Understanding the effect of oxidative and ER stress on CHO cell culture and product quality through multivariate analysis

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Experimental and Computational Approaches to Control Mammalian Cell Proliferation, Protein Production, and Post-translational Modifications

Therapeutic antibodies, with their high specificity and flexibility, are responsible for treating many acute and chronic diseases. In particular, monoclonal antibodies remain the largest sector in sales and market growth in the biotechnology industry. The production of antibody biologics involves a rigorous pipeline of target identification, cell line development, upstream processing, downstream processing, and product formulation - each facing its unique challenges. Specifically, in the upstream sector, two main characteristics critically define the production cost and quality of the antibodies made: antibody titer, or the total amount of protein harvestable, and protein critical quality attributes (CQAs). The first determines the batch consistency and cost of delivery, while the latter determines the safety and efficacy of the antibody product. In this thesis, we used a small molecule, rosmarinic acid, which significantly improved cellular proliferation as a model to study pathway stimulations to enhance antibody production. In addition, through a combination of media supplementation and process variation strategies, we improved antibody production maximally threefold without compromising either cellular-specific productivity or glycosylation attributes. In addition, to meet market demands and deliver safe and potent therapeutics in time, both high production and quality standards must be met. This requires parallel screening and development of clonal cells and optimal cell growth conditions at the bench scale before manufacturing. The complexity of cellular pathways and the different post-translational needs of products have created significant challenges for rational process design strategies. Importantly, with a rising interest in developing redox and endoplasmic reticulum (ER) stress biosensors to unravel and control cellular behavior for protein production runs, reports of varied cellular stress effects on cell growth and protein production convolute understanding; and determination of the effect of cellular stress on antibody quality is still deficient. In the second part of the thesis, we address this unique yet complicated problem by identifying representative oxidative and ER stressors combined with design-of-experiment (DOE)-guided experimentation to implement a high-dimensional space accommodating different degrees of cellular stress to study their impacts on the cell culture process and protein quality. We also develop a high- throughput assay platform to detect both absolute and relative glycosylation simultaneously and examine how these attributes may be controlled via hybrid modeling to interface with rapid digitization in the bioprocessing industry. Further, in the third part of my thesis, I use small molecules and empirical models to actively control antibody glycosylation, one of the most important CQAs, and discuss how the implementation of process analytical tools for glycosylation may benefit the overall control process. In the last part of this thesis, we explore protein quality control in the ER and nucleus in a protein misfolding disease driven by tau protein. Tau protein aggregation drives the onset and progression of Alzheimer’s disease, the 6th leading cause of death in the United States reported in 2021. While tau protein commonly localizes in the cytosol, under pathological conditions it has been reported to associate with the nucleus and endoplasmic reticulum. Here, we use protein localization motifs to reroute tau localization to study its expression and phosphorylation characteristics in the ER and nucleus. Finally, possible mechanisms driven by the tau variant P301L, a common mutation in Alzheimer’s disease, will be discussed through an omics analysis of miRNA sequencing from exosomes derived from wildtype and P301L tau variants in neuronal cells.</p

Moving protein PEGylation from an art to a data science

[Image: see text] PEGylation is a well-established and clinically proven half-life extension strategy for protein delivery. Protein modification with amine-reactive poly(ethylene glycol) (PEG) generates heterogeneous and complex bioconjugate mixtures, often composed of several PEG positional isomers with varied therapeutic efficacy. Laborious and costly experiments for reaction optimization and purification are needed to generate a therapeutically useful PEG conjugate. Kinetic models which accurately predict the outcome of so-called “random” PEGylation reactions provide an opportunity to bypass extensive wet lab experimentation and streamline the bioconjugation process. In this study, we propose a protein tertiary structure-dependent reactivity model that describes the rate of protein-amine PEGylation and introduces “PEG chain coverage” as a tangible metric to assess the shielding effect of PEG chains. This structure-dependent reactivity model was implemented into three models (linear, structure-based, and machine-learned) to gain insight into how protein-specific molecular descriptors (exposed surface areas, pK(a), and surface charge) impacted amine reactivity at each site. Linear and machine-learned models demonstrated over 75% prediction accuracy with butylcholinesterase. Model validation with Somavert, PEGASYS, and phenylalanine ammonia lyase showed good correlation between predicted and experimentally determined degrees of modification. Our structure-dependent reactivity model was also able to simulate PEGylation progress curves and estimate “PEGmer” distribution with accurate predictions across different proteins, PEG linker chemistry, and PEG molecular weights. Moreover, in-depth analysis of these simulated reaction curves highlighted possible PEG conformational transitions (from dumbbell to brush) on the surface of lysozyme, as a function of PEG molecular weight

Re-engineering lysozyme solubility and activity through surfactant complexation

Hydrophobic ion-pairing is an established solubility engineering technique that uses amphiphilic surfactants to modulate drug lipophilicity and facilitate encapsulation in polymeric and lipid-based drug delivery systems. For proteins, surfactant complexation can also lead to unfolding processes and loss in bioactivity. In this study, we investigated the impact of two surfactants, sodium dodecyl sulphate (SDS) and dioctyl sulfosuccinate (DOSS) on lysozyme's solubility, activity, and structure. SDS and DOSS were combined with lysozyme at increasing charge ratios (4 : 1, 2 : 1, 1 : 1, 1 : 2 and 1 : 4) via hydrophobic ion pairing at pH 4.5. Maximum complexation efficiency at the 1 : 1 charge ratio was confirmed by protein quantitation assays and zeta potential measurements, showing a near neutral surface charge. Lysozyme lipophilicity was successfully increased, with log D n-octanol/PBS values up to 2.5 with SDS and 1.8 with DOSS. Bioactivity assays assessing lysis of M. lysodeikticus cell walls showed up to a 2-fold increase in lysozyme's catalytic ability upon complexation with SDS at ratios less than stoichiometric, suggesting favourable mechanisms of stabilisation. Secondary structural analysis using Fourier-transform infrared spectroscopy indicated that lysozyme underwent a partial unfolding process upon complexation with low SDS concentrations. Molecular dynamic simulations further confirmed that at these low concentrations, a positive conformation was obtained with the active site residue Glu 35 more solvent-exposed. Combined, this suggested that sub-stoichiometric SDS altered the active site's secondary structure through increased backbone flexibility, leading to higher substrate accessibility. For DOSS, low surfactant concentrations retained lysozyme's native function and structure while still increasing the protein's lipophilic character. Our research findings demonstrate that modulation of protein activity can be related to surfactant chemistry and that controlled ion-pairing can lead to re-engineering of lysozyme solubility, activity, and structure. This has significant implications for advanced protein applications in healthcare, particularly towards the development of formulation strategies for oral biotherapeutics.<br/