A human proteome detection and quantitation project

Blood Plasma Proteome: A Meta-Analysis of the Results of Protein Quantification in Human Blood by Targeted Mass Spectrometry

A meta-analysis of the results of targeted quantitative screening of human blood plasma was performed to generate a reference standard kit that can be used for health analytics. The panel included 53 of the 296 proteins that form a “stable” part of the proteome of a healthy individual; these proteins were found in at least 70% of samples and were characterized by an interindividual coefficient of variation <40%. The concentration range of the selected proteins was 10−10−10−3 M and enrichment analysis revealed their association with rare familial diseases. The concentration of ceruloplasmin was reduced by approximately three orders of magnitude in patients with neurological disorders compared to healthy volunteers, and those of gelsolin isoform 1 and complement factor H were abruptly reduced in patients with lung adenocarcinoma. Absolute quantitative data of the individual proteome of a healthy and diseased individual can be used as the basis for personalized medicine and health monitoring. Storage over time allows us to identify individual biomarkers in the molecular landscape and prevent pathological conditions.

Proteomic discovery of non-invasive biomarkers of localized prostate cancer using mass spectrometry

Prostate cancer is the second most frequently diagnosed non-skin cancer in men worldwide. Patient outcomes are remarkably heterogeneous and the best existing clinical prognostic tools such as International Society of Urological Pathology Grade Group, pretreatment serum PSA concentration and T-category, do not accurately predict disease outcome for individual patients. Thus, patients newly diagnosed with prostate cancer are often overtreated or undertreated, reducing quality of life and increasing disease-specific mortality. Biomarkers that can improve the risk stratification of these patients are, therefore, urgently needed. The ideal biomarker in this setting will be non-invasive and affordable, enabling longitudinal evaluation of disease status. Prostatic secretions, urine and blood can be sources of biomarker discovery, validation and clinical implementation, and mass spectrometry can be used to detect and quantify proteins in these fluids. Protein biomarkers currently in use for diagnosis, prognosis and relapse-monitoring of localized prostate cancer in fluids remain centred around PSA and its variants, and opportunities exist for clinically validating novel and complimentary candidate protein biomarkers and deploying them into the clinic.

Hepatotoxic evaluation of toosendanin via biomarker quantification and pathway mapping of large-scale chemical proteomics

Drug-induced liver injury (DILI) is a major side effect, sometimes can't be exactly evaluated by current approaches partly as the covalent modification of drug or its reactive metabolites (RMs) with proteins is a possible reason. In this study, we developed a rapid, sensitive, and specific analytical method to assess the hepatotoxicity induced by drug covalently modified proteins based on the quantification of the modified amino acids using toosendanin (TSN), a hepatotoxic chemical, as an example. TSN RM-protein adducts both in rat liver and blood showed good correlation with the severity of hepatotoxicity. Thus, TSN RM-protein adducts in serum can potentially serve as minimally invasive biomarkers of hepatotoxicity. Meanwhile, large-scale chemical proteomics analysis showed that at least 84 proteins were modified by TSN RMs in rat liver, and the bioinformatics analysis revealed that TSN might induce hepatotoxicity through multi-target protein-protein interaction especially involved in energy metabolism. These findings suggest that our approach may serve as a valuable tool to evaluate DILI and investigate the possible mechanism, especially for complex compounds.

iTRAQ-based proteome profiling revealed the role of Phytochrome A in regulating primary metabolism in tomato seedling

In plants, during growth and development, photoreceptors monitor fluctuations in their environment and adjust their metabolism as a strategy of surveillance. Phytochromes (Phys) play an essential role in plant growth and development, from germination to fruit development. FR-light (FR) insensitive mutant (fri) carries a recessive mutation in Phytochrome A and is characterized by the failure to de-etiolate in continuous FR. Here we used iTRAQ-based quantitative proteomics along with metabolomics to unravel the role of Phytochrome A in regulating central metabolism in tomato seedlings grown under FR. Our results indicate that Phytochrome A has a predominant role in FR-mediated establishment of the mature seedling proteome. Further, we observed temporal regulation in the expression of several of the late response proteins associated with central metabolism. The proteomics investigations identified a decreased abundance of enzymes involved in photosynthesis and carbon fixation in the mutant. Profound accumulation of storage proteins in the mutant ascertained the possible conversion of sugars into storage material instead of being used or the retention of an earlier profile associated with the mature embryo. The enhanced accumulation of organic sugars in the seedlings indicates the absence of photomorphogenesis in the mutant.

Immunoaffinity-Based Liquid Chromatography Mass Spectrometric Assay to Accurately Quantify the Protein Concentration of HMGB1 in EDTA Plasma

Targeted protein quantification can be challenging in body fluids such as plasma with regard to sensitivity and selectivity. In this chapter, we present a protocol for the quantification of high mobility group box 1 protein (HMGB1) in plasma using an immunoaffinity liquid chromatography mass spectrometric assay (IA-LC-MSMS). The protocol provides detailed assay instructions involving sample proteolysis, peptide-targeted immunoprecipitation, and LC-MSMS-based read out.

