Methods for peptide and protein quantitation by liquid chromatography-multiple reaction monitoring mass spectrometry

Absolute quantification of viral proteins from pseudotyped VSV-GP using UPLC-MRM

The rapidly developing field of oncolytic virus (OV) therapy necessitates the development of new and improved analytical approaches for the characterization of the virus during production and development. Accurate monitoring and absolute quantification of viral proteins are crucial for OV product characterization and can facilitate the understanding of infection, immunogenicity, and development stages of viral replication. Targeted mass spectrometry methods like multiple reaction monitoring (MRM) offer a robust way to directly detect and quantify specific targeted proteins represented by surrogate peptides. We have leveraged the power of MRM by combining ultra-high performance liquid chromatography (UPLC) with a Sciex 6500 triple-stage quadrupole mass spectrometer to develop an assay that accurately and absolutely quantifies the structural proteins of a pseudotyped vesicular stomatitis virus (VSV) intended for use as a new biotherapeutic (designated hereafter as VSV-GP to differentiate it from native VSV). The new UPLC-MRM method provides absolute quantification with the use of heavy-labeled reference standard surrogate peptides. When added in known exact amounts to standards and samples, the reference standards normalize and account for any small perturbations during sample preparation and/or instrument performance, resulting in accurate and precise quantification. Because of the multiplexed nature of MRM, all targeted proteins are quantified at the same time. The optimized assay has been enhanced to quantify the ratios of the processed GP1 and GP2 proteins while simultaneously measuring any remaining or unprocessed form of the envelope protein GP complex (GPC; full-length GPC).

IMPORTANCE

The development of oncolytic viral therapy has gained considerable momentum in recent years. Vesicular stomatitis virus glycoprotein (VSV-GP) is a new biotherapeutic emerging in the oncolytic viral therapy platform. Novel analytical assays that can accurately and precisely quantify the viral proteins are a necessity for the successful development of viral vector as a biotherapeutic. We developed an ultra-high performance liquid chromatography multiple reaction monitoring-based assay to quantify the absolute concentrations of the different structural proteins of VSV-GP. The complete processing of GP complex (GPC) is a prerequisite for the infectivity of the virus. The assay extends the potential for quantifying full-length GPC, which provides an understanding of the processing of GPC (along with the quantification of GP1 and GP2 separately). We used this assay in tracking GPC processing in HEK-293-F production cell lines infected with VSV-GP.

Maximizing Analytical Performance in Biomolecular Discovery with LC-MS: Focus on Psychiatric Disorders

In this review, we discuss the cutting-edge developments in mass spectrometry proteomics and metabolomics that have brought improvements for the identification of new disease-based biomarkers. A special focus is placed on psychiatric disorders, for example, schizophrenia, because they are considered to be not a single disease entity but rather a spectrum of disorders with many overlapping symptoms. This review includes descriptions of various types of commonly used mass spectrometry platforms for biomarker research, as well as complementary techniques to maximize data coverage, reduce sample heterogeneity, and work around potentially confounding factors. Finally, we summarize the different statistical methods that can be used for improving data quality to aid in reliability and interpretation of proteomics findings, as well as to enhance their translatability into clinical use and generalizability to new data sets.

Prognostic biomarkers of intracerebral hemorrhage identified using targeted proteomics and machine learning algorithms

Early prognostication of patient outcomes in intracerebral hemorrhage (ICH) is critical for patient care. We aim to investigate protein biomarkers' role in prognosticating outcomes in ICH patients. We assessed 22 protein biomarkers using targeted proteomics in serum samples obtained from the ICH patient dataset (N = 150). We defined poor outcomes as modified Rankin scale score of 3-6. We incorporated clinical variables and protein biomarkers in regression models and random forest-based machine learning algorithms to predict poor outcomes and mortality. We report Odds Ratio (OR) or Hazard Ratio (HR) with 95% Confidence Interval (CI). We used five-fold cross-validation and bootstrapping for internal validation of prediction models. We included 149 patients for 90-day and 144 patients with ICH for 180-day outcome analyses. In multivariable logistic regression, UCH-L1 (adjusted OR 9.23; 95%CI 2.41-35.33), alpha-2-macroglobulin (aOR 5.57; 95%CI 1.26-24.59), and Serpin-A11 (aOR 9.33; 95%CI 1.09-79.94) were independent predictors of 90-day poor outcome; MMP-2 (aOR 6.32; 95%CI 1.82-21.90) was independent predictor of 180-day poor outcome. In multivariable Cox regression models, IGFBP-3 (aHR 2.08; 95%CI 1.24-3.48) predicted 90-day and MMP-9 (aOR 1.98; 95%CI 1.19-3.32) predicted 180-day mortality. Machine learning identified additional predictors, including haptoglobin for poor outcomes and UCH-L1, APO-C1, and MMP-2 for mortality prediction. Overall, random forest models outperformed regression models for predicting 180-day poor outcomes (AUC 0.89), and 90-day (AUC 0.81) and 180-day mortality (AUC 0.81). Serum biomarkers independently predicted short-term poor outcomes and mortality after ICH. Further research utilizing a multi-omics platform and temporal profiling is needed to explore additional biomarkers and refine predictive models for ICH prognosis.

A multiplexed parallel reaction monitoring assay to monitor bovine pregnancy-associated glycoproteins throughout pregnancy and after gestation

Bovine pregnancy-associated glycoproteins (boPAGs) are extensively glycosylated secretory proteins of trophoblast cells. Roughly 20 different boPAG members are known but their distribution patterns and degree of glycosylation during pregnancy are not well characterized. The objective of the present study was the development of a parallel reaction monitoring-based assay for the profiling of different boPAGs during pregnancy and after gestation. Furthermore, we investigated the effects of N-glycosylation on our analytical results. BoPAGs were purified from cotyledons of four different pregnancy stages. The assay detects 25 proteotypic peptides from 18 boPAGs in a single run. The highest abundances were found for boPAG 1 in both, glycosylated and deglycosylated samples. Strongest effects of glycosylation were detected during mid and late pregnancy as well as in afterbirth samples. Furthermore, we identified different boPAG-clusters based on the observed relative protein abundances between glycosylated and deglycosylated samples. A linkage between the impact of glycosylation and potential N-glycosylation sites or phylogenetic relation was not detected. In conclusion, the newly developed parallel reaction monitoring-based assay enables for the first time a comprehensive semi-quantitative profiling of 18 different boPAGs during pregnancy and post-partum on protein level, thereby investigating the influence of glycosylation. The results of this study provide new and important starting points to address further research on boPAGs to better understand their physiological role during pregnancy and for the development of new pregnancy detection tests.

An Introduction to Advanced Targeted Acquisition Methods

Targeted proteomics via selected reaction monitoring (SRM) or parallel reaction monitoring (PRM) enables fast and sensitive detection of a preselected set of target peptides. However, the number of peptides that can be monitored in conventional targeting methods is usually rather small. Recently, a series of methods has been described that employ intelligent acquisition strategies to increase the efficiency of mass spectrometers to detect target peptides. These methods are based on one of two strategies. First, retention time adjustment-based methods enable intelligent scheduling of target peptide retention times. These include Picky, iRT, as well as spike-in free real-time adjustment methods such as MaxQuant.Live. Second, in spike-in triggered acquisition methods such as SureQuant, Pseudo-PRM, TOMAHAQ, and Scout-MRM, targeted scans are initiated by abundant labeled synthetic peptides added to samples before the run. Both strategies enable the mass spectrometer to better focus data acquisition time on target peptides. This either enables more sensitive detection or a higher number of targets per run. Here, we provide an overview of available advanced targeting methods and highlight their intrinsic strengths and weaknesses and compatibility with specific experimental setups. Our goal is to provide a basic introduction to advanced targeting methods for people starting to work in this field.

