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In the last 15 years, increasing evidence linking epigenetics to various aspects of cancer biology has prompted the investigation of histone post-translational modifications (PTMs) and histone variants in the context of clinical samples. The studies performed so far demonstrated the potential of this type of investigations for the discovery of both potential epigenetic biomarkers for patient stratification and novel epigenetic mechanisms potentially targetable for cancer therapy. Although traditionally the analysis of histones in clinical samples was performed through antibody-based methods, mass spectrometry (MS) has emerged as a more powerful tool for the unbiased, comprehensive, and quantitative investigation of histone PTMs and variants. MS has been extensively used for the analysis of epigenetic marks in cell lines and animal tissue and, thanks to recent technological advances, is now ready to be applied also to clinical samples. In this review, we will provide an overview on the quantitative MS-based analysis of histones, their PTMs and their variants in cancer clinical samples, highlighting current achievements and future perspectives for this novel field of research. Among the different MS-based approaches currently available for histone PTM profiling, we will focus on the 'bottom-up' strategy, namely the analysis of short proteolytic peptides, as it has been already successfully employed for the analysis of clinical samples.

The human ether-a-go-go-related gene (hERG) encodes a tetrameric potassium channel called Kv11.1. This channel can be blocked by certain drugs, which leads to long QT syndrome, causing cardiotoxicity. This is a significant problem during drug development. Using computer models to predict compound cardiotoxicity during the early stages of drug design will help to solve this problem. In this study, we used a dataset of 1865 compounds exhibiting known hERG inhibitory activities as a training set. Thirty cardiotoxicity classification models were established using three machine learning algorithms based on molecular fingerprints and molecular descriptors. Through using these models as the base classifier, a new cardiotoxicity classification model with better predictive performance was developed using ensemble learning method. The accuracy of the best base classifier, which was generated using the XGBoost method with molecular descriptors, was 84.8 %, and the area under the receiver-operating characteristic curve (AUC) was 0.876 in the five fold cross-validation. However, all of the ensemble models that we developed had higher predictive performance than the base classifiers in the five fold cross-validation. The best predictive performance was achieved by the Ensemble-Top7 model, with accuracy of 84.9 % and AUC of 0.887. We also tested the ensemble model using external validation data and achieved accuracy of 85.0 % and AUC of 0.786. Furthermore, we identified several hERG-related substructures, which provide valuable information for designing drug candidates.

The intracellular accumulation of α-synuclein (α-syn) amyloid fibrils is a hallmark of Parkinson’s disease. Because lysosomes are responsible for degrading aggregated species, enhancing lysosomal function could alleviate the overburden of α-syn. Previously, we showed that cysteine cathepsins (Cts) is the main class of lysosomal proteases that degrade α-syn, and in particular, CtsL was found to be capable of digesting α-syn fibrils. Here, we report that CtsK is a more potent protease for degrading α-syn amyloids. Using peptide mapping by liquid chromatography with mass spectrometry, critical cleavage sites involved in destabilizing fibril structure are identified. CtsK is only able to devour the internal regions after the removal of both N- and C-termini, indicating their protective role of the amyloid core from proteolytic attack. Our results suggest that if overexpressed in lysosomes, CtsK has the potential to ameliorate α-syn pathology.

The multi-attribute method (MAM) has garnered attention as a new quality control method of therapeutic monoclonal antibodies (mAbs). MAM analysis allows multiple relative quantifications of several structural attributes of therapeutic mAbs; however, some issues remain to be addressed in its procedures especially for sample preparation. The goal of this study was to optimize the sample preparation method for MAM analysis of mAbs. Using a model mAb, we compared five sample preparation methods based on sequence coverage, peptide redundancy, missed cleavage and chemical deamidation. It was found that low pH buffer and short digestion time reduced artificial deamidation. The desalting process after carboxymethylation was essential to obtaining high sequence coverage by a short digestion time. The generation of missed cleavage peptides was also improved by using a trypsin/lysyl endopeptidase (Lys-C) mixture. Next, we evaluated the usefulness of our method as a part of MAM analysis. Finally, 17 glycopeptides, 2 deamidated peptides and N- and C-terminal peptides of the heavy chain were successfully monitored with acceptable mass accuracy and coefficient of variation (CV, %) of the relative peak area. On the other hand, 4 oxidated peptides indicated the unavoidable slightly higher inter-assay CV (%) of the peak area ratio due to the instability in the MS sample solution. Collectively, we demonstrated that our method was applicable as an easy and reliable sample preparation method for MAM analysis, and the variation in the relative peak area could be influenced by the modification type rather than by the amount of each peptide., Graphical Abstract

