Multiple reaction monitoring (MRM): principles and application to coronary artery disease

A novel SPE-UPLC-MS/MS-based assay for the selective, simultaneous quantification of xylosyltransferase-I and -II activity

Xylosyltransferase-I and -II (XT-I, -II) possess a central role during the glycosylation of proteoglycans (PGs). They catalyze the formation of an O-glycosidic bond between the xylosyl residue of uridinediphosphate-xylose and the core protein of a PG. Thereafter, three following glycosyltransferases lead to the generation of a tetrasaccharide linker, which connects the PG core protein to the respective glycosaminoglycan. The selective quantification of XT-I and XT-II activity is of biological and clinical interest due to their association with fibrotic processes and skeletal dysplasia. There is no assay available to date that simultaneously determines the activity of the two XT isoforms. Although an XT-I selective UPLC MS/MS-based assay was published by Fischer et al., in 2021, the determination of XT-II activity can only be performed simultaneously by the improved assay presented here. To establish the assay, two synthetic peptides, selectively xylosylated by the respective isoform, were identified and the associated measurement parameters for the mass spectrometer were optimized. In addition, the quantitative range of the xylosylated peptides were validated, and the incubation time of the enzyme reaction was optimized for cell culture samples and human sera. The specific enzyme kinetics (KM and Vmax) of the respective XT isoform for the two peptides were also determined. Subsequently, a mathematical model was developed, allowing the simultaneous determination of XT-I and XT-II activity from the chromatographic results. Summarized, a mass spectrometric method suitable for the simultaneous analysis of XT-I and XT-II activity in cell culture lysates, supernatants and human sera was successfully developed.

Synthesis and Trace-Level Quantification of Mutagenic and Cohort-of-Concern Ciprofloxacin Nitroso Drug Substance-Related Impurities (NDSRIs) and Other Nitroso Impurities Using UPLC-ESI-MS/MS-Method Optimization Using I-Optimal Mixture Design

Globally, the pharmaceutical industry has been facing challenges from nitroso drug substance-related impurities (NDSRIs). In the current study, we synthesized and developed a rapid new UPLC-MS/MS method for the trace-level quantification of ciprofloxacin NDSRIs and a couple of N-nitroso impurities simultaneously. (Q)-SAR methodology was employed to assess and categorize the genotoxicity of all ciprofloxacin N-nitroso impurities. The projected results were positive, and the cohort of concern (CoC) for all three N-nitroso impurities indicates potential genotoxicity. AQbD-driven I-optimal mixture design was used to optimize the mixture of solvents in the method. The chromatographic resolution was accomplished using an Agilent Poroshell 120 Aq-C18 column (150 mm × 4.6 mm, 2.7 μm) in isocratic elution mode with 0.1% formic acid in a mixture of water, acetonitrile, and methanol in the ratio of 475:500:25 v/v/v at a flow rate of 0.5 mL/min. Quantification was carried out using triple quadrupole mass detection with electrospray ionization (ESI) in a multiple reaction monitoring technique. The finalized method was validated successfully, affording ICH guidelines. All N-nitroso impurities revealed excellent linearity over the concentration range of 0.00125-0.0250 ppm. The Pearson correlation coefficient of each N-nitroso impurity was >0.999. The method accuracy recoveries ranged from 93.98 to 108.08% for the aforementioned N-nitrosamine impurities. Furthermore, the method was effectively applied to quantify N-nitrosamine impurities simultaneously in commercially available formulated samples, with its efficiency recurring at trace levels. Thus, the current method is capable of determining the trace levels of three N-nitroso ciprofloxacin impurities simultaneously from the marketed tablet dosage forms for commercial release and stability testing.