Emerging mass spectrometry-based proteomics methodologies for novel biomedical applications

Research into the basic biology of human health and disease, as well as translational human research and clinical applications, all benefit from the growing accessibility and versatility of mass spectrometry (MS)-based proteomics. Although once limited in throughput and sensitivity, proteomic studies have quickly grown in scope and scale over the last decade due to significant advances in instrumentation, computational approaches, and bio-sample preparation. Here, we review these latest developments in MS and highlight how these techniques are used to study the mechanisms, diagnosis, and treatment of human diseases. We first describe recent groundbreaking technological advancements for MS-based proteomics, including novel data acquisition techniques and protein quantification approaches. Next, we describe innovations that enable the unprecedented depth of coverage in protein signaling and spatiotemporal protein distributions, including studies of post-translational modifications, protein turnover, and single-cell proteomics. Finally, we explore new workflows to investigate protein complexes and structures, and we present new approaches for protein-protein interaction studies and intact protein or top-down MS. While these approaches are only recently incipient, we anticipate that their use in biomedical MS proteomics research will offer actionable discoveries for the improvement of human health.

A sensitive quantitative analysis of abiotically synthesized short homopeptides using ultraperformance liquid chromatography and time-of-flight mass spectrometry

In the origins of life field understanding the abiotic polymerization of simple organic monomers (e.g., amino acids) into larger biomolecules (e.g., oligopeptides), remains a seminal challenge. Recently, preliminary observations showed a limited set of peptides formed in the presence of the plausible prebiotic phosphorylating agent, diamidophosphate (DAP), highlighting the need for an analytical tool to critically evaluate the ability of DAP to induce oligomerization of simple organics under aqueous conditions. However, performing accurate and precise, targeted analyses of short oligopeptides remains a distinct challenge in the analytical chemistry field. Here, we developed a new technique to detect and quantitate amino acids and their homopeptides in a single run using ultraperformance liquid chromatography-fluorescence detection/time of flight mass spectrometry. Over an 8-minute retention time window, 18 target analytes were identified and quantitated, 16 of which were chromatographically separated at, or near baseline resolution. Compound identity was confirmed by accurate mass analysis using a 10 ppm mass tolerance window. This method featured limits of detection < 5 nM (< 1 fmol on column) and limits of quantitation (LOQs) <15 nM (< 3 fmol on column). The LODs and LOQs were upwards of ∼28x and ∼788x lower, respectively, than previous methods for the same analytes, highlighting the quantifiable advantages of this new method. Both detectors provided good quantitative linearity (R2 > 0.985) for all analytes spanning concentration ranges ∼3 - 4 orders of magnitude. We performed a series of laboratory experiments to investigate DAP-mediated oligomerization of amino acids and peptides and analyzed experimental products with the new method. DAP readily polymerized amino acids and peptides under a range of simulated environmental conditions. This research underscores the potential of DAP to have generated oligopeptides on the primordial Earth, enhancing prebiotic chemical diversity and complexity at or near the origin of life.

Quantitative Analysis of Antibody Survival across the Infant Digestive Tract Using Mass Spectrometry with Parallel Reaction Monitoring

Orally delivered antibodies may be useful for the prevention of enteric pathogen infection, but to be effective they need to survive intact across digestion through the gastrointestinal tract. As a test case, we fed a recombinant human antibody, palivizumab, spiked into human milk to four infants and collected gastric, intestinal and stool samples. We identified a tryptic peptide from palivizumab (LLIYDTSK) that differs from all endogenous human antibodies and used this for quantitation of the intact palivizumab. To account for dilution by digestive fluids, we co-fed a non-digestible, non-absorbable molecule-polyethylene glycol 28-quantified it in each sample and used this value to normalize the observed palivizumab concentration. The palivizumab peptide, a stable isotope-labeled synthetic peptide and polyethylene glycol 28 were quantified via a highly sensitive and selective parallel-reaction monitoring approach using nano-liquid chromatography/Orbitrap mass spectrometry. On average, the survival of intact palivizumab from the feed to the stomach, upper small intestine and stool were 88.4%, 30.0% and 5.2%, respectively. This approach allowed clear determination of the extent to which palivizumab was degraded within the infant digestive tract. This method can be applied with some modifications to study the digestion of any protein.

The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics

Skyline is a freely available, open-source Windows client application for accelerating targeted proteomics experimentation, with an emphasis on the proteomics and mass spectrometry community as users and as contributors. This review covers the informatics encompassed by the Skyline ecosystem, from computationally assisted targeted mass spectrometry method development, to raw acquisition file data processing, and quantitative analysis and results sharing.

Development and validation of an LC-MS/MS method for simultaneous quantification of co-administered trastuzumab and pertuzumab

Given the increasing use of combination therapy with multiple monoclonal antibodies (mAbs), there is a clinical need for multiplexing assays. For the frequently co-administered anti-human epidermal growth factor receptor 2 (HER2) mAbs trastuzumab and pertuzumab, we developed a high-throughput and robust hybrid ligand-binding liquid chromatography-mass spectrometry (LC-MS)/MS quantitative assay. Nanomolar concentrations of trastuzumab and pertuzumab were determined in 10 µL serum samples after extraction by affinity purification through protein A beads, followed by on-bead reduction, alkylation, and trypsin digestion. After electrospray ionization, quantification was obtained by multiple reaction monitoring LC-MS/MS using SILuMab as an internal standard. The method was validated according to the current guidelines from the US Food and Drug Administration and the European Medicines Agency. Assay linearity was established in the ranges 0.250-250 μg/mL for trastuzumab and 0.500-500 μg/mL for pertuzumab. The method was accurate and selective for the simultaneous determination of trastuzumab and pertuzumab in clinical samples, thereby overcoming the limitation of ligand binding assays that cannot quantify mAbs targeting the same receptor. Furthermore, this method requires a small blood volume, which reduces blood collection time and stress for patients. The assay robustness was verified in a clinical trial where trastuzumab and pertuzumab concentrations were determined in 670 serum samples. As we used commercially available reagents and standards, the described generic bioanalytical strategy can easily be adapted to multiplex quantifications of other mAb combinations in non-clinical and clinical samples.

Targeted Quantitative Proteomic Approach for High-Throughput Quantitative Profiling of Small GTPases in Brain Tissues of Alzheimer's Disease Patients

Neurodegenerative disorders, including Alzheimer's disease (AD), are prevalent among the elderly. Small GTPases of the Ras superfamily are essential regulators of intracellular trafficking and signal transduction. In this study, we develop a targeted quantification method for small GTPase proteins, where the method involves scheduled multiple-reaction monitoring analysis and the use of synthetic stable isotope-labeled peptides as internal standards or surrogate standards. We further applied this method to examine the altered expression of small GTPase proteins in post-mortem frontal cortex tissues from AD patients with different degrees of disease severity. We were able to achieve sensitive and reproducible quantifications of 80 small GTPases in brain tissue samples from 15 patients. Our results revealed substantial up-regulations of several synaptic GTPases, i.e., RAB3A/C, RAB4A/B, and RAB27B, in tissues from patients with higher degrees of AD pathology, suggesting that aberrant synaptic trafficking may modulate the progression of AD. The method should be generally applicable for high-throughput targeted quantification of small GTPase proteins in other tissue and cellular samples.

Validation of a multiplexed LC-MS/MS clinical assay to quantify insulin-like growth factor-binding proteins in human serum and its application in a clinical study

Circulating insulin-like growth factor-binding proteins (IGFBPs) continue to gain attention as biomarkers of drug activities on insulin like growth factor (IGF)/IGF receptor signaling pathways. A multiplexed LC-MS/MS method was validated for the absolute quantitation of IGFBPs in human serum. The method was used to measure screening concentrations of IGFBPs in spinal and bulbar muscular atrophy (SBMA) patients in a phase 2 clinical trial. Concentrations of IGFBP 1, 2, 3, and 5 were simultaneously determined based on representative signature peptides derived from an optimized trypsin digestion procedure. Signature peptide levels were absolutely quantitated using a sensitive/specific targeted LC-MS/MS method. Corresponding mass-shifted, stable isotope-labeled peptides were employed as internal standards. A true blank matrix for the quantitation of IGFBPs was not available since they are endogenous proteins in human serum. In this method, calibration standards/curves were prepared using authentic synthetic peptides spiked into a surrogate matrix. The surrogate matrix was generated from human serum treated in the same way as the study samples, but using iodoacetic acid instead of iodoacetamide as the alkylation reagent. This surrogate matrix approach allowed for the direct and sensitive/specific quantification of IGFBP 1, 2, 3, and 5 due to the lack of any endogenous background. Equivalent matrix effect and recovery of analytes was achieved for the authentic and surrogate matrices. The fully validated LC-MS/MS assay will allow further evaluation of the utility of IGFBP biomarkers in clinical trials.

