Lipid identification and quantification are essential objectives in comprehensive lipidomics studies challenged by the high number of lipids, their chemical diversity, and their dynamic range. In this work, we developed a tailored method for profiling and quantification combining (1) isotope dilution, (2) enhanced isomer separation by C30 fused-core reversed-phase material, and (3) parallel Orbitrap and ion trap detection by the Orbitrap Fusion Lumos Tribid mass spectrometer. The combination of parallelizable ion analysis without time loss together with different fragmentation techniques (HCD/CID) and an inclusion list led to higher quality in lipid identifications exemplified in human plasma and yeast samples. Moreover, we used lipidome isotope-labeling of yeast (LILY)-a fast and efficient in vivo labeling strategy in Pichia pastoris-to produce (nonradioactive) isotopically labeled eukaryotic lipid standards in yeast. We integrated the C lipids in the LC-MS workflow to enable relative and absolute compound-specific quantification in yeast and human plasma samples by isotope dilution. Label-free and compound-specific quantification was validated by comparison against a recent international interlaboratory study on human plasma SRM 1950. In this way, we were able to prove that LILY enabled quantification leads to accurate results, even in complex matrices. Excellent analytical figures of merit with enhanced trueness, precision and linearity over 4-5 orders of magnitude were observed applying compound-specific quantification withC-labeled lipids. We strongly believe that lipidomics studies will benefit from incorporating isotope dilution and LC-MSn strategies.

Charge variant analysis (CVA) of monoclonal antibodies (mAbs) using cation exchange chromatography is routinely used as a fingerprint of the distribution of posttranslational modifications present on the molecule. Traditional salt or pH based eluents are not suited for direct coupling to mass spectrometry due to nonvolatility or high ionic strength. This makes further analysis complicated when an alteration in the charge variant profile or the emergence of an additional peak is encountered. Here, the use of pH gradient elution using volatile, low ionic strength buffers is reported with direct coupling to high-resolution Orbitrap mass spectrometry. The development of a universal method based on pH elution was explored using a number of mAb drug products. Optimized methods facilitated the separation and identification of charge variants including individual glycoforms of the mAbs investigated using the same buffer system but with tailored gradient slopes. The developed method represents an exciting advance for the characterization of biopharmaceuticals as intact entities through the combination of native charge variant separations with high-resolution native mass spectrometry.

Charge variant analysis is a widely used tool to monitor changes in product quality during the manufacturing process of monoclonal antibodies (mAbs). Although it is a powerful technique for revealing mAb heterogeneity, an unexpected outcome, for example the appearance of previously undetected isoforms, requires further, time-consuming analysis. The process of identifying these unknowns can also result in unwanted changes to the molecule that are not attributable to the manufacturing process. To overcome this, we recently reported a method combining highly selective cation exchange chromatography-based charge variant analysis with on-line mass spectrometric (MS) detection. We further explored and adapted the chromatographic buffer system to expand the application range. Moreover, we observed no salt adducts on the native protein, also supported by the optimal choice of MS parameters, resulting in increased data quality and mass accuracy. Here, we demonstrate the utility of this improved method by performing an in-depth analysis of adalimumab before and after forced degradation. By combining molecular mass and retention time information, we were able to identify multiple modifications on adalimumab, including lysine truncation, glycation, deamidation, succinimide formation, isomerisation, N-terminal aspartic acid loss or C-terminal proline amidation and fragmentation along with the N-glycan distribution of each of these identified proteoforms. Host cell protein (HCP) analysis was performed using liquid chromatography-mass spectrometry that verified the presence of the protease Cathepsin L. Based on the presence of trace HCPs with catalytic activity, it can be questioned if fragmentation is solely driven by spontaneous hydrolysis or possibly also by enzymatic degradation.