Systematic Evaluation of Chromatographic Peak Quality for Targeted Mass Spectrometry via Variational Autoencoder

Targeted mass spectrometry is a powerful technique for quantifying specific proteins or metabolites in complex biological samples. Accurate peak picking is a critical step as it determines the absolute abundance of each analyte by integrating the area under the picked peaks. Although automated software exists for handling such complex tasks, manual intervention is often required to rectify potential errors like misclassification or mis-picking events, which can significantly affect quantification accuracy. Therefore, it is necessary to develop objective scoring functions to evaluate peak-picking results and to identify problematic cases for further inspection. In this study, we present targeted mass spectrometry quality encoder (TMSQE), a data-driven scoring function that summarizes peak quality in three types: transition level, peak group level, and consistency level across samples. Through unsupervised learning from large data sets containing 1,703,827 peak groups, TMSQE establishes a reliable standard for systematic and objective evaluations of chromatographic peak quality in targeted mass spectrometry. TMSQE shows a high degree of consistency with expert experiences and can efficiently capture problematic cases after the automated software. Furthermore, we demonstrate the generalizability of TMSQE by successfully applying it to various data sets, including both peptide and metabolite data sets. Our proposed scoring approach provides a reliable solution for consistent and accurate peak quality evaluation, facilitating peak quality control for targeted mass spectrometry.

Quantitative analysis of therapeutic proteins in biological fluids: recent advancement in analytical techniques

Pharmaceutical application of therapeutic proteins has been continuously expanded for the treatment of various diseases. Efficient and reliable bioanalytical methods are essential to expedite the identification and successful clinical development of therapeutic proteins. In particular, selective quantitative assays in a high-throughput format are critical for the pharmacokinetic and pharmacodynamic evaluation of protein drugs and to meet the regulatory requirements for new drug approval. However, the inherent complexity of proteins and many interfering substances presented in biological matrices have a great impact on the specificity, sensitivity, accuracy, and robustness of analytical assays, thereby hindering the quantification of proteins. To overcome these issues, various protein assays and sample preparation methods are currently available in a medium- or high-throughput format. While there is no standard or universal approach suitable for all circumstances, a liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay often becomes a method of choice for the identification and quantitative analysis of therapeutic proteins in complex biological samples, owing to its high sensitivity, specificity, and throughput. Accordingly, its application as an essential analytical tool is continuously expanded in pharmaceutical R&D processes. Proper sample preparation is also important since clean samples can minimize the interference from co-existing substances and improve the specificity and sensitivity of LC-MS/MS assays. A combination of different methods can be utilized to improve bioanalytical performance and ensure more accurate quantification. This review provides an overview of various protein assays and sample preparation methods, with particular emphasis on quantitative protein analysis by LC-MS/MS.

Exploring the cardiac ECM during fibrosis: A new era with next-gen proteomics

Extracellular matrix (ECM) plays a critical role in maintaining elasticity in cardiac tissues. Elasticity is required in the heart for properly pumping blood to the whole body. Dysregulated ECM remodeling causes fibrosis in the cardiac tissues. Cardiac fibrosis leads to stiffness in the heart tissues, resulting in heart failure. During cardiac fibrosis, ECM proteins get excessively deposited in the cardiac tissues. In the ECM, cardiac fibroblast proliferates into myofibroblast upon various kinds of stimulations. Fibroblast activation (myofibroblast) contributes majorly toward cardiac fibrosis. Other than cardiac fibroblasts, cardiomyocytes, epithelial/endothelial cells, and immune system cells can also contribute to cardiac fibrosis. Alteration in the expression of the ECM core and ECM-modifier proteins causes different types of cardiac fibrosis. These different components of ECM culminated into different pathways inducing transdifferentiation of cardiac fibroblast into myofibroblast. In this review, we summarize the role of different ECM components during cardiac fibrosis progression leading to heart failure. Furthermore, we highlight the importance of applying mass-spectrometry-based proteomics to understand the key changes occurring in the ECM during fibrotic progression. Next-gen proteomics studies will broaden the potential to identify key targets to combat cardiac fibrosis in order to achieve precise medicine-development in the future.

