Long-Range Conformational Changes in Monoclonal Antibodies Revealed Using FPOP-LC-MS/MS

Differences in conformational dynamics between two full-length monoclonal antibodies have been probed in detail using Fast Photochemical Oxidation of Proteins (FPOP) followed by proteolysis and LC-ESI-MS/MS analyses. FPOP uses hydroxyl radical labelling to probe the surface-accessible regions of proteins and has the advantage that the resulting covalent modifications are irreversible, thus permitting optimal down-stream analysis. Despite the two monoclonal antibodies (mAbs) differing by only three amino acids in the heavy chain complementarity determining regions (CDRs), one mAb, MEDI1912-WFL, has been shown to undergo reversible self-association at high concentrations and exhibited poor pharmacokinetic properties in vivo, properties which are markedly improved in the variant, MEDI1912-STT. Identifying the differences in oxidative labelling between the two antibodies at residue level revealed long-range effects which provide a key insight into their conformational differences. Specifically, the amino acid mutations in the CDR region of the heavy chain resulted in significantly different labelling patterns at the interfaces of the CL–CH1 and CH1–CH2 domains, with the non-aggregating variant undergoing up to four times more labelling in this region than the aggregation prone variant, thus suggesting a change in the structure and orientation of the CL – CH1 interface. The wealth of FPOP and LC-MS data obtained enabled the study of the LC elution properties of FPOP-oxidised peptides. Some oxidised amino acids, specifically histidine and lysine, were noted to have unique effects on the retention time of the peptide, offering the promise of using such an analysis as an aid to MS/MS in assigning oxidation sites

massPix: an R package for annotation and interpretation of mass spectrometry imaging data for lipidomics

INTRODUCTION: Mass spectrometry imaging (MSI) experiments result in complex multi-dimensional datasets, which require specialist data analysis tools. OBJECTIVES: We have developed massPix—an R package for analysing and interpreting data from MSI of lipids in tissue. METHODS: massPix produces single ion images, performs multivariate statistics and provides putative lipid annotations based on accurate mass matching against generated lipid libraries. RESULTS: Classification of tissue regions with high spectral similarly can be carried out by principal components analysis (PCA) or k-means clustering. CONCLUSION: massPix is an open-source tool for the analysis and statistical interpretation of MSI data, and is particularly useful for lipidomics applications.This work was supported by the Medical Research Council (Lipid Profiling and Signalling [MC UP A90 1006] & Lipid Dynamics and Regulation [MC PC 13030])

Trace element concentrations in feathers from three seabird species breeding in the Timor Sea

Mobile marine predators, such as seabirds, are frequently used as broad samplers of contaminants that are widespread in the marine environment. The Timor Sea off remote Western Australia is a poorly studied, yet rapidly expanding area of offshore development. To provide much needed data on contamination in this region, we quantified trace element concentrations in breast feathers of three seabird species breeding on Bedout Island. While adult Masked Boobies Sula dactylatra exhibited some of the highest concentrations, values for all species were below toxicology thresholds for seabirds and were comparable to those reported in other closely related species. The low concentrations detected in the birds provide a valuable baseline and suggest that the local marine environment around Bedout is in relatively good condition. However, careful monitoring is warranted in light increasing anthropogenic activity in this region.© 2019 Published by Elsevier Ltd. The attached file is the final authors' accepted manuscript version

Next-generation cell line selection methodology leveraging data lakes, natural language generation and advanced data analytics

Cell line development is an essential stage in biopharmaceutical development that often lies on the critical path. Failure to fully characterise the lead clone during initial screening can lead to lengthy project delays during scale-up, which can potentially compromise commercial manufacturing success. In this study, we propose a novel cell line development methodology, referenced as CLD4, which involves four steps enabling autonomous data-driven selection of the lead clone. The first step involves the digitalisation of the process and storage of all available information within a structured data lake. The second step calculates a new metric referenced as the cell line manufacturability index (MICL) quantifying the performance of each clone by considering the selection criteria relevant to productivity, growth and product quality. The third step implements machine learning (ML) to identify any potential risks associated with process operation and relevant critical quality attributes (CQAs). The final step of CLD4 takes into account the available metadata and summaries all relevant statistics generated in steps 1–3 in an automated report utilising a natural language generation (NLG) algorithm. The CLD4 methodology was implemented to select the lead clone of a recombinant Chinese hamster ovary (CHO) cell line producing high levels of an antibody-peptide fusion with a known product quality issue related to end-point trisulfide bond (TSB) concentration. CLD4 identified sub-optimal process conditions leading to increased levels of trisulfide bond that would not be identified through conventional cell line development methodologies. CLD4 embodies the core principles of Industry 4.0 and demonstrates the benefits of increased digitalisation, data lake integration, predictive analytics and autonomous report generation to enable more informed decision making

An in vivo platform to select and evolve aggregation-resistant proteins

Protein biopharmaceuticals are highly successful, but their utility is compromised by their propensity to aggregate during manufacture and storage. As aggregation can be triggered by non-native states, whose population is not necessarily related to thermodynamic stability, prediction of poorly-behaving biologics is difficult, and searching for sequences with desired properties is labour-intensive and time-consuming. Here we show that an assay in the periplasm of E. coli linking aggregation directly to antibiotic resistance acts as a sensor for the innate (un-accelerated) aggregation of antibody fragments. Using this assay as a directed evolution screen, we demonstrate the generation of aggregation resistant scFv sequences when reformatted as IgGs. This powerful tool can thus screen and evolve ‘manufacturable’ biopharmaceuticals early in industrial development. By comparing the mutational profiles of three different immunoglobulin scaffolds, we show the applicability of this method to investigate protein aggregation mechanisms important to both industrial manufacture and amyloid disease

