Decoding the Challenges: navigating Intact Peptide Mass Spectrometry-Based Analysis for Biological Applications

Quantitative analysis of peptides in biological fluids offers a high diagnostic and prognostic tool to reflect the pathophysiological condition of the patient. Recently, methods based on liquid chromatography coupled with mass spectrometry (LC-MS) for the quantitative determination of intact peptides have been replacing traditionally used ligand-binding assays, which suffer from cross-reactivity issues. The use of "top-down" analysis of peptides is rapidly increasing since it does not undergo incomplete or non-reproducible digestion like "bottom-up" approaches. However, the low abundance of peptides and their peculiar characteristics, as well as the complexity of biological fluids, make their quantification challenging. Herein, the analytical pitfalls that may be encountered during the development of an LC-MS method for the analysis of intact peptides in biological fluids are discussed. Challenges in the pre-analytical phase, stability after sampling and sample processing, significantly impact the accuracy of peptide quantification. Emerging techniques, such as microextractions, are becoming crucial for improved sample cleanup and enrichment of target analytes. A comparison between the roles of high-resolution and low-resolution mass spectrometry in the quantification of intact peptides, as well as the introduction of supercharging reagents to enhance ionization, will be discussed.

A Trapping-Micro-LC-FAIMS/dCV-MS Strategy for Ultrasensitive and Robust Targeted Quantification of Protein Drugs and Biomarkers

The sensitivity of LC-MS in quantifying target proteins in plasma/tissues is significantly hindered by coeluted matrix interferences. While antibody-based immuno-enrichment effectively reduces interferences, developing and optimizing antibodies are often time-consuming and costly. Here, by leveraging the orthogonal separation capability of Field Asymmetric Ion Mobility Spectrometry (FAIMS), we developed a FAIMS/differential-compensation-voltage (FAIMS/dCV) method for antibody-free, robust, and ultrasensitive quantification of target proteins directly from plasma/tissue digests. By comparing the intensity-CV profiles of the target vs coeluted endogenous interferences, the FAIMS/dCV approach identifies the optimal CV for quantification of each target protein, thus maximizing the signal-to-noise ratio (S/N). Compared to quantification without FAIMS, this technique dramatically reduces endogenous interferences, showing a median improvement of the S/N by 14.8-fold for the quantification of 17 representative protein drugs and biomarkers in plasma or tissues and a 5.2-fold median increase in S/N over conventional FAIMS approach, which uses the peak CV of each target. We also discovered that the established CV parameters remain consistent over months and are matrix-independent, affirming the robustness of the developed FAIMS/dCV method and the transferability of the method across matrices. The developed method was successfully demonstrated in three applications: the quantification of monoclonal antibodies with subng/mL LOQ in plasma, an investigation of the time courses of evolocumab and its target PCSK9 in a preclinical setting, and a clinical investigation of low abundance obesity-related biomarkers. This innovative and easy-to-use method has extensive potential in clinical and pharmaceutical research, particularly where sensitive and high-throughput quantification of protein drugs and biomarkers is required.

PANAMA-enabled high-sensitivity dual nanoflow LC-MS metabolomics and proteomics analysis

High-sensitivity nanoflow liquid chromatography (nLC) is seldom employed in untargeted metabolomics because current sample preparation techniques are inefficient at preventing nanocapillary column performance degradation. Here, we describe an nLC-based tandem mass spectrometry workflow that enables seamless joint analysis and integration of metabolomics (including lipidomics) and proteomics from the same samples without instrument duplication. This workflow is based on a robust solid-phase micro-extraction step for routine sample cleanup and bioactive molecule enrichment. Our method, termed proteomic and nanoflow metabolomic analysis (PANAMA), improves compound resolution and detection sensitivity without compromising the depth of coverage as compared with existing widely used analytical procedures. Notably, PANAMA can be applied to a broad array of specimens, including biofluids, cell lines, and tissue samples. It generates high-quality, information-rich metabolite-protein datasets while bypassing the need for specialized instrumentation.

Cyclic Ion Mobility-Mass Spectrometry and Tandem Collision Induced Unfolding for Quantification of Elusive Protein Biomarkers

Sensitive analytical techniques that are capable of detecting and quantifying disease-associated biomolecules are indispensable in our efforts to understand disease mechanisms and guide therapeutic intervention through early detection, accurate diagnosis, and effective monitoring of disease. Parkinson's Disease (PD), for example, is one of the most prominent neurodegenerative disorders in the world, but the diagnosis of PD has primarily been based on the observation of clinical symptoms. The protein α-synuclein (α-syn) has emerged as a promising biomarker candidate for PD, but a lack of analytical methods to measure complex disease-associated variants of α-syn has prevented its widespread use as a biomarker. Antibody-based methods such as immunoassays and mass spectrometry-based approaches have been used to measure a limited number of α-syn forms; however, these methods fail to differentiate variants of α-syn that display subtle differences in only the sequence and structure. In this work, we developed a cyclic ion mobility-mass spectrometry method that combines multiple stages of activation and timed ion selection to quantify α-syn variants using both mass- and structure-based measurements. This method can allow for the quantification of several α-syn variants present at physiological levels in biological fluid. Taken together, this approach can be used to galvanize future efforts aimed at understanding the underlying mechanisms of PD and serves as a starting point for the development of future protein-structure-based diagnostics and therapeutic interventions.

Assessment and incorporation of in vitro correlates to pharmacokinetic outcomes in antibody developability workflows

In vitro assessments for the prediction of pharmacokinetic (PK) behavior of biotherapeutics can help identify corresponding liabilities significantly earlier in the discovery timeline. This can minimize the need for extensive early in vivo PK characterization, thereby reducing animal usage and optimizing resources. In this study, we recommend bolstering classical developability workflows with in vitro measures correlated with PK. In agreement with current literature, in vitro measures assessing nonspecific interactions, self-interaction, and FcRn interaction are demonstrated to have the highest correlations to clearance in hFcRn Tg32 mice. Crucially, the dataset used in this study has broad sequence diversity and a range of physicochemical properties, adding robustness to our recommendations. Finally, we demonstrate a computational approach that combines multiple in vitro measurements with a multivariate regression model to improve the correlation to PK compared to any individual assessment. Our work demonstrates that a judicious choice of high throughput in vitro measurements and computational predictions enables the prioritization of candidate molecules with desired PK properties.