Techniques, perspectives, and challenges of bioactive peptide generation: A comprehensive systematic review

Due to the digestible refractory and absorbable structures of bioactive peptides (BPs), they could induce notable biological impacts on the living organism. In this regard, the current study was devoted to providing an overview regarding the available methods for BPs generation by the aid of a systematic review conducted on the published articles up to April 2019. In this context, the PubMed and Scopus databases were screened to retrieve the related publications. According to the results, although the characterization of BPs mainly has been performed using enzymatic and microbial in-vitro methods, they cannot be considered as suitable techniques for further stimulation of digestion in the gastrointestinal tract. Therefore, new approaches for both in-vivo and in-silico methods for BPs identification should be developed to overcome the obstacles that belonged to the current methods. The purpose of this review was to compile the recent analytical methods applied for studying various aspects of food-derived biopeptides, and emphasizing generation at in vitro, in vivo, and in silico.

A Bordetella pertussis MgtC homolog plays a role in the intracellular survival

Bordetella pertussis, the causative agent of whooping cough, has the capability to survive inside the host cells. This process requires efficient adaptation of the pathogen to the intracellular environment and the associated stress. Among the proteins produced by the intracellular B. pertussis we identified a protein (BP0414) that shares homology with MgtC, a protein which was previously shown to be involved in the intracellular survival of other pathogens. To explore if BP0414 plays a role in B. pertussis intracellular survival a mutant strain defective in the production of this protein was constructed. Using standard in vitro growth conditions we found that BP0414 is required for B. pertussis growth under low magnesium availability or low pH, two environmental conditions that this pathogen might face within the host cell. Intracellular survival studies showed that MgtC is indeed involved in B. pertussis viability inside the macrophages. The use of bafilomycin A1, which inhibits phagosome acidification, abolished the survival defect of the mgtC deficient mutant strain suggesting that in intracellular B. pertussis the role of MgtC protein is mainly related to the bacterial adaptation to the acidic conditions found inside the of phagosomes. Overall, this work provides an insight into the importance of MgtC in B. pertussis pathogenesis and its contribution to bacterial survival within immune cells.

Plasma Proteomics for Epidemiology: Increasing Throughput With Standard-Flow Rates

BACKGROUND

Mass spectrometry is selective and sensitive, permitting routine quantification of multiple plasma proteins. However, commonly used nanoflow liquid chromatography (LC) approaches hamper sample throughput, reproducibility, and robustness. For this reason, most publications using plasma proteomics to date are small in study size.

METHODS AND RESULTS

Here, we tested a standard-flow LC mass spectrometry (MS) method using multiple reaction monitoring for the application to large epidemiological cohorts. We have reduced the LC-MS run time to almost a third of the nanoflow LC-MS approach. On the basis of a comparison of the quantification of 100 plasma proteins in >1500 LC-MS runs, the SD range of the retention time during continuous operation was substantially lower with the standard-flow LC-MS (<0.05 minutes) compared with the nanoflow LC-MS method (0.26-0.44 minutes). In addition, the standard-flow LC method also offered less variation in protein measurements. However, 5× more sample volume was required to achieve similar sensitivity. Two different commercial multiple reaction monitoring kits and an antibody-based multiplexing kit were used to compare the apolipoprotein measurements in a subset of samples. In general, good agreement was observed between the 2 multiple reaction monitoring kits, but some of the multiple reaction monitoring-based measurements differed from antibody-based assays.

CONCLUSIONS

The multiplexing capability of LC-MS combined with a standard-flow method increases throughput and reduces the costs of large-scale protein measurements in epidemiological cohorts, but protein rather than peptide standards will be required for defined absolute proteoform quantification.

Wisdom of artificial crowds feature selection in untargeted metabolomics: An application to the development of a blood-based diagnostic test for thrombotic myocardial infarction

INTRODUCTION

Heart disease remains a leading cause of global mortality. While acute myocardial infarction (colloquially: heart attack), has multiple proximate causes, proximate etiology cannot be determined by a blood-based diagnostic test. We enrolled a suitable patient cohort and conducted a non-targeted quantification of plasma metabolites by mass spectrometry for developing a test that can differentiate between thrombotic MI, non-thrombotic MI, and stable disease. A significant challenge in developing such a diagnostic test is solving the NP-hard problem of feature selection for constructing an optimal statistical classifier.

