Isobaric tagging approaches in quantitative proteomics: the ups and downs

High-Throughput Nanoflow Proteomics Using a Dual-Column Electrospray Source

With current trends in proteomics, especially regarding clinical and low input (to single cell) samples, it is increasingly important to both maximize the throughput of the analysis and maintain as much sensitivity as possible. The new generation of mass spectrometers (MS) are taking a huge leap in sensitivity, allowing analysis of samples with shorter liquid chromatography (LC) methods while digging as deep in the proteome. However, the throughput can be doubled by implementing a dual column nano-LC-MS configuration. For this purpose, we used a dual-column setup with a two-outlet electrospray source and compared it to a classic dual-column setup with a single-outlet source.

Updates of the current strategies of labeling for N-glycan analysis

This mini review summarizes the current methods used for screening N-glycosylation of glycoproteins, with a specific focus on therapeutic proteins and on techniques involving the release of N-glycans. With the continuous development of biopharmaceuticals, particularly monoclonal antibodies (mAbs), which are N-glycosylated proteins, monitoring has gained importance in recent decades. Glycosylation of therapeutic glycoproteins is considered a critical quality attribute because it can impact the efficacy and safety of these therapeutic drugs. The protocols and instrumentation have evolved with the advancement of technologies. Nowadays, methods are becoming increasingly robust, rapid, and sensitive. For the release of N-glycans, the most commonly used method is enzymatic release using PNGase F. The latter is discussed in light of the advent of rapid release that is now possible. The strategy for separating N-glycans using either liquid chromatography (LC) with hydrophilic interaction liquid chromatography (HILIC) chemistry or capillary electrophoresis will be discussed. The selection of the labeling agent is a crucial step in sample preparation for the analysis of released N-glycans. This review also discusses labeling agents that are compatible with and dependent on the separation and detection techniques employed. The emergence of multiplex labeling agents is also summarized. The latter enables the analysis of multiple samples in a single run, but it requires MS analysis.

Recent advances in microfluidics for single-cell functional proteomics

Single-cell proteomics (SCP) reveals phenotypic heterogeneity by profiling individual cells, their biological states and functional outcomes upon signaling activation that can hardly be probed via other omics characterizations. This has become appealing to researchers as it enables an overall more holistic view of biological details underlying cellular processes, disease onset and progression, as well as facilitates unique biomarker identification from individual cells. Microfluidic-based strategies have become methods of choice for single-cell analysis because they allow facile assay integrations, such as cell sorting, manipulation, and content analysis. Notably, they have been serving as an enabling technology to improve the sensitivity, robustness, and reproducibility of recently developed SCP methods. Critical roles of microfluidics technologies are expected to further expand rapidly in advancing the next phase of SCP analysis to reveal more biological and clinical insights. In this review, we will capture the excitement of the recent achievements of microfluidics methods for both targeted and global SCP, including efforts to enhance the proteomic coverage, minimize sample loss, and increase multiplexity and throughput. Furthermore, we will discuss the advantages, challenges, applications, and future prospects of SCP.

Multiplex measurement of protein-peptide dissociation constants using dialysis and mass spectrometry

We propose a high-throughput method for quantitively measuring hundreds of protein-peptide binding affinities in parallel. In this assay a solution of protein is dialyzed into a buffer containing a pool of potential binding peptides, such that upon equilibration the relative abundance of a peptide species is mathematically related to that peptide's dissociation constant, K_d . We use isobaric multiplexed quantitative proteomics to simultaneously determine the relative abundance, and hence the K_d and its associated error, for an entire peptide library. We apply this technique, which we call PEDAL (Parallel Equilibrium Dialysis for Affinity Learning), to determine accurate K_d 's between a PDZ domain and hundreds of peptides, spanning an affinity range of multiple orders of magnitude in a single experiment. PEDAL is a convenient, fast, and low-cost method for measuring large numbers of protein-peptide affinities in parallel, providing a rare combination of true in-solution binding equilibria with the ability to multiplex. This article is protected by copyright. All rights reserved.

Combined Transcriptomic and Proteomic Profiling of E. coli under Microaerobic versus Aerobic Conditions: The Multifaceted Roles of Noncoding Small RNAs and Oxygen-Dependent Sensing in Global Gene Expression Control

Adaptive mechanisms that facilitate intestinal colonization by the human microbiota, including Escherichia coli, may be better understood by analyzing the physiology and gene expression of bacteria in low-oxygen environments. We used high-throughput transcriptomics and proteomics to compare the expression profiles of E. coli grown under aerobic versus microaerobic conditions. Clustering of high-abundance transcripts under microaerobiosis highlighted genes controlling acid-stress adaptation (gadAXW, gadAB, hdeAB-yhiD and hdeD operons), cell adhesion/biofilm formation (pgaABCD and csgDEFG operons), electron transport (cydAB), oligopeptide transport (oppABCDF), and anaerobic respiration/fermentation (hyaABCDEF and hycABCDEFGHI operons). In contrast, downregulated genes were involved in iron transport (fhuABCD, feoABC and fepA-entD operons), iron-sulfur cluster assembly (iscRSUA and sufABCDSE operons), aerobic respiration (sdhDAB and sucABCDSE operons), and de novo nucleotide synthesis (nrdHIEF). Additionally, quantitative proteomics showed that the products (proteins) of these high- or low-abundance transcripts were expressed consistently. Our findings highlight interrelationships among energy production, carbon metabolism, and iron homeostasis. Moreover, we have identified and validated a subset of differentially expressed noncoding small RNAs (i.e., CsrC, RyhB, RprA and GcvB), and we discuss their regulatory functions during microaerobic growth. Collectively, we reveal key changes in gene expression at the transcriptional and post-transcriptional levels that sustain E. coli growth when oxygen levels are low.

Review of the Real and Sometimes Hidden Costs in Proteomics Experimental Workflows

A typical proteomics workflow covers all the steps from growing or collecting the cells/tissues/organism, protein extraction, digestion and cleanup, mass spectrometric analysis, and, finally, extensive bioinformatics to derive biological insight from the data. The details of the procedures employed for this can vary widely by laboratory and by sample type: e.g., hard tissues or cells with walls require much more mechanical disruption to extract proteins than do soft tissues, biological fluids, or wall-less cells. Everything then converges on the mass spectrometer, where there are further choices to be made about how to do the analysis. There is one commonality, however, virtually every group around the world now uses liquid chromatography on-line coupled to tandem mass spectrometry, which means that significant amounts of instrument time are dedicated to every sample. There are many other reviews or methods papers, including in this volume, that cover the details of the various procedures involved in proteomic analyses of all types of samples. Our focus here will be on the cost considerations for such analyses, including considerations to ensure that useful data can be obtained the first time a sample is analyzed. Some of these costs are often overlooked, particularly for those groups who operate their own mass spectrometer(s) and do not have to go to a fee-for-service facility to have something analyzed. The chapter presents several challenges and key suggestions in proving hypotheses in proteomics experimental workflow in different biological systems with specific regard to the costs involved, both real and hidden. The detailed methodology for cost-based studies reported in this chapter can help researchers to set up their laboratory with appropriate equipment as well as to identify potential collaborations based on their analytical instrumentation.