A diagnostic electrochemical aptasensor development for sCD80 protein detection in human serum

Elevating soluble CD80 (sCD80) in human serum is a natural response to autoimmune diseases such as rheumatoid arthritis (RA). The level of sCD80 is associated with RA development and prognosis; therefore, it is potentially used as a biomarker. sCD80 is commonly measured in human serum using immunoassays (e.g., ELISA) with multiple drawbacks, mainly cross-reactivity. Aptamer-based biosensors (aptasensors) development for quantifying and detecting different biological molecules demonstrates applicability in next-generation medicine and biomarker detection. Herein, we selected a specific aptamer for sCD80 by conventional in-vitro selection process (SELEX) with the high-affinity aptamer (Kd = 47.69 nM). A sensitive aptasensor, for the first time, was developed on a screen-printed gold electrode (AuSPE) platform compatible with easy-to-use label-free electrochemical impedance spectroscopy. The immobilization of the aptamer on the gold surface and the presence of sCD80 in a complex with the aptamer were characterized by photo-induced force microscopy, which revealed the uniform assembly of the aptamer monolayer and the distribution of sCD80 on the electrode surface. The developed aptasensor showed a linear performance (0.025-10.0 nM of protein) with a detection limit of 8.0 pM. Furthermore, the aptasensor was tested in a biological matrix, where a linear signal was observed for the increased amount of spiked sCD80 (R2 = 0.9887). The recovery of the spiked amounts ranged from 105 to 125% with coefficient of variation (CV%) <7%, which supported the applicability of this sensor in detecting sCD80 for diagnosis.

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.

Development of a rapid and specific MALDI-TOF mass spectrometric assay for SARS-CoV-2 detection

We have developed a rapid and highly specific assay for detecting and monitoring SARS-CoV-2 infections by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). As MALDI-TOF mass spectrometers are available in a clinical setting, our assay has the potential to serve as alternative to the commonly used reverse transcriptase quantitative polymerase chain reaction (RT-qPCR). Sample preparation prior to MALDI-TOF-MS involves the tryptic digestion of SARS-CoV-2 proteins, followed by an enrichment of virus-specific peptides from SARS-CoV-2 nucleoprotein via magnetic antibody beads. Our MALDI-TOF-MS method allows the detection of SARS-CoV-2 nucleoprotein in sample collection medium as low as 8 amol/µl. MALDI-TOF mass spectra are obtained in just a few seconds, which makes our MS-based assay suitable for a high-throughput screening of SARS-CoV-2 in healthcare facilities in addition to PCR. Due to the specific detection of virus peptides, different SARS-CoV-2 variants are readily distinguished from each other. Specifically, we show that our MALDI-TOF-MS assay discriminates SARS-CoV-2 strain B.1.617.2 "delta variant" from all other variants in patients' samples, making our method highly valuable to monitor the emergence of new virus variants.

Enhanced Pharmacokinetic Bioanalysis of Antibody-drug Conjugates using Hybrid Immunoaffinity Capture and Microflow LC-MS/MS

The increasing complexity and diversity of antibody-drug conjugates (ADCs) have led to a need for comprehensive and informative bioanalytical methods to enhance pharmacokinetic (PK) understanding. This study aimed to evaluate the feasibility of a hybrid immunoaffinity (IA) capture microflow LC-MS/MS (μLC-MS/MS) method for ADC analysis, utilizing a minimal sample volume for PK assessments in a preclinical study. A robust workflow was established for the quantitative analysis of ADCs by the implementation of solid-phase extraction (SPE) and semi-automation in µLC-MS/MS. Utilizing the µLC-MS/MS approach in conjunction with 1 µL of ADC-dosed mouse plasma sample volume, standard curves of two representative surrogate peptides for total antibody (heavy chain, HC) and intact antibody (light chain, LC) ranged from 1.00 ng/mL (LLOQ) to 5000 ng/mL with correlation coefficients (r2) values of > 0.99. The linear range of the standard curve for payload as a surrogate for the concentration of total ADC was from 0.5 ng/mL (LLOQ) to 2000 ng/mL with high accuracy and precision (< 10% CV at all concentrations). Moreover, a high correlation of concentrations of total antibody between two assay approaches (µLC-MS and ELISA) was achieved with less than 20% difference at all time points, indicating that the two methods are comparable in quantitation of total antibody in plasma samples. The µLC-MS platform demonstrated a greater dynamic range, sensitivity, robustness, and good reproducibility. These findings demonstrated that the cost-effective µLC-MS method can reduce reagent consumption and minimize the use of mice plasma samples while providing more comprehensive information about ADCs being analyzed, including the total antibody, intact antibody, and total ADC.

Proteomics Methodologies: The Search of Protein Biomarkers Using Microfluidic Systems Coupled to Mass Spectrometry

Protein biomarkers have been the subject of intensive studies as a target for disease diagnostics and monitoring. Indeed, biomarkers have been extensively used for personalized medicine. In biological samples, these biomarkers are most often present in low concentrations masked by a biologically complex proteome (e.g., blood) making their detection difficult. This complexity is further increased by the needs to detect proteoforms and proteome complexity such as the dynamic range of compound concentrations. The development of techniques that simultaneously pre-concentrate and identify low-abundance biomarkers in these proteomes constitutes an avant-garde approach to the early detection of pathologies. Chromatographic-based methods are widely used for protein separation, but these methods are not adapted for biomarker discovery, as they require complex sample handling due to the low biomarker concentration. Therefore, microfluidics devices have emerged as a technology to overcome these shortcomings. In terms of detection, mass spectrometry (MS) is the standard analytical tool given its high sensitivity and specificity. However, for MS, the biomarker must be introduced as pure as possible in order to avoid chemical noise and improve sensitivity. As a result, microfluidics coupled with MS has become increasingly popular in the field of biomarker discovery. This review will show the different approaches to protein enrichment using miniaturized devices and the importance of their coupling with MS.

A Streamlined High-Throughput Plasma Proteomics Platform for Clinical Proteomics with Improved Proteome Coverage, Reproducibility, and Robustness

Mass spectrometry-based clinical proteomics requires high throughput, reproducibility, robustness, and comprehensive coverage to serve the needs of clinical diagnosis, prognosis, and personalized medicine. Oftentimes these requirements are contradictory to each other. We report the development of a streamlined High-Throughput Plasma Proteomics (sHTPP) platform for untargeted profiling of the blood plasma proteome, which includes 96-well plates and simplified procedures for sample preparation, disposable trap column for peptide loading, robust liquid chromatographic system for separation, data-independent acquisition in tandem mass spectrometry, and DIA-NN, FragPipe, and in-house peptide spectral library-based data analysis. Using the optimized platform at a throughput of 60 samples per day, over 600 protein groups including 57 FDA-approved biomarkers can be consistently identified from whole human plasma, and more than 85% of the detected proteins have 100% completeness in quantitative values across 300 samples. The balance achieved between proteome coverage, throughput, and reproducibility of this sHTPP platform makes it promising in clinical settings, where a large number of samples are to be measured quickly and reliably to support various needs of clinical medicine.

