Systematic quantification of peptides/proteins in urine using selected reaction monitoring

An overview of proteomics approaches applied to biopharmaceuticals and cyclotides research

The evolution in proteomics approaches is notable, including quantitative proteomics and strategies for elucidation of post-translational modifications. Faster and more accurate mass spectrometers as well as cleverer bioinformatics tolls are making the difference in such advancement. Among the wide range of research in plant proteomics, biopharmaceutical production using plants as "biofactories" and the screening of new activities of new molecules, in this case, peptides, are quite important regarding translational proteomics. The present review is focused on "recombinant proteins and bioactive peptides", with biopharmaceuticals and cyclotides chosen as examples. Their application and challenges are focused on a "translational proteomics" point of view, in order to exemplify some new areas of research based on proteomics strategies. This article is part of a Special Issue entitled: Translational Plant Proteomics.

Proteomic studies of urinary biomarkers for prostate, bladder and kidney cancers

Urine is an ideal body fluid for the detection of protein markers produced by urological cancers as it can be sampled noninvasively and contains secreted and directly shed proteins from the prostate, bladder and kidney. Major challenges of working with urine include high inter-individual and intra-individual variability, low protein concentration, the presence of salts and the dynamic range of protein expression. Despite these challenges, significant progress is being made using modern proteomic methods to identify and characterize protein-based markers for urological cancers. The development of robust, easy-to-use clinical tests based on novel biomarkers has the potential to impact upon diagnosis, prognosis and monitoring and could revolutionize the treatment and management of these cancers.

Systematic proteomic analysis identifies β-site amyloid precursor protein cleaving enzyme 2 and 1 (BACE2 and BACE1) substrates in pancreatic β-cells

Expansion of functional islet β-cell mass is a physiological process to compensate for increased insulin demand. Deficiency or pharmacological inhibition of the plasma membrane protease BACE2 enhances pancreatic β-cell function and proliferation, and therefore BACE2 is a putative target for the therapeutic intervention under conditions of β-cell loss and dysfunction. To gain a molecular understanding of BACE2 function, we performed a systematic and quantitative proteomic analysis to map the natural substrate repertoire of BACE2 and its homologue BACE1 in β-cells. Loss- and gain-of-function studies of in vitro and in vivo models identified specific and functionally heterogeneous targets. Our analysis revealed non-redundant roles of BACE1/2 in ectodomain shedding with BACE1 regulating a broader and BACE2 a more distinct set of β-cell-enriched substrates including two proteins of the seizure 6 protein family (SEZ6L and SEZ6L2). Lastly, our study provides insights into the global β-cell sheddome and secretome, an important prerequisite to uncover novel mechanisms contributing to β-cell homeostasis and a resource for therapeutic target and biomarker discoveries.

Deglycosylation systematically improves N-glycoprotein identification in liquid chromatography-tandem mass spectrometry proteomics for analysis of cell wall stress responses in Saccharomyces cerevisiae lacking Alg3p

Post-translational modification of proteins with glycosylation is of key importance in many biological systems in eukaryotes, influencing fundamental biological processes and regulating protein function. Changes in glycosylation are therefore of interest in understanding these processes and are also useful as clinical biomarkers of disease. The presence of glycosylation can also inhibit protease digestion and lower the quality and confidence of protein identification by mass spectrometry. While deglycosylation can improve the efficiency of subsequent protease digest and increase protein coverage, this step is often excluded from proteomic workflows. Here, we performed a systematic analysis that showed that deglycosylation with peptide-N-glycosidase F (PNGase F) prior to protease digestion with AspN or trypsin improved the quality of identification of the yeast cell wall proteome. The improvement in the confidence of identification of glycoproteins following PNGase F deglycosylation correlated with a higher density of glycosylation sites. Optimal identification across the proteome was achieved with PNGase F deglycosylation and complementary proteolysis with either AspN or trypsin. We used this combination of deglycosylation and complementary protease digest to identify changes in the yeast cell wall proteome caused by lack of the Alg3p protein, a key component of the biosynthetic pathway of protein N-glycosylation. The cell wall of yeast lacking Alg3p showed specifically increased levels of Cis3p, a protein important for cell wall integrity. Our results showed that deglycosylation prior to protease digestion improved the quality of proteomic analyses even if protein glycosylation is not of direct relevance to the study at hand.

