we describe the development of a simple, integrated microfluidic chip that can perform targeted, quantitative analysis of phosphopeptides involved in cancer-relevant signaling pathways. The microfluidic device comprises microreactors packed with C18 and TiO₂ particles for on-chip solid phase extraction (SPE) and phosphopeptide enrichment, and an ESI interface for facilitating multiple reaction monitoring (MRM)-mass spectrometry (MS) detection. The chips are demonstrated for the detection of three phosphopeptides involved in ERBB2/MAPK signaling pathways, selected from the outcome of a proteomic study involving EGF stimulation of SKBR3/HER2+ breast cancer cells. The data demonstrate that the proposed microfluidic strategy can be used for the MS quantification of phosphopeptides in the low nM range from cell lysates without any prior sample pretreatment, fractionation or bioaffinity enrichment, and is generally applicable to the analysis of any phosphopeptide targets.

Data-independent acquisition-based SWATH-MS for quantitative proteomics: a tutorial

Many research questions in fields such as personalized medicine, drug screens or systems biology depend on obtaining consistent and quantitatively accurate proteomics data from many samples. SWATH-MS is a specific variant of data-independent acquisition (DIA) methods and is emerging as a technology that combines deep proteome coverage capabilities with quantitative consistency and accuracy. In a SWATH-MS measurement, all ionized peptides of a given sample that fall within a specified mass range are fragmented in a systematic and unbiased fashion using rather large precursor isolation windows. To analyse SWATH-MS data, a strategy based on peptide-centric scoring has been established, which typically requires prior knowledge about the chromatographic and mass spectrometric behaviour of peptides of interest in the form of spectral libraries and peptide query parameters. This tutorial provides guidelines on how to set up and plan a SWATH-MS experiment, how to perform the mass spectrometric measurement and how to analyse SWATH-MS data using peptide-centric scoring. Furthermore, concepts on how to improve SWATH-MS data acquisition, potential trade-offs of parameter settings and alternative data analysis strategies are discussed.

Insights into the role of androgen receptor in human testicular peritubular cells

Contractile smooth muscle-like peritubular cells build the wall of seminiferous tubules in men. They are crucial for sperm transport and complement the functions of Sertoli cells by secreting factors, including glial cell line-derived neurotrophic factor. Previous studies revealed that they also secrete the chemokine C-X-C motif chemokine ligand 12 (CXCL12), which has known roles in spermatogenesis. Peritubular cells express the androgen receptor (AR), which is retained in isolated human testicular peritubular cells. We aimed to explore AR-regulated functions in human testicular peritubular cells. Bearing in mind that infertile men often have high aromatase activity, which may lower intratesticular androgen concentrations, an animal model for male infertility was studied. These mice display an age-dependent loss in spermatogenesis due to high aromatase activity. Human testicular peritubular cells were exposed to dihydrotestosterone or the antiandrogen flutamide. We studied AR, smooth muscle cell markers, glial cell line-derived neurotrophic factor and 15 secreted factors previously identified, including CXCL12. We used qPCR, Western blotting, ELISA or selected reaction monitoring (SRM). In the animal model for male infertility, we employed qPCR and immunohistochemistry. Dihydrotestosterone increased AR and flutamide prevented these actions. The smooth muscle cell markers calponin and smooth muscle actin were likewise increased, while cell size or cellular proliferation was not changed. Dihydrotestosterone did not increase glial cell line-derived neurotrophic factor or CXCL12 secretion but increased levels of serine proteinase inhibitor (SERPIN) E1. The animal model for male infertility with high aromatase activity showed reduced numbers of AR-immunoreactive testicular peritubular cells, suggesting that altered androgen and/or oestrogen levels could influence AR-mediated responses in peritubular cells. Androgens act on human testicular peritubular cells to enhance AR levels, their contractile phenotype and to modulate the secretion of some secreted factors. This study suggests that some aspects of human peritubular cell functions are regulated by androgens.