Quantitative Proteomics Using Isobaric Labeling: A Practical Guide

In the past decade, relative proteomic quantification using isobaric labeling technology has developed into a key tool for comparing the expression of proteins in biological samples. Although its multiplexing capacity and flexibility make this a valuable technology for addressing various biological questions, its quantitative accuracy and precision still pose significant challenges to the reliability of its quantification results. Here, we give a detailed overview of the different kinds of isobaric mass tags and the advantages and disadvantages of the isobaric labeling method. We also discuss which precautions should be taken at each step of the isobaric labeling workflow, to obtain reliable quantification results in large-scale quantitative proteomics experiments. In the last section, we discuss the broad applications of the isobaric labeling technology in biological and clinical studies, with an emphasis on thermal proteome profiling and proteogenomics.

Inflect: Optimizing Computational Workflows for Thermal Proteome Profiling Data Analysis

The CETSA and Thermal Proteome Profiling (TPP) analytical methods are invaluable for the study of protein-ligand interactions and protein stability in a cellular context. These tools have increasingly been leveraged in work ranging from understanding signaling paradigms to drug discovery. Consequently, there is an important need to optimize the data analysis pipeline that is used to calculate protein melt temperatures (Tm) and relative melt shifts from proteomics abundance data. Here, we report a user-friendly analysis of the melt shift calculation workflow where we describe the impact of each individual calculation step on the final output list of stabilized and destabilized proteins. This report also includes a description of how key steps in the analysis workflow quantitatively impact the list of stabilized/destabilized proteins from an experiment. We applied our findings to develop a more optimized analysis workflow that illustrates the dramatic sensitivity of chosen calculation steps on the final list of reported proteins of interest in a study and have made the R based program Inflect available for research community use through the CRAN repository [McCracken, N. Inflect: Melt Curve Fitting and Melt Shift Analysis. R package version 1.0.3, 2021]. The Inflect outputs include melt curves for each protein which passes filtering criteria in addition to a data matrix which is directly compatible with downstream packages such as UpsetR for replicate comparisons and identification of biologically relevant changes. Overall, this work provides an essential resource for scientists as they analyze data from TPP and CETSA experiments and implement their own analysis pipelines geared toward specific applications.

Multi-Q 2 software facilitates isobaric labeling quantitation analysis with improved accuracy and coverage

Mass spectrometry-based proteomics using isobaric labeling for multiplex quantitation has become a popular approach for proteomic studies. We present Multi-Q 2, an isobaric-labeling quantitation tool which can yield the largest quantitation coverage and improved quantitation accuracy compared to three state-of-the-art methods. Multi-Q 2 supports identification results from several popular proteomic data analysis platforms for quantitation, offering up to 12% improvement in quantitation coverage for accepting identification results from multiple search engines when compared with MaxQuant and PatternLab. It is equipped with various quantitation algorithms, including a ratio compression correction algorithm, and results in up to 336 algorithmic combinations. Systematic evaluation shows different algorithmic combinations have different strengths and are suitable for different situations. We also demonstrate that the flexibility of Multi-Q 2 in customizing algorithmic combination can lead to improved quantitation accuracy over existing tools. Moreover, the use of complementary algorithmic combinations can be an effective strategy to enhance sensitivity when searching for biomarkers from differentially expressed proteins in proteomic experiments. Multi-Q 2 provides interactive graphical interfaces to process quantitation and to display ratios at protein, peptide, and spectrum levels. It also supports a heatmap module, enabling users to cluster proteins based on their abundance ratios and to visualize the clustering results. Multi-Q 2 executable files, sample data sets, and user manual are freely available at http://ms.iis.sinica.edu.tw/COmics/Software_Multi-Q2.html.

Skin proteomics - analysis of the extracellular matrix in health and disease

INTRODUCTION

The skin protects the human body from external insults and regulates water and temperature homeostasis. A highly developed extracellular matrix (ECM) supports the skin and instructs its cell functions. Reduced functionality of the ECM is often associated with skin diseases that cause physical impairment and also have implications on social interactions and quality of life of affected individuals.

AREAS COVERED

With a focus on the skin ECM we discuss how mass spectrometry (MS)-based proteomic approaches first contributed to establishing skin protein inventories and then facilitated elucidation of molecular functions and disease mechanisms.

EXPERT OPINION

MS-based proteomic approaches have significantly contributed to our understanding of skin pathophysiology, but also revealed the challenges in assessing the skin ECM. The numerous posttranslational modifications of ECM proteins, like glycosylation, crosslinking, oxidation, and proteolytic maturation in disease settings can be difficult to tackle and remain understudied. Increased ease of handling of LC-MS/MS systems and automated/streamlined data analysis pipelines together with the accompanying increased usage of LC-MS/MS approaches will ensure that in the coming years MS-based proteomic approaches will continue to play a vital part in skin disease research. They will facilitate the elucidation of molecular disease mechanisms and, ultimately, identification of new druggable targets.

Progress and pitfalls of using isobaric mass tags for proteome profiling

Introduction: Quantitative proteomics using mass spectrometry is performed via label-free or label-based approaches. Labeling strategies rely on the incorporation of stable heavy isotopes by metabolic, enzymatic, or chemical routes. Isobaric labeling uses chemical labels of identical masses but of different fragmentation behaviors to allow the relative quantitative comparison of peptide/protein abundances between biological samples.Areas covered: We have carried out a systematic review on the use of isobaric mass tags in proteomic research since their inception in 2003. We focused on their quantitative performances, their multiplexing evolution, as well as their broad use for relative quantification of proteins in pre-clinical models and clinical studies. Current limitations, primarily linked to the quantitative ratio distortion, as well as state-of-the-art and emerging solutions to improve their quantitative readouts are discussed.Expert opinion: The isobaric mass tag technology offers a unique opportunity to compare multiple protein samples simultaneously, allowing higher sample throughput and internal relative quantification for improved trueness and precision. Large studies can be performed when shared reference samples are introduced in multiple experiments. The technology is well suited for proteome profiling in the context of proteomic discovery studies.