Structures of an unusual 3-hydroxyacyl dehydratase (FabZ) from a ladderane-producing organism with an unexpected substrate preference

The genomes of anaerobic ammonium-oxidizing (anammox) bacteria contain a gene cluster comprising genes of unusual fatty acid biosynthesis enzymes that were suggested to be involved in the synthesis of the unique "ladderane" lipids produced by these organisms. This cluster encodes an acyl carrier protein (denoted as "amxACP") and a variant of FabZ, an ACP-3-hydroxyacyl dehydratase. In this study, we characterize this enzyme, which we call anammox-specific FabZ ("amxFabZ"), to investigate the unresolved biosynthetic pathway of ladderane lipids. We find that amxFabZ displays distinct sequence differences to "canonical" FabZ, such as a bulky, apolar residue on the inside of the substrate binding tunnel, where the canonical enzyme has a glycine. Additionally, substrate screens suggest that amxFabZ efficiently converts substrates with acyl chain lengths of up to eight carbons, whereas longer substrates are converted much more slowly under the conditions used. We also present crystal structures of amxFabZs, mutational studies and the structure of a complex between amxFabZ and amxACP, which show that the structures alone cannot explain the apparent differences from canonical FabZ. Moreover, we find that while amxFabZ does dehydrate substrates bound to amxACP, it does not convert substrates bound to canonical ACP of the same anammox organism. We discuss the possible functional relevance of these observations in the light of proposals for the mechanism for ladderane biosynthesis.

Bioanalytical strategy for the characterization and bioanalysis of biologics: a global, nonregulated bioanalytical lab perspective

Over the past two decades, we have seen an increase in the complexity and diversity of biotherapeutic modalities pursued by biopharmaceutical companies. These biologics are multifaceted and susceptible to post-translational modifications and in vivo biotransformation that could impose challenges for bioanalysis. It is vital to characterize the functionality, stability and biotransformation products of these molecules to enable screening, identify potential liabilities at an early stage and devise a bioanalytical strategy. This article highlights our perspective on characterization and bioanalysis of biologics using hybrid LC-MS in our global nonregulated bioanalytical laboratories. AbbVie's suite of versatile, stage-appropriate characterization assays and quantitative bioanalytical approaches are discussed, along with guidance on their utility in answering project-specific questions to aid in decision-making.

Biotransformation of Trastuzumab and Pertuzumab in Breast Cancer Patients Assessed by Affinity Enrichment and Ion-Exchange Chromatography

Therapeutic proteins (TPs) are known to be heterogeneous due to modifications that occur during the production process and storage. Modifications may also occur in TPs after their administration to patients due to in vivo biotransformation. Ligand binding assays, which are widely used in the bioanalysis of TPs in body fluids, are typically unable to distinguish such modifications. Liquid chromatography coupled to mass spectrometry is being increasingly used to study modifications in TPs, but its use to study in vivo biotransformation has been limited until now. We present a novel approach that combines affinity enrichment using Affimer reagents with ion-exchange chromatography (IEX) to analyze charge variants of the TPs trastuzumab and pertuzumab in plasma of patients undergoing therapy for HER2-positive breast cancer. Affimer reagents were immobilized via engineered Cys tags to maleimide beads, and the TPs were eluted under acidic conditions followed by rapid neutralization. The enriched TPs were analyzed by cation-exchange chromatography (IEX) using pH-gradient elution, resulting in the separation of about 20 charge variants for trastuzumab and about five charge variants for pertuzumab. A comparison between in vitro stressed TPs spiked into plasma, and TPs enriched from patient plasma showed that the observed profiles were highly similar. This indicates that in vitro stress testing in plasma can mimic the situation in patient plasma, as far as the generation of charge variants is concerned. SIGNIFICANCE STATEMENT: This research attempts to elucidate the modifications that occur in therapeutic proteins (TPs) after they have been administered to patients. This is important because there is little knowledge about the fate of TPs in this regard, and certain modifications could affect their efficiency. Our results show that the modifications discovered are most likely due to a chemical process and are not patient specific.

Purification, Characterization and Bactericidal Action of Lysozyme, Isolated from Bacillus subtillis BSN314: A Disintegrating Effect of Lysozyme on Gram-Positive and Gram-Negative Bacteria

In the present study, lysozyme was purified by the following multi-step methodology: salt (ammonium sulfate) precipitation, dialysis, and ultrafiltration. The lysozyme potential was measured by enzymatic activity after each purification step. However, after ultrafiltration, the resulting material was considered extra purified. It was concentrated in an ultrafiltration centrifuge tube, and the resulting protein/lysozyme was used to determine its bactericidal potential against five bacterial strains, including three gram-positive (Bacillus subtilis 168, Micrococcus luteus, and Bacillus cereus) and two gram-negative (Salmonella typhimurium and Pseudomonas aeruginosa) strains. The results of ZOI and MIC/MBC showed that lysozyme had a higher antimicrobial activity against gram-positive than gram-negative bacterial strains. The results of the antibacterial activity of lysozyme were compared with those of ciprofloxacin (antibiotic). For this purpose, two indices were applied in the present study: antimicrobial index (AMI) and percent activity index (PAI). It was found that the purified lysozyme had a higher antibacterial activity against Bacillus cereus (AMI/PAI; 1.01/101) and Bacillus subtilis 168 (AMI/PAI; 1.03/103), compared to the antibiotic (ciprofloxacin) used in this study. Atomic force microscopy (AFM) was used to determine the bactericidal action of the lysozyme on the bacterial cell. The purified protein was further processed by gel column chromatography and the eluate was collected, its enzymatic activity was 21.93 U/mL, while the eluate was processed by native-PAGE. By this analysis, the un-denatured protein with enzymatic activity of 40.9 U/mL was obtained. This step shows that the protein (lysozyme) has an even higher enzymatic potential. To determine the specific peptides (in lysozyme) that may cause the bactericidal potential and cell lytic/enzymatic activity, the isolated protein (lysozyme) was further processed by the SDS-PAGE technique. SDS-PAGE analysis revealed different bands with sizes of 34 kDa, 24 kDa, and 10 kDa, respectively. To determine the chemical composition of the peptides, the bands (from SDS-PAGE) were cut, enzymatically digested, desalted, and analyzed by LC-MS (liquid chromatography-mass spectrometry). LC-MS analysis showed that the purified lysozyme had the following composition: the number of proteins in the sample was 56, the number of peptides was 124, and the number of PSMs (peptide spectrum matches) was 309. Among them, two peptides related to lysozyme and bactericidal activities were identified as: A0A1Q9G213 (N-acetylmuramoyl-L-alanine amidase) and A0A1Q9FRD3 (D-alanyl-D-alanine carboxypeptidase). The corresponding protein sequence and nucleic acid sequence were determined by comparison with the database.