OBJECTIVE

We employed a Wisdom of Artificial Crowds (WoAC) strategy for solving the feature selection problem and evaluated the accuracy and parsimony of downstream classifiers in comparison with traditional feature selection techniques including the Lasso and selection using Random Forest variable importance criteria.

MATERIALS AND METHODS

Artificial Crowd Wisdom was generated via aggregation of the best solutions from independent and diverse genetic algorithm populations that were initialized with bootstrapping and a random subspaces constraint.

RESULTS/CONCLUSIONS

Strong evidence was observed that a statistical classifier utilizing WoAC feature selection can discriminate between human subjects presenting with thrombotic MI, non-thrombotic MI, and stable Coronary Artery Disease given abundances of selected plasma metabolites. Utilizing the abundances of twenty selected metabolites, a leave-one-out cross-validation estimated misclassification rate of 2.6% was observed. However, the WoAC feature selection strategy did not perform better than the Lasso over the current study.

A new mass spectrometry-based method for the quantification of histones in plasma from septic shock patients

The aim of this study was to develop a novel method to detect circulating histones H3 and H2B in plasma based on multiple reaction monitoring targeted mass spectrometry and a multiple reaction monitoring approach (MRM-MS) for its clinical application in critical bacteriaemic septic shock patients. Plasma samples from 17 septic shock patients with confirmed bacteraemia and 10 healthy controls were analysed by an MRM-MS method, which specifically detects presence of histones H3 and H2B. By an internal standard, it was possible to quantify the concentration of circulating histones in plasma, which were significantly higher in patients, and thus confirmed their potential as biomarkers for diagnosing septic shock. After comparing surviving patients and non-survivors, a correlation was found between higher levels of circulating histones and unfavourable outcome. Indeed, histone H3 proved a more efficient and sensitive biomarker for septic shock prognosis. In conclusion, these findings suggest the accuracy of the MRM-MS technique and stable isotope labelled peptides to detect and quantify circulating plasma histones H2B and H3. This method may be used for early septic shock diagnoses and for the prognosis of fatal outcomes.

Traditional approaches versus mass spectrometry in bacterial identification and typing

Biochemical methods such as metabolite testing and serotyping are traditionally used in clinical microbiology laboratories to identify and categorize microorganisms. Due to the large variety of bacteria, identifying representative metabolites is tedious, while raising high-quality antisera or antibodies unique to specific biomarkers used in serotyping is very challenging, sometimes even impossible. Although serotyping is a certified approach for differentiating bacteria such as E. coli and Salmonella at the subspecies level, the method is tedious, laborious, and not practical during an infectious disease outbreak. Mass spectrometry (MS) platforms, especially matrix assisted laser desorption and ionization-time of flight mass spectrometry (MALDI-TOF-MS), have recently become popular in the field of bacterial identification due to their fast speed and low cost. In the past few years, we have used liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based approaches to solve various problems hindering serotyping and have overcome some insufficiencies of the MALDI-TOF-MS platform. The current article aims to review the characteristics, advantages, and disadvantages of MS-based platforms over traditional approaches in bacterial identification and categorization.

Towards reproducible MRM based biomarker discovery using dried blood spots

There is an increasing interest in the use of dried blood spot (DBS) sampling and multiple reaction monitoring in proteomics. Although several groups have explored the utility of DBS by focusing on protein detection, the reproducibility of the approach and whether it can be used for biomarker discovery in high throughput studies is yet to be determined. We assessed the reproducibility of multiplexed targeted protein measurements in DBS compared to serum. Eighty-two medium to high abundance proteins were monitored in a number of technical and biological replicates. Importantly, as part of the data analysis, several statistical quality control approaches were evaluated to detect inaccurate transitions. After implementing statistical quality control measures, the median CV on the original scale for all detected peptides in DBS was 13.2% and in Serum 8.8%. We also found a strong correlation (r = 0.72) between relative peptide abundance measured in DBS and serum. The combination of minimally invasive sample collection with a highly specific and sensitive mass spectrometry (MS) technique allows for targeted quantification of multiple proteins in a single MS run. This approach has the potential to fundamentally change clinical proteomics and personalized medicine by facilitating large-scale studies.