PRMT5 methylome profiling uncovers a direct link to splicing regulation in acute myeloid leukemia

Protein arginine methyltransferase 5 (PRMT5) has emerged as a promising cancer drug target, and three PRMT5 inhibitors are currently in clinical trials for multiple malignancies. In this study, we investigated the role of PRMT5 in human acute myeloid leukemia (AML). Using an enzymatic dead version of PRMT5 and a PRMT5-specific inhibitor, we demonstrated the requirement of the catalytic activity of PRMT5 for the survival of AML cells. We then identified PRMT5 substrates using multiplexed quantitative proteomics and investigated their role in the survival of AML cells. We found that the function of the splicing regulator SRSF1 relies on its methylation by PRMT5 and that loss of PRMT5 leads to changes in alternative splicing of multiple essential genes. This explains the requirement of PRMT5 for leukemia cell survival. We show that PRMT5 regulates binding of SRSF1 to mRNAs and proteins and provide potential biomarkers for the treatment response to PRMT5 inhibitors.

Feasibility of Utilizing Stable-Isotope Dimethyl Labeling in Liquid Chromatography⁻Tandem Mass Spectrometry-Based Determination for Food Allergens-Case of Kiwifruit

Stable-isotope dimethyl labeling is a highly reactive and cost-effective derivatization procedure that could be utilized in proteomics analysis. In this study, a liquid chromatography- tandem mass spectrometry in multiple reaction monitoring mode (LC-MS-MRM) platform for the quantification of kiwi allergens was first developed using this strategy. Three signature peptides for target allergens Act d 1, Act d 5, and Act d 11 were determined and were derivatized with normal and deuterated formaldehyde as external calibrants and internal standards, respectively. The results showed that sample preparation with the phenol method provided comprehensive protein populations. Recoveries at four different levels ranging from 72.5-109.3% were achieved for the H-labeled signature peptides of Act d 1 (SPA1-H) and Act d 5 (SPA5-H) with precision ranging from 1.86-9.92%. The limit of quantification (LOQ) was set at 8 pg mL^-1 for SPA1-H and at 8 ng mL^-1 for SPA5-H. The developed procedure was utilized to analyze seven kinds of hand-made kiwi foods containing 0.0175-0.0515 mg g^-1 of Act d 1 and 0.0252-0.0556 mg g^-1 of Act d 5. This study extended the applicability of stable-isotope dimethyl labeling to the economical and precise determination of food allergens and peptides.

iTRAQ comparison of proteomic profiles of endometrial receptivity

Endometrial receptivity is a limiting step in human reproduction. A disruption in the development of endometrial receptivity is responsible for recurrent implantation failures (RIF) of endometrial origin. To understand the molecular mechanisms behind the endometrial receptivity process, we used the isobaric tag for relative and absolute quantitation (iTRAQ) method to compare three different endometrial statuses: fertile women, intrauterine device (IUD) carriers, and RIF patients. Overall, iTRAQ allowed identified 1889 non-redundant proteins. Of these, 188 were differentially expressed proteins (DEP) (p-value < .05). Pairwise comparisons revealed 133 significant DEP in fertile vs. IUD carriers and 158 DEP in RIF vs. IUD carriers. However, no DEP were identified between fertile and RIF patients. Western blot validation of three DEP involved in endometrial receptivity (plastin 2, lactotransferrin, and lysozyme) confirmed our iTRAQ results. Moreover, functional KEGG enrichment revealed that complement and coagulation cascades and peroxisome were the two most significant pathways for the RIF vs. IUD comparison and ribosome and spliceosome for the fertile vs. IUD comparison, as possible important pathways involved in the endometrial receptivity acquisition. The lack of DEP between fertile and RIF patient endometria suggest that idiopathic RIF may not have an endometrial origin, with other as-yet-unknown factors involved. SIGNIFICANCE: A pilot study where a comparison of the endometrial protein profile from women with different endometrial receptive grade (fertile women, IUD carriers and RIF patients) during the same period of time (overlapping with the window of implantation) of a hormone replacement therapy was performed using a high-throughput proteomic technique. This approach lead us to better understand the molecular mechanisms undergoing endometrial receptivity, a time-limiting step to achieve pregnancy in humans. Moreover, the number of samples per group (10 Fertile women, 10 IUD carriers and 8 RIF patients) according to the methodology here employed (8plex iTRAQ), give more robustness to our results. Our findings confirm that an IUD introduces numerous changes in the endometrial protein profile when compared to fertile and RIF endometria, revealing some key proteins involved in endometrial receptivity. Finding no significant differences between Fertile and RIF patient endometria could suggest that other as-yet-unknown factors could be involved in the etiology of idiopathic RIF.

iTRAQ-based pharmacoproteomics reveals potential targets of berberine, a promising therapy for ulcerative colitis

Previous studies by us and others have indicated that berberine is a promising therapy for ulcerative colitis (UC). However, the mechanisms of UC and the therapeutic targets of berberine are poorly understood. iTRAQ-based proteomics was utilized to characterize the proteins and pathways associated with the development of colitis and its improvement after berberine treatment. By using a modified dextran sodium sulfate (DSS) colitis as the UC model, confirmed that berberine significantly attenuated clinical symptoms and colon shorting of the colitis mice. Proteomics identified 140 and 391 proteins that were differentially expressed in the colons of DSS- or DSS plus berberine-treated mice, respectively. Subsequent verification of 15 selected differentially expressed proteins (DEPs) by multiple reaction monitoring confirmed the reliability of the iTRAQ data. Further comparisons and bioinformatics analysis demonstrated that among the identified DEPs, 26, including Hist2h2be, Tubb3, and five immunoglobulins, were oppositely regulated by DSS and DSS plus berberine treatments. In addition, five commonly dysregulated pathways, including natural killer cell-mediated cytotoxicity and RRAR signaling were identified. Network analysis revealed that proteins involved in 7 and 11 pathways in DSS and DSS plus berberine treated mice, respectively, engaged in protein-protein interactions. Our study provides the first pharmacoproteomics profiling of colitis and its recovery after berberine treatment. The proteins, pathways and networks identified provide novel insights into the pathogenesis of colitis and the action mechanism of berberine, demonstrating their values for validation in human UC which could serve as targets for the development of novel therapies for UC.

Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics

The study of protein localisation has greatly benefited from high-throughput methods utilising cellular fractionation and proteomic profiling. Hyperplexed Localisation of Organelle Proteins by Isotope Tagging (hyperLOPIT) is a well-established method in this area. It achieves high-resolution separation of organelles and subcellular compartments but is relatively time- and resource-intensive. As a simpler alternative, we here develop Localisation of Organelle Proteins by Isotope Tagging after Differential ultraCentrifugation (LOPIT-DC) and compare this method to the density gradient-based hyperLOPIT approach. We confirm that high-resolution maps can be obtained using differential centrifugation down to the suborganellar and protein complex level. HyperLOPIT and LOPIT-DC yield highly similar results, facilitating the identification of isoform-specific localisations and high-confidence localisation assignment for proteins in suborganellar structures, protein complexes and signalling pathways. By combining both approaches, we present a comprehensive high-resolution dataset of human protein localisations and deliver a flexible set of protocols for subcellular proteomics.

Distinct urinary glycoprotein signatures in prostate cancer patients

Novel biomarkers are needed to complement prostate specific antigen (PSA) in prostate cancer (PCa) diagnostic screening programs. Glycoproteins represent a hitherto largely untapped resource with a great potential as specific and sensitive tumor biomarkers due to their abundance in bodily fluids and their dynamic and cancer-associated glycosylation. However, quantitative glycoproteomics strategies to detect potential glycoprotein cancer markers from complex biospecimen are only just emerging. Here, we describe a glycoproteomics strategy for deep quantitative mapping of N- and O-glycoproteins in urine with a view to investigate the diagnostic value of the glycoproteome to discriminate PCa from benign prostatic hyperplasia (BPH), two conditions that remain difficult to clinically stratify. Total protein extracts were obtained, concentrated and digested from urine of six PCa patients (Gleason score 7) and six BPH patients. The resulting peptide mixtures were TMT-labeled and mixed prior to a multi-faceted sample processing including hydrophilic interaction liquid chromatography (HILIC) and titanium dioxide SPE based enrichment, endo-/exoglycosidase treatment and HILIC-HPLC pre-fractionation. The isolated N- and O-glycopeptides were detected and quantified using high resolution mass spectrometry. We accurately quantified 729 N-glycoproteins spanning 1,310 unique N-glycosylation sites and observed 954 and 965 unique intact N- and O-glycopeptides, respectively, across the two disease conditions. Importantly, a panel of 56 intact N-glycopeptides perfectly discriminated PCa and BPH (ROC: AUC = 1). This study has generated a panel of intact glycopeptides that has a potential for PCa detection.

Quantitative Proteome and Phosphoproteome Analyses of Streptomyces coelicolor Reveal Proteins and Phosphoproteins Modulating Differentiation and Secondary Metabolism

Streptomycetes are multicellular bacteria with complex developmental cycles. They are of biotechnological importance as they produce most bioactive compounds used in biomedicine, e.g. antibiotic, antitumoral and immunosupressor compounds. Streptomyces genomes encode many Ser/Thr/Tyr kinases, making this genus an outstanding model for the study of bacterial protein phosphorylation events. We used mass spectrometry based quantitative proteomics and phosphoproteomics to characterize bacterial differentiation and activation of secondary metabolism of Streptomyces coelicolor We identified and quantified 3461 proteins corresponding to 44.3% of the S. coelicolor proteome across three developmental stages: vegetative hypha (first mycelium); secondary metabolite producing hyphae (second mycelium); and sporulating hyphae. A total of 1350 proteins exhibited more than 2-fold expression changes during the bacterial differentiation process. These proteins include 136 regulators (transcriptional regulators, transducers, Ser/Thr/Tyr kinases, signaling proteins), as well as 542 putative proteins with no clear homology to known proteins which are likely to play a role in differentiation and secondary metabolism. Phosphoproteomics revealed 85 unique protein phosphorylation sites, 58 of them differentially phosphorylated during differentiation. Computational analysis suggested that these regulated protein phosphorylation events are implicated in important cellular processes, including cell division, differentiation, regulation of secondary metabolism, transcription, protein synthesis, protein folding and stress responses. We discovered a novel regulated phosphorylation site in the key bacterial cell division protein FtsZ (pSer319) that modulates sporulation and regulates actinorhodin antibiotic production. We conclude that manipulation of distinct protein phosphorylation events may improve secondary metabolite production in industrial streptomycetes, including the activation of cryptic pathways during the screening for new secondary metabolites from streptomycetes.

Omics approaches for subcellular translation studies

Koppel & Fainzilber review translatomics and proteomics methods for studying protein synthesis at subcellular resolution.

Investigating the Effect of Growth Phase on the Surface-Layer Associated Proteome of Lactobacillus acidophilus Using Quantitative Proteomics

Bacterial surface-layers (S-layers) are semi-porous crystalline arrays that self-assemble to form the outermost layer of some cell envelopes. S-layers have been shown to act as scaffolding structures for the display of auxiliary proteins externally. These S-layer associated proteins have recently gained attention in probiotics due to their direct physical contact with the intestinal mucosa and potential role in cell proliferation, adhesion, and immunomodulation. A number of studies have attempted to catalog the S-layer associated proteome of Lactobacillus acidophilus NCFM under a single condition. However, due to the versatility of the cell surface, we chose to employ a multiplexing-based approach with the intention of accurately contrasting multiple conditions. In this study, a previously described lithium chloride isolation protocol was used to release proteins bound to the L. acidophilus S-layer during logarithmic and early stationary growth phases. Protein quantification values were obtained via TMT (tandem mass tag) labeling combined with a triple-stage mass spectrometry (MS3) method. Results showed significant growth stage-dependent alterations to the surface-associated proteome while simultaneously highlighting the sensitivity and reproducibility of the technology. Thus, this study establishes a framework for quantifying condition-dependent changes to cell surface proteins that can easily be applied to other S-layer forming bacteria.

Aneuploidy Causes Non-genetic Individuality

Phenotypic variability is a hallmark of diseases involving chromosome gains and losses, such as Down syndrome and cancer. Allelic variances have been thought to be the sole cause of this heterogeneity. Here, we systematically examine the consequences of gaining and losing single or multiple chromosomes to show that the aneuploid state causes non-genetic phenotypic variability. Yeast cell populations harboring the same defined aneuploidy exhibit heterogeneity in cell-cycle progression and response to environmental perturbations. Variability increases with degree of aneuploidy and is partly due to gene copy number imbalances, suggesting that subtle changes in gene expression impact the robustness of biological networks and cause alternate behaviors when they occur across many genes. As inbred trisomic mice also exhibit variable phenotypes, we further propose that non-genetic individuality is a universal characteristic of the aneuploid state that may contribute to variability in presentation and treatment responses of diseases caused by aneuploidy.

