Lipidomic analysis to enhance the understanding of Chinese Hamster ovary cells

Chinese Hamster Ovary (CHO) cell lines are common hosts for the production of biotherapeutic proteins. Achieving high level of specific protein production by CHO cell lines remains a challenge. In order to address this issue, we are incorporating lipidomic analyses to study the role of lipids played in CHO-S cells. In our study, we have applied chromatography (TLC) methods for lipid analysis in terms of lipid polarity. For polar lipids, 2-D HPTLC (2-dimensional high performance TLC) was used instead of conventional 1D- TLC by virtue of its high separation capacity. The eluting solvent system was optimized for the 1st and 2nd dimension, respectively. Neutral lipids were separated on 1-D HPTLC with the optimal elution solvent of hexane-diethyl ether-acetic acid. The lipid spots on the TLC plates were stained by 0.2% of 2,7-dichlorofluorescein dissolved in ethanol solution and illuminated with UV. Multiple lipid standards were also run to correctly identify the lipid spots and the fluorescence of lipid spots was semi-quantitatively measured with ImageJ. By optimization of TLC conditions, the lipids of CHO-S cell line were separated successfully and the lipid contents were semi-quantified. From neutral lipids result, we observed high level of certain lipids in CHO-S cell lines. We will further investigate which lipid play a key role in various cell processes

Demonstrating a powerful scale-up strategy for Biosimilar mAb in single use systems via physicochemical and functional characterization

Biosimilars have received a remarkable attention in the recent years. Due to the heterogeneity of biosimilar mAbs, they need to be well-characterized by various orthogonal techniques in order to identify their physicochemical and functional characteristics. Characterization of the post translational modifications, especially, glycosylation is vital to define the critical quality attributes (CQAs) which affect safety, efficacy and quality of drugs. In this study, we were able to manipulate the quality of the drug by using scale-up strategies for single use systems. By using ultra-performance liquid chromatography (UPLC) coupled to mass spectrometry (MS), we were able to demonstrate physicochemical similarities between innovator and its biosimilar candidate. Even the PTM (N-terminal pyroglutamic acid formation, C-terminal lysine truncation, methionine and tryptophan oxidation, asparagine deamidation, N-glycosylation and glycation) levels of two products from 3 and 200-liter single-use bioreactors were highly similar compared to the innovator. The mass spectrometry studies showed that the scale-up strategy from 3 liter to 200 liter was successful. Deconvoluted mass spectrum for intact and reduced masses (heavy and light chain) of innovator and its biosimilar candidates from different production scales were significantly similar. Oxidation was observed to be lower in 200 liter bioreactor compared to the 3 liter. The N-glycan profiles for the major and minor glycan species were highly similar compared to the originator. Aggregation level in 200 liter was slightly lower than that of the small scale production. Mass spectrometry becomes an important tool to enhance the biosimilarity to the originator in order to decrease the clinical efforts to be able to provide affordable drugs to the patients

Glycoproteomic and glycomic databases

Protein glycosylation serves critical roles in the cellular and biological processes of many organisms. Aberrant glycosylation has been associated with many illnesses such as hereditary and chronic diseases like cancer, cardiovascular diseases, neurological disorders, and immunological disorders. Emerging mass spectrometry (MS) technologies that enable the high-throughput identification of glycoproteins and glycans have accelerated the analysis and made possible the creation of dynamic and expanding databases. Although glycosylation-related databases have been established by many laboratories and institutions, they are not yet widely known in the community. Our study reviews 15 different publicly available databases and identifies their key elements so that users can identify the most applicable platform for their analytical needs. These databases include biological information on the experimentally identified glycans and glycopeptides from various cells and organisms such as human, rat, mouse, fly and zebrafish. The features of these databases - 7 for glycoproteomic data, 6 for glycomic data, and 2 for glycan binding proteins are summarized including the enrichment techniques that are used for glycoproteome and glycan identification. Furthermore databases such as Unipep, GlycoFly, GlycoFish recently established by our group are introduced. The unique features of each database, such as the analytical methods used and bioinformatical tools available are summarized. This information will be a valuable resource for the glycobiology community as it presents the analytical methods and glycosylation related databases together in one compendium. It will also represent a step towards the desired long term goal of integrating the different databases of glycosylation in order to characterize and categorize glycoproteins and glycans better for biomedical research

Genome-scale reconstructions of the mammalian secretory pathway predict metabolic costs and limitations of protein secretion

In mammalian cells, >25% of synthesized proteins are exported through the secretory pathway. The pathway complexity, however, obfuscates its impact on the secretion of different proteins. Unraveling its impact on diverse proteins is particularly important for biopharmaceutical production. Here we delineate the core secretory pathway functions and integrate them with genome-scale metabolic reconstructions of human, mouse, and Chinese hamster ovary\ua0cells. The resulting reconstructions enable the computation of energetic costs and machinery demands of each secreted protein. By integrating additional omics data, we find that highly secretory cells have adapted to reduce expression and secretion of other expensive host cell proteins. Furthermore, we predict metabolic costs and maximum productivities of biotherapeutic proteins and identify protein features that most significantly impact protein secretion. Finally, the model successfully predicts the increase in secretion of a monoclonal antibody after silencing a highly expressed selection marker. This work represents a knowledgebase of the mammalian secretory pathway that serves as a novel tool for systems biotechnology

Genome-scale reconstructions of the mammalian secretory pathway predict metabolic costs and limitations of protein secretion.

In mammalian cells, >25% of synthesized proteins are exported through the secretory pathway. The pathway complexity, however, obfuscates its impact on the secretion of different proteins. Unraveling its impact on diverse proteins is particularly important for biopharmaceutical production. Here we delineate the core secretory pathway functions and integrate them with genome-scale metabolic reconstructions of human, mouse, and Chinese hamster ovary cells. The resulting reconstructions enable the computation of energetic costs and machinery demands of each secreted protein. By integrating additional omics data, we find that highly secretory cells have adapted to reduce expression and secretion of other expensive host cell proteins. Furthermore, we predict metabolic costs and maximum productivities of biotherapeutic proteins and identify protein features that most significantly impact protein secretion. Finally, the model successfully predicts the increase in secretion of a monoclonal antibody after silencing a highly expressed selection marker. This work represents a knowledgebase of the mammalian secretory pathway that serves as a novel tool for systems biotechnology