Exploiting arginine distributions for the selective and efficient depletion of arginine-rich plasma proteins

The number and arrangement of arginine (Arg) residues in protein chains contribute greatly to the selective capturing of proteins on a designed adsorbent consisting of organic phosphate functionalized fibrous SiO2 microspheres, and the efficient depletion of high abundance Arg-rich protein species from human plasma is achieved.

Induction and repression effects on CYP and transporter protein abundance by azole mixture uptake in rat liver

Detection of mixture effects is a major challenge in current experimental and regulatory toxicology. Robust markers are needed that are easy to quantify and responsive to chemical stressors in a broad dose range. Several hepatic enzymes and proteins related to drug metabolism like cytochrome-P-450 (CYP) enzymes and transporters have been shown to be responsive to pesticide active substances in a broad dose range and are therefore good candidates to be used as markers for mixture toxicity. Even though they can be well quantified at the mRNA level, quantification on the protein level is challenging because most of these proteins are membrane bound. Here we report the development of mass spectrometry-based assays using triple-x-proteomics (TXP) antibodies in combination with targeted selected ion monitoring (tSIM) to quantify changes of protein levels due to exposure to mixtures of pesticide active substances. Our results indicate that changes on the protein level of CYP1A1, ABCB2, ABCC3 are in line with observations on the mRNA and enzyme activity level and are indicative of mixture effects. Therefore, the tests are promising to reveal effects by chemical mixture effects in toxicological studies in rats.

ITRAQ-based proteomic analysis reveals possible target-related proteins in human adrenocortical adenomas

Background

Adrenocortical adenomas (ACAs) can lead to the autonomous secretion of aldosterone responsible for primary aldosteronism (PA), which is the most common form of secondary arterial hypertension. However, the authentic fundamental mechanisms underlying ACAs remain unclear.

Objective

Isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomics and bioinformatics analyses from etiological studies of ACAs were performed to screen the differentially expressed proteins (DEPs) and investigate the relevant mechanisms of their occurrence and development. Results could help determine therapeutic targets of clinical significance.

Methods

In the present study, iTRAQ-based proteomics was applied to analyze ACA tissue samples from normal adrenal cortex tissues adjacent to the tumor. Using proteins extracted from a panel of four pairs of ACA samples, we identified some upregulated proteins and other downregulated proteins in all four pairs of ACA samples compared with adjacent normal tissue. Subsequently, we predicted protein–protein interaction networks of three DEPs to determine the authentic functional factors in ACA.

Results

A total of 753 DEPs were identified, including 347 upregulated and 406 downregulated proteins. The expression of three upregulated proteins (E2F3, KRT6A, and ALDH1A2) was validated by Western blot in 24 ACA samples. Our data suggested that some DEPs might be important hallmarks during the development of ACA.

Conclusions

This study is the first proteomic research to investigate alterations in protein levels and affected pathways in ACA using the iTRAQ technique. Thus, this study not only provides a comprehensive dataset on overall protein changes but also sheds light on its potential molecular mechanism in human ACAs.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-6030-5) contains supplementary material, which is available to authorized users.

LC‑MS/MS proteomic analysis revealed novel associations of 37 proteins with T2DM and notable upregulation of immunoglobulins

Type 2 diabetes mellitus (T2DM) is a disease associated with a number of metabolic disturbances, including protein metabolism. In the present study, blood samples were obtained from Bahraini subjects, including 6 patients with T2DM and 6 age‑ and sex‑matched, non‑diabetic, healthy controls. Depleted and non‑depleted sera were prepared from the collected blood, and the global protein expression changes were evaluated by liquid chromatography tandem mass spectrometry. Only significantly and markedly differentially‑expressed proteins (P<0.05, analysis of variance; maximum fold change ≥1.5) were considered as candidate proteins for informatics analysis. Accordingly, a total of 62 proteins were identified to be differentially expressed in T2DM, compared with control subjects, and they were grouped functionally into 16 classes of proteins. The largest class was that of the immune‑associated proteins. Additionally, ~25 of these proteins (40%) had previously been associated with DM; however, the association of the other 37 proteins with T2DM was a novel observation. The majority of the identified proteins were upregulated in T2DM. The identified proteins could be involved in the pathogenesis of the disease or serve as disease biomarkers. Further validation of the identified proteins in a large study cohort is required, in order to fully access their potential clinical usefulness.

Pyridine boronic acid-polyoxometalate based porous hybrid for efficient depletion of high abundant glycoproteins in plasma

A porous hybrid, namely PW₁₂@TiO₂-Si(Et)Si/Pba, is fabricated by the modification of PW₁₂@TiO₂-Si(Et)Si with pyridine boronic acid via a solvothermal method. The covalent interactions between the boronic acid group of the hybrid and the glycosylated site of proteins provide the as-prepared hybrid with favorable adsorption performance towards glycoproteins. The adsorption behaviors of glycoproteins onto the hybrid fit well with the Langmuir model, and the adsorption capacities for glycoprotein IgG and Trf are high, up to 348.5 mg g^-1 and 262.6 mg g^-1, respectively. Thus, a protocol for the depletion of high abundant glycoproteins from human plasma is proposed. The percentage contents of Trf, IgG, haptoglobinis and IgM are reduced from 7.38%, 5.5%, 3.01% and 1.02% to 0.951%, 4.7%, 0.126% and 0.76%, respectively. 85 low abundant proteins are identified from the raw plasma after the depletion of the high abundance proteins, demonstrating the potential of PW₁₂@TiO₂-Si(Et)Si/Pba hybrid in proteomic studies.