Bicarbonate Induced Redox Proteome Changes in Arabidopsis Suspension Cells

Climate change as a result of increasing atmospheric CO₂ affects plant growth and productivity. CO₂ is not only a carbon donor for photosynthesis but also an environmental signal that can perturb cellular redox homeostasis and lead to modifications of redox-sensitive proteins. Although redox regulation of protein functions has emerged as an important mechanism in several biological processes, protein redox modifications and how they function in plant CO₂ response remain unclear. Here a new iodoTMTRAQ proteomics technology was employed to analyze changes in protein redox modifications in Arabidopsis thaliana suspension cells in response to bicarbonate (mimic of elevated CO₂) in a time-course study. A total of 47 potential redox-regulated proteins were identified with functions in carbohydrate and energy metabolism, transport, ROS scavenging, cell structure modulation and protein turnover. This inventory of previously unknown redox responsive proteins in Arabidopsis bicarbonate responses lays a foundation for future research toward understanding the molecular mechanisms underlying plant CO₂ responses.

Quantitative proteomics and terminomics to elucidate the role of ubiquitination and proteolysis in adaptive immunity

Adaptive immunity is the specialized defence mechanism in vertebrates that evolved to eliminate pathogens. Specialized lymphocytes recognize specific protein epitopes through antigen receptors to mount potent immune responses, many of which are initiated by nuclear factor-kappa B activation and gene transcription. Most, if not all, pathways in adaptive immunity are further regulated by post-translational modification (PTM) of signalling proteins, e.g. phosphorylation, citrullination, ubiquitination and proteolytic processing. The importance of PTMs is reflected by genetic or acquired defects in these pathways that lead to a dysfunctional immune response. Here we discuss the state of the art in targeted proteomics and systems biology approaches to dissect the PTM landscape specifically regarding ubiquitination and proteolysis in B- and T-cell activation. Recent advances have occurred in methods for specific enrichment and targeted quantitation. Together with improved instrument sensitivity, these advances enable the accurate analysis of often rare PTM events that are opaque to conventional proteomics approaches, now rendering in-depth analysis and pathway dissection possible. We discuss published approaches, including as a case study the profiling of the N-terminome of lymphocytes of a rare patient with a genetic defect in the paracaspase protease MALT1, a key regulator protease in antigen-driven signalling, which was manifested by elevated linear ubiquitination.This article is part of the themed issue 'Quantitative mass spectrometry'.

Emerging power of proteomics for delineation of intrinsic tumor subtypes and resistance mechanisms to anti-cancer therapies

INTRODUCTION

Despite extreme genetic heterogeneity, tumors often show similar alterations in the expression, stability, and activation of proteins important in oncogenic signaling pathways. Thus, classifying tumor samples according to shared proteomic features may help facilitate the identification of cancer subtypes predictive of therapeutic responses and prognostic for patient outcomes. Meanwhile, understanding mechanisms of intrinsic and acquired resistance to anti-cancer therapies at the protein level may prove crucial to devising reversal strategies. Areas covered: Herein, we review recent advances in quantitative proteomic technology and their applications in studies to identify intrinsic tumor subtypes of various tumors, to illuminate mechanistic aspects of pharmacological and oncogenic adaptations, and to highlight interaction targets for anti-cancer compounds and cancer-addicted proteins. Expert commentary: Quantitative proteomic technologies are being successfully employed to classify tumor samples into distinct intrinsic subtypes, to improve existing DNA/RNA based classification methods, and to evaluate the activation status of key signaling pathways.

Quantitative LC-MS/MS Glycomic Analysis of Biological Samples Using AminoxyTMT

Protein glycosylation plays an important role in various biological processes, such as modification of protein function, regulation of protein-protein interactions, and control of turnover rates of proteins. Moreover, glycans have been considered as potential biomarkers for many mammalian diseases and development of aberrant glycosylation profiles is an important indicator of the pathology of a disease or cancer. Hence, quantitation is an important aspect of a comprehensive glycomics study. Although numerous MS-based quantitation strategies have been developed in the past several decades, some issues affecting sensitivity and accuracy of quantitation still exist, and the development of more effective quantitation strategies is still required. Aminoxy tandem mass tag (aminoxyTMT) reagents are recently commercialized isobaric tags which enable relative quantitation of up to six different glycan samples simultaneously. In this study, liquid chromatography and mass spectrometry conditions have been optimized to achieve reliable LC-MS/MS quantitative glycomic analysis using aminoxyTMT reagents. Samples were resuspended in 0.2 M sodium chloride solution to promote the formation of sodium adduct precursor ions, which leads to higher MS/MS reporter ion yields. This method was first evaluated with glycans from model glycoproteins and pooled human blood serum samples. The observed variation of reporter ion ratios was generally less than 10% relative to the theoretical ratio. Even for the highly complex minor N-glycans, the variation was still below 15%. This strategy was further applied to the glycomic profiling of N-glycans released from blood serum samples of patients with different esophageal diseases. Our results demonstrate the benefits of utilizing aminoxyTMT reagents for reliable quantitation of biological glycomic samples.

A universal SI-traceable isotope dilution mass spectrometry method for protein quantitation in a matrix by tandem mass tag technology

Isotope dilution mass spectrometry (IDMS), an important metrological method, is widely used for absolute quantification of peptides and proteins. IDMS employs an isotope-labeled peptide or protein as an internal standard although the use of a protein provides improved accuracy. Generally, the isotope-labeled protein is obtained by stable isotope labeling by amino acids in cell culture (SILAC) technology. However, SILAC is expensive, laborious, and time-consuming. To overcome these drawbacks, a novel universal SI-traceable IDMS method for absolute quantification of proteins in a matrix is described with human transferrin (hTRF). The hTRF and a human serum sample were labeled with different tandem mass tags (TMTs). After mixing the TMT-labeled hTRF and serum sample together followed by digestion, the peptides were separated by nano-liquid chromatography and analyzed by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Using the signature peptides, we calculated the ratios of reporter ions from the TMT-labeled peptides which, in turn, allowed determination of the mass fraction of hTRF. The recovery ranged from 97% to 105% with a CV of 3.9%. The LOD and LOQ were 1.71 × 10(-5) g/g and 5.69 × 10(-5) g/g of hTRF in human serum, respectively, and the relative expanded uncertainty was 4.7% with a mass fraction of 2.08 mg/g. For comparison, an enzyme-linked immunosorbent assay (ELISA) method for hTRF yielded a mass fraction of 2.03 mg/g. This method provides a starting point for establishing IDMS technology to accurately determine the mass fractions of protein biomarkers in a matrix with traceability to SI units. This technology should support the development of a metrological method useful for quantification of a wide variety of proteins.