Two Functionally Deviating Type 6 Secretion Systems Occur in the Nitrogen-Fixing Endophyte Azoarcus olearius BH72

Type VI protein secretion systems (T6SSs) have been identified in many plant-associated bacteria. However, despite the fact that effector proteins may modulate host responses or interbacterial competition, only a few have been functionally dissected in detail. We dissected the T6SS in Azoarcus olearius strain BH72, a nitrogen-fixing model endophyte of grasses. The genome harbors two gene clusters encoding putative T6SSs, tss-1 and tss-2, of which only T6SS-2 shared genetic organization and functional homology with the H1-T6SS of Pseudomonas aeruginosa. While tss-2 genes were constitutively expressed, tss-1 genes were strongly up-regulated under conditions of nitrogen fixation. A comparative analysis of the wild type and mutants lacking either functional tss-1 or tss-2 allowed to differentiate the functions of both secretion systems. Abundance of Hcp in the culture supernatant as an indication for T6SS activity revealed that only T6SS-2 was active, either under aerobic or nitrogen-fixing conditions. Our data show that T6SS-2 but not T6SS-1 is post-translationally regulated by phosphorylation mediated by TagE/TagG (PpkA/PppA), and by the phosphorylation-independent inhibitory protein TagF, similar to published work in Pseudomonas. Therefore, T6SS-1 appears to be post-translationally regulated by yet unknown mechanisms. Thus, both T6SS systems appear to perform different functions in Azoarcus, one of them specifically adapted to the nitrogen-fixing lifestyle.

Quantitation of seven transmembrane proteins from the DHA biosynthesis pathway in genetically engineered canola by targeted mass spectrometry

Examining tissue-specific expression and the measurement of protein abundance are important steps when assessing the performance of genetically engineered crops. Liquid chromatography-mass spectrometry offers many advantages over traditional methods for protein quantitation, especially when dealing with transmembrane proteins that are often difficult to express or generate antibodies against. In this study, discovery proteomics was used to detect the seven transgenic membrane-bound enzymes from the docosahexaenoic acid (DHA) biosynthetic pathway that had been engineered into canola. Subsequently, a targeted LC-MS/MS method for absolute quantitation was developed and applied to the simultaneous measurement of the seven DHA biosynthetic pathway enzymes in genetically modified canola grown across three sites. The results of this study demonstrated that the enzymatic proteins that drive the production of DHA using seed-specific promoters were detected only in mature and developing seed of DHA canola. None of the DHA biosynthesis pathway proteins were detected in wild-type canola planted in the same site or in the non-seed tissues of the transgenic canola, irrespective of the sampling time or the tissues tested. This study describes a streamlined approach to simultaneously measure multiple membrane-bound proteins in planta.

Simultaneous extraction and analysis of multiple cystine-dense peptides by μSPE and microflow-MS/MS from plasma

Aim: Develop a universal extraction and liquid chromatography-mass spectrometer method to simultaneously analyze cystine-dense peptide (CDP) miniproteins from rat and human plasma. The results of the analysis will be used to assist selection of therapeutic drug candidates from the vast CDP library. Methods & results: A micro-elution solid-phase extraction method was developed for the sample preparation of the CDP peptides in rat and human plasma followed by analysis by microflow liquid chromatography MS/MS. The methods developed for drug discovery were found to be accurate (±≤15.2% from nominal concentrations) and precise (≤13.4% CV), with a dynamic range of 1.00–500 ng/ml and extraction recoveries of 47.2–99.0%. Conclusion: This bioanalytical method can be utilized to screen CDP proteins and other miniproteins for drug discovery, candidate selection and further drug development.

A multiplexed UPLC-MS/MS assay for the simultaneous measurement of urinary safety biomarkers of drug-induced kidney injury and phospholipidosis

Drug-induced kidney injury (DIKI) is a major concern in drug risk assessment given its clinical importance and the absence of a sensitive/specific method of diagnosis. Pharmaceutical regulatory agencies have qualified and issued letters of support for new biomarkers to better evaluate DIKI in nonclinical toxicity and clinical studies. Additional efforts have focused on drug-induced phospholipidosis (DIPL) and its potential link with collateral renal damage. The combined use of urinary biomarkers is an efficient way to evaluate renal safety in nonclinical and clinical studies. Eight FDA/EMA/PMDA qualified (or supported) urinary biomarkers, including kidney injury molecule-1 (KIM-1), β2-microglobulin (B2M), clusterin (CLU), cystatin C (CysC), trefoil factor 3 (TFF3), neutrophil gelatinase-associated lipocalin (NGAL), osteopontin (OPN), and alpha-glutathione S-transferase (α-GST), were quantified by multiplex UPLC-MS/MS in a repeat dose study of gentamicin in rats. Rats administered gentamicin at 100 mg/kg/day for 2 weeks developed renal lesions detected by histopathology. Biomarkers of tubular damage (CLU, KIM-1, OPN) increased 9.8, 34.7, and 35.6-fold (relative to concurrent controls), respectively, after 2 weeks of dosing. Biomarkers of glomerular damage and/or impairment of tubular reabsorption (CysC, B2M) increased 11.7 and 22.6-fold. NGAL and α-GST increased <3-fold after 2 weeks of dosing. TFF3 was comparable to concurrent controls. The elevated biomarker concentrations met PSTC threshold criteria and were consistent with mechanisms of gentamicin nephrotoxicity. Increased urinary di-22:6-BMP indicated concomitant DIPL as confirmed by TEM. This work provides evidence supporting the combined use of the DIKI biomarker panel and di-22:6-BMP as a biomarker of DIPL in drug risk assessment.

A Guide to Mass Spectrometry-Based Quantitative Proteomics

Proteomics has become an attractive science in the postgenomic era, given its capacity to identify up to thousands of molecules in a single, complex sample and quantify them in an absolute and/or relative manner. The use of these techniques enables understanding of cellular and molecular mechanisms of diseases and other biological conditions, as well as identification and screening of protein biomarkers. Here we provide a straightforward, up-to-date compilation and comparison of the main quantitation techniques used in comparative proteomics such as in vitro and in vivo stable isotope labeling and label-free techniques. Additionally, this chapter includes common methods for data acquisition in proteomics and some appropriate methods for data processing. This compilation can serve as a reference for scientists who are new to, or already familiar with, quantitative proteomics.

Multiple-Enzyme-Digestion Strategy Improves Accuracy and Sensitivity of Label- and Standard-Free Absolute Quantification to a Level That Is Achievable by Analysis with Stable Isotope-Labeled Standard Spiking

Quantification of individual proteins is an essential task in understanding biological processes. For example, determination of concentrations of proteins transporting and metabolizing xenobiotics is a prerequisite for drug disposition predictions in humans based on in vitro data. So far, this task has frequently been accomplished by targeted proteomics. This type of analyses requires preparation of stable isotope labeled standards for each protein of interest. The selection of appropriate standard peptides is usually tedious and the number of proteins that can be studied in a single experiment by these approaches is limited. In addition, incomplete digestion of proteins often affects the accuracy of the quantification. To circumvent these constrains in proteomic protein quantification, label- and standard-free approaches, such as "total protein approach" (TPA) have been proposed. Here we directly compare an approach using stable isotope labeled (SIL) standards and TPA for quantification of transporters and enzymes in human liver samples within the same LC-MS/MS runs. We show that TPA is a convenient alternative to SIL-based methods. Optimization of the sample preparation beyond commonly used single tryptic digestion, by adding consecutive cleavage steps, improves accuracy and reproducibility of the TPA method to a level, which is achievable by analysis using stable isotope-labeled standard spiking.