Myoglobin (MG) is a biomarker for heart muscle injury, making it a potential target protein for early detection of myocardial infarction. Elevated myoglobin levels alone have low specificity for acute myocardial infarction (AMI) but in combination with cardiac troponin T have been considered highly efficient diagnostic biomarkers. Myoglobin is a monomeric heme protein with a molecular weight of 17 kDa that is found in skeletal and cardiac tissue as an intracellular storage unit of oxygen. MG consists of eight α-helices connected by loops and a heme group responsible for oxygen-binding. Monoclonal antibodies are widely used analytical tools in biomedical research and have been employed for immunoanalytical detection of MG. However, the epitope(s) recognized by MG antibodies have been hitherto unknown. Precise molecular identification of the epitope(s) recognized by antibodies is of key importance for the development of MG as a diagnostic biomarker. The epitope of a monoclonal MG antibody was identified by proteolytic epitope extraction mass spectrometry in combination with surface plasmon resonance (SPR) biosensor analysis. The MG antibody was immobilized both on an affinity microcolumn and a gold SPR chip. The SPR kinetic analysis provided an affinity-binding constant KD of 270 nM for MG. Binding of a tryptic peptide mixture followed by elution of the epitope from the SPR-MS affinity interface by mild acidification provided a single-epitope peptide located at the C-terminus [146-153] [YKELGFQG] of MG. The specificity and affinity of the epitope were ascertained by synthesis and affinity-mass spectrometric characterization of the epitope peptide.

Peptide mapping analysis is a regulatory expectation to verify the primary structure of a recombinant product sequence and to monitor post-translational modifications (PTMs). Although proteolytic digestion has been used for decades, it remains a labour-intensive procedure that can be challenging to accurately reproduce. Here, we describe a fast and reproducible protocol for protease digestion that is automated using immobilised trypsin on magnetic beads, which has been incorporated into an optimised peptide mapping workflow to show method transferability across laboratories. The complete workflow has the potential for use within a multi-attribute method (MAM) approach in drug development, production and QC laboratories. The sample preparation workflow is simple, ideally suited to inexperienced operators and has been extensively studied to show global applicability and robustness for mAbs by performing sample digestion and LC-MS analysis at four independent sites in Europe. LC-MS/MS along with database searching was used to characterise the protein and determine relevant product quality attributes (PQAs) for further testing. A list of relevant critical quality attributes (CQAs) was then established by creating a peptide workbook containing the specific mass-to-charge (m/z) ratios of the modified and unmodified peptides of the selected CQAs, to be monitored in a subsequent test using LC-MS analysis. Data is provided that shows robust digestion efficiency and low levels of protocol induced PTMs. Graphical abstract Electronic supplementary material The online version of this article (10.1007/s00216-020-02809-z) contains supplementary material, which is available to authorized users.

Peptide mapping coupled with liquid chromatography-mass spectrometry (LC-MS) has become an essential analytical technique to quantify the quality attributes (e.g., post-translational modifications [PTMs]) of monoclonal antibodies (mAbs) during drug development. However, the traditional label-free approach for relative quantitation of PTMs requires a great amount of instrument time for LC-MS data acquisition of individual digested samples, which limits the efficiency of peptide mapping when there is an increasing demand for protein characterization. Here, we developed a tandem mass tag (TMT)-based approach in combination with targeted mass spectrometry for multiplexed site-specific PTM quantitation of monoclonal antibodies to overcome this limitation. This approach enables the simultaneous quantitation of quality attributes (e.g., PTMs) for multiple samples in a single LC-MS run. By adjusting higher-energy collision dissociation (HCD) normalized collisional energies (NCEs) from 35 to 90, different types of PTMs were quantified with percentages comparable to those obtained using the conventional approach. The TMT overlabeling on the off-target amino acid residues serine, threonine, and tyrosine was observed to pose a challenge for this targeted MS/MS-based PTM quantitation. However, we inhibited this off-target overlabeling by adding a small-molecule additive during the TMT labeling as a decoy reagent to deplete the excess amount of TMT reagent. The PTM quantitative performance of this approach demonstrated high sensitivity and reproducibility of PTM quantitation with levels as low as 1.0%. Finally, this approach has been utilized to quantify the PTMs for forced degradation samples, comparability samples, and trisulfide standards of monoclonal antibodies.