Cancer proteomics

Cancer presents high mortality and morbidity globally, largely due to its complex and heterogenous nature, and lack of biomarkers for early diagnosis. A proteomics study of cancer aims to identify and characterize functional proteins that drive the transformation of malignancy, and to discover biomarkers to detect early-stage cancer, predict prognosis, determine therapy efficacy, identify novel drug targets, and ultimately develop personalized medicine. The various sources of human samples such as cell lines, tissues, and plasma/serum are probed by a plethora of proteomics tools to discover novel biomarkers and elucidate mechanisms of tumorigenesis. Innovative proteomics technologies and strategies have been designed for protein identification, quantitation, fractionation, and enrichment to delve deeper into the oncoproteome. In addition, there is the need for high-throughput methods for biomarker validation, and integration of the various platforms of oncoproteome data to fully comprehend cancer biology.

Total ApoE and ApoE4 isoform assays in an Alzheimer's disease case-control study by targeted mass spectrometry (n=669): a pilot assay for methionine-containing proteotypic peptides

Allelic polymorphism of the apolipoprotein E (ApoE) gene (ApoE ε2, ApoE ε3 and ApoE ε4 alleles) gives rise to three protein isoforms (ApoE2, ApoE3 and ApoE4) that differ by 1 or 2 amino acids. Inheritance of the ApoE ε4 allele is a risk factor for developing Alzheimer's disease (AD). The potential diagnostic value of ApoE protein levels in biological fluids (i.e. cerebrospinal fluid, plasma and serum) for distinguishing between AD patients and healthy elderly subjects is subject to great controversy. Although a recent study reported subnormal total ApoE and ApoE4 levels in the plasma of AD patients, other studies have found normal or even elevated protein levels (versus controls). Because all previously reported assays were based on immunoenzymatic techniques, we decided to develop an orthogonal assay based on targeted mass spectrometry by tracking (i) a proteotypic peptide common to all ApoE isoforms and (ii) a peptide that is specific for the ε4 allele. After trypsin digestion, the ApoE4-specific peptide contains an oxidation-prone methionine residue. The endogenous methionine oxidation level was evaluated in a small cohort (n=68) of heterozygous ε3ε4 carriers containing both healthy controls and AD patients. As expected, the proportion of oxidized residues varied from 0 to 10%, with an average of 5%. We therefore developed a standardized strategy for the unbiased, absolute quantification of ApoE4, based on performic acid oxidization of methionine. Once the sample workflow had been thoroughly validated, it was applied to the concomitant quantification of total ApoE and ApoE4 isoform in a large case-control study (n=669). The final measurements were consistent with most previously reported ApoE concentration values and confirm the influence of the different alleles on the protein expression level. Our results illustrate (i) the reliability of selected reaction monitoring-based assays and (ii) the value of the oxidization step for unbiased monitoring of methionine-containing proteotypic peptides. Furthermore, a statistical analysis indicated that neither total ApoE and ApoE4 levels nor the ApoE/ApoE4 ratio correlated with the diagnosis of AD. These findings reinforce the conclusions of previous studies in which plasma ApoE levels had no obvious clinical significance.

Hydronephrosis: a view from the inside

Unilateral ureteropelvic junction obstruction (UPJO) is the most common prenatally detected disease leading to hydronephrosis. The obstructive anatomic lesion leads to varying degrees of hydronephrosis, ranging from no apparent effect on renal function to atrophy. Furthermore, the natural course of hydronephrosis varies from spontaneous resolution to progressive deterioration and may take upwards of 3 years for a kidney to declare itself. The objectives of this article are to update our knowledge regarding the evaluation and management of UPJO in depth and to discuss the emerging value of urinary proteome analysis to the clinical arena.