Quantitative measurement of selected protein biomarkers of endothelial dysfunction in plasma by micro-liquid chromatography-tandem mass spectrometry based on stable isotope dilution method

The aim of this study was to develop and validate the novel microLC/MS-MRM method for the simultaneous quantification of six proteins: angiopoietin 2 (Angpt-2), soluble form of fms-like tyrosine kinase 1 (sFLT-1), plasminogen activator inhibitor 1 (PAI-1), tissue plasminogen activator (t-PA), endocan (ESM-1), soluble form of E-selectin (sE-sel), and one peptide: adrenomedullin (ADM) in mouse plasma. Two approaches were compared: a stable isotope dilution (SID) method- used as a reference and a modified SID (mSID) procedure. In SID strategy the calibration curves were used, whereas in mSID the ratio between the chromatogram peak area of endogenous tryptic peptides at unknown concentration to chromatogram peak area of exogenous, stable isotope-labelled internal standards (SISs) added to the sample at known concentration was calculated. The microLC/MS-MRM method in the SID approach was linear from 0.250 pmol/mL to 250 pmol/mL for Angpt-2; 5 pmol/mL to 5000 pmol/mL for sFLT-1; 2.5 pmol/mL to 5000 pmol/mL for PAI-1; 0.375 pmol/mL to 250 pmol/mL for t-PA; 0.375 pmol/mL to 187.5 pmol/mL for ESM-1; 2.5 pmol/mL to 5000 pmol/mL for sE-sel and 0.375 pmol/mL to 250 pmol/mL for ADM. LPS-induced changes in plasma assessed based on SID and mSID approaches gave comparable quantitative results and featured LPS-induced dysregulation of endothelial permeability (Angpt-2, sFLT-1), glycocalyx injury (SDC-1) accompanied by a pro-thrombotic response (PAI-1). In addition, we applied microLC/MS-MRM method with mSID strategy to analyze human plasma samples from patients with chronic myeloid leukemia (CML) and obstructive sleep apnoea (OSA) and demonstrated usefulness of the method to characterize endothelial function in humans. In conclusion, the microLC/MS-MRM method with mSID strategy applied for simultaneous quantification of protein biomarkers of endothelial function in plasma represents a novel targeted proteomic platform for the comprehensive evaluation of endothelial function in mice and humans.

Multiple reaction monitoring targeted LC-MS analysis of potential cell death marker proteins for increased bioprocess control

The monitoring of protein biomarkers for the early prediction of cell stress and death is a valuable tool for process characterization and efficient biomanufacturing control. A representative set of six proteins, namely GPDH, PRDX1, LGALS1, CFL1, TAGLN2 and MDH, which were identified in a previous CHO-K1 cell death model using discovery LC-MS^E was translated into a targeted liquid chromatography multiple reaction monitoring mass spectrometry (LC-MRM-MS) platform and verified. The universality of the markers was confirmed in a cell growth model for which three Chinese hamster ovary host cell lines (CHO-K1, CHO-S, CHO-DG44) were grown in batch culture in two different types of basal media. LC-MRM-MS was also applied to spent media (n = 39) from four perfusion biomanufacturing series. Stable isotope-labelled peptide analogues and a stable isotope-labelled monoclonal antibody were used for improved protein quantitation and simultaneous monitoring of the workflow reproducibility. Significant increases in protein concentrations were observed for all viability marker proteins upon increased dead cell numbers and allowed for discrimination of spent media with dead cell densities below and above 1 × 10⁶ dead cells/mL which highlights the potential of the selected viability marker proteins in bioprocess control. Graphical abstract Overview of the LC-MRM-MS workflow for the determination of proteomic markers in conditioned media from the bioreactor that correlate with CHO cell death.

Selected reaction monitoring approach for validating peptide biomarkers

We here describe a selected reaction monitoring (SRM)-based approach for the discovery and validation of peptide biomarkers for cancer. The first stage of this approach is the direct identification of candidate peptides through comparison of proteolytic peptides derived from the plasma of cancer patients or healthy individuals. Several hundred candidate peptides were identified through this method, providing challenges for choosing and validating the small number of peptides that might prove diagnostically useful. To accomplish this validation, we used 2D chromatography coupled with SRM of candidate peptides. We applied this approach, called sequential analysis of fractionated eluates by SRM (SAFE-SRM), to plasma from cancer patients and discovered two peptides encoded by the peptidyl-prolyl cis-trans isomerase A (PPIA) gene whose abundance was increased in the plasma of ovarian cancer patients. At optimal thresholds, elevated levels of at least one of these two peptides was detected in 43 (68.3%) of 63 women with ovarian cancer but in none of 50 healthy controls. In addition to providing a potential biomarker for ovarian cancer, this approach is generally applicable to the discovery of peptides characteristic of various disease states.

Lipid-Based Nutrient Supplements During Pregnancy and Lactation Did Not Affect Human Milk Oligosaccharides and Bioactive Proteins in a Randomized Trial

BACKGROUND

Human milk oligosaccharides (HMOs) and bioactive proteins are beneficial to infant health. Recent evidence suggests that maternal nutrition may affect the amount of HMOs and proteins in breast milk; however, the effect of nutrient supplementation on HMOs and bioactive proteins has not yet been well studied.

OBJECTIVE

We aimed to determine whether lipid-based nutrient supplements (LNSs) affect milk bioactive protein and HMO concentrations at 6 mo postpartum in women in rural Malawi. These are secondary outcomes of a previously published randomized controlled trial.

METHODS

Women were randomly assigned to consume either an iron and folic acid capsule (IFA) daily from ≤20 wk gestation until delivery, followed by placebo daily from delivery to 6 mo postpartum, or a multiple micronutrient (MMN) capsule or LNS daily from ≤20 wk gestation to 6 mo postpartum. Breast milk concentrations of total HMOs, sialylated HMOs, fucosylated HMOs, lactoferrin, lactalbumin, lysozymes, antitrypsin, immunoglobulin A, and osteopontin were analyzed at 6 mo postpartum (n = 647). Between-group differences in concentrations and in proportions of women classified as having low concentrations were tested.

RESULTS

HMO and bioactive protein concentrations did not differ between groups (P > 0.10 for all comparisons). At 6 mo postpartum, the proportions of women with low HMOs or bioactive proteins were not different between groups except for osteopontin. A lower proportion of women in the IFA group had low osteopontin compared with the LNS group after adjusting for covariates (OR: 0.5; 95% CI: 0.3, 0.9; P = 0.016).

CONCLUSION

The study findings do not support the hypothesis that supplementation with an LNS or MMN capsule during pregnancy and postpartum would increase HMO or bioactive milk proteins at 6 mo postpartum among Malawian women. This trial was registered at clinicaltrials.gov as NCT01239693.