Computational proteomics tools for identification and quality control

Computational proteomics is a constantly growing field to support end users with powerful and reliable tools for performing several computational steps within an analytics workflow for proteomics experiments. Typically, after capturing with a mass spectrometer, the proteins have to be identified and quantified. After certain follow-up analyses, an optional targeted approach is suitable for validating the results. The de.NBI (German network for bioinformatics infrastructure) service center in Dortmund provides several software applications and platforms as services to meet these demands. In this work, we present our tools and services, which is the combination of SearchGUI and PeptideShaker. SearchGUI is a managing tool for several search engines to find peptide spectra matches for one or more complex MS² measurements. PeptideShaker combines all matches and creates a consensus list of identified proteins providing statistical confidence measures. In a next step, we are planning to release a web service for protein identification containing both tools. This system will be designed for high scalability and distributed computing using solutions like the Docker container system among others. As an additional service, we offer a web service oriented database providing all necessary high-quality and high-resolution data for starting targeted proteomics analyses. The user can easily select proteins of interest, review the according spectra and download both protein sequences and spectral library. All systems are designed to be intuitively and user-friendly operable.

Prediction of Hopeless Peptides Unlikely to be Selected for Targeted Proteome Analysis

In targeted proteomics using liquid chromatography-tandem triple quadrupole mass spectrometry (LC/MS/MS) in the selected reaction monitoring (SRM) mode, selecting the best observable or visible peptides is a key step in the development of SRM assay methods of target proteins. A direct comparison of signal intensities among all candidate peptides by brute-force LC/MS/MS analysis is a concrete approach for peptide selection. However, the analysis requires an SRM method with hundreds of transitions. This study reports on the development of a method for predicting and identifying hopeless peptides to reduce the number of candidate peptides needed for brute-force experiments. Hopeless peptides are proteotypic peptides that are unlikely to be selected for targets in SRM analysis owing to their poor ionization characteristics. Targeted proteomics data from Escherichia coli demonstrated that the relative ionization efficiency between two peptides could be predicted from sequences of two peptides, when a multivariate regression model is used. Validation of the method showed that >20% of the candidate peptides could be successfully eliminated as hopeless peptides with a false positive rate of less than 2%.

Optimization by infusion of multiple reaction monitoring transitions for sensitive quantification of peptides by liquid chromatography/mass spectrometry

RATIONALE

In peptide quantification by liquid chromatography/mass spectrometry (LC/MS), the optimization of multiple reaction monitoring (MRM) parameters is essential for sensitive detection. We have compared different approaches to build MRM assays, based either on flow injection analysis (FIA) of isotopically labelled peptides, or on the knowledge and the prediction of the best settings for MRM transitions and collision energies (CE). In this context, we introduce MRMOptimizer, an open-source software tool that processes spectra and assists the user in selecting transitions in the FIA workflow.

METHODS

MS/MS spectral libraries with CE voltages from 10 to 70 V are automatically acquired in FIA mode for isotopically labelled peptides. Then MRMOptimizer determines the optimal MRM settings for each peptide. To assess the quantitative performance of our approach, 155 peptides, representing 84 proteins, were analysed by LC/MRM-MS and the peak areas were compared between: (A) the MRMOptimizer-based workflow, (B1) the SRMAtlas transitions set used 'as-is'; (B2) the same SRMAtlas set with CE parameters optimized by Skyline.

RESULTS

51% of the three most intense transitions per peptide were shown to be common to both A and B1/B2 methods, and displayed similar sensitivity and peak area distributions. The peak areas obtained with MRMOptimizer for transitions sharing either the precursor ion charge state or the fragment ions with the SRMAtlas set at unique transitions were increased 1.8- to 2.3-fold. The gain in sensitivity using MRMOptimizer for transitions with different precursor ion charge state and fragment ions (8% of the total), reaches a ~ 11-fold increase.

CONCLUSIONS

Isotopically labelled peptides can be used to optimize MRM transitions more efficiently in FIA than by searching databases. The MRMOptimizer software is MS independent and enables the post-acquisition selection of MRM parameters. Coefficients of variation for optimal CE values are lower than those obtained with the SRMAtlas approach (B2) and one additional peptide was detected. Copyright © 2017 John Wiley & Sons, Ltd.

Correlation of pre-operative plasma protein concentrations in cardiac surgery patients with bleeding outcomes using a targeted quantitative proteomics approach

PURPOSE

Despite recent advancements in the use of thrombelastography (TEG) in the surgical setting, adequate technology to accurately predict bleeding phenotypes for patients undergoing cardiopulmonary bypass on the basis of non-mechanical parameters is lacking. While basic science and translational studies have provided key mechanistic insights about the protein components of coagulation cascades and regulatory mediators of hemostasis and fibrinolysis, targeted protein assays are still missing and the association of protein profiles to bleeding phenotypes and TEG readouts have yet to be discovered.