Algorithms and design strategies towards automated glycoproteomics analysis

Glycoproteomics involves the study of glycosylation events on protein sequences ranging from purified proteins to whole proteome scales. Understanding these complex post-translational modification (PTM) events requires elucidation of the glycan moieties (monosaccharide sequences and glycosidic linkages between residues), protein sequences, as well as site-specific attachment of glycan moieties onto protein sequences, in a spatial and temporal manner in a variety of biological contexts. Compared with proteomics, bioinformatics for glycoproteomics is immature and many researchers still rely on tedious manual interpretation of glycoproteomics data. As sample preparation protocols and analysis techniques have matured, the number of publications on glycoproteomics and bioinformatics has increased substantially; however, the lack of consensus on tool development and code reuse limits the dissemination of bioinformatics tools because it requires significant effort to migrate a computational tool tailored for one method design to alternative methods. This review discusses algorithms and methods in glycoproteomics, and refers to the general proteomics field for potential solutions. It also introduces general strategies for tool integration and pipeline construction in order to better serve the glycoproteomics community. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:475-498, 2017.

Uncovering stem cell differentiation factors for salivary gland regeneration by quantitative analysis of differential proteomes

Severe xerostomia (dry mouth) compromises the quality of life in patients with Sjögren's syndrome or radiation therapy for head and neck cancer. A clinical management of xerostomia is often unsatisfactory as most interventions are palliative with limited efficacy. Following up our previous study demonstrating that mouse BM-MSCs are capable of differentiating into salivary epithelial cells in a co-culture system, we further explored the molecular basis that governs the MSC reprogramming by utilizing high-throughput iTRAQ-2D-LC-MS/MS-based proteomics. Our data revealed the novel induction of pancreas-specific transcription factor 1a (PTF1α), muscle, intestine and stomach expression-1 (MIST-1), and achaete-scute complex homolog 3 (ASCL3) in 7 day co-cultured MSCs but not in control MSCs. More importantly, a common notion of pancreatic-specific expression of PTF1 α was challenged for the first time by our verification of PTF1 α expression in the mouse salivary glands. Furthermore, a molecular network simulation of our selected putative MSC reprogramming factors demonstrated evidence for their perspective roles in salivary gland development. In conclusion, quantitative proteomics with extensive data analyses narrowed down a set of MSC reprograming factors potentially contributing to salivary gland regeneration. Identification of their differential/synergistic impact on MSC conversion warrants further investigation.

Quantitative Proteomics Based on Optimized Data-Independent Acquisition in Plasma Analysis

The advent of high-resolution and frequency mass spectrometry has ushered in an era of data-independent acquisition (DIA). This approach affords enormous multiplexing capacity and is particularly suitable for clinical biomarker studies. However, DIA-based quantification of clinical plasma samples is a daunting task due to the high complexity of clinical plasma samples, the diversity of peptides within the samples, and the high biologic dynamic range of plasma proteins. Here we applied DIA methodology, including a highly reproducible sample preparation and LC-MS/MS analysis, and assessed its utility for clinical plasma biomarker detection. A pancreatic cancer-relevant plasma spectral library was constructed consisting of over 14 000 confidently identified peptides derived from over 2300 plasma proteins. Using a nonhuman protein as the internal standard, various empirical parameters were explored to maximize the reliability and reproducibility of the DIA quantification. The DIA parameters were optimized based on the quantification cycle times and fragmentation profile complexity. Higher analytical and biological reproducibility was recorded for the tryptic peptides without labile residues and missed cleavages. Quantification reliability was developed for the peptides identified within a consistent retention time and signal intensity. Linear analytical dynamic range and the lower limit of quantification were assessed, suggesting the critical role of sample complexity in optimizing DIA settings. Technical validation of the assay using a cohort of clinical plasma indicated the robustness and unique advantage for targeted analysis of clinical plasma samples in the context of biomarker development.

A large-scale targeted proteomics assay resource based on an in vitro human proteome

Targeted proteomics approaches are of value for deep and accurate quantification of protein abundance. Extending such methods to quantify large numbers of proteins requires the construction of predefined targeted assays. We developed a targeted proteomics platform-in vitro proteome-assisted multiple reaction monitoring (MRM) for protein absolute quantification (iMPAQT)-by using >18,000 human recombinant proteins, thus enabling protein absolute quantification on a genome-wide scale. Our platform comprises experimentally confirmed MRM assays of mass tag (mTRAQ)-labeled peptides to allow for rapid and straightforward measurement of the absolute abundance of predefined sets of proteins by mass spectrometry. We applied iMPAQT to delineate the quantitative metabolic landscape of normal and transformed human fibroblasts. Oncogenic transformation gave rise to relatively small but global changes in metabolic pathways resulting in aerobic glycolysis (Warburg effect) and increased rates of macromolecule synthesis. iMPAQT should facilitate quantitative biology studies based on protein abundance measurements.