Quantitative Mass Spectrometry Analysis of PD-L1 Protein Expression, N-glycosylation and Expression Stoichiometry with PD-1 and PD-L2 in Human Melanoma

Quantitative assessment of key proteins that control the tumor-immune interface is one of the most formidable analytical challenges in immunotherapeutics. We developed a targeted MS platform to quantify programmed cell death-1 (PD-1), programmed cell death 1 ligand 1 (PD-L1), and programmed cell death 1 ligand 2 (PD-L2) at fmol/microgram protein levels in formalin fixed, paraffin-embedded sections from 22 human melanomas. PD-L1 abundance ranged 50-fold, from ∼0.03 to 1.5 fmol/microgram protein and the parallel reaction monitoring (PRM) data were largely concordant with total PD-L1-positive cell content, as analyzed by immunohistochemistry (IHC) with the E1L3N antibody. PD-1 was measured at levels up to 20-fold lower than PD-L1, but the abundances were not significantly correlated (r² = 0.062, p = 0.264). PD-1 abundance was weakly correlated (r² = 0.3057, p = 0.009) with the fraction of lymphocytes and histiocytes in sections. PD-L2 was measured from 0.03 to 1.90 fmol/microgram protein and the ratio of PD-L2 to PD-L1 abundance ranged from 0.03 to 2.58. In 10 samples, PD-L2 was present at more than half the level of PD-L1, which suggests that PD-L2, a higher affinity PD-1 ligand, is sufficiently abundant to contribute to T-cell downregulation. We also identified five branched mannose and N-acetylglucosamine glycans at PD-L1 position N192 in all 22 samples. Extent of PD-L1 glycan modification varied by ∼10-fold and the melanoma with the highest PD-L1 protein abundance and most abundant glycan modification yielded a very low PD-L1 IHC estimate, thus suggesting that N-glycosylation may affect IHC measurement and PD-L1 function. Additional PRM analyses quantified immune checkpoint/co-regulator proteins LAG3, IDO1, TIM-3, VISTA, and CD40, which all displayed distinct expression independent of PD-1, PD-L1, and PD-L2. Targeted MS can provide a next-generation analysis platform to advance cancer immuno-therapeutic research and diagnostics.

Identification of Proteomic Features To Distinguish Benign Pulmonary Nodules from Lung Adenocarcinoma

We hypothesized that distinct protein expression features of benign and malignant pulmonary nodules may reveal novel candidate biomarkers for the early detection of lung cancer. We performed proteome profiling by liquid chromatography-tandem mass spectrometry to characterize 34 resected benign lung nodules, 24 untreated lung adenocarcinomas (ADCs), and biopsies of bronchial epithelium. Group comparisons identified 65 proteins that differentiate nodules from ADCs and normal bronchial epithelium and 66 proteins that differentiate ADCs from nodules and normal bronchial epithelium. We developed a multiplexed parallel reaction monitoring (PRM) assay to quantify a subset of 43 of these candidate biomarkers in an independent cohort of 20 benign nodules, 21 ADCs, and 20 normal bronchial biopsies. PRM analyses confirmed significant nodule-specific abundance of 10 proteins including ALOX5, ALOX5AP, CCL19, CILP1, COL5A2, ITGB2, ITGAX, PTPRE, S100A12, and SLC2A3 and significant ADC-specific abundance of CEACAM6, CRABP2, LAD1, PLOD2, and TMEM110-MUSTN1. Immunohistochemistry analyses for seven selected proteins performed on an independent set of tissue microarrays confirmed nodule-specific expression of ALOX5, ALOX5AP, ITGAX, and SLC2A3 and cancer-specific expression of CEACAM6. These studies illustrate the value of global and targeted proteomics in a systematic process to identify and qualify candidate biomarkers for noninvasive molecular diagnosis of lung cancer.

A selected reaction monitoring mass spectrometric assessment of biomarker candidates diagnosing large-cell neuroendocrine lung carcinoma by the scaling method using endogenous references

Selected reaction monitoring mass spectrometry (SRM-MS) -based semi-quantitation was performed to assess the validity of 46 selected candidate proteins for specifically diagnosing large-cell neuroendocrine lung carcinoma (LCNEC) and differentiating it from other lung cancer subtypes. The scaling method was applied in this study using specific SRM peak areas (AUCs) derived from the endogenous reference protein that normalizes all SRM AUCs obtained for the candidate proteins. In a screening verification study, we found that seven out of the 46 candidate proteins were statistically significant for the LCNEC phenotype, including 4F2hc cell surface antigen heavy chain (4F2hc/CD98) (p-ANOVA ≤ 0.0012), retinal dehydrogenase 1 (p-ANOVA ≤ 0.0029), apolipoprotein A-I (p-ANOVA ≤ 0.0004), β-enolase (p-ANOVA ≤ 0.0043), creatine kinase B-type (p-ANOVA ≤ 0.0070), and galectin-3-binding protein (p-ANOVA = 0.0080), and phosphatidylethanolamine-binding protein 1 (p-ANOVA ≤ 0.0012). In addition, we also identified candidate proteins specific to the small-cell lung carcinoma (SCLC) subtype. These candidates include brain acid soluble protein 1 (p-ANOVA < 0.0001) and γ-enolase (p-ANOVA ≤ 0.0013). This new relative quantitation-based approach utilizing the scaling method can be applied to assess hundreds of protein candidates obtained from discovery proteomic studies as a first step of the verification phase in biomarker development processes.

Targeted mass spectrometry: An emerging powerful approach to unblock the bottleneck in phosphoproteomics

Following the rapid expansion of the proteomics field, the investigation of post translational modifications (PTM) has become extremely popular changing our perspective of how proteins constantly fine tune cellular functions. Reversible protein phosphorylation plays a pivotal role in virtually all biological processes in the cell and it is one the most characterized PTM up to date. During the last decade, the development of phosphoprotein/phosphopeptide enrichment strategies and mass spectrometry (MS) technology has revolutionized the field of phosphoproteomics discovering thousands of new site-specific phosphorylations and unveiling unprecedented evidence about their modulation under distinct cellular conditions. The field has expanded so rapidly that the use of traditional methods to validate and characterize the biological role of the phosphosites is not feasible any longer. Targeted MS holds great promise for becoming the method of choice to study with high precision and sensitivity already known site-specific phosphorylation events. This review summarizes the contribution of large-scale unbiased MS analyses and highlights the need of targeted MS-based approaches for follow-up investigation. Additionally, the article illustrates the biological relevance of protein phosphorylation by providing examples of disease-related phosphorylation events and emphasizes the benefits of applying targeted MS in clinics for disease diagnosis, prognosis and drug-response evaluation.

Harnessing the power of proteomics for identification of oncogenic, druggable signalling pathways in cancer

INTRODUCTION

Genomic and transcriptomic profiling of tumours has revolutionised our understanding of cancer. However, the majority of tumours possess multiple mutations, and determining which oncogene, or even which pathway, to target is difficult. Proteomics is emerging as a powerful approach to identify the functionally important pathways driving these cancers, and how they can be targeted therapeutically. Areas covered: The authors provide a technical overview of mass spectrometry based approaches for proteomic profiling, and review the current and emerging strategies available for the identification of dysregulated networks, pathways, and drug targets in cancer cells, with a key focus on the ability to profile cancer kinomes. The potential applications of mass spectrometry in the clinic are also highlighted. Expert opinion: The addition of proteomic information to genomic platforms - 'proteogenomics' - is providing unparalleled insight in cancer cell biology. Application of improved mass spectrometry technology and methodology, in particular the ability to analyse post-translational modifications (the PTMome), is providing a more complete picture of the dysregulated networks in cancer, and uncovering novel therapeutic targets. While the application of proteomics to discovery research will continue to rise, improved workflow standardisation and reproducibility is required before mass spectrometry can enter routine clinical use.

A Timely Shift from Shotgun to Targeted Proteomics and How It Can Be Groundbreaking for Cancer Research

The fact that cancer is a leading cause of death all around the world has naturally sparked major efforts in the pursuit of novel and more efficient biomarkers that could better serve as diagnostic tools, prognostic predictors, or therapeutical targets in the battle against this type of disease. Mass spectrometry-based proteomics has proven itself as a robust and logical alternative to the immuno-based methods that once dominated the field. Nevertheless, intrinsic limitations of classic proteomic approaches such as the natural gap between shotgun discovery-based methods and clinically applicable results have called for the implementation of more direct, hypothesis-based studies such as those made available through targeted approaches, that might be able to streamline biomarker discovery and validation as a means to increase survivability of affected patients. In fact, the paradigm shifting potential of modern targeted proteomics applied to cancer research can be demonstrated by the large number of advancements and increasing examples of new and more useful biomarkers found during the course of this review in different aspects of cancer research. Out of the many studies dedicated to cancer biomarker discovery, we were able to devise some clear trends, such as the fact that breast cancer is the most common type of tumor studied and that most of the research for any given type of cancer is focused on the discovery diagnostic biomarkers, with the exception of those that rely on samples other than plasma and serum, which are generally aimed toward prognostic markers. Interestingly, the most common type of targeted approach is based on stable isotope dilution-selected reaction monitoring protocols for quantification of the target molecules. Overall, this reinforces that notion that targeted proteomics has already started to fulfill its role as a groundbreaking strategy that may enable researchers to catapult the number of viable, effective, and validated biomarkers in cancer clinical practice.