Reproducible quantification of cancer-associated proteins in body fluids using targeted proteomics

The rigorous testing of hypotheses on suitable sample cohorts is a major limitation in translational research. This is particularly the case for the validation of protein biomarkers; the lack of accurate, reproducible, and sensitive assays for most proteins has precluded the systematic assessment of hundreds of potential marker proteins described in the literature. Here, we describe a high-throughput method for the development and refinement of selected reaction monitoring (SRM) assays for human proteins. The method was applied to generate such assays for more than 1000 cancer-associated proteins, which are functionally related to candidate cancer driver mutations. We used the assays to determine the detectability of the target proteins in two clinically relevant samples: plasma and urine. One hundred eighty-two proteins were detected in depleted plasma, spanning five orders of magnitude in abundance and reaching below a concentration of 10 ng/ml. The narrower concentration range of proteins in urine allowed the detection of 408 proteins. Moreover, we demonstrate that these SRM assays allow reproducible quantification by monitoring 34 biomarker candidates across 83 patient plasma samples. Through public access to the entire assay library, researchers will be able to target their cancer-associated proteins of interest in any sample type using the detectability information in plasma and urine as a guide. The generated expandable reference map of SRM assays for cancer-associated proteins will be a valuable resource for accelerating and planning biomarker verification studies.

A computational tool to detect and avoid redundancy in selected reaction monitoring

Selected reaction monitoring (SRM), also called multiple reaction monitoring, has become an invaluable tool for targeted quantitative proteomic analyses, but its application can be compromised by nonoptimal selection of transitions. In particular, complex backgrounds may cause ambiguities in SRM measurement results because peptides with interfering transitions similar to those of the target peptide may be present in the sample. Here, we developed a computer program, the SRMCollider, that calculates nonredundant theoretical SRM assays, also known as unique ion signatures (UIS), for a given proteomic background. We show theoretically that UIS of three transitions suffice to conclusively identify 90% of all yeast peptides and 85% of all human peptides. Using predicted retention times, the SRMCollider also simulates time-scheduled SRM acquisition, which reduces the number of interferences to consider and leads to fewer transitions necessary to construct an assay. By integrating experimental fragment ion intensities from large scale proteome synthesis efforts (SRMAtlas) with the information content-based UIS, we combine two orthogonal approaches to create high quality SRM assays ready to be deployed. We provide a user friendly, open source implementation of an algorithm to calculate UIS of any order that can be accessed online at http://www.srmcollider.org to find interfering transitions. Finally, our tool can also simulate the specificity of novel data-independent MS acquisition methods in Q1-Q3 space. This allows us to predict parameters for these methods that deliver a specificity comparable with that of SRM. Using SRM interference information in addition to other sources of information can increase the confidence in an SRM measurement. We expect that the consideration of information content will become a standard step in SRM assay design and analysis, facilitated by the SRMCollider.

Advancing the sensitivity of selected reaction monitoring-based targeted quantitative proteomics

Selected reaction monitoring (SRM) - also known as multiple reaction monitoring (MRM) - has emerged as a promising high-throughput targeted protein quantification technology for candidate biomarker verification and systems biology applications. A major bottleneck for current SRM technology, however, is insufficient sensitivity for, e.g. detecting low-abundance biomarkers likely present at the low ng/mL to pg/mL range in human blood plasma or serum, or extremely low-abundance signaling proteins in cells or tissues. Herein, we review recent advances in methods and technologies, including front-end immunoaffinity depletion, fractionation, selective enrichment of target proteins/peptides including posttranslational modifications, as well as advances in MS instrumentation which have significantly enhanced the overall sensitivity of SRM assays and enabled the detection of low-abundance proteins at low- to sub-ng/mL level in human blood plasma or serum. General perspectives on the potential of achieving sufficient sensitivity for detection of pg/mL level proteins in plasma are also discussed.