OBJECTIVE

To identify protein biomarkers of bleeding phenotypes of cardiopulmonary bypass patients in pre-operative plasma.

EXPERIMENTAL DESIGN

We applied a targeted proteomics approach to quantify 123 plasma proteins from 23 patients undergoing cardiopulmonary bypass (CPB) and sternotomy. We then correlated these measurements to bleeding outcomes and TEG parameters, associated with speed of clot formation and strength.

RESULTS

In this pilot study, we demonstrate the feasibility of protein quantitation as a viable strategy to predict low versus high bleeding phenotypes (loss of < or > than 20% of estimated blood volume, calculated as 70 mL/kg for BMI<29.9, 60 mL/kg for BMI = 30-39.9, and 50 mL/kg for BMI>40. Statistical elaborations highlighted a core set of proteins showing significant correlations to either total blood loss or TEG R/MA parameters.

CONCLUSION AND CLINICAL RELEVANCE

Though prospective verification and validation in larger cohorts will be necessary, this report suggests a potential for targeted quantitative proteomics of pre-operative plasma protein concentrations in the prediction of estimated blood loss following CPB.

Targeted proteome analysis of single-gene deletion strains of Saccharomyces cerevisiae lacking enzymes in the central carbon metabolism

Central carbon metabolism is controlled by modulating the protein abundance profiles of enzymes that maintain the essential systems in living organisms. In this study, metabolic adaptation mechanisms in the model organism Saccharomyces cerevisiae were investigated by direct determination of enzyme abundance levels in 30 wild type and mutant strains. We performed a targeted proteome analysis using S. cerevisiae strains that lack genes encoding the enzymes responsible for central carbon metabolism. Our analysis revealed that at least 30% of the observed variations in enzyme abundance levels could be explained by global regulatory mechanisms. A enzyme-enzyme co-abundance analysis revealed that the abundances of enzyme proteins involved in the trehalose metabolism and glycolysis changed in a coordinated manner under the control of the transcription factors for global regulation. The remaining variations were derived from local mechanisms such as a mutant-specific increase in the abundances of remote enzymes. The proteome data also suggested that, although the functional compensation of the deficient enzyme was attained by using more resources for protein biosynthesis, available resources for the biosynthesis of the enzymes responsible for central metabolism were not abundant in S. cerevisiae cells. These results showed that global and local regulation of enzyme abundance levels shape central carbon metabolism in S. cerevisiae by using a limited resource for protein biosynthesis.

Selective Reaction Monitoring for Quantitation of Cellular Proteins

Proteins and proteomes are dynamic and complex. The accurate identification and measurement of their properties such as abundance, location, and turnover are challenging tasks. Even though high-throughput proteomics has significantly evolved, the technique still lacks fully quantitative and reproducible qualities. A mass spectrometry-based targeted proteomic strategy called selective reaction monitoring (SRM) has emerged in recent years as an important multiplex platform to precisely quantify sets of proteins in multiple samples. This has several advantages in terms of sensitivity, reproducibility, and sample consumption compared to classical methods including those based on antibodies. Here, we present a detailed protocol for quantitation of panels of proteins from cell line extracts using the SRM targeted proteomics approach.

Multiplexed Liquid Chromatography-Multiple Reaction Monitoring Mass Spectrometry Quantification of Cancer Signaling Proteins

Quantitative evaluation of protein expression across multiple cancer-related signaling pathways (e.g., Wnt/β-catenin, TGF-β, receptor tyrosine kinases (RTK), MAP kinases, NF-κB, and apoptosis) in tumor tissues may enable the development of a molecular profile for each individual tumor that can aid in the selection of appropriate targeted cancer therapies. Here, we describe the development of a broadly applicable protocol to develop and implement quantitative mass spectrometry assays using cell line models and frozen tissue specimens from colon cancer patients. Cell lines are used to develop peptide-based assays for protein quantification, which are incorporated into a method based on SDS-PAGE protein fractionation, in-gel digestion, and liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM/MS). This analytical platform is then applied to frozen tumor tissues. This protocol can be broadly applied to the study of human disease using multiplexed LC-MRM assays.