Metabolic signaling functions of ER-mitochondria contact sites: role in metabolic diseases

Beyond the maintenance of cellular homeostasis and the determination of cell fate, ER-mitochondria contact sites, defined as mitochondria-associated membranes (MAM), start to emerge as an important signaling hub that integrates nutrient and hormonal stimuli and adapts cellular metabolism. Here, we summarize the established structural and functional features of MAM and mainly focus on the latest breakthroughs highlighting a crucial role of organelle crosstalk in the control of metabolic homeostasis. Lastly, we discuss recent studies that have revealed the importance of MAM in not only metabolic diseases but also in other pathologies with disrupted metabolism, shedding light on potential common molecular mechanisms and leading hopefully to novel treatment strategies.

Adductomics Pipeline for Untargeted Analysis of Modifications to Cys34 of Human Serum Albumin

An important but understudied class of human exposures is comprised of reactive electrophiles that cannot be measured in vivo because they are short-lived. An avenue for assessing these meaningful exposures focuses on adducts from reactions with nucleophilic loci of blood proteins, particularly Cys34 of human serum albumin, which is the dominant scavenger of reactive electrophiles in serum. We developed an untargeted analytical scheme and bioinformatics pipeline for detecting, quantitating, and annotating Cys34 adducts in tryptic digests of human serum/plasma. The pipeline interrogates tandem mass spectra to find signatures of the Cys34-containing peptide, obtains accurate masses of putative adducts, quantitates adduct levels relative to a "housekeeping peptide", and annotates modifications based on a combination of retention time, accurate mass, elemental composition, and database searches. We used the adductomics pipeline to characterize 43 adduct features in archived plasma from healthy human subjects and found several that were highly associated with smoking status, race, and other covariates. Since smoking is a strong risk factor for cancer and cardiovascular disease, our ability to discover adducts that distinguish smokers from nonsmokers with untargeted adductomics indicates that the pipeline is suitable for use in epidemiologic studies. In fact, adduct features were both positively and negatively associated with smoking, indicating that some adducts arise from reactions between Cys34 and constituents of cigarette smoke (e.g., ethylene oxide and acrylonitrile) while others (Cys34 oxidation products and disulfides) appear to reflect alterations in the serum redox state that resulted in reduced adduct levels in smokers.

Automated Microchromatography Enables Multiplexing of Immunoaffinity Enrichment of Peptides to Greater than 150 for Targeted MS-Based Assays

Immunoaffinity enrichment of peptides coupled with analysis by stable isotope dilution multiple reaction mass spectrometry has been shown to have analytical performance and detection limits suitable for many biomarker verification studies and biological applications. Prior studies have shown that antipeptide antibodies can be multiplexed up to 50 in a single assay without significant loss of performance. Achieving higher multiplex levels is relevant to all studies involving precious biological material as this minimizes the amount of sample that must be consumed to measure a given set of analytes and reduces the assay cost per analyte. Here we developed automated methods employing the Agilent AssayMAP Bravo microchromatography platform and used these methods to characterize the performance of immunoaffinity enrichment of peptides up to multiplex levels of 172. Median capture efficiency for the target peptides remained high (88%) even at levels of 150-plex and declined to 70% at 172-plex compared to antibody performance observed at standard lower multiplex levels (n = 25). Subsequently, we developed and analytically characterized a multiplexed immuno-multiple reaction monitoring-mass spectrometry (immuno-MRM-MS) assay (n = 110) and applied it to measure candidate protein biomarkers of cardiovascular disease in plasma of patients undergoing planned myocardial infarction. The median lower limit of detection of all peptides was 71.5 amol/μL (nM), and the coefficient of variation (CV) was less than 15% at the lower limit of quantification. The results demonstrate that high multiplexed immuno-MRM-MS assays are readily achievable using the optimized sample processing and peptide capture methods described here.

Oncogenic KRAS and BRAF Drive Metabolic Reprogramming in Colorectal Cancer

Metabolic reprogramming, in which altered utilization of glucose and glutamine supports rapid growth, is a hallmark of most cancers. Mutations in the oncogenes KRAS and BRAF drive metabolic reprogramming through enhanced glucose uptake, but the broader impact of these mutations on pathways of carbon metabolism is unknown. Global shotgun proteomic analysis of isogenic DLD-1 and RKO colon cancer cell lines expressing mutant and wild type KRAS or BRAF, respectively, failed to identify significant differences (at least 2-fold) in metabolic protein abundance. However, a multiplexed parallel reaction monitoring (PRM) strategy targeting 73 metabolic proteins identified significant protein abundance increases of 1.25-twofold in glycolysis, the nonoxidative pentose phosphate pathway, glutamine metabolism, and the phosphoserine biosynthetic pathway in cells with KRAS G13D mutations or BRAF V600E mutations. These alterations corresponded to mutant KRAS and BRAF-dependent increases in glucose uptake and lactate production. Metabolic reprogramming and glucose conversion to lactate in RKO cells were proportional to levels of BRAF V600E protein. In DLD-1 cells, these effects were independent of the ratio of KRAS G13D to KRAS wild type protein. A study of 8 KRAS wild type and 8 KRAS mutant human colon tumors confirmed the association of increased expression of glycolytic and glutamine metabolic proteins with KRAS mutant status. Metabolic reprogramming is driven largely by modest (<2-fold) alterations in protein expression, which are not readily detected by the global profiling methods most commonly employed in proteomic studies. The results indicate the superiority of more precise, multiplexed, pathway-targeted analyses to study functional proteome systems. Data are available through MassIVE Accession MSV000079486 at ftp://MSV000079486@massive.ucsd.edu.

Efficient Microscale Basic Reverse Phase Peptide Fractionation for Global and Targeted Proteomics

Analysis of small biological samples would benefit from an efficient microscale fractionation strategy that minimizes sample handling, transfer steps, and accompanying losses. Here we describe a microscale basic reverse phase liquid chromatographic (bRPLC) fractionation method that offers high reproducibility and efficiency for peptide mixtures from small (5-20 μg) samples. We applied our platform to detect differentially expressed proteins from lung tumor cell lines that are sensitive (11-18) and resistant (11-18R) to the tyrosine kinase inhibitor erlotinib. Label-free analyses of 5-20 μg samples yielded identifications of approximately 3,200 to 4,000 proteins with coefficients of variation of 1.9-8.9% in replicate analyses. iTRAQ analyses produced similar protein inventories. Label-free and iTRAQ analyses displayed high concordance in identifications of proteins differentially expressed in 11-18 and 11-18R cells. Micro-bRPLC fractionation of cell proteomes increased sensitivity by an average of 4.5-fold in targeted quantitation using parallel reaction monitoring for three representative receptor tyrosine kinases (EGFR, PDGFRA, and BMX), which are present at low abundance in 11-18 and 11-18R cells. These data illustrate the broad utility of micro-bRPLC fractionation for global and targeted proteomic analyses. Data are available through Proteome eXchange Accession PXD003604.