A draft map of the mouse pluripotent stem cell spatial proteome

Knowledge of the subcellular distribution of proteins is vital for understanding cellular mechanisms. Capturing the subcellular proteome in a single experiment has proven challenging, with studies focusing on specific compartments or assigning proteins to subcellular niches with low resolution and/or accuracy. Here we introduce hyperLOPIT, a method that couples extensive fractionation, quantitative high-resolution accurate mass spectrometry with multivariate data analysis. We apply hyperLOPIT to a pluripotent stem cell population whose subcellular proteome has not been extensively studied. We provide localization data on over 5,000 proteins with unprecedented spatial resolution to reveal the organization of organelles, sub-organellar compartments, protein complexes, functional networks and steady-state dynamics of proteins and unexpected subcellular locations. The method paves the way for characterizing the impact of post-transcriptional and post-translational modification on protein location and studies involving proteome-level locational changes on cellular perturbation. An interactive open-source resource is presented that enables exploration of these data.

Sample Preparation Approaches for iTRAQ Labeling and Quantitative Proteomic Analyses in Systems Biology

Among a variety of global quantification strategies utilized in mass spectrometry (MS)-based proteomics, isobaric tags for relative and absolute quantitation (iTRAQ) are an attractive option for examining the relative amounts of proteins in different samples. The inherent complexity of mammalian proteomes and the diversity of protein physicochemical properties mean that complete proteome coverage is still unlikely from a single analytical method. Numerous options exist for reducing protein sample complexity and resolving digested peptides prior to MS analysis. Indeed, the reliability and efficiency of protein identification and quantitation from an iTRAQ workflow strongly depend on sample preparation upstream of MS. Here we describe our methods for: (1) total protein extraction from immortalized cells; (2) subcellular fractionation of murine tissue; (3) protein sample desalting, digestion, and iTRAQ labeling; (4) peptide separation by strong cation-exchange high-performance liquid chromatography; and (5) peptide separation by isoelectric focusing.

Proteomic analysis of early-stage embryos: implications for egg quality in hapuku (Polyprion oxygeneios)

In order to develop biomarkers that may help predict the egg quality of captive hapuku (Polyprion oxygeneios) and provide potential avenues for its manipulation, the present study (1) sequenced the proteome of early-stage embryos using isobaric tag for relative and absolute quantification analysis, and (2) aimed to establish the predictive value of the abundance of identified proteins with regard to egg quality through regression analysis. Egg quality was determined for eight different egg batches by blastomere symmetry scores. In total, 121 proteins were identified and assigned to one of nine major groups according to their function/pathway. A mixed-effects model analysis revealed a decrease in relative protein abundance that correlated with (decreasing) egg quality in one major group (heat-shock proteins). No differences were found in the other protein groups. Linear regression analysis, performed for each identified protein separately, revealed seven proteins that showed a significant decrease in relative abundance with reduced blastomere symmetry: two correlates that have been named in other studies (vitellogenin, heat-shock protein-70) and a further five new candidate proteins (78 kDa glucose-regulated protein, elongation factor-2, GTP-binding nuclear protein Ran, iduronate 2-sulfatase and 6-phosphogluconate dehydrogenase). Notwithstanding issues associated with multiple statistical testing, we conclude that these proteins, and especially iduronate 2-sulfatase and the generic heat-shock protein group, could serve as biomarkers of egg quality in hapuku.

Quantitation of protein post-translational modifications using isobaric tandem mass tags

Post-translational modifications (PTMs) of proteins are known to modulate many cellular processes and their qualitative and quantitative evaluation is fundamental for understanding the mechanisms of biological events. Over the past decade, improvements in sample preparation techniques and enrichment strategies, the development of quantitative labeling strategies, the launch of a new generation of mass spectrometers and the creation of bioinformatics tools for the interrogation of ever larger datasets has established MS-based quantitative proteomics as a powerful workflow for global proteomics, PTM analysis and the elucidation of key biological mechanisms. With the advantage of their multiplexing capacity and the flexibility of an ever-growing family of different peptide-reactive groups, isobaric tandem mass tags facilitate quantitative proteomics and PTM experiments and enable higher sample throughput. In this review, we focus on the technical concept and utility of the isobaric tandem mass tag labeling approach to PTM analysis, including phosphorylation, glycosylation and S-nitrosylation.

Redefining the Breast Cancer Exosome Proteome by Tandem Mass Tag Quantitative Proteomics and Multivariate Cluster Analysis

Exosomes are microvesicles of endocytic origin constitutively released by multiple cell types into the extracellular environment. With evidence that exosomes can be detected in the blood of patients with various malignancies, the development of a platform that uses exosomes as a diagnostic tool has been proposed. However, it has been difficult to truly define the exosome proteome due to the challenge of discerning contaminant proteins that may be identified via mass spectrometry using various exosome enrichment strategies. To better define the exosome proteome in breast cancer, we incorporated a combination of Tandem-Mass-Tag (TMT) quantitative proteomics approach and Support Vector Machine (SVM) cluster analysis of three conditioned media derived fractions corresponding to a 10 000g cellular debris pellet, a 100 000g crude exosome pellet, and an Optiprep enriched exosome pellet. The quantitative analysis identified 2 179 proteins in all three fractions, with known exosomal cargo proteins displaying at least a 2-fold enrichment in the exosome fraction based on the TMT protein ratios. Employing SVM cluster analysis allowed for the classification 251 proteins as "true" exosomal cargo proteins. This study provides a robust and vigorous framework for the future development of using exosomes as a potential multiprotein marker phenotyping tool that could be useful in breast cancer diagnosis and monitoring disease progression.