Unprocessed C-terminal lysine (C-term Lys) is one of the most common causes for the formation of basic variants in therapeutic monoclonal antibodies (mAbs). Although the C-term Lys variants are routinely quantified by a LC-MS-based peptide mapping method using the relative MS responses from both C-terminal peptides (with and without Lys), this approach often leads to overestimation of Lys-containing peptide due to the intrinsic difference in ionization efficiency. Herein, we report an 18O-labeling assisted LC-MS method, which takes advantage of the carboxypeptidase B-catalyzed Lys removal and 18O-labeling to achieve improved accuracy of C-term Lys quantitation. The fidelity of this method was first demonstrated using synthetic peptide mixture standards that mimic a wide range of C-term Lys levels. Finally, the newly developed method was applied in a case study where C-term Lys variants in mAb samples manufactured from different processes were accurately quantified and compared. This new method provides a valuable solution for studies where accurate C-term Lys levels are needed to assist decision-making and root-cause investigation.

The objective of the study was to identify the fertility-associated metabolites in bovine spermatozoa using liquid chromatography-mass spectrometry (LC-MS). Six Holstein Friesian crossbred bulls (three high-fertile and three low-fertile bulls) were the experimental animals. Sperm proteins were isolated and protein-normalized samples were processed for metabolite extraction and subjected to LC-MS/MS analysis. Mass spectrometry data were processed using iMETQ software and metabolites were identified using Human Metabolome DataBase while, Metaboanalyst 4.0 tool was used for statistical and pathway analysis. A total of 3,704 metabolites belonging to various chemical classes were identified in bull spermatozoa. After sorting out exogenous metabolites, 56 metabolites were observed common to both the groups while 44 and 35 metabolites were found unique to high- and low-fertile spermatozoa, respectively. Among the common metabolites, concentrations of 19 metabolites were higher in high-fertile compared to low-fertile spermatozoa (fold change > 1.00). Spermatozoa metabolites with variable importance in projections score of more than 1.5 included hypotaurine, d-cysteine, selenocystine. In addition, metabolites such as spermine and l-cysteine were identified exclusively in high-fertile spermatozoa. Collectively, the present study established the metabolic profile of bovine spermatozoa and identified the metabolomic differences between spermatozoa from high- and low-fertile bulls. Among the sperm metabolites, hypotaurine, selenocysteine, l-malic acid, d-cysteine, and chondroitin 4-sulfate hold the potential to be recognized as fertility-associated metabolites.

Summary Chromatographic application of two recent HPLC stationary phases for protein analysis was demonstrated. These two stationary phases are namely monolithic rods and core-shell particles. Monolithic rods have higher permeability and larger porous structure allowing faster elution, while smaller core-shell particles have narrower particle size distribution and better packing allowing larger number of resolved peptides. Peptide mapping of erythropoietin hormone, which is used in the treatment of symptomatic anaemia associated with chronic renal failure in adult and pediatric patients, was carried out on monolithic column and core-shell particles. Comparison between the effectiveness of separation on both columns was established and the new morphologies proved their capability of replacing the totally porous particles with higher resolution power at shorter analysis time. Carbetocin is an oxytocin analogue with a longer duration of action that stimulates uterine contraction and milk ejection in mammals. Monolithic column was also applied for quantitative HPLC analysis of carbetocin using ethanol as cheap and greener alternative organic modifier without compromise to a full impurity profiling. The proposed method was validated concerning with accuracy, precision, robustness, sensitivity, limits of detection and quantitation and proved to be green and stability indicating.