Recent development of mass spectrometry and proteomics applications in identification and typing of bacteria

Identification and typing of bacteria occupy a large fraction of time and work in clinical microbiology laboratories. With the certification of some MS platforms in recent years, more applications and tests of MS‐based diagnosis methods for bacteria identification and typing have been created, not only on well‐accepted MALDI‐TOF‐MS‐based fingerprint matches, but also on solving the insufficiencies of MALDI‐TOF‐MS‐based platforms and advancing the technology to areas such as targeted MS identification and typing of bacteria, bacterial toxin identification, antibiotics susceptibility/resistance tests, and MS‐based diagnostic method development on unique bacteria such as Clostridium and Mycobacteria. This review summarizes the recent development in MS platforms and applications in bacteria identification and typing of common pathogenic bacteria.

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.

Quantitative proteomics in cardiovascular research: global and targeted strategies

Extensive technical advances in the past decade have substantially expanded quantitative proteomics in cardiovascular research. This has great promise for elucidating the mechanisms of cardiovascular diseases and the discovery of cardiac biomarkers used for diagnosis and treatment evaluation. Global and targeted proteomics are the two major avenues of quantitative proteomics. While global approaches enable unbiased discovery of altered proteins via relative quantification at the proteome level, targeted techniques provide higher sensitivity and accuracy, and are capable of multiplexed absolute quantification in numerous clinical/biological samples. While promising, technical challenges need to be overcome to enable full utilization of these techniques in cardiovascular medicine. Here, we discuss recent advances in quantitative proteomics and summarize applications in cardiovascular research with an emphasis on biomarker discovery and elucidating molecular mechanisms of disease. We propose the integration of global and targeted strategies as a high-throughput pipeline for cardiovascular proteomics. Targeted approaches enable rapid, extensive validation of biomarker candidates discovered by global proteomics. These approaches provide a promising alternative to immunoassays and other low-throughput means currently used for limited validation.

Mass spectrometry based biomarker discovery, verification, and validation--quality assurance and control of protein biomarker assays

In its early years, mass spectrometry (MS)-based proteomics focused on the cataloging of proteins found in different species or different tissues. By 2005, proteomics was being used for protein quantitation, typically based on "proteotypic" peptides which act as surrogates for the parent proteins. Biomarker discovery is usually done by non-targeted "shotgun" proteomics, using relative quantitation methods to determine protein expression changes that correlate with disease (output given as "up-or-down regulation" or "fold-increases"). MS-based techniques can also perform "absolute" quantitation which is required for clinical applications (output given as protein concentrations). Here we describe the differences between these methods, factors that affect the precision and accuracy of the results, and some examples of recent studies using MS-based proteomics to verify cancer-related biomarkers.

Proteomics and metabolomics for mechanistic insights and biomarker discovery in cardiovascular disease

In the last decade, proteomics and metabolomics have contributed substantially to our understanding of cardiovascular diseases. The unbiased assessment of pathophysiological processes without a priori assumptions complements other molecular biology techniques that are currently used in a reductionist approach. In this review, we highlight some of the "omics" methods used to assess protein and metabolite changes in cardiovascular disease. A discrete biological function is very rarely attributed to a single molecule; more often it is the combined input of many proteins. In contrast to the reductionist approach, in which molecules are studied individually, "omics" platforms allow the study of more complex interactions in biological systems. Combining proteomics and metabolomics to quantify changes in metabolites and their corresponding enzymes will advance our understanding of pathophysiological mechanisms and aid the identification of novel biomarkers for cardiovascular disease.