Apolipoprotein A1-Unique Peptide as a Diagnostic Biomarker for Acute Ischemic Stroke

Clinically-informative biomarkers of ischemic stroke are needed for rapid diagnosis and timely treatment. In the present study, APOA1 unique peptide (APOA1-UP), a novel peptide biomarker, was identified and quantified by multiple reaction monitoring (MRM) using labeled reference peptide (LRP). Serum samples of 94 patients in the ischemic stroke group and 37 patients in the non-stroke group were analyzed for the levels of total APOA1-UP, low density lipoprotein cholesterol (LDL-C), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and total cholesterol (TC). Median ratio of total APOA1-UP/LRP was 2.14 (interquartile range, 0.40) in the non-stroke group and 1.32 (0.44) in the ischemic stroke group (p < 0.0001). The serum level of total APOA1-UP was independently correlated with the presence of ischemic stroke by multivariate logistic regression analysis (p < 0.0001). From the receiver operating characteristic (ROC) curve, the area under the curve (AUC) was 0.9750 and the optimal cutoff value of the serum APOA1-UP level was 1.80, which yielded a sensitivity of 90.63% and a specificity of 97.14%. The diagnostic efficiency of HDL-C was lower, with an AUC of 0.7488. Therefore, the serum level of APOA1-UP is a diagnostic biomarker candidate for ischemic stroke in the early stage.

Assembly Dynamics and Stoichiometry of the Apoptosis Signal-regulating Kinase (ASK) Signalosome in Response to Electrophile Stress

Apoptosis signal-regulating kinase 1 (ASK1) is a key sensor kinase in the mitogen-activated protein kinase pathway that transduces cellular responses to oxidants and electrophiles. ASK1 is regulated by a large, dynamic multiprotein signalosome complex, potentially including over 90 reported ASK1-interacting proteins. We employed both shotgun and targeted mass spectrometry assays to catalogue the ASK1 protein-protein interactions in HEK-293 cells treated with the prototypical lipid electrophile 4-hydroxy-2-nonenal (HNE). Using both epitope-tagged overexpression and endogenous expression cell systems, we verified most of the previously reported ASK1 protein-protein interactions and identified 14 proteins that exhibited dynamic shifts in association with ASK1 in response to HNE stress. We used precise stable isotope dilution assays to quantify protein stoichiometry in the ASK signalosome complex and identified ASK2 at a 1:1 stoichiometric ratio with ASK1 and 14-3-3 proteins (YWHAQ, YWHAB, YWHAH, and YWHAE) collectively at a 0.5:1 ratio with ASK1 as the main components. Several other proteins, including ASK3, PARK7, PRDX1, and USP9X were detected with stoichiometries of 0.1:1 or less. These data support an ASK signalosome comprising a multimeric core complex of ASK1, ASK2, and 14-3-3 proteins, which dynamically engages other binding partners needed to mediate diverse stress-response signaling events. This study further demonstrates the value of combining global and targeted MS approaches to interrogate multiprotein complex composition and dynamics.

Quantitative Profiling of Protein Tyrosine Kinases in Human Cancer Cell Lines by Multiplexed Parallel Reaction Monitoring Assays

Protein tyrosine kinases (PTKs) play key roles in cellular signal transduction, cell cycle regulation, cell division, and cell differentiation. Dysregulation of PTK-activated pathways, often by receptor overexpression, gene amplification, or genetic mutation, is a causal factor underlying numerous cancers. In this study, we have developed a parallel reaction monitoring-based assay for quantitative profiling of 83 PTKs. The assay detects 308 proteotypic peptides from 54 receptor tyrosine kinases and 29 nonreceptor tyrosine kinases in a single run. Quantitative comparisons were based on the labeled reference peptide method. We implemented the assay in four cell models: 1) a comparison of proliferating versus epidermal growth factor-stimulated A431 cells, 2) a comparison of SW480Null (mutant APC) and SW480APC (APC restored) colon tumor cell lines, and 3) a comparison of 10 colorectal cancer cell lines with different genomic abnormalities, and 4) lung cancer cell lines with either susceptibility (11-18) or acquired resistance (11-18R) to the epidermal growth factor receptor tyrosine kinase inhibitor erlotinib. We observed distinct PTK expression changes that were induced by stimuli, genomic features or drug resistance, which were consistent with previous reports. However, most of the measured expression differences were novel observations. For example, acquired resistance to erlotinib in the 11-18 cell model was associated not only with previously reported up-regulation of MET, but also with up-regulation of FLK2 and down-regulation of LYN and PTK7. Immunoblot analyses and shotgun proteomics data were highly consistent with parallel reaction monitoring data. Multiplexed parallel reaction monitoring assays provide a targeted, systems-level profiling approach to evaluate cancer-related proteotypes and adaptations. Data are available through Proteome eXchange Accession PXD002706.

Parallel Reaction Monitoring: A Targeted Experiment Performed Using High Resolution and High Mass Accuracy Mass Spectrometry

The parallel reaction monitoring (PRM) assay has emerged as an alternative method of targeted quantification. The PRM assay is performed in a high resolution and high mass accuracy mode on a mass spectrometer. This review presents the features that make PRM a highly specific and selective method for targeted quantification using quadrupole-Orbitrap hybrid instruments. In addition, this review discusses the label-based and label-free methods of quantification that can be performed with the targeted approach.

Accuracy and Reproducibility in Quantification of Plasma Protein Concentrations by Mass Spectrometry without the Use of Isotopic Standards

Background

Quantitative proteomic analysis with mass spectrometry holds great promise for simultaneously quantifying proteins in various biosamples, such as human plasma. Thus far, studies addressing the reproducible measurement of endogenous protein concentrations in human plasma have focussed on targeted analyses employing isotopically labelled standards. Non-targeted proteomics, on the other hand, has been less employed to this end, even though it has been instrumental in discovery proteomics, generating large datasets in multiple fields of research.

Results

Using a non-targeted mass spectrometric assay (LCMS^E), we quantified abundant plasma proteins (43 mg/mL—40 ug/mL range) in human blood plasma specimens from 30 healthy volunteers and one blood serum sample (ProteomeXchange: PXD000347). Quantitative results were obtained by label-free mass spectrometry using a single internal standard to estimate protein concentrations. This approach resulted in quantitative results for 59 proteins (cut off ≥11 samples quantified) of which 41 proteins were quantified in all 31 samples and 23 of these with an inter-assay variability of ≤ 20%. Results for 7 apolipoproteins were compared with those obtained using isotope-labelled standards, while 12 proteins were compared to routine immunoassays. Comparison of quantitative data obtained by LCMS^E and immunoassays showed good to excellent correlations in relative protein abundance (r = 0.72–0.96) and comparable median concentrations for 8 out of 12 proteins tested. Plasma concentrations of 56 proteins determined by LCMS^E were of similar accuracy as those reported by targeted studies and 7 apolipoproteins quantified by isotope-labelled standards, when compared to reference concentrations from literature.

Conclusions

This study shows that LCMS^E offers good quantification of relative abundance as well as reasonable estimations of concentrations of abundant plasma proteins.

Development and Validation of a Multiplexed Protein Quantitation Assay for the Determination of Three Recombinant Proteins in Soybean Tissues by Liquid Chromatography with Tandem Mass Spectrometry

Currently, traditional immunochemistry technologies such as enzyme-linked immunosorbent assays (ELISA) are the predominant analytical tool used to measure levels of recombinant proteins expressed in genetically engineered (GE) plants. Recent advances in agricultural biotechnology have created a need to develop methods capable of selectively detecting and quantifying multiple proteins in complex matrices because of increasing numbers of transgenic proteins being coexpressed or "stacked" to achieve tolerance to multiple herbicides or to provide multiple modes of action for insect control. A multiplexing analytical method utilizing liquid chromatography with tandem mass spectrometry (LC-MS/MS) has been developed and validated to quantify three herbicide-tolerant proteins in soybean tissues: aryloxyalkanoate dioxygenase (AAD-12), 5-enol-pyruvylshikimate-3-phosphate synthase (2mEPSPS), and phosphinothricin acetyltransferase (PAT). Results from the validation showed high recovery and precision over multiple analysts and laboratories. Results from this method were comparable to those obtained with ELISA with respect to protein quantitation, and the described method was demonstrated to be suitable for multiplex quantitation of transgenic proteins in GE crops.