Clostridioides difficile infection is the leading cause of nosocomial diarrhoea globally. Immune responses to toxins produced by C. difficile are important in disease progression and outcome. Here, we analysed the anti-toxin A and anti-toxin B serum antibody proteomes following natural infection or vaccination with a C. difficile toxoid A/toxoid B vaccine using a modified miniaturised proteomic approach based on de novo mass spectrometric sequencing. Analysis of immunoglobulin variable region (IgV) subfamily expression in immunoprecipitated toxin A and toxin B antibodies from four and seven participants of a vaccine trial, respectively, revealed a polyclonal proteome with restricted IGHV, IGKV and IGLV subfamily usage. No dominant IGHV subfamily was observed in the toxin A response, however the dominant anti-toxin B heavy (H)-chain was encoded by IGHV3-23. Light (L)-chain usage was convergent for both anti-toxin A and anti-toxin B proteomes with IGKV3-11, 3-15, 3-20 and 4-1 shared among all subjects in both cohorts. Peptide mapping of common IgV families showed extensive public and private amino acid substitutions. The cohort responses to toxin A and toxin B showed limited similarity in shared IGHV subfamilies. L-chain subfamily usage was more similar in the anti-toxin A and anti-toxin B responses, however the mutational signatures for each subfamily were toxin-dependent. Samples taken both post vaccination (n = 5) or at baseline, indicating previous exposure (n = 2), showed similar anti-toxin B IgV subfamily usage and mutational profiles. In summary, this study provides the first sequence-based proteomic analysis of the antibody response to the major disease-mediating toxins of C. difficile, toxin A and toxin B, and demonstrates that despite the potential for extreme diversity, the immunoglobulin repertoire can raise convergent responses to specific pathogens whether through natural infection or following vaccination.

Infant formulations are constantly evolving as novel protein ingredients are added to make them more closely mimic the protein profile of human milk; however, precise analytical methods for characterizing and quantifying the major milk proteins in such formulations are currently lacking. This article describes an ultra-performance liquid chromatography-high-resolution mass spectrometry method for intact proteins that can efficiently detect, identify, and characterize the major milk proteins and their proteoforms (phosphorylation status, degree of glycation, genetic variants among others) in ingredients and final products, with an emphasis on detecting and quantifying specific genetic variants of β-casein in infant formulas. Method sensitivity allows detection of β-casein A1 in A2-based infant formulas with a limit of detection of 2% (grams of β-casein A1 per 100 g of total β-casein). Protein glycation affects signal intensity in a linear fashion, which permits proteins to be quantified from their mass spectrometry signals after correction according to their measured glycation index. The method was validated for the quantification of β-casein in infant formulas. Repeatability ranged from 2 to 3% and intermediate reproducibility from 5 to 9%. Calculated β-casein amounts ranged between 77 and 110% of the values based on formulations and published protein profiles for milk. Altogether, this method can be used for general fingerprinting as well as specific characterization and quantification of individual major milk proteins in dairy-based ingredients and products.

With the size of the biopharmaceutical market exponentially increasing, there is an aligned growth in the importance of data-rich analyses, not only to assess drug product safety but also to assist drug development driven by the deeper understanding of structure/function relationships. In monoclonal antibodies, many functions are regulated by N-glycans present in the constant region of the heavy chains and their mechanisms of action are not completely known. The importance of their function focuses analytical research efforts on the development of robust, accurate and fast methods to support drug development and quality control. Released N-glycan analysis is considered as the gold standard for glycosylation characterisation; however, it is not the only method for quantitative analysis of glycoform heterogeneity. In this study, ten different analytical workflows for N-glycan analysis were compared using four monoclonal antibodies. While observing good comparability between the quantitative results generated, it was possible to appreciate the advantages and disadvantages of each technique and to summarise all the observations to guide the choice of the most appropriate analytical workflow according to application and the desired depth of data generated., Graphical abstract Image 1, Highlights • Comparative analysis of N-glycans present on four monoclonal antibodies using ten analytical methods reported. • Data presented to allow for impartial selection of appropriate analytical strategy depending on depth of information desired and ease of approach. • Methods included intact and subunit strategies and glycopeptide characterisation compared to released N-glycan as the current gold standard.