Mass Spectrometry-Based Bottom-Up Proteomics: Sample Preparation, LC-MS/MS Analysis, and Database Query Strategies

Recent technological advances in mass spectrometry (MS) have made possible the investigation and quantification of complex mixtures of biomolecules. The exceptional sensitivity and resolving power of today's mass spectrometers allow for the detection of proteins and peptides at low femtomole quantities; however, these attributes demand high sample purity to minimize artifacts and achieve the highest degree of biomolecule identification. Tissue preparation for proteomic studies is particularly challenging due to their heterogeneity in cell type, presence of insoluble biomaterials, and wide diversity of biomolecules. The workflow described herein details sample preparation from tissues through protein extraction, proteolysis, and purification to generate peptides for MS analysis. Increased peptide resolution and a corresponding increase in protein identification is accomplished using polarity-based fractionation (C18 resin) at the peptide level. Additionally, approaches to instrument set up, including the use of nanoscale liquid chromatography and quadrupole Orbitrap MS, along with database searching, are described. © 2016 by John Wiley & Sons, Inc.

Analysis of Major Histocompatibility Complex (MHC) Immunopeptidomes Using Mass Spectrometry

The myriad of peptides presented at the cell surface by class I and class II major histocompatibility complex (MHC) molecules are referred to as the immunopeptidome and are of great importance for basic and translational science. For basic science, the immunopeptidome is a critical component for understanding the immune system; for translational science, exact knowledge of the immunopeptidome can directly fuel and guide the development of next-generation vaccines and immunotherapies against autoimmunity, infectious diseases, and cancers. In this mini-review, we summarize established isolation techniques as well as emerging mass spectrometry-based platforms (i.e. SWATH-MS) to identify and quantify MHC-associated peptides. We also highlight selected biological applications and discuss important current technical limitations that need to be solved to accelerate the development of this field.

Food allergen detection by mass spectrometry: the role of systems biology

Food allergy prevalence is rising worldwide, motivating the development of assays that can sensitively and reliably detect trace amounts of allergens in manufactured food. Mass spectrometry (MS) is a promising alternative to commonly employed antibody-based assays owing to its ability to quantify multiple proteins in complex matrices with high sensitivity. In this review, we discuss a targeted MS workflow for the quantitation of allergenic protein in food products that employs selected reaction monitoring (SRM). We highlight the aspects of SRM method development unique to allergen quantitation and identify opportunities for simplifying the process. One promising avenue identified through a comprehensive survey of published MS literature is the use of proteotypic peptides, which are peptides whose presence appears robust to variations in food matrix, sample preparation protocol, and MS instrumentation. We conclude that proteotypic peptides exist for a subset of allergenic milk, egg, and peanut proteins. For less studied allergens such as soy, wheat, fish, shellfish, and tree nuts, we offer guidance and tools for peptide selection and specificity verification as part of an interactive web database, the Allergen Peptide Browser (http://www.AllergenPeptideBrowser.org). With ongoing improvements in MS instrumentation, analysis software, and strategies for targeted quantitation, we expect an increasing role of MS as an analytical tool for ensuring regulatory compliance.

Cancer associated proteins in blood plasma: Determining normal variation

Protein biomarkers have the potential to improve diagnosis, stratification of patients into treatment cohorts, follow disease progression and treatment response. One distinct group of potential biomarkers comprises proteins which have been linked to cancer, known as cancer associated proteins (CAPs). We determined the normal variation of 86 CAPs in 72 individual plasma samples collected from ten individuals using SRM mass spectrometry. Samples were collected weekly during 5 weeks from ten volunteers and over one day at nine fixed time points from three volunteers. We determined the degree of the normal variation depending on interpersonal variation, variation due to time of day, and variation over weeks and observed that the variation dependent on the time of day appeared to be the most important. Subdivision of the proteins resulted in two predominant protein groups containing 21 proteins with relatively high variation in all three factors (day, week and individual), and 22 proteins with relatively low variation in all factors. We present a strategy for prioritizing biomarker candidates for future studies based on stratification over their normal variation and have made all data publicly available. Our findings can be used to improve selection of biomarker candidates in future studies and to determine which proteins are most suitable depending on study design.

Supernatant protein biomarkers of red blood cell storage hemolysis as determined through an absolute quantification proteomics technology

BACKGROUND

Laboratory technologies have highlighted the progressive accumulation of the so-called "storage lesion," a wide series of alterations to stored red blood cells (RBCs) that may affect the safety and effectiveness of the transfusion therapy. New improvements in the field are awaited to ameliorate this lesion, such as the introduction of washing technologies in the cell processing pipeline. Laboratory studies that have tested such technologies so far rely on observational qualitative or semiquantitative techniques.