High-Throughput Discovery of Aptamers for Sandwich Assays

Sandwich assays are among the most powerful tools in molecular detection. These assays use "pairs" of affinity reagents so that the detection signal is generated only when both reagents bind simultaneously to different sites on the target molecule, enabling highly sensitive and specific measurements in complex samples. Thus, the capability to efficiently screen affinity reagent pairs at a high throughput is critical. In this work, we describe an experimental strategy for screening "aptamer pairs" at a throughput of 10⁶ aptamer pairs per hour-which is many orders of magnitude higher than the current state of the art. The key step in our process is the conversion of solution-phase aptamers into "aptamer particles" such that we can directly measure the simultaneous binding of multiple aptamers to a target protein based on fluorescence signals and sort individual particles harboring aptamer pairs via the fluorescence-activated cell-sorter instrument. As proof of principle, we successfully isolated a high-quality DNA aptamer pair for plasminogen activator inhibitor 1 (PAI-1). Within only two rounds of screening, we discovered DNA aptamer pairs with low-nanomolar sensitivity in dilute serum and excellent specificity with minimal off-target binding even to closely related proteins such as PAI-2.

Highlights of the Biology and Disease-driven Human Proteome Project, 2015-2016

The Biology and Disease-driven Human Proteome Project (B/D-HPP) is aimed at supporting and enhancing the broad use of state-of-the-art proteomic methods to characterize and quantify proteins for in-depth understanding of the molecular mechanisms of biological processes and human disease. Based on a foundation of the pre-existing HUPO initiatives begun in 2002, the B/D-HPP is designed to provide standardized methods and resources for mass spectrometry and specific protein affinity reagents and facilitate accessibility of these resources to the broader life sciences research and clinical communities. Currently there are 22 B/D-HPP initiatives and 3 closely related HPP resource pillars. The B/D-HPP groups are working to define sets of protein targets that are highly relevant to each particular field to deliver relevant assays for the measurement of these selected targets and to disseminate and make publicly accessible the information and tools generated. Major developments are the 2016 publications of the Human SRM Atlas and of "popular protein sets" for six organ systems. Here we present the current activities and plans of the BD-HPP initiatives as highlighted in numerous B/D-HPP workshops at the 14th annual HUPO 2015 World Congress of Proteomics in Vancouver, Canada.

Quantification of Human Kallikrein-Related Peptidases in Biological Fluids by Multiplatform Targeted Mass Spectrometry Assays

Human kallikrein-related peptidases (KLKs) are a group of 15 secreted serine proteases encoded by the largest contiguous cluster of protease genes in the human genome. KLKs are involved in coordination of numerous physiological functions including regulation of blood pressure, neuronal plasticity, skin desquamation, and semen liquefaction, and thus represent promising diagnostic and therapeutic targets. Until now, quantification of KLKs in biological and clinical samples was accomplished by enzyme-linked immunosorbent assays (ELISA). Here, we developed multiplex targeted mass spectrometry assays for the simultaneous quantification of all 15 KLKs. Proteotypic peptides for each KLK were carefully selected based on experimental data and multiplexed in single assays. Performance of assays was evaluated using three different mass spectrometry platforms including triple quadrupole, quadrupole-ion trap, and quadrupole-orbitrap instruments. Heavy isotope-labeled synthetic peptides with a quantifying tag were used for absolute quantification of KLKs in sweat, cervico-vaginal fluid, seminal plasma, and blood serum, with limits of detection ranging from 5 to 500 ng/ml. Analytical performance of assays was evaluated by measuring endogenous KLKs in relevant biological fluids, and results were compared with selected ELISAs. The multiplex targeted proteomic assays were demonstrated to be accurate, reproducible, sensitive, and specific alternatives to antibody-based assays. Finally, KLK4, a highly prostate-specific protein and a speculated biomarker of prostate cancer, was unambiguously detected and quantified by immunoenrichment-SRM assay in seminal plasma and blood serum samples from individuals with confirmed prostate cancer and negative biopsy. Mass spectrometry revealed exclusively the presence of a secreted isoform and thus unequivocally resolved earlier disputes about KLK4 identity in seminal plasma. Measurements of KLK4 in either 41 seminal plasma or 58 blood serum samples revealed no statistically significant differences between patients with confirmed prostate cancer and negative biopsy. The presented multiplex targeted proteomic assays are an alternative analytical tool to study the biological and pathological roles of human KLKs.

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.