Bioanalytical LC-MS/MS method for simultaneous estimation of atorvastatin, its major active metabolites and ezetimibe

Background: Hyperlipidemia is one of the most common chronic diseases encountered globally, and atorvastatin (ATV) is mainly metabolized into two major active metabolites. Methodology: Hence, we aimed to estimate ATV and ezetimibe (EZE) simultaneously in the presence of ATV major and active metabolites using a validated LC-MS/MS method. Conclusion: The proposed method was linear (r² >0.99), accurate (92.02-109.94%) and precise (CV% ≤14) over the concentration range of 0.50-120 ng/ml, 0.20-48 ng/ml, 0.50-120 ng/ml and 0.20-48 ng/ml for ATV, EZE, 2-hydroxy ATV and 4-hydroxy ATV, respectively. The applied liquid-liquid extraction gave rise to reliable extraction recoveries of 84.91 ± 1.14%, 85.20 ± 1.62%, 85.46 ± 0.41% and 105.46 ± 2.35% for ATV, EZE, 2-hydroxy ATV and 4-hydroxy ATV, respectively.

Current Analytical Strategies for Antibody-Drug Conjugates in Biomatrices

Antibody-drug conjugates (ADCs) are a new class of biotherapeutics, consisting of a cytotoxic payload covalently bound to an antibody by a linker. Ligand-binding assay (LBA) and liquid chromatography-mass spectrometry (LC-MS) are the favored techniques for the analysis of ADCs in biomatrices. The goal of our review is to provide current strategies related to a series of bioanalytical assays for pharmacokinetics (PK) and anti-drug antibody (ADA) assessments. Furthermore, the strengths and limitations of LBA and LC-MS platforms are compared. Finally, potential factors that affect the performance of the developed assays are also provided. It is hoped that the review can provide valuable insights to bioanalytical scientists on the use of an integrated analytical strategy involving LBA and LC-MS for the bioanalysis of ADCs and related immunogenicity evaluation.

Surrogate peptide selection and internal standardization for accurate quantification of endogenous proteins

Relative quantification techniques have dominated the field of proteomics. However, biomarker discovery, mathematical model development and studies on transporter-mediated drug disposition still need absolute quantification of proteins. The quality of data of trace-level protein quantification is solely dependent on the specific selection of surrogate peptides. Selection of surrogate peptides has a major impact on the accuracy of the method. In this article, the advanced approaches for selection of surrogate peptides, which can provide absolute quantification of the proteins are discussed. In addition, internal standardization, which accounts for variations in the quantitation process to achieve absolute protein quantification is discussed.

Identification of Antibiotic Resistance Proteins via MiCId's Augmented Workflow. A Mass Spectrometry-Based Proteomics Approach

Fast and accurate identifications of pathogenic bacteria along with their associated antibiotic resistance proteins are of paramount importance for patient treatments and public health. To meet this goal from the mass spectrometry aspect, we have augmented the previously published Microorganism Classification and Identification (MiCId) workflow for this capability. To evaluate the performance of this augmented workflow, we have used MS/MS datafiles from samples of 10 antibiotic resistance bacterial strains belonging to three different species: Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa. The evaluation shows that MiCId's workflow has a sensitivity value around 85% (with a lower bound at about 72%) and a precision greater than 95% in identifying antibiotic resistance proteins. In addition to having high sensitivity and precision, MiCId's workflow is fast and portable, making it a valuable tool for rapid identifications of bacteria as well as detection of their antibiotic resistance proteins. It performs microorganismal identifications, protein identifications, sample biomass estimates, and antibiotic resistance protein identifications in 6-17 min per MS/MS sample using computing resources that are available in most desktop and laptop computers. We have also demonstrated other use of MiCId's workflow. Using MS/MS data sets from samples of two bacterial clonal isolates, one being antibiotic-sensitive while the other being multidrug-resistant, we applied MiCId's workflow to investigate possible mechanisms of antibiotic resistance in these pathogenic bacteria; the results showed that MiCId's conclusions agree with the published study. The new version of MiCId (v.07.01.2021) is freely available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

Uncovering the seasonal brain: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) as a biochemical approach for studying seasonal social behaviors

Many animals show pronounced changes in physiology and behavior across the annual cycle, and these adaptations enable individuals to prioritize investing in the neuroendocrine mechanisms underlying reproduction and/or survival based on the time of year. While prior research has offered valuable insight into how seasonal variation in neuroendocrine processes regulates social behavior, the majority of these studies have investigated how a single hormone influences a single behavioral phenotype. Given that hormones are synthesized and metabolized via complex biochemical pathways and often act in concert to control social behavior, these approaches provide a limited view of how hormones regulate seasonal changes in behavior. In this review, we discuss how seasonal influences on hormones, the brain, and social behavior can be studied using liquid chromatography-tandem mass spectrometry (LC-MS/MS), an analytical chemistry technique that enables researchers to simultaneously quantify the concentrations of multiple hormones and the activities of their synthetic enzymes. First, we examine studies that have investigated seasonal plasticity in brain-behavior interactions, specifically by focusing on how two groups of hormones, sex steroids and nonapeptides, regulate sexual and aggressive behavior. Then, we explain the operations of LC-MS/MS, highlight studies that have used LC-MS/MS to study the neuroendocrine mechanisms underlying social behavior, both within and outside of a seasonal context, and discuss potential applications for LC-MS/MS in the field of behavioral neuroendocrinology. We propose that this cutting-edge technology will provide a more comprehensive understanding of how the multitude of hormones that comprise complex neuroendocrine networks affect seasonal variation in the brain and behavior.