STUDY DESIGN AND METHODS

A state-of-the-art quantitative proteomics approach utilizing quantitative concatamers (QconCAT) was used to simultaneously monitor fluctuations in the abundance of 114 proteins in AS-3 RBC supernatants (n = 5; 11 time points, including before and after leukoreduction, at 3 hours, on Days 1 and 2, and weekly sampling from Day 7 through Day 42).

RESULTS

Leukoreduction-dependent depletion of plasma proteins was observed at the earliest time points. A subset of proteins showed very high linear correlation (r(2)  > 0.9) not only with storage time, but also with absolute levels of hemoglobin α1 and β, a proxy for RBC hemolysis and vesiculation. Linear regression was performed to describe the temporal relationship between these proteins. Our findings suggest a role for supernatant glyceraldehyde-3-phosphate dehydrogenase; peroxiredoxin-1, -2, and -6; carbonic anhydrase-1 and -2; selenium binding protein-1; biliverdin reductase; aminolevulinate dehydratase; and catalase as potential biomarkers of RBC quality during storage.

CONCLUSION

A targeted proteomics technology revealed novel biomarkers of the RBC storage lesion and promises to become a key analytical readout for the development and testing of alternative cell processing strategies.

Proteomics of ovarian cancer: functional insights and clinical applications

In the past decade, there has been an increasing interest in applying proteomics to assist in understanding the pathogenesis of ovarian cancer, elucidating the mechanism of drug resistance, and in the development of biomarkers for early detection of ovarian cancer. Although ovarian cancer is a spectrum of different diseases, the strategies for diagnosis and treatment with surgery and adjuvant therapy are similar across ovarian cancer types, increasing the general applicability of discoveries made through proteomics research. While proteomic experiments face many difficulties which slow the pace of clinical applications, recent advances in proteomic technology contribute significantly to the identification of aberrant proteins and networks which can serve as targets for biomarker development and individualized therapies. This review provides a summary of the literature on proteomics' contributions to ovarian cancer research and highlights the current issues, future directions, and challenges. We propose that protein-level characterization of primary lesion in ovarian cancer can decipher the mystery of this disease, improve diagnostic tools, and lead to more effective screening programs.

Selecting Optimal Peptides for Targeted Proteomic Experiments in Human Plasma Using In Vitro Synthesized Proteins as Analytical Standards

In targeted proteomics, the development of robust methodologies is dependent upon the selection of a set of optimal peptides for each protein-of-interest. Unfortunately, predicting which peptides and respective product ion transitions provide the greatest signal-to-noise ratio in a particular assay matrix is complicated. Using in vitro synthesized proteins as analytical standards, we report here an empirically driven method for the selection of said peptides in a human plasma assay matrix.

Using the CPTAC Assay Portal to Identify and Implement Highly Characterized Targeted Proteomics Assays

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal (http://assays.cancer.gov) to serve as an open-source repository of well-characterized targeted proteomic assays. The portal is designed to curate and disseminate highly characterized, targeted mass spectrometry (MS)-based assays by providing detailed assay performance characterization data, standard operating procedures, and access to reagents. Assay content is accessed via the portal through queries to find assays targeting proteins associated with specific cellular pathways, protein complexes, or specific chromosomal regions. The position of the peptide analytes for which there are available assays are mapped relative to other features of interest in the protein, such as sequence domains, isoforms, single nucleotide polymorphisms, and posttranslational modifications. The overarching goals are to enable robust quantification of all human proteins and to standardize the quantification of targeted MS-based assays to ultimately enable harmonization of results over time and across laboratories.

