Fast and ultra-sensitive glycoform analysis by supercritical fluid chromatography-tandem mass spectrometry

Therapeutic monoclonal antibodies (mAbs) are currently the largest and fastest growing category of biopharmaceuticals. Glycosylation of mAbs has a significant impact on their effector functions, as well as on their safety and pharmacokinetics. Heterogeneity of glycoforms is affected by various factors such as the producing cells and cell culture process. Therefore, accurate glycoform characterization is essential for drug design, process optimization, manufacturing, and quality control of therapeutic mAbs. In this study, we developed a fast, quantitative, and highly sensitive analytical platform for mAb glycan profiling by supercritical fluid chromatography-tandem mass spectrometry (SFC-MS/MS). An 8-minute analysis of bevacizumab, nivolumab, ramucirumab, rituximab, and trastuzumab by SFC-MS detected a total of 102 glycoforms, with a detection limit of 5 attomole. The dynamic range of glycan abundance was over 6 orders of magnitude for bevacizumab analysis by SFC-MS, compared to 3 orders of magnitude for conventional fluorescence HPLC analysis. This method revealed the glycan profile characteristics and lot-to-lot heterogeneity of various therapeutic mAbs. We were also able to detect a series of structural variations in pharmacologically important glycan structures. SFC-MS-based glycoform profiling method will provide an ideal platform for in-depth analysis of precise glycan structure and abundance.

Automated Confluence Measurement Method for Mesenchymal Stem Cell from Brightfield Microscopic Images

Cell confluence is an important metric in cell culture, as proper timing is essential to maintain cell phenotype and culture quality. To estimate cell confluence, transparent cells are observed under a phase-contrast or differential interference contrast microscope by a biologist, whose estimations are error-prone and subjective. To overcome the necessity of using the phase-contrast microscope and reducing intra- and inter-observer errors, we have proposed an algorithm that automatically measures cell confluence by using a commonly used brightfield microscope. The proposed method consists of a transport-of-intensity equation-based brightfield microscopic image processing, an image reconstruction method, and an adaptive image segmentation method based on edge detection, entropy filtering, and range filtering. Experimental results have shown that our method has outperformed several popular algorithms, with an F-score of 0.84 ± 0.07, in images with various cell confluence values. The proposed algorithm is robust and accurate enough to perform confluence measurement with various lighting conditions under a low-cost brightfield microscope, making it simple and cost-effective to use for a fully automated cell culture process.

Mechanistic understanding of CHO cell culture improvement by rosmarinic acid through multi-omics analysis

The use of antioxidants in Chinese hamster ovary (CHO) cell cultures to improve monoclonal antibody production has been a topic of great interest. Nevertheless, the mechanisms by which antioxidant pathways are regulated in CHO cells and their effect on metabolism are not fully understood. In this work, we investigated how treatment with the antioxidant rosmarinic acid (RA) improved viable cell density and titer in CHO cell cultures, and attempted to explore the underlying mechanism(s) using transcriptomics and metabolomics. In particular, transcriptomics analysis indicated that RA treatment modified gene expression and strongly affected the MAPK and Akt signaling pathways which regulate cell survival and cell death. Moreover, we observed that these effects did not appear related to an intracellular metabolism change. In summary, this integrated ‘omics analysis has important implications for the role of the antioxidant RA in industrial cell culture processes. The current study also represents an example in the industry of how multi-omics can be applied to gain an in‐depth understanding of CHO cell biology and to identify critical pathways that can contribute to cell culture process improvement and cell line engineering.

Designing a Strategy for pH Control to Improve CHO Cell Productivity in Bioreactor

Background: Drastic pH drop is a common consequence of scaling up a mammalian cell culture process, where it may affect the final performance of cell culture. Although CO2 sparging and base addition are used as common approaches for pH control, these strategies are not necessarily successful in large scale bioreactors due to their effect on osmolality and cell viability. Accordingly, a series of experiments were conducted using an IgG1 producing Chinese Hamster Ovary (CHO-S) cell culture in 30 L bioreactor to assess the efficiency of an alternative strategy in controlling culture pH. Methods: Factors inducing partial pressure of CO2 and lactate accumulation (as the main factors altering culture pH) were assessed by Plackett-Burman design to identify the significant ones. As culture pH directly influences process productivity, protein titer was measured as the response variable. Subsequently, Central Composite Design (CCD) was employed to obtain a model for product titer prediction as a function of individual and interaction effects of significant variables. Results: The results indicated that the major factor affecting pH is non-efficient CO2 removal. CO2 accumulation was found to be affected by an interaction between agitation speed and overlay air flow rate. Accordingly, after increasing the agitation speed and headspace aeration, the culture pH was successfully maintained in the range of 6.95-7.1, resulting in 51% increase in final product titer. Similar results were obtained during 250 L scale bioreactor culture, indicating the scalability of the approach. Conclusion: The obtained results showed that pH fluctuations could be effectively controlled by optimizing CO2 stripping.