Proteomics in evolutionary ecology

Evolutionary ecologists are traditionally gene-focused, as genes propagate phenotypic traits across generations and mutations and recombination in the DNA generate genetic diversity required for evolutionary processes. As a consequence, the inheritance of changed DNA provides a molecular explanation for the functional changes associated with natural selection. A direct focus on proteins on the other hand, the actual molecular agents responsible for the expression of a phenotypic trait, receives far less interest from ecologists and evolutionary biologists. This is partially due to the central dogma of molecular biology that appears to define proteins as the 'dead-end of molecular information flow' as well as technical limitations in identifying and studying proteins and their diversity in the field and in many of the more exotic genera often favored in ecological studies. Here we provide an overview of a newly forming field of research that we refer to as 'Evolutionary Proteomics'. We point out that the origins of cellular function are related to the properties of polypeptide and RNA and their interactions with the environment, rather than DNA descent, and that the critical role of horizontal gene transfer in evolution is more about coopting new proteins to impact cellular processes than it is about modifying gene function. Furthermore, post-transcriptional and post-translational processes generate a remarkable diversity of mature proteins from a single gene, and the properties of these mature proteins can also influence inheritance through genetic and perhaps epigenetic mechanisms. The influence of post-transcriptional diversification on evolutionary processes could provide a novel mechanistic underpinning for elements of rapid, directed evolutionary changes and adaptations as observed for a variety of evolutionary processes. Modern state-of the art technologies based on mass spectrometry are now available to identify and quantify peptides, proteins, protein modifications and protein interactions of interest with high accuracy and assess protein diversity and function. Therefore, proteomic technologies can be viewed as providing evolutionary biologist with exciting novel opportunities to understand very early events in functional variation of cellular molecular machinery that are acting as part of evolutionary processes.

Mycobacterial proteomics: analysis of expressed proteomes and post-translational modifications to identify candidate virulence factors

The Mycobacterium tuberculosis bacillus has a number of unique features that make it a particularly effective human pathogen. Although genomic analysis has added to our current understanding of the molecular basis by which M. tuberculosis damages its host, proteomics may be better suited to describe the dynamic interactions between mycobacterial and host systems that underpin this disease. The M. tuberculosis proteome has been investigated using proteomics for over a decade, with increasingly sophisticated mass spectrometry technology and sensitive methods for comparative proteomic profiling. Deeper coverage of the M. tuberculosis proteome has led to the identification of hundreds of putative virulence determinants, as well as an unsurpassed coverage of post-translational modifications. Proteomics is therefore uniquely poised to contribute to our understanding of this pathogen, which may ultimately lead to better management of the disease.

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.

High-throughput screening of cellular redox sensors using modern redox proteomics approaches

Cancer cells are characterized by higher levels of intracellular reactive oxygen species (ROS) due to metabolic aberrations. ROS are widely accepted as second messengers triggering pivotal signaling pathways involved in the process of cell metabolism, cell cycle, apoptosis, and autophagy. However, the underlying cellular mechanisms remain largely unknown. Recently, accumulating evidence has demonstrated that ROS initiate redox signaling through direct oxidative modification of the cysteines of key redox-sensitive proteins (termed redox sensors). Uncovering the functional changes underlying redox regulation of redox sensors is urgently required, and the role of different redox sensors in distinct disease states still remains to be identified. To assist this, redox proteomics has been developed for the high-throughput screening of redox sensors, which will benefit the development of novel therapeutic strategies for cancer treatment. Highlighted here are recent advances in redox proteomics approaches and their applications in identifying redox sensors involved in tumor development.

Study of quantitative changes of cereal allergenic proteins after food processing

BACKGROUND

Within last few years, the occurrence of food allergens and corresponding food allergies has been increasing, therefore research into the individual allergens is required. In the present work, the effect of cereal processing on the amounts of allergenic proteins is studied by modern proteomic-based approaches. The most important wheat and barley allergens are low-molecular-weight (LMW) proteins. Therefore we investigated the relative quantitative changes of these proteins after food technological processing, namely wheat couscous production and barley malting.

RESULTS

A comparative study using mass spectrometry in connection with the technique of isobaric tag for relative and absolute quantification (iTRAQ) revealed that the amount of wheat allergenic LMW proteins decreased significantly during couscous production (approximately to 5-26% of their initial content in wheat flour). After barley malting, the amounts of the majority of LMW proteins decreased as well, although to a lesser extent than in the case of wheat/couscous. The level of two allergens even slightly increased.

CONCLUSION

Suggested proteomic strategy proved as universal and sensitive method for fast and reliable identification of various cereal allergens and monitoring of their quantitative changes during food processing. Such information is important for consumers who suffer from allergies.

Determination of variation parameters as a crucial step in designing TMT-based clinical proteomics experiments

In quantitative shotgun proteomic analyses by liquid chromatography and mass spectrometry, a rigid study design is necessary in order to obtain statistically relevant results. Hypothesis testing, sample size calculation and power estimation are fundamental concepts that require consideration upon designing an experiment. For this reason, the reproducibility and variability of the proteomic platform needs to be assessed. In this study, we evaluate the technical (sample preparation), labeling (isobaric labels), and total (biological + technical + labeling + experimental) variability and reproducibility of a workflow that employs a shotgun LC-MS/MS approach in combination with TMT peptide labeling for the quantification of peripheral blood mononuclear cell (PBMC) proteome. We illustrate that the variability induced by TMT labeling is small when compared to the technical variation. The latter is also responsible for a substantial part of the total variation. Prior knowledge about the experimental variability allows for a correct design, a prerequisite for the detection of biologically significant disease-specific differential proteins in clinical proteomics experiments.

Understanding the rules of the road: proteomic approaches to interrogate the blood brain barrier

The blood brain barrier (BBB) is often regarded as a passive barrier that protects brain parenchyma from toxic substances, circulating leukocytes, while allowing the passage of selected molecules. Recently, a combination of molecular profiling techniques have characterized the constituents of the BBB based on in vitro models using isolated endothelial cells and ex vivo models analyzing isolated blood vessels. Characterization of gene expression profiles that are specific to the endothelium of brain blood vessels, and the identification of proteins, cells and multi-cellular structure that comprise the BBB have led to a emerging consensus that the BBB is not, in and of itself, a simple barrier of specialized endothelial cells. Instead, regulation of transcytosis, permeability, and drug translocation into the central nervous system is now viewed as a collection of neurovascular units (NVUs) that, together, give the BBB its unique biological properties. We will review recent technology advancing the understanding of the molecular basis of the BBB with a focus on proteomic approaches.

Comparative analysis of monoclonal antibody N-glycosylation using stable isotope labelling and UPLC-fluorescence-MS

A twoplex method using ¹²C₆ and ¹³C₆ stable isotope analogies of 2-aminobenzoic acid (2-AA) is described for LC-fluorescence-MS based quantitative and comparative analysis of N-glycans present on monoclonal antibodies.