Proteomic techniques to probe the ubiquitin landscape

Protein ubiquitination is a powerful modulator of cellular functions. Classically linked to the degradation of proteins, it also plays a role in intracellular localization, DNA damage response, vesicle fusion events, and the immune and transcriptional responses. Ubiquitin is versatile and can code for several distinct signals, either by adding a single ubiquitin or forming a chain of ubiquitins on the target protein. The enzymatic cascade associated with the cellular process determines the nature of the modification. Numerous efforts have been made for the identification of ubiquitin acceptor sites in the target proteins using genetic, biochemical or MS-based proteomic methods, such as affinity-based enrichment of ubiquitinated proteins, and antibody-based enrichment of modified peptides. Modern instrumentation enables quantitative MS strategies to identify and characterize hundreds of ubiquitin substrates in a single analysis making it the dominant method for ubiquitin site detection. Characterization of the interubiquitin connectivity in ubiquitin polymers has also moved into focus, with the field of targeted proteomics techniques proving invaluable for identifying and quantifying linkage types found in such polyubiquitin chains. This review seeks to provide an overview of the many MS-based proteomics techniques available for exploring this dynamic field.

Making proteomics data accessible and reusable: current state of proteomics databases and repositories

Compared to other data-intensive disciplines such as genomics, public deposition and storage of MS-based proteomics, data are still less developed due to, among other reasons, the inherent complexity of the data and the variety of data types and experimental workflows. In order to address this need, several public repositories for MS proteomics experiments have been developed, each with different purposes in mind. The most established resources are the Global Proteome Machine Database (GPMDB), PeptideAtlas, and the PRIDE database. Additionally, there are other useful (in many cases recently developed) resources such as ProteomicsDB, Mass Spectrometry Interactive Virtual Environment (MassIVE), Chorus, MaxQB, PeptideAtlas SRM Experiment Library (PASSEL), Model Organism Protein Expression Database (MOPED), and the Human Proteinpedia. In addition, the ProteomeXchange consortium has been recently developed to enable better integration of public repositories and the coordinated sharing of proteomics information, maximizing its benefit to the scientific community. Here, we will review each of the major proteomics resources independently and some tools that enable the integration, mining and reuse of the data. We will also discuss some of the major challenges and current pitfalls in the integration and sharing of the data.

A clinically based protein discovery strategy to identify potential biomarkers of response to anti-TNF-α treatment of psoriatic arthritis

PURPOSE

Psoriatic arthritis (PsA) can be treated using biologic therapies targeting biomolecules such as tumor necrosis factor alpha, interleukins (IL)-17 and IL-23. Although 70% PsA patients respond well to therapy, 30% patients show no or limited clinical improvement. Biomarkers that predict response to therapy would help to avoid unnecessary use of expensive biologics in nonresponding patients and enable alternative treatments to be explored.

EXPERIMENTAL DESIGN

Patient synovial tissue samples from two clinical studies were analysed using difference in-gel electrophoresis-based proteomics to identify protein expression differences in response to anti-TNF-α treatment. Subsequent multiplexed MRM measurements were used to verify potential biomarkers.

RESULTS

A total of 119 proteins were differentially expressed (p<0.05) in response to anti-TNF-α treatment and 25 proteins were differentially expressed (p<0.05) between "good responders" and "poor responders". From these differentially expressed proteins, MRM assays were developed for four proteins to explore their potential as treatment predictive biomarkers.

CONCLUSION AND CLINICAL RELEVANCE

Gel-based proteomics strategy has demonstrated differential protein expression in synovial tissue of PsA patients, in response to anti-TNF-α treatment. Development of multiplex MRM assays to these differentially expressed proteins has the potential to predict response to therapy and allow alternative, more effective treatments to be explored sooner.

Proteomic tools to decipher microbial community structure and functioning

Recent advances in microbial ecology allow studying microorganisms in their environment, without laboratory cultivation, in order to get access to the large uncultivable microbial community. With this aim, environmental proteomics has emerged as an appropriate complementary approach to metagenomics providing information on key players that carry out main metabolic functions and addressing the adaptation capacities of living organisms in situ. In this review, a wide range of proteomic approaches applied to investigate the structure and functioning of microbial communities as well as recent examples of such studies are presented.

Advances in high-resolution quantitative proteomics: implications for clinical applications

The advances in high-resolution mass spectrometry instrumentation, capable of accurate mass measurement and fast acquisition, have enabled new approaches for targeted quantitative proteomics. More specifically, analyses performed on quadrupole-orbitrap mass spectrometers operated in parallel reaction monitoring (PRM) mode leverage the intrinsic high resolving power and trapping capabilities. The PRM technique offers unmatched degrees of selectivity and analytical sensitivity, typically required to analyze peptides in complex samples, such as those encountered in biomedical research or clinical studies. The features of PRM have provoked a paradigm change in targeted experiments, by decoupling acquisition and data processing. It has resulted in a new analytical workflow comprising distinct methods for each step, thus enabling much larger flexibility. The PRM technique was further enhanced by a new data acquisition scheme, allowing dynamic parameter settings. The potential of the technique may radically impact future quantitative proteomics studies.