Targeted quantitative proteomic investigation employing multiple reaction monitoring on quantitative changes in proteins that regulate volatile biosynthesis of strawberry fruit at different ripening stages

A targeted quantitative proteomic investigation employing the multiple reaction monitoring (MRM, SRM) technique was conducted on strawberry fruit at different development stages. We investigated 22 proteins and isoforms from 32 peptides with 111 peptide transitions, which may be involved in the volatile aroma biosynthesis pathway. The normalized protein abundance was significantly changed in coincidence with increased volatile production and advanced fruit maturities. Among them, alcohol acyltransferase (AAT), quinone oxidoreductase (QR), malonyl Co-A decarboxylase, (MLYCD), pyruvate decarboxylase (PDC), acetyl Co-A carboxylase (ACCase), and acyl Co-A synthetase (ACAs) were increased significantly. Several alcohol dehydrogenases (ADHs), and 3-oxoacyl-ACP synthase were significantly decreased. Furthermore, the expression of seven genes related to strawberry volatile production was also investigated using real-time qPCR. Among the tested genes, QR, AAT, ACCase, OMT, PDC and ADH showed increased up-regulation during fruit ripening, while 3-isopropylmalate dehydrogenase (IMD) decreased. Strong correlation between quantitative proteomic data and gene expression suggested that AAT, QR, ACCase, and PDC played critical roles in volatile biosynthesis of strawberry during fruit ripening. Poor correlation between protein abundance and gene expression of ADH was found.

Identification of Site-Specific Stroke Biomarker Candidates by Laser Capture Microdissection and Labeled Reference Peptide

The search to date for accurate protein biomarkers in acute ischemic stroke has taken into consideration the stage and/or the size of infarction, but has not accounted for the site of stroke. In the present study, multiple reaction monitoring using labeled reference peptide (LRP) following laser capture microdissection (LCM) is used to identify site-specific protein biomarker candidates. In middle cerebral artery occlusion (MCAO) rat models, both intact and infarcted brain tissue was collected by LCM, followed by on-film digestion and semi-quantification using triple-quadrupole mass spectrometry. Thirty-four unique peptides were detected for the verification of 12 proteins in both tissue homogenates and LCM-captured samples. Six insoluble proteins, including neurofilament light polypeptide (NEFL), alpha-internexin (INA), microtubule-associated protein 2 (MAP2), myelin basic protein (MBP), myelin proteolipid protein (PLP) and 2′,3′-cyclic-nucleotide 3′-phosphodiesterase (CNP), were found to be site-specific. Soluble proteins, such as neuron-specific enolase (NSE) and ubiquitin carboxyl-terminal hydrolase isozyme L1 (UCHL1), and some insoluble proteins, including neurofilament heavy polypeptide (NEFH), glial fibrillary acidic protein (GFAP), microtubule-associated protein tau (MAPT) and tubulin β-3 chain (TUBB3), were found to be evenly distributed in the brain. Therefore, we conclude that some insoluble protein biomarkers for stroke are site-specific, and would make excellent candidates for the design and analysis of relevant clinical studies in the future.

A multiplexed, targeted mass spectrometry assay of the S100 protein family uncovers the isoform-specific expression in thyroid tumours

Background

Mounting evidence demonstrates a causal role for S100 proteins in tumourigenesis and several S100 isoforms have shown utility as biomarkers of several types of cancer. The S100 family is comprised of 21 small isoforms, many of them implicated in important cellular functions such as proliferation, motility and survival. Furthermore, in vivo experiments have proven the role of S100 proteins in tumour growth and disease progression, while other studies have shown their prognostic value and involvement in resistance to chemotherapy drugs. Taken together, all these aspects highlight S100 proteins as potential therapeutic targets and as a promising panel of cancer biomarkers. In this work, we have developed a mass spectrometry (MS)-based method for the multiplexed and specific analysis of the entire S100 protein family in tumour tissues and have applied it to investigate the expression of S100 isoforms in the context of thyroid cancer, the main endocrine malignancy.

Methods

Selected Reaction Monitoring (SRM)-MS and stable isotope labelling/label-free analysis were employed to investigate the expression of the 21 S100 protein isoforms in thyroid tissue samples. Specimens included 9 normal thyroid tissues and 27 tumour tissues consisting of 9 follicular adenomas (FA), 8 follicular carcinomas (FTC) and 10 papillary carcinomas (PTC).

Results

The multiplexed and targeted mass spectrometry method led to the detection of eleven S100 protein isoforms across all tissues. Label- and label-free analyses showed the same significant differences and results were confirmed by western blot. S100A6, S100A11 and its putative interaction partner annexin A1 showed the highest overexpression in PTC compared to normal thyroid. S100A13 was also elevated in PTC. Reduced S100A4 expression was observed in FA compared to all other tissues. FA and FTC showed reduction of S100A10 and annexin A2 expression.

Conclusions

Targeted mass spectrometry allows the multiplexed and specific analysis of S100 protein isoforms in tumour tissue specimens. It revealed S100A13 as a novel candidate PTC biomarker. Results show that S100A6, S100A11 and Annexin A1 could help discriminate follicular and papillary tumours. The diagnostic and functional significance of S100A4 and S100A10 reduction in follicular tumours requires further investigation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-015-1217-x) contains supplementary material, which is available to authorized users.

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.

An integrated quantification method to increase the precision, robustness, and resolution of protein measurement in human plasma samples

Background

Current quantification methods for mass spectrometry (MS)-based proteomics either do not provide sufficient control of variability or are difficult to implement for routine clinical testing.

Results

We present here an integrated quantification (InteQuan) method that better controls pre-analytical and analytical variability than the popular quantification method using stable isotope-labeled standard peptides (SISQuan). We quantified 16 lung cancer biomarker candidates in human plasma samples in three assessment studies, using immunoaffinity depletion coupled with multiple reaction monitoring (MRM) MS. InteQuan outperformed SISQuan in precision in all three studies and tolerated a two-fold difference in sample loading. The three studies lasted over six months and encountered major changes in experimental settings. Nevertheless, plasma proteins in low ng/ml to low μg/ml concentrations were measured with a median technical coefficient of variation (CV) of 11.9% using InteQuan. The corresponding median CV using SISQuan was 15.3% after linear fitting. Furthermore, InteQuan surpassed SISQuan in measuring biological difference among clinical samples and in distinguishing benign versus cancer plasma samples.

Conclusions

We demonstrated that InteQuan is a simple yet robust quantification method for MS-based quantitative proteomics, especially for applications in biomarker research and in routine clinical testing.

Electronic supplementary material

The online version of this article (doi:10.1186/1559-0275-12-3) contains supplementary material, which is available to authorized users.

Vitreous humor in the pathologic scope: insights from proteomic approaches

The vitreous humor (VH) is the largest component of the eye. It is a colorless, gelatinous, highly hydrated matrix that fills the posterior segment of the eye between the lens and retina in vertebrates. In VH, a diversity of proteins that can influence retinal physiology is present, including growth factors, hormones, proteins with transporter activity, and enzymes. More importantly, the protein composition of VH has been described as being altered in a number of disease states. Therefore, attempts aiming at establishing a map of VH proteins and detecting putative biomarkers for ocular illness or protein fluctuations with putative physiologic significance were conducted over the last two decades, using proteomic approaches. Proteomic strategies often involve gel-based or LC techniques as sample fractioning approaches, subsequently coupled with MS procedures. This set of studies resulted in the proteomic characterization of a range of ocular disease samples, with particular incidence on diabetic retinopathy. However, practical therapeutic applications arising from these studies are scarce at the moment. A pertinent example of therapeutic targets arising from VH proteomics has emerged concerning vasoproliferative factors present in the vitreous, which should be involved in neovascularization and subsequent fibrovascular proliferation of the retina, in ocular disease context. Therefore, this review attempts to sum up the information acquired from the proteomic approaches to ocular disease conducted in VH samples, highlighting its clinical potential for disclosing ocular disease mechanisms and engendering pharmacological therapeutic treatments.