The Size of the Human Proteome: The Width and Depth

This work discusses bioinformatics and experimental approaches to explore the human proteome, a constellation of proteins expressed in different tissues and organs. As the human proteome is not a static entity, it seems necessary to estimate the number of different protein species (proteoforms) and measure the number of copies of the same protein in a specific tissue. Here, meta-analysis of neXtProt knowledge base is proposed for theoretical prediction of the number of different proteoforms that arise from alternative splicing (AS), single amino acid polymorphisms (SAPs), and posttranslational modifications (PTMs). Three possible cases are considered: (1) PTMs and SAPs appear exclusively in the canonical sequences of proteins, but not in splice variants; (2) PTMs and SAPs can occur in both proteins encoded by canonical sequences and in splice variants; (3) all modification types (AS, SAP, and PTM) occur as independent events. Experimental validation of proteoforms is limited by the analytical sensitivity of proteomic technology. A bell-shaped distribution histogram was generated for proteins encoded by a single chromosome, with the estimation of copy numbers in plasma, liver, and HepG2 cell line. The proposed metabioinformatics approaches can be used for estimation of the number of different proteoforms for any group of protein-coding genes.

Impact of Whole-Blood Processing Conditions on Plasma and Serum Concentrations of Cytokines

Pre-analytical variations in plasma and serum samples can occur because of variability in whole-blood processing procedures. The aim of this study was to determine the impact of delayed separation of whole blood on the plasma and serum concentrations of cytokines. The concentrations of 16 cytokines were measured in plasma and serum samples when the centrifugation of whole blood at room temperature was delayed for 4, 6, 24, or 48 h, and the values were compared with those observed after separation within 2 h of whole-blood collection. Receiver operating characteristic (ROC) curve analysis was also performed for cytokines to determine whether cytokine levels in plasma and serum samples can be used to assess delayed separation of whole blood. Plasma concentrations of interleukin (IL)-1β, granulocyte-macrophage colony-stimulating factor (GM-CSF), and soluble CD40 ligand (sCD40L) and serum concentrations of IL-1β, IL-6, IL-8, macrophage inflammatory protein-1α (MIP-1α), and MIP-1β increased significantly (>2-fold) when separation was delayed at room temperature for 24 h. The concentrations of 6 of these cytokines (all except serum IL-1β and IL-6) demonstrated high diagnostic performance (area under the ROC curve >0.8) for delayed separation of whole blood. Furthermore, these cytokine concentrations typically exhibited high sensitivity and specificity at each optimal cutoff point. Conversely, IL-17A was stable in both plasma and serum samples, even when whole-blood centrifugation was delayed at room temperature for 48 h. This study shows that certain cytokines (IL-1β, GM-CSF, sCD40L, IL-8, MIP-1α, and MIP-1β) could be used for assessing the quality of plasma or serum samples.

Computational Methods in Mass Spectrometry-Based Proteomics

This chapter introduces computational methods used in mass spectrometry-based proteomics, including those for addressing the critical problems such as peptide identification and protein inference, peptide and protein quantification, characterization of posttranslational modifications (PTMs), and data-independent acquisitions (DIA). The chapter concludes with emerging applications of proteomic techniques, such as metaproteomics, glycoproteomics, and proteogenomics.

Inorganic Phosphorus and Potassium Are Putative Indicators of Delayed Separation of Whole Blood

OBJECTIVES

The delayed separation of whole blood can influence the concentrations of circulating blood components, including metabolites and cytokines. The aim of this study was to determine whether clinical-biochemistry analytes can be used to assess the delayed separation of whole blood.

METHODS

We investigated the plasma and serum concentrations of five clinical-biochemistry analytes and free hemoglobin when the centrifugation of whole blood stored at 4°C or room temperature was delayed for 4 hours, 6 hours, 24 hours, or 48 hours, and compared the values with those of matched samples that had been centrifuged within 2 hours after whole-blood collection.

RESULTS

The inorganic phosphorus (IP) levels in the plasma and serum samples were elevated ≥ 1.5-fold when whole-blood centrifugation was delayed at room temperature for 48 hours. Furthermore, the IP levels in the plasma samples showed excellent assessment accuracy [area under the receiver-operating-characteristic curve (AUC) > 0.9] after a 48-hour delay in whole-blood separation, and high sensitivity (100%) and specificity (95%) at an optimal cutoff point. The IP levels in the serum samples also exhibited good assessment accuracy (AUC > 0.8), and high sensitivity (81%) and specificity (100%). The potassium (K(+)) levels were elevated 1.4-fold in the serum samples following a 48-hour delay in whole-blood separation. The K(+) levels showed excellent assessment accuracy (AUC > 0.9) following a 48-hour delay in whole-blood separation, and high sensitivity (95%) and specificity (91%) at an optimal cutoff point.

CONCLUSION

Our study showed that the IP and K(+) levels in the plasma or serum samples could be considered as putative indicators to determine whether whole-blood separation had been delayed for extended periods.

Complementary PTM Profiling of Drug Response in Human Gastric Carcinoma by Immunoaffinity and IMAC Methods with Total Proteome Analysis

Gaining insight into normal cellular signaling and disease biology is a critical goal of proteomic analyses. The ability to perform these studies successfully to extract the maximum value and discovery of biologically relevant candidate biomarkers is therefore of primary importance. Many successful studies in the past have focused on total proteome analysis (changes at the protein level) combined with phosphorylation analysis by metal affinity enrichment (changes at the PTM level). Here, we use the gastric carcinoma cell line MKN-45 treated with the c-Met inhibitor SU11274 and PKC inhibitor staurosporine to investigate the most efficient and most comprehensive strategies for both total protein and PTM analysis. Under the conditions used, total protein analysis yielded few changes in response to either compound, while analysis of phosphorylation identified thousands of sites that changed differentially between the two treatments. Both metal affinity and antibody-based enrichments were used to assess phosphopeptide changes, and the data generated by the two methods was largely complementary (non-overlapping). Label-free quantitation of peptide peak abundances was used to accurately determine fold-changes between control and treated samples. Protein interaction network analysis allowed the data to be placed in a biologically relevant context, and follow-up validation of selected findings confirmed the accuracy of the proteomic data. Together, this study provides a framework for start-to-finish proteomic analysis of any experimental system under investigation to maximize the value of the proteomic study and yield the best chance for uncovering actionable target candidates.