Due to its compatibility and orthogonality to reversed phase (RP) liquid chromatography (LC) separation, ion exchange chromatography, and mainly strong cation exchange (SCX), has often been the first choice in multidimensional LC experiments in proteomics. Here, we have tested the ability of three strong anion exchanger (SAX) columns differing in their hydrophobicity to fractionate RAW264.7 macrophage cell lysate. IonPac AS24, a strong anion exchange material with ultralow hydrophobicity, demonstrated to be superior to other materials by fractionation and separation of tryptic peptides from both a mixture of 6 proteins as well as mouse cell lysate. The chromatography displayed very high orthogonality and high robustness depending on the hydrophilicity of column chemistry, which we termed hydrophilic strong anion exchange (hSAX). Mass spectrometry analysis of 34 SAX fractions from RAW264.7 macrophage cell lysate digest resulted in an identification of 9469 unique proteins and 126318 distinct peptides in one week of instrument time. Moreover, when compared to an optimized high pH/low pH RP separation approach, the method presented here raised the identification of proteins and peptides by 10 and 28%, respectively. This novel hSAX approach provides robust, reproducible, and highly orthogonal separation of complex protein digest samples for deep coverage proteome analysis.

This work describes a novel application of capillary-flow ion chromatography mass spectrometry for metabolomic analysis, and comparison of the technique to octadecyl silica and hydrophilic interaction chromatography (HILIC)-based mass spectrometry. While liquid chromatography/mass spectrometry (LC/MS) is rapidly becoming the standard technique for metabolomic analysis, metabolomic samples are extremely heterogeneous, leading to a requirement for multiple methods of analysis and separation techniques to perform a 'global' metabolomic analysis. While C18 is suitable for hydrophobic metabolites and has been used extensively in pharmaceutical drug metabolism studies, HILIC is, in general, efficient at separating polar metabolites. Phosphorylated species and organic acids are challenging to analyse and effectively quantitate on both systems. There is therefore a requirement for an MS-compatible analytical technique that can separate negatively charged compounds, such as ion-exchange chromatography. Evaluation of capillary flow ion chromatography with electrolytic suppression was performed on a library of metabolite standards and was shown to effectively separate organic acids and sugar di- and tri-phosphates. Limits of detection for these compounds range from 0.01 to 100 pmol on-column. Application of capillary ion chromatography to a comparative analysis of energy metabolism in procyclic forms of the parasitic protozoan Trypanosoma brucei where cells were grown on glucose or proline as a carbon source was demonstrated to be more effective than HILIC for detection of the organic acids that comprise glucose central metabolism and the tricarboxylic acid (TCA) cycle.

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.

Large RNA including mRNA (mRNA) has emerged as an important new class of therapeutics. Recently, this has been demonstrated by two highly efficacious vaccines based on mRNA sequences encoding for a modified version of the SARS-CoV-2 spike protein. There is currently significant demand for the development of new and improved analytical methods for the characterization of large RNA including mRNA therapeutics. In this study, we have developed an automated, high-throughput workflow for the rapid characterization and direct sequence mapping of large RNA and mRNA therapeutics. Partial RNase digestions using RNase T1 immobilized on magnetic particles were performed in conjunction with high-resolution liquid chromatography–mass spectrometry analysis. Sequence mapping was performed using automated oligoribonucleotide annotation and identifications based on MS/MS spectra. Using this approach, a >80% sequence of coverage of a range of large RNAs and mRNA therapeutics including the SARS-CoV-2 spike protein was obtained in a single analysis. The analytical workflow, including automated sample preparation, can be completed within 90 min. The ability to rapidly identify, characterize, and sequence map large mRNA therapeutics with high sequence coverage provides important information for identity testing, sequence validation, and impurity analysis.

Charge variant analysis is a widely used analytical tool in characterization of monoclonal antibodies (mAbs). It depicts the heterogeneity of charge variant forms, some of which may differ by only minor modifications of a single amino acid. The analysis ensures product consistency with no unwanted changes to the protein. With increasing numbers of new mAb drug products emerging in the market, the need for a robust charge variant analysis has intensified. The charge variant profiles often display partially resolved peaks on shoulders of larger peaks. This puts considerably more pressure on the robustness of the method to maintain the suboptimum selectivity. New products and techniques have emerged to address these requirements, in addition to the pre-existing older methods that may not have been optimized correctly in the past. This has led to some confusion as to the best approach and strategies in optimization of charge variant analysis. We show studies from several different approaches using on-line pH monitoring to check the performance characteristics of the methods. This has led to new insights on the interactions between the protein, column, and buffer constituents. We dispel some inaccurate assumptions about the different ion-exchange elution mechanisms and suggest ways to develop high-throughput methods that remain robust and of high resolution. Streamlined automatable method development tools are presented that will result in more efficient method optimization. The mechanisms behind poor chromatography design have provided an alternative explanation behind some methods failing when in the QC laboratories.