Spontaneous Coassembly of the Protein Terthiophene into Fluorescent Electroactive Microfibers in 2D and 3D Cell Cultures

Protein-based microfibers are biomaterials of paramount importance in materials science, nanotechnology, and medicine. Here we describe the spontaneous in situ formation and secretion of nanostructured protein microfibers in 2D and 3D cell cultures of 3T3 fibroblasts and B104 neuroblastoma cells upon treatment with a micromolar solution of either unmodified terthiophene or terthiophene modified by mono-oxygenation (thiophene → thiophene S-oxide) or dioxygenation (thiophene → thiophene S,S-dioxide) of the inner ring. We demonstrate via metabolic cytotoxicity tests that modification to the S-oxide leads to a severe drop in cell viability. By contrast, unmodified terthiophene and the respective S,S-dioxide cause no harm to the cells and lead to the formation and secretion of fluorescent and electroactive protein-fluorophore coassembled microfibers with a large aspect ratio, a micrometer-sized length and width, and a nanometer-sized thickness, as monitored in real-time by laser scanning confocal microscopy (LSCM). With respect to the microfibers formed by unmodified terthiophene, those formed by the S,S-dioxide display markedly red-shifted fluorescence and an increased n-type character of the material, as shown by macroscopic Kelvin probe in agreement with cyclovoltammetry data. Electrophoretic analyses and Q-TOF mass spectrometry of the isolated microfibers indicate that in all cases the prevalent proteins present are vimentin and histone H4, thus revealing the capability of these fluorophores to selectively coassemble with these proteins. Finally, DFT calculations help to illuminate the fluorophore-fluorophore intermolecular interactions contributing to the formation of the microfibers.

Development and validation of a ligand-binding assay for quantification of the F(ab')2 antivenom of Daboia russelii siamensis in human serum and its application to a phase I clinical study

Daboia russelii siamensis accounts for most of snakebite mortalities in China, yet, specific treatment against the venom toxins is absent in clinical practice. The F(ab')2 antivenom of Daboia russelii siamensis is manufactured and approved for the clinical trial in China. To satisfy the need for clinical pharmacokinetic research, this study aimed to develop a ligand binding assay (LBA) for the quantification of F(ab')2 antivenom of Daboia russelii siamensis in human serum. A diverse combination of conditions was optimized based on the fitness of the calibration curve and selectivity. The established LBA undergoes thorough method validation according to the guidelines of regulatory authorities. In the calibration range 1.0-64 μg/mL, the correlation coefficient r2 was from 0.9970 to 1.000, indicating good fitness. Accuracy and precision were within ± 20%. Dilution linearity was observed in the ultra-high quality-control (QC) samples (500 μg/mL). In addition, the assay was free from hook effect, the endogenous interferences and exogenous interferences. The QC samples were stable under different handling and storage conditions. The validated assay was successfully applied to a phase I clinical study of the F(ab')2 antivenom of Daboia russelii siamensis in Chinese healthy volunteers. The peak concentrations exhibited dose-proportionality. In conclusion, this study provides a novel and reliable LBA method for the clinical pharmacokinetic research of F(ab')2 antivenom of Daboia russelii siamensis. It will facilitate further clinical trials in treating the snakebite of Daboia russelii siamensis.

Assay pH and critical reagent optimization in measuring concentrations of a monoclonal antibody and its target

Aim: To mitigate assay interference in the drug and target assays to support the development of monoclonal antibody REGN-Z. Results: Mild acidic assay conditions and capture and detection antibodies with different affinities and t_1/2 under different assay pHs were used to mitigate interference in the total drug and total target assays. A free target assay was also developed using a lower-affinity capture antibody with a much slower association and dissociation rate. The impact of sample incubation, dilution and storage on the accurate detection of the free target was also evaluated. Conclusion: The total drug, total and free target assays can accurately quantitate drug and target concentrations when tested with a subset of clinical study samples.

Enhancement of sensitivity and quantification quality in the LC-MS/MS measurement of large biomolecules with sum of MRM (SMRM)

Liquid chromatography (LC) coupled with tandem mass spectrometry (MS/MS) provides a simple and efficient means for the measurement of analytes in biological matrices with high selectivity and specificity. LC-MS/MS plays an important role in the pharmaceutical industry and biomedical research, but it requires analytes to be in an ionized form in order to be detected. This can pose a challenge for large molecules such as proteins and peptides, because they can exist in multiple charged forms, and this will reduce the total analyte signal by distributing it into multiple ion peaks with a different number of charges in a mass spectrum. In conventional LC-MS/MS analysis of such macromolecules, one charged form is selected as the precursor ion which is then fragmented by collision-induced dissociation (CID) in MS/MS to generate product ions, a process referred to as multiple-reaction monitoring (MRM). The MRM method minimizes interference from endogenous molecules within biological matrices that share the same molecular weight of the precursor ion, but at the expense of signal intensity as compared to precursor ion intensity. We describe here an approach to boost detection sensitivity and expand dynamic range in the quantitation of large molecules while maintaining analytical specificity using summation of MRM (SMRM) transitions and LC separation technique. Protein image from PDB-101 (PDB101.rscb.org).

Development and validation of a targeted LC-MS/MS quantitation method to monitor cell culture expression of tetanus neurotoxin during vaccine production

The tetanus neurotoxin (TeNT) is one of the most toxic proteins known to man, which prior to the use of the vaccine against the TeNT producing bacteria Clostridium tetani, resulted in a 20% mortality rate upon infection. The clinical detrimental effects of tetanus have decreased immensely since the introduction of global vaccination programs, which depend on sustainable vaccine production. One of the major critical points in the manufacturing of these vaccines is the stable and reproducible production of high levels of toxin by the bacterial seed strains. In order to minimize time loss, the amount of TeNT is often monitored during and at the end of the bacterial culturing. The different methods that are currently available to assess the amount of TeNT in the bacterial medium suffer from variability, lack of sensitivity, and/or require specific antibodies. In accordance with the consistency approach and the three Rs (3Rs), both aiming to reduce the use of animals for testing, in-process monitoring of TeNT production could benefit from animal and antibody-free analytical tools. In this paper, we describe the development and validation of a new and reliable antibody free targeted LC-MS/MS method that is able to identify and quantify the amount of TeNT present in the bacterial medium during the different production time points up to the harvesting of the TeNT just prior to further upstream purification and detoxification. The quantitation method, validated according to ICH guidelines and by the application of the total error approach, was utilized to assess the amount of TeNT present in the cell culture medium of two TeNT production batches during different steps in the vaccine production process prior to the generation of the toxoid. The amount of TeNT generated under different physical stress conditions applied during bacterial culture was also monitored.