A Cluster of Proteins Implicated in Kidney Disease Is Increased in High-Density Lipoprotein Isolated from Hemodialysis Subjects

Cardiovascular disease is the leading cause of death in end-stage renal disease (ESRD) patients treated with hemodialysis. An important contributor might be a decline in the cardioprotective effects of high-density lipoprotein (HDL). One important factor affecting HDL's cardioprotective properties may involve the alterations of protein composition in HDL. In the current study, we used complementary proteomics approaches to detect and quantify relative levels of proteins in HDL isolated from control and ESRD subjects. Shotgun proteomics analysis of HDL isolated from 20 control and 40 ESRD subjects identified 63 proteins in HDL. Targeted quantitative proteomics by isotope-dilution selective reaction monitoring revealed that 22 proteins were significantly enriched and 6 proteins were significantly decreased in ESRD patients. Strikingly, six proteins implicated in renal disease, including B2M, CST3, and PTGDS, were markedly increased in HDL of uremic subjects. Moreover, several of these proteins (SAA1, apoC-III, PON1, etc.) have been associated with atherosclerosis. Our observations indicate that the HDL proteome is extensively remodeled in uremic subjects. Alterations of the protein cargo of HDL might impact HDL's proposed cardioprotective properties. Quantifying proteins in HDL may be useful in the assessment of cardiovascular risk in patients with ESRD and in assessing response to therapeutic interventions.

Stable isotope labelling methods in mass spectrometry-based quantitative proteomics

Mass-spectrometry based proteomics has evolved as a promising technology over the last decade and is undergoing a dramatic development in a number of different areas, such as; mass spectrometric instrumentation, peptide identification algorithms and bioinformatic computational data analysis. The improved methodology allows quantitative measurement of relative or absolute protein amounts, which is essential for gaining insights into their functions and dynamics in biological systems. Several different strategies involving stable isotopes label (ICAT, ICPL, IDBEST, iTRAQ, TMT, IPTL, SILAC), label-free statistical assessment approaches (MRM, SWATH) and absolute quantification methods (AQUA) are possible, each having specific strengths and weaknesses. Inductively coupled plasma mass spectrometry (ICP-MS), which is still widely recognised as elemental detector, has recently emerged as a complementary technique to the previous methods. The new application area for ICP-MS is targeting the fast growing field of proteomics related research, allowing absolute protein quantification using suitable elemental based tags. This document describes the different stable isotope labelling methods which incorporate metabolic labelling in live cells, ICP-MS based detection and post-harvest chemical label tagging for protein quantification, in addition to summarising their pros and cons.

Evaluating kinase ATP uptake and tyrosine phosphorylation using multiplexed quantification of chemically labeled and post-translationally modified peptides

Cancer biologists and other healthcare researchers face an increasing challenge in addressing the molecular complexity of disease. Biomarker measurement tools and techniques now contribute to both basic science and translational research. In particular, liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM) for multiplexed measurements of protein biomarkers has emerged as a versatile tool for systems biology. Assays can be developed for specific peptides that report on protein expression, mutation, or post-translational modification; discovery proteomics data rapidly translated into multiplexed quantitative approaches. Complementary advances in affinity purification enrich classes of enzymes or peptides representing post-translationally modified or chemically labeled substrates. Here, we illustrate the process for the relative quantification of hundreds of peptides in a single LC-MRM experiment. Desthiobiotinylated peptides produced by activity-based protein profiling (ABPP) using ATP probes and tyrosine-phosphorylated peptides are used as examples. These targeted quantification panels can be applied to further understand the biology of human disease.

Identification of clinical biomarkers for pre-analytical quality control of blood samples

BACKGROUND

Pre-analytical conditions are key factors in maintaining the high quality of biospecimens. They are necessary for accurate reproducibility of experiments in the field of biomarker discovery as well as achieving optimal specificity of laboratory tests for clinical diagnosis. In research at the National Biobank of Korea, we evaluated the impact of pre-analytical conditions on the stability of biobanked blood samples by measuring biochemical analytes commonly used in clinical laboratory tests.

METHODS

We measured 10 routine laboratory analytes in serum and plasma samples from healthy donors (n = 50) with a chemistry autoanalyzer (Hitachi 7600-110). The analyte measurements were made at different time courses based on delay of blood fractionation, freezing delay of fractionated serum and plasma samples, and at different cycles (0, 1, 3, 6, 9) of freeze-thawing. Statistically significant changes from the reference sample mean were determined using the repeated-measures ANOVA and the significant change limit (SCL).