Drug-load (DL) characterization of antibody-drug conjugates (ADCs) is an important analytical task due to its designation as a critical quality attribute (CQA) affecting potency and stability. Intact and subunit liquid chromatography-mass spectrometry (LC-MS) analyses can determine global drug-to-antibody ratios (DARs) that correlate well with other orthogonal analytical methods; however, peptide mapping liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis has struggled to provide complementary site-specific quantitation of drug conjugation sites. The peptide mapping method described herein utilizes stable isotope labeling to accurately quantitate the site-specific conjugation levels of a cysteine-conjugated ADC to provide "bottom-up" DAR characterization in parallel with protein sequence and post-translational modification (PTM) characterization in one multi-attribute analytical method (MAM).

Large molecule protein therapeutics have steadily grown and now represent a significant portion of the overall pharmaceutical market. These complex therapies are commonly manufactured using cell culture technology. Sequence variants (SVs) are undesired minor variants that may arise from the cell culture biomanufacturing process that can potentially affect the safety and efficacy of a protein therapeutic. SVs have unintended amino acid substitutions and can come from genetic mutations or translation errors. These SVs can either be detected using genetic screening methods or by mass spectrometry (MS). Recent advances in Next-generation Sequencing (NGS) technology have made genetic testing cheaper, faster, and more convenient compared to time-consuming low-resolution tandem MS and Mascot Error Tolerant Search (ETS)-based workflows which often require ~6 to 8 weeks data turnaround time. However, NGS still cannot detect non-genetic derived SVs while MS analysis can do both. Here, we report a highly efficient Sequence Variant Analysis (SVA) workflow using high-resolution MS and tandem mass spectrometry combined with improved software to greatly reduce the time and resource cost associated with MS SVA workflows. Method development was performed to optimize the high-resolution tandem MS and software score cutoff for both SV identification and quantitation. We discovered that a feature of the Fusion Lumos caused significant relative under-quantitation of low-level peptides and turned it off. A comparison of common Orbitrap platforms showed that similar quantitation values were obtained on a spiked-in sample. With this new workflow, the amount of false positive SVs was decreased by up to 93%, and SVA turnaround time by LC-MS/MS was shortened to 2 weeks, comparable to NGS analysis speed and making LC-MS/MS the top choice for SVA workflow.

Asparagine deamidation and aspartic acid isomerization in the complementarity determining regions (CDRs) of monoclonal antibodies may alter their affinity to the target antigen. Trastuzumab has two hot spots for deamidation and one position for isomerization in the CDRs. Little is known how complex formation with its target antigen HER2 affects these modifications. Modifications in the CDRs of trastuzumab were thus compared between the free antibody and the trastuzumab–HER2 complex when stressed under physiological conditions at 37°C. Complex formation and stability of the complex upon stressing were assessed by size-exclusion chromatography. Deamidation of light-chain Asn-30 (Lc-Asn-30) was extensive when trastuzumab was stressed free but reduced about 10-fold when the antibody was stressed in complex with HER2. Almost no deamidation of heavy-chain (Hc-Asn-55) was detected in the trastuzumab–HER2 complex, while deamidation was observed when the antibody was stressed alone. Hc-Asp-102 isomerization, a modification that critically affects biological activity, was observed to a moderate degree when the free antibody was stressed but was not detected at all in the trastuzumab–HER2 complex. This shows that complex formation has a major influence on critical modifications in the CDRs of trastuzumab.

Collagen peptide mass fingerprinting by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry, also known as zooarchaeology by mass spectrometry (ZooMS), is a rapidly growing analytical technique in the fields of archaeology, ecology, and cultural heritage. Minimally destructive and cost effective, ZooMS enables rapid taxonomic identification of large bone assemblages, cultural heritage objects, and other organic materials of animal origin. As its importance grows as both a research and a conservation tool, it is critical to ensure that its expanding body of users understands its fundamental principles, strengths, and limitations. Here, we outline the basic functionality of ZooMS and provide guidance on interpreting collagen spectra from archaeological bones. We further examine the growing potential of applying ZooMS to nonmammalian assemblages, discuss available options for minimally and nondestructive analyses, and explore the potential for peptide mass fingerprinting to be expanded to noncollagenous proteins. We describe the current limitations of the method regarding accessibility, and we propose solutions for the future. Finally, we review the explosive growth of ZooMS over the past decade and highlight the remarkably diverse applications for which the technique is suited.