Proteomic signatures of antiplatelet drugs: new approaches to exploring drug effects

Antiplatelet agents represent the mainstay of acute coronary syndrome (ACS) therapy to prevent ischemic events and to improve safety in patients undergoing percutaneous coronary intervention. However, despite the availability of several drugs and the use of dual antiplatelet therapy, the pharmacological response is highly variable with a subset of patients continuing to experience recurrent thrombotic events, revealing a wide variability in platelet response to antiplatelet drugs. Several factors may explain this, including genetic variation and environmental factors. Here we look at the application of proteomic analysis, an approach that provides an integrated readout of these diverse influences.

Proteomic Validation of Transcript Isoforms, Including Those Assembled from RNA-Seq Data

Human proteome analysis now requires an understanding of protein isoforms. We recently published the PG Nexus pipeline, which facilitates high confidence validation of exons and splice junctions by integrating genomics and proteomics data. Here we comprehensively explore how RNA-seq transcriptomics data, and proteomic analysis of the same sample, can identify protein isoforms. RNA-seq data from human mesenchymal (hMSC) stem cells were analyzed with our new TranscriptCoder tool to generate a database of protein isoform sequences. MS/MS data from matching hMSC samples were then matched against the TranscriptCoder-derived database, along with Ensembl and the neXtProt database. Querying the TranscriptCoder-derived or Ensembl database could unambiguously identify ∼450 protein isoforms, with isoform-specific proteotypic peptides, including candidate hMSC-specific isoforms for the genes DPYSL2 and FXR1. Where isoform-specific peptides did not exist, groups of nonisoform-specific proteotypic peptides could specifically identify many isoforms. In both the above cases, isoforms will be detectable with targeted MS/MS assays. Unfortunately, our analysis also revealed that some isoforms will be difficult to identify unambiguously as they do not have peptides that are sufficiently distinguishing. We covisualize mRNA isoforms and peptides in a genome browser to illustrate the above situations. Mass spectrometry data is available via ProteomeXchange (PXD001449).

Plasma QconCATs reveal a gender-specific proteomic signature in apheresis platelet plasma supernatants

Clinical translation of proteomic technologies is often hampered by technical limitations, including inter-laboratory inconsistencies of label-free derived relative quantification, time-consuming analytical approaches and the subsequent challenge of performing proteomic analyses on large cohorts of subjects. Here we introduce plasma QconCAT-based targeted proteomics, an approach that allows the simultaneous absolute quantitation down to the picogram level of hundreds of proteins in a single liquid chromatography-selected reaction monitoring mass spectrometry run. We demonstrate the robustness of the approach by analyzing apheresis platelet concentrate supernatants at storage day 1 and the end of the shelf life for this blood-derived therapeutic, day 5. The targeted approach was repeatable and robust revealing potential gender-specific signatures across a set of three male and female donors. This technical note represents a proof-of-principle of the application of QconCAT-based MRM strategies to transfusion-medicine relevant issues, such as storage and gender-dependent proteomic signatures in blood-derived therapeutics.

BIOLOGICAL SIGNIFICANCE

Gender differences in the proteome composition of apheresis platelet supernatants have always been postulated, and might underlie a higher risk of adverse reactions when transfusing apheresis products from female donors. Preliminary proteomic studies provided an overview of gender-dependent relative compositional differences in the proteome of apheresis platelet supernatants during routine storage in the blood bank. Here we apply a proteomics approach for absolute quantitation of approximately 100 proteins in apheresis platelet supernatants from male and female donors at storage days 1 and 5. Absolute quantitative proteomic analyses allowed us to confirm and expand on previous observations about gender and storage-dependency of platelet supernatant protein profiles.