Characteristic Energy of the Coulomb Interactions and the Pileup of States

Tunneling data on $\mathrm{La_{1.28}Sr_{1.72}Mn_2O_7}$ crystals confirm Coulomb interaction effects through the $\sqrt{\mathrm{E}}$ dependence of the density of states. Importantly, the data and analysis at high energy, E, show a pileup of states: most of the states removed from near the Fermi level are found between ~40 and 130 meV, from which we infer the possibility of universal behavior. The agreement of our tunneling data with recent photoemission results further confirms our analysis.Comment: 4 pages, 4 figures, submitted to PR

Using extensional flow to reveal diverse aggregation landscapes for three IgG1 molecules

Monoclonal antibodies (mAbs) currently dominate the biopharmaceutical sector due to their potency and efficacy against a range of disease targets. These proteinaceous therapeutics are, however, susceptible to unfolding, mis‐folding, and aggregation by environmental perturbations. Aggregation thus poses an enormous challenge to biopharmaceutical development, production, formulation, and storage. Hydrodynamic forces have also been linked to aggregation, but the ability of different flow fields (e.g., shear and extensional flow) to trigger aggregation has remained unclear. To address this question, we previously developed a device that allows the degree of extensional flow to be controlled. Using this device we demonstrated that mAbs are particularly sensitive to the force exerted as a result of this flow‐field. Here, to investigate the utility of this device to bio‐process/biopharmaceutical development, we quantify the effects of the flow field and protein concentration on the aggregation of three mAbs. We show that the response surface of mAbs is distinct from that of bovine serum albumin (BSA) and also that mAbs of similar sequence display diverse sensitivity to hydrodynamic flow. Finally, we show that flow‐induced aggregation of each mAb is ameliorated by different buffers, opening up the possibility of using the device as a formulation tool. Perturbation of the native state by extensional flow may thus allow identification of aggregation‐resistant mAb candidates, their bio‐process parameters and formulation to be optimized earlier in the drug‐discovery pipeline using sub‐milligram quantities of material

Multi-Attribute Monitoring Method for Process Development of Engineered Antibody for Site-Specific Conjugation

Supporting Information: Additional experimental design, data, and analyses (PDF) is available online at https://pubs.acs.org/doi/10.1021/jasms.3c00037?goto=supporting-info .Copyright © 2022 The Authors. Antibody drug conjugates, a class of biotherapeutic proteins, have been extensively developed in recent years, resulting in new approvals and improved standard of care for cancer patients. Among the numerous strategies of conjugating cytotoxic payloads to monoclonal antibodies, insertion of a cysteine residue achieves a tightly controlled, site-specific drug to antibody ratio. Tailored analytical tools are required to direct the development of processes capable of manufacturing novel antibody scaffolds with the desired product quality. Here, we describe the development of a 12 min, mass-spectrometry-based method capable of monitoring four distinct quality attributes simultaneously: variations in the thiol state of the inserted cysteines, N-linked glycosylation, reduction of interchain disulfide bonds, and polypeptide fragmentation. This method provides new insight into the properties of the antibody intermediate and associated manufacturing processes. Oxidized thiol states are formed within the bioreactor, of which a variant containing an additional disulfide bond was produced and remained relatively constant throughout the fed-batch process; reduced thiol variants were introduced upon harvest. Nearly 20 percent of N-linked glycans contained sialic acid, substantially higher than anticipated for wildtype IgG1. Lastly, previously unreported polypeptide fragmentation sites were identified in the C239i constant domain, and the relationship between fragmentation and glycoform were explored. This work illustrates the utility of applying a high-throughput liquid chromatography–mass spectrometry multi-attribute monitoring method to support the development of engineered antibody scaffolds.AstraZeneca

Neurodegeneration and Epilepsy in a Zebrafish Model of CLN3 Disease (Batten Disease)

The neuronal ceroid lipofuscinoses are a group of lysosomal storage disorders that comprise the most common, genetically heterogeneous, fatal neurodegenerative disorders of children. They are characterised by childhood onset, visual failure, epileptic seizures, psychomotor retardation and dementia. CLN3 disease, also known as Batten disease, is caused by autosomal recessive mutations in the CLN3 gene, 80–85% of which are a ~1 kb deletion. Currently no treatments exist, and after much suffering, the disease inevitably results in premature death. The aim of this study was to generate a zebrafish model of CLN3 disease using antisense morpholino injection, and characterise the pathological and functional consequences of Cln3 deficiency, thereby providing a tool for future drug discovery. The model was shown to faithfully recapitulate the pathological signs of CLN3 disease, including reduced survival, neuronal loss, retinopathy, axonopathy, loss of motor function, lysosomal storage of subunit c of mitochondrial ATP synthase, and epileptic seizures, albeit with an earlier onset and faster progression than the human disease. Our study provides proof of principle that the advantages of the zebrafish over other model systems can be utilised to further our understanding of the pathogenesis of CLN3 disease and accelerate drug discovery