Fc-fusion proteins represent a successful class of biopharmaceutical products. They are considered highly heterogeneous products due to the common degradation of amino acids that occurs during their production in upstream and downstream processes (e.g., oxidation and deamidation) and, above all, their complex glycosylation profile. Multi-dimensional liquid chromatography-mass spectrometry (mD-LC-MS) has recently gained much interest for process analytical technology, enabling the integration of this analytical technology in production and purification environments. In this study, an online mD-LC-MS/MS peptide mapping method was developed for monitoring multiple quality attributes, including the N-glycosylation state of a complex Fc-fusion protein, which is made by combining two heavily glycosylated cytokines with an Fc domain. This fully automated workflow includes sample purification, reduction, digestion, peptide mapping, and subsequent mass spectrometric analysis. Two immobilized enzyme cartridges based on trypsin and Lys-C protease were employed to generate a detailed glycosylation mapping, as trypsin allowed the identification of only one of four glycosylation sites, while Lys-C was more informative for two other sites. Site-specific glycosylation information such as antennarity, sialyation, and core fucosylation state was also determined. In addition to glycans, other post-translational modifications could be monitored simultaneously during the cell culture production processes by the mD-LC-MS/MS approach. In summary, the generated data demonstrate the applicability of mD-LC-MS for the monitoring and trending of multiple attributes for complex antibody formats over production processes in an automated and fast manner, compared to the complex and time-consuming traditional offline assays.

A newly introduced HIV-1 vaccination utilizes a fusion peptide (FP)-based immunogen-carrier conjugate system, where the FP is coupled to a protein carrier via a bifunctional linker. Such heterogeneous materials present a challenge for the routine product quality assessment. Peptide mapping LC-MS analysis has become an indispensable tool for assessing the site-specific conjugation ratio, estimating site occupancy, monitoring conjugation profiles, and analyzing post-translational modifications (PTMs) and disulfide bonds as well as high-order protein structures. To streamline the peptide mapping approach to match the needs of a fast-paced conjugate vaccine product characterization, a selection of signature fragment ions generated by MS(E) fragmentation was successfully applied to assess the product quality at the different stages of a conjugates’ manufacturing process with an emphasis on monitoring the amount of a reactive linker. This technique was employed in different conjugation studies of the protein carriers, linkers, and FP compositions as well as the cross-linked species formed during stress-degradation studies. Multiple derivatives of the intermediate and final conjugated products formed during a multistaged synthesis were monitored by means of the sensitive extracted-ion chromatogram (XIC) profiling and were included in the estimation of the site-specific conjugation loads. Differentiation of the conjugates with various FP compositions was demonstrated. The conjugation site occupancy was evaluated with respect to the solvent exposure of Lys residues. The findings of these LC-MS studies greatly aided in choosing the best conjugation strategy to ensure that the final recombinant tetanus toxoid heavy chain (rTTHc) product is chemically inert and represents a safe vaccine candidate for clinical evaluation.

Characterization of post-translational modifications (PTMs) of therapeutic antibodies is commonly performed by bottom-up approaches, involving sample preparation and peptide analysis by liquid chromatography-mass spectrometry (LC-MS). Conventional sample preparation requires extensive hands-on time and can increase the risk of inducing artificial modifications as many off-line steps - denaturation, disulfide-reduction, alkylation and tryptic digestion - are performed. In this study, we developed an on-line multidimensional (mD)-LC-MS bottom-up approach for fast sample preparation and analysis of (formulated) monoclonal antibodies and antibody-derived therapeutics. This approach allows on-column reduction, tryptic digestion and subsequent peptide analysis by RP-MS. Optimization of the 1D -and 2D flow and temperature improved the trapping of small polar peptides during on-line peptide mapping analysis. These adaptations increased the sequence coverage (95-98% versus 86-94% for off-line approaches) and allowed identification of various PTMs (i.e. deamidation of asparagine, methionine oxidation and lysine glycation) within a single analysis. This workflow enables a fast (