Mass spectrometry based approaches and strategies in bioanalysis for qualitative and quantitative analysis of pharmaceutically relevant molecules

Mass spectrometry plays an essential role in qualitative and quantitative analysis of pharmaceutically relevant molecules. The present review summarizes some the most common applications of LC-MS for the characterization of therapeutic low-molecular-weight compounds, peptides and proteins, and oligonucleotides using low-resolution and high-resolution tandem mass spectrometry. In addition, the benefit of multistage MS, differential ion mobility, and data independent acquisition is emphasized. At last, the potential of coupling MS with novel interfaces for high-throughput analysis is discussed.

Antibody-Free Quantification of Serum Chromogranin A by Targeted Mass Spectrometry

BACKGROUND

Chromogranin A (CgA) is a 48 kDa protein that serves as a diagnostically sensitive, but nonspecific, serum biomarker for neuroendocrine tumors. Immunoassays for CgA are not standardized and have a narrow dynamic range, which requires dilution of concentrated specimens. We developed and validated an antibody-free, liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based method for CgA without these limitations.

METHODS

CgA was extracted from serum using a mixed-mode anion exchange solid-phase extraction plate, digested with trypsin, and analyzed by LC-MS/MS using well-characterized CgA calibration standards. After validation, the mass spectrometry method was compared with the CISBIO immunoassay using 200 serum specimens previously submitted for CgA analysis. Specimens with discordant results were reanalyzed by high-resolution mass spectrometry- (HRMS) -based methods to assess the contribution of truncated and post-translationally modified forms of CgA.

RESULTS

The assay had a linear range of 50 to 50 000 ng/mL, recoveries between 89% and 115%, and intra- and interassay imprecision <10%. LC-MS/MS assay results showed a Pearson's correlation of r = 0.953 with the CISBIO immunoassay, with CgA values being a mean 2- to 4-fold higher. Concordance for CgA between the 2 assays was 80.9% (95% CI 72.8%-89.2%), showing substantial agreement. Truncation and posttranslational modification, including 2 phosphorylation sites that had not been previously observed or predicted to our knowledge, did not appear to contribute directly to discordance between the 2 assays.

CONCLUSION

Quantification of CgA by LC-MS/MS provides an analytically sensitive and reproducible alternative to commercially available immunoassays.

Mass Spectrometry for the Monitoring of Lipoprotein Oxidations by Myeloperoxidase in Cardiovascular Diseases

Oxidative modifications of HDLs and LDLs by myeloperoxidase (MPO) are regularly mentioned in the context of atherosclerosis. The enzyme adsorbs on protein moieties and locally produces oxidizing agents to modify specific residues on apolipoproteins A-1 and B-100. Oxidation of lipoproteins by MPO (Mox) leads to dysfunctional Mox-HDLs associated with cholesterol-efflux deficiency, and Mox-LDLs that are no more recognized by the LDL receptor and become proinflammatory. Several modification sites on apoA-1 and B-100 that are specific to MPO activity are described in the literature, which seem relevant in patients with cardiovascular risk. The most appropriate analytical method to assess these modifications is based on liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). It enables the oxidized forms of apoA-1and apoB-100 to be quantified in serum, in parallel to a quantification of these apolipoproteins. Current standard methods to quantify apolipoproteins are based on immunoassays that are well standardized with good analytical performances despite the cost and the heterogeneity of the commercialized kits. Mass spectrometry can provide simultaneous measurements of quantity and quality of apolipoproteins, while being antibody-independent and directly detecting peptides carrying modifications for Mox-HDLs and Mox-LDLs. Therefore, mass spectrometry is a potential and reliable alternative for apolipoprotein quantitation.

Bioanalytical strategies in drug discovery and development

A reliable, rapid, and effective bioanalytical method is essential for the determination of the pharmacokinetic, pharmacodynamic, and toxicokinetic parameters that inform the safety and efficacy profile of investigational drugs. The overall goal of bioanalytical method development is to elucidate the procedure and operating conditions under which a method can sufficiently extract, qualify, and/or quantify the analyte(s) of interest and/or their metabolites for the intended purpose. Given the difference in the physicochemical properties of small and large molecule drugs, different strategies need to be adopted for the development of an effective and efficient bioanalytical method. Herein, we provide an overview of different sample preparation strategies, analytical platforms, as well as procedures for achieving high throughput for bioanalysis of small and large molecule drugs.

Intact Protein Mass Spectrometry for Therapeutic Protein Quantitation, Pharmacokinetics, and Biotransformation in Preclinical and Clinical Studies: An Industry Perspective

Recent advancements in immunocapture methods and mass spectrometer technology have enabled intact protein mass spectrometry to be applied for the characterization of antibodies and other large biotherapeutics from in-life studies. Protein molecules have not been traditionally studied by intact mass or screened for catabolites in the same manner as small molecules, but the landscape has changed. Researchers have presented methods that can be applied to the drug discovery and development stages, and others are exploring the possibilities of the new approaches. However, a wide variety of options for assay development exists without clear recommendation on best practice, and data processing workflows may have limitations depending on the vendor. In this perspective, we share experiences and recommendations for current and future application of mass spectrometry for biotherapeutic molecule monitoring from preclinical and clinical studies.

The role of ligand-binding assay and LC-MS in the bioanalysis of complex protein and oligonucleotide therapeutics

Ligand-binding assay (LBA) and LC-MS have been the preferred bioanalytical techniques for the quantitation and biotransformation assessment of various therapeutic modalities. This review provides an overview of the applications of LBA, LC-MS/MS and LC-HRMS for the bioanalysis of complex protein therapeutics including antibody-drug conjugates, fusion proteins and PEGylated proteins as well as oligonucleotide therapeutics. The strengths and limitations of LBA and LC-MS, along with some guidelines on the choice of appropriate bioanalytical technique(s) for the bioanalysis of these therapeutic modalities are presented. With the discovery of novel and more complex therapeutic modalities, there is an increased need for the biopharmaceutical industry to develop a comprehensive bioanalytical strategy integrating both LBA and LC-MS.