RESULTS

The serum levels of GGT and LDH were changed significantly depending on both the time interval between blood collection and fractionation and the time interval between fractionation and freezing of serum and plasma samples. The glucose level was most sensitive only to the elapsed time between blood collection and centrifugation for blood fractionation. Based on these findings, a simple formula (glucose decrease by 1.387 mg/dL per hour) was derived to estimate the length of time delay after blood collection. In addition, AST, BUN, GGT, and LDH showed sensitive responses to repeated freeze-thaw cycles of serum and plasma samples.

CONCLUSION

These results suggest that GGT and LDH measurements can be used as quality control markers for certain pre-analytical conditions (eg, delayed processing or repeated freeze-thawing) of blood samples which are either directly used in the laboratory tests or stored for future research in the biobank.

Anti-peptide monoclonal antibodies generated for immuno-multiple reaction monitoring-mass spectrometry assays have a high probability of supporting Western blot and ELISA

Immunoaffinity enrichment of peptides coupled to targeted, multiple reaction monitoring-mass spectrometry (immuno-MRM) has recently been developed for quantitative analysis of peptide and protein expression. As part of this technology, antibodies are generated to short, linear, tryptic peptides that are well-suited for detection by mass spectrometry. Despite its favorable analytical performance, a major obstacle to widespread adoption of immuno-MRM is a lack of validated affinity reagents because commercial antibody suppliers are reluctant to commit resources to producing anti-peptide antibodies for immuno-MRM while the market is much larger for conventional technologies, especially Western blotting and ELISA. Part of this reluctance has been the concern that affinity reagents generated to short, linear, tryptic peptide sequences may not perform well in traditional assays that detect full-length proteins. In this study, we test the feasibility and success rates of generating immuno-MRM monoclonal antibodies (mAbs) (targeting tryptic peptide antigens) that are also compatible with conventional, protein-based immuno-affinity technologies. We generated 40 novel, peptide immuno-MRM assays and determined that the cross-over success rates for using immuno-MRM monoclonals for Western blotting is 58% and for ELISA is 43%, which compare favorably to cross-over success rates amongst conventional immunoassay technologies. These success rates could most likely be increased if conventional and immuno-MRM antigen design strategies were combined, and we suggest a workflow for such a comprehensive approach. Additionally, the 40 novel immuno-MRM assays underwent fit-for-purpose analytical validation, and all mAbs and assays have been made available as a resource to the community via the Clinical Proteomic Tumor Analysis Consortium's (CPTAC) Antibody (http://antibodies.cancer.gov) and Assay Portals (http://assays.cancer.gov), respectively. This study also represents the first determination of the success rate (92%) for generating mAbs for immuno-MRM using a recombinant B cell cloning approach, which is considerably faster than the traditional hybridoma approach.

AFFIRM--a multiplexed immunoaffinity platform that combines recombinant antibody fragments and LC-SRM analysis

Targeted measurements of low abundance proteins in complex mixtures are in high demand in many areas, not the least in clinical applications measuring biomarkers. We here present the novel platform AFFIRM (AFFInity sRM) that utilizes the power of antibody fragments (scFv) to efficiently enrich for target proteins from a complex background and the exquisite specificity of SRM-MS based detection. To demonstrate the ability of AFFIRM, three target proteins of interest were measured in a serum background in single-plexed and multiplexed experiments in a concentration range of 5-1000 ng/mL. Linear responses were demonstrated down to low ng/mL concentrations with high reproducibility. The platform allows for high throughput measurements in 96-well format, and all steps are amendable to automation and scale-up. We believe the use of recombinant antibody technology in combination with SRM MS analysis provides a powerful way to reach sensitivity, specificity, and reproducibility as well as the opportunity to build resources for fast on-demand implementation of novel assays.

Advances in Proteomic Technologies and Its Contribution to the Field of Cancer

Systematic studies of the cancer genome have generated a wealth of knowledge in recent years. These studies have uncovered a number of new cancer genes not previously known to be causal targets in cancer. Genetic markers can be used to determine predisposition to tumor development, but molecularly targeted treatment strategies are not widely available for most cancers. Precision care plans still must be developed by understanding and implementing basic science research into clinical treatment. Proteomics is continuing to make major strides in the discovery of fundamental biological processes as well as more recent transition into an assay platform capable of measuring hundreds of proteins in any biological system. As such, proteomics can translate basic science discoveries into the clinical practice of precision medicine. The proteomic field has progressed at a fast rate over the past five years in technology, breadth and depth of applications in all areas of the bioscience. Some of the previously experimental technical approaches are considered the gold standard today, and the community is now trying to come to terms with the volume and complexity of the data generated. Here I describe contribution of proteomics in general and biological mass spectrometry in particular to cancer research, as well as related major technical and conceptual developments in the field.