Recent advances in targeted proteomics for clinical applications

MS-based approaches using targeted methods have been widely adopted by the proteomics community to study clinical questions such as the evaluation of biomarkers. At present, the most widely used targeted MS method is the SRM technique typically performed on a triple quadrupole instrument. However, the high analytical demands for performing clinical studies in combination with the extreme complexity of the samples involved are a serious challenge. The segmentation of the biomarker evaluation workflow has only partially alleviated these issues by differently balancing the analytical requirements and throughput at different stages of the process. The recent introduction of targeted high-resolution and accurate-mass analyses on fast sequencing mass spectrometers operated in parallel reaction monitoring (PRM) mode offers new avenues to conduct clinical studies and thus overcome some of the limitations of the triple quadrupole instrument. This article discusses the attributes and specificities of the PRM technique, in terms of experimental design, execution, and data analysis, and the implications for biomarker evaluation. The benefits of PRM on data quality and the impact on the consistency of results are highlighted and the definitive progress on the overall output of clinical studies, including high throughput, is discussed.

Building high-quality assay libraries for targeted analysis of SWATH MS data

Targeted proteomics by selected/multiple reaction monitoring (S/MRM) or, on a larger scale, by SWATH (sequential window acquisition of all theoretical spectra) MS (mass spectrometry) typically relies on spectral reference libraries for peptide identification. Quality and coverage of these libraries are therefore of crucial importance for the performance of the methods. Here we present a detailed protocol that has been successfully used to build high-quality, extensive reference libraries supporting targeted proteomics by SWATH MS. We describe each step of the process, including data acquisition by discovery proteomics, assertion of peptide-spectrum matches (PSMs), generation of consensus spectra and compilation of MS coordinates that uniquely define each targeted peptide. Crucial steps such as false discovery rate (FDR) control, retention time normalization and handling of post-translationally modified peptides are detailed. Finally, we show how to use the library to extract SWATH data with the open-source software Skyline. The protocol takes 2-3 d to complete, depending on the extent of the library and the computational resources available.

YPED: an integrated bioinformatics suite and database for mass spectrometry-based proteomics research

We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database (YPED) that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a single laboratory, group of laboratories within and beyond an institution, to the entire proteomics community. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography-tandem mass spectrometry (LC-MS/MS) database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring (MRM)/selective reaction monitoring (SRM) assay development. We have linked YPED's database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results.

Reproducible and consistent quantification of the Saccharomyces cerevisiae proteome by SWATH-mass spectrometry

Targeted mass spectrometry by selected reaction monitoring (S/MRM) has proven to be a suitable technique for the consistent and reproducible quantification of proteins across multiple biological samples and a wide dynamic range. This performance profile is an important prerequisite for systems biology and biomedical research. However, the method is limited to the measurements of a few hundred peptides per LC-MS analysis. Recently, we introduced SWATH-MS, a combination of data independent acquisition and targeted data analysis that vastly extends the number of peptides/proteins quantified per sample, while maintaining the favorable performance profile of S/MRM. Here we applied the SWATH-MS technique to quantify changes over time in a large fraction of the proteome expressed in Saccharomyces cerevisiae in response to osmotic stress. We sampled cell cultures in biological triplicates at six time points following the application of osmotic stress and acquired single injection data independent acquisition data sets on a high-resolution 5600 tripleTOF instrument operated in SWATH mode. Proteins were quantified by the targeted extraction and integration of transition signal groups from the SWATH-MS datasets for peptides that are proteotypic for specific yeast proteins. We consistently identified and quantified more than 15,000 peptides and 2500 proteins across the 18 samples. We demonstrate high reproducibility between technical and biological replicates across all time points and protein abundances. In addition, we show that the abundance of hundreds of proteins was significantly regulated upon osmotic shock, and pathway enrichment analysis revealed that the proteins reacting to osmotic shock are mainly involved in the carbohydrate and amino acid metabolism. Overall, this study demonstrates the ability of SWATH-MS to efficiently generate reproducible, consistent, and quantitatively accurate measurements of a large fraction of a proteome across multiple samples.

Microbial Proteome Profiling and Systems Biology: Applications to Mycobacterium tuberculosis

Each year, 1.3 million people die from tuberculosis, an infectious disease caused by Mycobacterium tuberculosis. Systems biology-based strategies might significantly contribute to the knowledge-guided development of more effective vaccines and drugs to prevent and cure infectious diseases. To build models simulating the behaviour of a system in response to internal or external stimuli and to identify potential targets for therapeutic intervention, systems biology approaches require the acquisition of quantitative molecular profiles on many perturbed states. Here we review the current state of proteomic analyses in Mycobacterium tuberculosis and discuss the potential of recently emerging targeting mass spectrometry-based techniques which enable fast, sensitive and accurate protein measurements.