An Automated Multicycle Immunoaffinity Enrichment Approach Developed for Sensitive Mouse IgG1 Antibody Drug Analysis in Mouse Plasma Using LC/MS/MS

In the immuno-oncology field, surrogate mouse monoclonal antibodies are often preferred in establishing proper PK/PD/efficacy correlations as well as supporting anticipated mouse to human translation. Thus, a highly sensitive and specific bioanalytical method is needed in quantifying those surrogate mouse antibodies after dosing in mice. Unfortunately, when specific reagents, such as recombinant target antigen and anti-idiotypic antibody, are not available, measuring mouse surrogate antibody drugs in mice is very challenging for ligand binding assay (LBA) due to the severe cross reactivity potential. Different from LBA, if at least one unique surrogate peptide can be identified from the surrogate antibody sequence, the immunoaffinity enrichment based LC/MS/MS assay may be able to differentiate the analyte response from the high endogenous immunoglobulin background and provide adequate sensitivity. Herein, a new automated multicycle immunoaffinity enrichment method was recently developed to extract a surrogate mouse IgG1 (mIgG1) antibody drug from mouse plasma using a commercially available antimouse IgG1 secondary antibody. In the assay, reuse of the capture antibody up to six times mostly resolved the binding capacity issue caused by the abundant endogenous mIgG1 and made the immunoaffinity enrichment step more cost-effective. Combined with a unique surrogate peptide identified from the antibody, the LC/MS/MS assay achieved a limit of quantitation of 5 ng/mL with satisfactory assay precision, accuracy, and dynamic range. The successful implementation of this novel approach in discovery pharmacokinetic (PK) studies eliminates the dependence on specially generated immunoaffinity capturing reagents.

Aptamer-based immunoaffinity LC-MS using an ultra-short column for rapid attomole level quantitation of intact mAbs

Quantification of proteins in biofluids has largely involved either traditional ligand binding assays or "bottom-up" mass spectrometry. Recently, top-down mass spectrometry using reversed-phase liquid chromatography (RPLC) paired with high-resolution mass spectrometry (HRMS) has emerged as a promising technique, due to the potential of better identification of post-translational modifications (PTMs), lack of downstream interferences, and less time-consuming sample preparation and analysis times. However, it can be difficult with this approach to robustly obtain high-fidelity MS data, especially when pushing for low limits of detection. To address these issues, we developed a chromatographic device with an optimized form factor and stationary phase to improve protein recovery, while reducing run times. We have observed that by using this device, it is possible to achieve attomole quantitation of mAbs without the addition of carrier proteins and with over three-fold higher throughput than columns employed in previous studies. Moreover, we have devised a novel affinity capture method, based on repurposing a unique aptamer ligand that can give 93% recovery of mAb using only a 2 h incubation. When hyphenated together, these two technologies greatly improve the ability to analyze proteins in complex matrices.

A Critical Review on Advancement in Analytical Strategies for the Quantification of Clinically Relevant Biological Transporters

Success of a drug discovery program is highly dependent on rapid scientific advancement and periodic inclusion of sensitive and specific analytical techniques. Biological membrane transporters can significantly alter the bioavailability of a molecule in its actual site of action. Expression of transporter proteins responsible for drug transport is extremely low in the biological system. Therefore, proper scientific planning in selection of their quantitative analytical technique is essential. This article discusses critical advancement in the analytical strategies for quantification of clinically relevant biological transporters for the drugs. Article cross-talked key planning and execution strategies concerning analytical quantification of the transporters during drug discovery programs.

Barcode signal amplifying strategy for sensitive and accurate protein detection on LC-MS/MS

Protein drugs showing strong pharmaceutical activity, high specificity, and low toxicity and side effects have drawn extensive attention in the field of life sciences and medicine. Precise evaluation of the function of these drugs requires accurate and sensitive detection methods. Here, we report a novel chromatography-tandem mass spectrometry (LC-MS/MS) method for sensitive and selective detection of protein drugs. Magnetic nanoparticles (Apt29@MNPs) were functionalized by thrombin aptamers, and quantum dots (Apt15@ss@QDs) were dual-functionalized with quantitative thrombin aptamers and small molecules with high ionization efficiency as the mass barcode. After Apt29@MNPs specifically purify and enrich thrombin from biological samples, they can form a nano "sandwich structure" when Apt15@ss@QDs are added, resulting in the release of the mass barcode for LC-MS/MS analysis via the cutting of the disulfide bond. Since there is a higher quantitative molecular ratio of mass barcode to thrombin in the nano-"sandwich structure", quantitative detection of thrombin with high sensitivity and selectivity can be achieved via the LC-MS/MS detection of the mass barcode with high ionization efficiency rather than thrombin, which effectively avoids the disadvantages of direct protein detection by mass spectrometry. The established method for thrombin detection shows a good linear relationship in a concentration range of 0.00115-1.15 nM with a limit of detection (LOD) of 0.0007 nM. The present work provides a new approach for the effective and sensitive quantitative analysis of protein drugs and would be of great significance in promoting the development of protein drugs and clinical applications.

The Azospirillum brasilense Core Chemotaxis Proteins CheA1 and CheA4 Link Chemotaxis Signaling with Nitrogen Metabolism

Bacterial chemotaxis affords motile bacteria the ability to navigate the environment to locate niches for growth and survival. At the molecular level, chemotaxis depends on chemoreceptor signaling arrays that interact with cytoplasmic proteins to control the direction of movement. In Azospirillum brasilense, chemotaxis is mediated by two distinct chemotaxis pathways: Che1 and Che4. Both Che1 and Che4 are critical in the A. brasilense free-living and plant-associated lifestyles. Here, we use whole-cell proteomics and metabolomics to characterize the role of chemotaxis in A. brasilense physiology. We found that mutants lacking CheA1 or CheA4 or both are affected in nonchemotaxis functions, including major changes in transcription, signaling transport, and cell metabolism. We identify specific effects of CheA1 and CheA4 on nitrogen metabolism, including nitrate assimilation and nitrogen fixation, that may depend, at least, on the transcriptional control of rpoN, which encodes RpoN, a global regulator of metabolism, including nitrogen. Consistent with proteomics, the abundance of several nitrogenous compounds (purines, pyrimidines, and amino acids) changed in the metabolomes of the chemotaxis mutants relative to the parental strain. Further, we uncover novel, and yet uncharacterized, layers of transcriptional and posttranscriptional control of nitrogen metabolism regulators. Together, our data reveal roles for CheA1 and CheA4 in linking chemotaxis and nitrogen metabolism, likely through control of global regulatory networks.