Separation methodology to improve proteome coverage depth

So-called 'in-depth proteomics' and its applied separation methodology to improve the proteome coverage depth has become an important issue in mass spectrometric-based proteomics and system-wide cell biology studies. Employing a bottom-up approach and a variety of separation techniques, it allows for identification of proteins with low copy numbers and enables researchers to correlate the number of expressed genes in a cell with the proteome. Here we describe recent advances in this field with emphasis on peptide and protein separation technologies. The discussion is focused both on single injection analyses employing long reversed phase liquid chromatography separations of peptides ('single shot proteomics') and on the combination of orthogonal protein and peptide separation methods to achieve maximum protein coverage. Owing to these improvements, in-depth proteomics has now fully entered the field and is being implemented in an increasing number of laboratories.

Rapidly maturing field of proteomics: a gateway to studying diseases

The proteomics work reported by Smith et al. represents a giant step forward in characterizing the cerebrospinal fluid (CSF) proteome in mouse models of human diseases. Whereas prior studies were limited to analysis of CSF pools, Smith et al. (Proteomics 2014, 14, 1102-1106) base their conclusions on data derived from individual mice, thereby capturing a fuller range of the biological diversity present. These results underscore how far proteomics has come in the past few years, developing into a modern tool with the capacity to remove bottlenecks in the study of neuropsychiatric diseases. Past efforts with mass spectrometry (MS) have been hampered by limitations in access to CSF samples, and small volumes when available. These barriers have been overcome with newer MS platforms and advances in sample preparation. We are far closer than before to producing the production of clinically useful proteomic data for biomarker discovery and for deriving insights into pathogenesis that can lead to more effective treatments for many diseases.

Automated sample preparation platform for mass spectrometry-based plasma proteomics and biomarker discovery

The identification of novel biomarkers from human plasma remains a critical need in order to develop and monitor drug therapies for nearly all disease areas. The discovery of novel plasma biomarkers is, however, significantly hampered by the complexity and dynamic range of proteins within plasma, as well as the inherent variability in composition from patient to patient. In addition, it is widely accepted that most soluble plasma biomarkers for diseases such as cancer will be represented by tissue leakage products, circulating in plasma at low levels. It is therefore necessary to find approaches with the prerequisite level of sensitivity in such a complex biological matrix. Strategies for fractionating the plasma proteome have been suggested, but improvements in sensitivity are often negated by the resultant process variability. Here we describe an approach using multidimensional chromatography and on-line protein derivatization, which allows for higher sensitivity, whilst minimizing the process variability. In order to evaluate this automated process fully, we demonstrate three levels of processing and compare sensitivity, throughput and reproducibility. We demonstrate that high sensitivity analysis of the human plasma proteome is possible down to the low ng/mL or even high pg/mL level with a high degree of technical reproducibility.

Depletion of abundant plasma proteins by poly(N-isopropylacrylamide-acrylic acid) hydrogel particles

Protein and proteome analysis of human blood plasma presents a challenge to current analytical platforms such as mass spectrometry (MS). High abundance plasma proteins interfere with detection of potential protein biomarkers that are often 3-10 orders of magnitude lower in concentration. We report the application of pH-sensitive poly(N-isopropylacrylamide-acrylic acid) hydrogel particles for removal of abundant plasma proteins, prior to proteome analysis by MS. Protein depletion occurs by two separate mechanisms: (1) hydrogel particles incubated with low concentrations of plasma capture abundant proteins at higher efficiency than low abundance proteins, which are enriched in the supernatants, whereas (2) hydrogel particles incubated with high concentrations of plasma capture and irreversibly trap abundant proteins. During the elution step, irreversibly trapped proteins remain captured while low abundance proteins are released and recovered in the eluate. We developed a series of distinct depletion protocols that proved useful for sample depletion and fractionation and facilitated targeted analysis of putative biomarkers such as IGF1-2, IBP2-7, ALS, KLK6-7, ISK5, and PLF4 by selected reaction monitoring (SRM) liquid chromatography (LC)-MS/MS. This novel use of hydrogel particles opens new perspectives for biomarker analysis based on mass spectrometry.

Subclinical inflammatory status in Rett syndrome

Inflammation has been advocated as a possible common central mechanism for developmental cognitive impairment. Rett syndrome (RTT) is a devastating neurodevelopmental disorder, mainly caused by de novo loss-of-function mutations in the gene encoding MeCP2. Here, we investigated plasma acute phase response (APR) in stage II (i.e., “pseudo-autistic”) RTT patients by routine haematology/clinical chemistry and proteomic 2-DE/MALDI-TOF analyses as a function of four major MECP2 gene mutation types (R306C, T158M, R168X, and large deletions). Elevated erythrocyte sedimentation rate values (median 33.0 mm/h versus 8.0 mm/h, P < 0.0001) were detectable in RTT, whereas C-reactive protein levels were unchanged (P = 0.63). The 2-DE analysis identified significant changes for a total of 17 proteins, the majority of which were categorized as APR proteins, either positive (n = 6 spots) or negative (n = 9 spots), and to a lesser extent as proteins involved in the immune system (n = 2 spots), with some proteins having overlapping functions on metabolism (n = 7 spots). The number of protein changes was proportional to the severity of the mutation. Our findings reveal for the first time the presence of a subclinical chronic inflammatory status related to the “pseudo-autistic” phase of RTT, which is related to the severity carried by the MECP2 gene mutation.