Isobaric labeling-based relative quantification in shotgun proteomics

Mass spectrometry plays a key role in relative quantitative comparisons of proteins in order to understand their functional role in biological systems upon perturbation. In this review, we review studies that examine different aspects of isobaric labeling-based relative quantification for shotgun proteomic analysis. In particular, we focus on different types of isobaric reagents and their reaction chemistry (e.g., amine-, carbonyl-, and sulfhydryl-reactive). Various factors, such as ratio compression, reporter ion dynamic range, and others, cause an underestimation of changes in relative abundance of proteins across samples, undermining the ability of the isobaric labeling approach to be truly quantitative. These factors that affect quantification and the suggested combinations of experimental design and optimal data acquisition methods to increase the precision and accuracy of the measurements will be discussed. Finally, the extended application of isobaric labeling-based approach in hyperplexing strategy, targeted quantification, and phosphopeptide analysis are also examined.

Monitoring in vivo reversible cysteine oxidation in proteins using ICAT and mass spectrometry

Reversible thiol oxidation of cysteine residues occurs in many intracellular catalytic and signaling processes. Here we describe an optimized protocol, which can be completed in ∼5 d, to unambiguously identify specific cysteine residues that are transiently and reversibly oxidized by comparing two complex biological samples obtained from yeast cell cultures at the proteome level. After 'freezing' the in vivo thiol stage of cysteine residues by medium acidification, we first block reduced thiols in extracts with iodoacetamide (IAM), and then we sequentially reduce and label reversible oxidized thiols with the biotin-based heavy or light IAM derivatives, which are known as isotope-coded affinity tag (ICAT) reagents, so that the two samples can be compared at once after combination of the labeled extracts, trypsin digestion, streptavidin-affinity purification of peptides containing oxidized cysteines, and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. For the same protein extracts, before cysteine-containing peptide enrichment, individual relative protein concentrations are obtained by stable-isotope dimethyl labeling.

Organic acid quantitation by NeuCode methylamidation

We have developed a multiplexed quantitative analysis method for carboxylic acids by liquid chromatography high resolution mass spectrometry. The method employs neutron encoded (NeuCode) methylamine labels ((13)C or (15)N enriched) that are affixed to carboxylic acid functional groups to enable duplex quantitation via mass defect measurement. This work presents the first application of NeuCode quantitation to small molecules. We have applied this technique to detect adulteration of olive oil by quantitative analysis of fatty acid methyl amide derivatives, and the quantitative accuracy of the NeuCode analysis was validated by GC/MS. Currently, the method enables duplex quantitation and is expandable to at least 6-plex analysis.

Determining protein subcellular localization in mammalian cell culture with biochemical fractionation and iTRAQ 8-plex quantification

Protein subcellular localization is a fundamental feature of posttranslational functional regulation. Traditional microscopy based approaches to study protein localization are typically of limited throughput, and dependent on the availability of antibodies with high specificity and sensitivity, or fluorescent fusion proteins. In this chapter we describe how Localization of Organelle Proteins by Isotope Tagging (LOPIT), a mass spectrometry based workflow coupling biochemical fractionation and iTRAQ™ 8-plex quantification, can be applied for the high-throughput characterization of protein localization in a mammalian cell culture line.

High-throughput proteomics

Mass spectrometry (MS)-based high-throughput proteomics is the core technique for large-scale protein characterization. Due to the extreme complexity of proteomes, sophisticated separation techniques and advanced MS instrumentation have been developed to extend coverage and enhance dynamic range and sensitivity. In this review, we discuss the separation and prefractionation techniques applied for large-scale analysis in both bottom-up (i.e., peptide-level) and top-down (i.e., protein-level) proteomics. Different approaches for quantifying peptides or intact proteins, including label-free and stable-isotope-labeling strategies, are also discussed. In addition, we present a brief overview of different types of mass analyzers and fragmentation techniques as well as selected emerging techniques.

False-positive rate determination of protein target discovery using a covalent modification- and mass spectrometry-based proteomics platform

Detection and quantitation of protein-ligand binding interactions is important in many areas of biological research. Stability of proteins from rates of oxidation (SPROX) is an energetics-based technique for identifying the proteins targets of ligands in complex biological mixtures. Knowing the false-positive rate of protein target discovery in proteome-wide SPROX experiments is important for the correct interpretation of results. Reported here are the results of a control SPROX experiment in which chemical denaturation data is obtained on the proteins in two samples that originated from the same yeast lysate, as would be done in a typical SPROX experiment except that one sample would be spiked with the test ligand. False-positive rates of 1.2-2.2% and <0.8% are calculated for SPROX experiments using Q-TOF and Orbitrap mass spectrometer systems, respectively. Our results indicate that the false-positive rate is largely determined by random errors associated with the mass spectral analysis of the isobaric mass tag (e.g., iTRAQ®) reporter ions used for peptide quantitation. Our results also suggest that technical replicates can be used to effectively eliminate such false positives that result from this random error, as is demonstrated in a SPROX experiment to identify yeast protein targets of the drug, manassantin A. The impact of ion purity in the tandem mass spectral analyses and of background oxidation on the false-positive rate of protein target discovery using SPROX is also discussed.

Proteomics as a novel HIV immune monitoring tool

PURPOSE OF REVIEW

There is still a fundamental lack of understanding of what protected vaccinee's in the moderately successful RV144 Thailand trial. It is clear that better tools are needed to identify and study correlates of protection and immune responses to vaccine challenge. Quantitative mass spectrometry (MS) has evolved considerably to become a useful tool in biomarker discovery; however, until recently it has been scarcely used to define host responses to HIV exposure and/or viral infection. In this review we discuss current quantitative MS techniques, their application in current HIV studies as well as novel approaches that could be used to better examine innate or adaptive immune responses in HIV vaccine or microbicide trials.

RECENT FINDINGS

Several recently published studies have allowed researchers to utilize quantitative MS as part of a systems biology approach to better understand the HIV-affected host's interaction with HIV and/or vaccine challenge. Proteomics has shown it can play a major role in studies to demonstrate insight into HIV replication, early stages of pathogenesis, and identify potential correlates of mucosal protection.

SUMMARY

Novel advances in quantitative proteomic techniques are allowing the opportunity to profile and evaluate HIV specific innate and adaptive immune responses, and will increase our understanding of HIV pathogenesis.