An assessment of current bioinformatic solutions for analyzing LC-MS data acquired by selected reaction monitoring technology

Selected reaction monitoring (SRM) is an accurate quantitative technique, typically used for small-molecule mass spectrometry (MS). SRM has emerged as an important technique for targeted and hypothesis-driven proteomic research, and is becoming the reference method for protein quantification in complex biological samples. SRM offers high selectivity, a lower limit of detection and improved reproducibility, compared to conventional shot-gun-based tandem MS (LC-MS/MS) methods. Unlike LC-MS/MS, which requires computationally intensive informatic postanalysis, SRM requires preacquisition bioinformatic analysis to determine proteotypic peptides and optimal transitions to uniquely identify and to accurately quantitate proteins of interest. Extensive arrays of bioinformatics software tools, both web-based and stand-alone, have been published to assist researchers to determine optimal peptides and transition sets. The transitions are oftentimes selected based on preferred precursor charge state, peptide molecular weight, hydrophobicity, fragmentation pattern at a given collision energy (CE), and instrumentation chosen. Validation of the selected transitions for each peptide is critical since peptide performance varies depending on the mass spectrometer used. In this review, we provide an overview of open source and commercial bioinformatic tools for analyzing LC-MS data acquired by SRM.

Multiplexed quantification of 63 proteins in human urine by multiple reaction monitoring-based mass spectrometry for discovery of potential bladder cancer biomarkers

Three common urological diseases are bladder cancer, urinary tract infection, and hematuria. Seventeen bladder cancer biomarkers were previously discovered using iTRAQ - these findings were verified by MRM-MS in this current study. Urine samples from 156 patients with hernia (n=57, control), bladder cancer (n=76), or urinary tract infection/hematuria (n=23) were collected and subjected to multiplexed LC-MRM/MS to determine the concentrations of 63 proteins that are normally considered to be plasma proteins, but which include proteins found in our earlier iTRAQ study. Sixty-five stable isotope-labeled standard proteotypic peptides were used as internal standards for 63 targeted proteins. Twelve proteins showed higher concentrations in the bladder cancer group than in the hernia and the urinary tract infection/hematuria groups, and thus represent potential urinary biomarkers for detection of bladder cancer. Prothrombin had the highest AUC (0.796), with 71.1% sensitivity and 75.0% specificity for differentiating bladder cancer (n=76) from non-cancerous (n=80) patients. The multiplexed MRM-MS data was used to generate a six-peptide marker panel. This six-peptide panel (afamin, adiponectin, complement C4 gamma chain, apolipoprotein A-II precursor, ceruloplasmin, and prothrombin) can discriminate bladder cancer subjects from non-cancerous subjects with an AUC of 0.814, with a 76.3% positive predictive value, and a 77.5% negative predictive value. This article is part of a Special Section entitled: Understanding genome regulation and genetic diversity by mass spectrometry.

Towards clinical applications of selected reaction monitoring for plasma protein biomarker studies

The widespread clinical adoption of protein biomarkers with diagnostic, prognostic and/or predictive value remains a formidable challenge for the biomedical community. From discovery to validation, the path to biomarkers of clinical relevance abounds with many protein candidates, yet so few concrete examples have been substantiated. In this review, we focus on the recent adoption of selected reaction monitoring (SRM) of plasma proteins in the path to clinical use for a broad range of diseases including cancer, cardiovascular disease, genetic disorders and various metabolic disorders. Recent progress reveals a promising outlook for clinical applications using SRM, which now provides the routine analysis of clinically relevant protein markers at low nanogram per millilitre in plasma.

Analytical constraints for the analysis of human cell line secretomes by shotgun proteomics

Human cell line secretome represents a valuable source of therapeutic targets and candidate biomarkers. Secreted proteins found in biological fluids or culture media are by essence highly diluted. Secretome investigation with proteomic approaches is hardly compatible with the high content of proteins found in complete cell culture media. Therefore, many studies are currently done with media containing few or no protein. Such conditions may perturb cell metabolism and proliferation. Here, we compared seventeen different compositions of culture media for the human bronchial epithelial BEAS-2B cell line. Cell viability, proliferation rate and initial protein charge were systematically compared. We have shown that an important difficulty for the proteomic analysis is due to the presence of detergents such as Pluronic F-68 which hinders peptide mass spectrometry. The high glucose containing DMEM medium which is free of proteins was shown to preserve a good viability and proliferation of cells. With this conditioning medium, we identified 81 extracellular proteins in the secretome of BEAS-2B cells. Moreover, to illustrate this approach, we exposed BEAS-2B cells to a low toxic dose of CoCl(2,) and found 24 extracellular proteins modulated by cobalt. This study highlights the possible contribution of such proteomic approach in the field of toxicology.