IMPORTANCE Bacterial chemotaxis is widespread in bacteria, increasing competitiveness in diverse environments and mediating associations with eukaryotic hosts ranging from commensal to beneficial and pathogenic. In most bacteria, chemotaxis signaling is tightly linked to energy metabolism, with this coupling occurring through the sensory input of several energy-sensing chemoreceptors. Here, we show that in A. brasilense the chemotaxis proteins have key roles in modulating nitrogen metabolism, including nitrate assimilation and nitrogen fixation, through novel and yet unknown regulations. These results are significant given that A. brasilense is a model bacterium for plant growth promotion and free-living nitrogen fixation and is used as a bio-inoculant for cereal crops. Chemotaxis signaling in A. brasilense thus links locomotor behaviors to nitrogen metabolism, allowing cells to continuously and reciprocally adjust metabolism and chemotaxis signaling as they navigate gradients.

CASK, APBA1, and STXBP1 collaborate during insulin secretion

Calcium/calmodulin-dependent serine protein kinase (CASK) knockdown reduces insulin vesicle docking to cell membranes. Here, we explored CASK interactions with other proteins during insulin secretion. Using co-immunoprecipitation, liquid chromatography-mass spectrometry and bioinformatic analysis, we identified that CASK, Adapter protein X11 alpha (APBA1), and Syntaxin binding protein 1 (STXBP1) formed tripartite complex during insulin secretion. CASK enhanced APBA1-STXBP1 interaction and mediated their traffic from cytoplasm to plasma membrane during insulin release. High fatty acid stimulation decreased insulin secretion along with CASK, APBA1, and STXBP1 expression; Cask overexpression enhanced CASK/APBA1/STXBP1 tripartite complex function, and may thereby rescue lipotoxicity-induced insulin-release defects. Collectively, our results illustrated the function of CASK in insulin granules exocytosis, which broadens the underlying mechanism of insulin secretion and highlights the clinical potential of CASK as a drug target of type 2 Diabetes Mellitus (T2DM).

Using Deep Learning to Extrapolate Protein Expression Measurements

Mass spectrometry (MS)-based quantitative proteomics experiments typically assay a subset of up to 60% of the ≈20 000 human protein coding genes. Computational methods for imputing the missing values using RNA expression data usually allow only for imputations of proteins measured in at least some of the samples. In silico methods for comprehensively estimating abundances across all proteins are still missing. Here, a novel method is proposed using deep learning to extrapolate the observed protein expression values in label-free MS experiments to all proteins, leveraging gene functional annotations and RNA measurements as key predictive attributes. This method is tested on four datasets, including human cell lines and human and mouse tissues. This method predicts the protein expression values with average R 2 scores between 0.46 and 0.54, which is significantly better than predictions based on correlations using the RNA expression data alone. Moreover, it is demonstrated that the derived models can be "transferred" across experiments and species. For instance, the model derived from human tissues gave a R 2 = 0.51 when applied to mouse tissue data. It is concluded that protein abundances generated in label-free MS experiments can be computationally predicted using functional annotated attributes and can be used to highlight aberrant protein abundance values.

Finding a Needle in a Haystack: Proteomics in Heart Failure

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Proteomics has aided HF biomarker discovery, which allows for greater disease insights.

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Experiment design can be tailored to HF research to discover novel biomarkers.

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Primary methods include MS, protein microarray, aptamer, and PEA-based technologies.

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Proteomics can detect unique low abundance proteins and detect protein modifications.

Circulating protein biomarkers provide information regarding pathways in heart failure (HF) and can add important value to clinicians. Advancements in proteomics allow researchers to measure a multitude of proteins simultaneously with excellent sensitivity and selectivity to detect low abundance proteins. This helps identify previously unrecognized pathways in HF and discover biomarkers and potential targets for HF therapies. Although several proteomic methods exist, including mass spectrometry, protein microarray, aptamer, and proximity extension assay−based techniques, each have their unique advantages. This paper provides an overview of the various proteomic methods, with examples of how each has contributed to understanding the pathways in HF.

Integrated hemolysis monitoring for bottom-up protein bioanalysis

Background: Hemolysis can result in analyte suppression or enhancement and it can affect the extraction efficiency and analyte stability. Triskelion developed an LC–MS method to monitor hemolysis. The concept can be integrated into existing and new quantitative protein LC–MS methods and can be validated according to the most appropriate tier. Results/methodology: In this proof of concept study, the tryptic target LLVVYPWTQR was used to quantify hemoglobin. The peptide target has only few variations considering the most common (laboratory) animals and is thus nearly generic. It was shown that LC–MS is a suitable technique for the quantification of hemoglobin in hemolyzed samples and that the signals are not affected by lipemia. Conclusion: LC–MS exhibited the best performance to monitor hemolysis when the results were compared with UV–VIS and visual inspection, especially when samples were lipemic.

EnvCNN: A Convolutional Neural Network Model for Evaluating Isotopic Envelopes in Top-Down Mass-Spectral Deconvolution

Top-down mass spectrometry has become the main method for intact proteoform identification, characterization, and quantitation. Because of the complexity of top-down mass spectrometry data, spectral deconvolution is an indispensable step in spectral data analysis, which groups spectral peaks into isotopic envelopes and extracts monoisotopic masses of precursor or fragment ions. The performance of spectral deconvolution methods relies heavily on their scoring functions, which distinguish correct envelopes from incorrect ones. A good scoring function increases the accuracy of deconvoluted masses reported from mass spectra. In this paper, we present EnvCNN, a convolutional neural network-based model for evaluating isotopic envelopes. We show that the model outperforms other scoring functions in distinguishing correct envelopes from incorrect ones and that it increases the number of identifications and improves the statistical significance of identifications in top-down spectral interpretation.

Complexity, cost, and content – three important factors for translation of clinical protein mass spectrometry tests, and the case for apolipoprotein C-III proteoform testing

Complexity, cost, and content are three important factors that can impede translation of clinical protein mass spectrometry (MS) tests at a larger scale. Complexity stems from the many components/steps involved in bottom-up protein MS workflows, making them significantly more complicated than enzymatic immunoassays (EIA) that currently dominate clinical testing. This complexity inevitably leads to increased costs, which is detrimental in the price-competitive clinical marketplace. To successfully compete, new clinical protein MS tests need to offer something new and unique that EIAs cannot – a new content of proteoform detection. The preferred method for proteoform profiling is intact protein MS analysis, in which all proteins are measured as intact species thus allowing discovery of new proteoforms. To illustrate the importance of intact proteoform testing with MS and its potential clinical implications, we discuss here recent findings from multiple studies on the distribution of apolipoprotein C-III proteoforms and their correlations with key clinical measures of dyslipidemia. Such studies are only made possible with assays that are low in cost, avoid unnecessary complexity, and are unique in providing the content of proteoforms.