Applying genome scale metabolic models integrated with OMICs technologies for improvemwent of commercial CHO cell culture process

Although metabolic flux analysis has been established in microbial fermentation, their application in CHO cell culture is sparse. In general CHO cell culture process development is highly rely on empirical experience with limited cell and metabolite data without good mechanism understanding. The purpose of this research is to apply genome scale metabolic modeling for CHO cell culture process improvement. Recently we found that several medium components had significant impact on mAb production by BMSCHO1, a proprietary cell line (Fig. 1). Some of medium components at a low concentration, though within normal ranges for CHO cell culture, caused the BMSCHO1 crashed. Meanwhile some of the other medium components at a low concentration did not cause cell crash, but significantly decreased productivity. The preliminary genetic test results indicated no change in DNA copy number and southern blot integration profile under different medium conditions. Currently we are investigating both supernatant and cell pellets for metabolomics analysis using NMR and LCMS, and assessing epigenetic characteristics. In addition, transcriptomics data have been analyzed by RNA sequence and RT-PCR. Genome-scale modeling integrated with these OMICS datasets have been built and analyzed. In the presentation, we plan to share the investigation details of commercial cell-line and manufacturing process based on the application of genome scale modeling integrated with OMICS technology. Please click Additional Files below to see the full abstract

Upstream control strategy development for afucosylated species in mAb biomanufacturing

Please click Additional Files below to see the full abstract

Insights into the Impact of Rosmarinic Acid on CHO Cell Culture Improvement through Transcriptomics 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 antioxidants do not have consistent benefits of production improvement, which might be cell line specific and/or process specific. In this work, we investigated how treatment with the antioxidant rosmarinic acid (RA) improved cell growth and titer in CHO cell cultures using transcriptomics. In particular, transcriptomics analysis indicated that RA treatment modified gene expression and strongly affected the MAPK and PI3K/Akt signaling pathways, which regulate cell survival and cell death. Moreover, it was observed that these signaling pathways, which had been identified to be up-regulated on day 2 and day 6 by RA, were also up-regulated over time (from initial growth phase day 2 to slow growth or protein production phase day 6) in both conditions. In summary, this transcriptomics analysis provides insights into the role of the antioxidant RA in industrial cell culture processes. The current study also represents an example in the industry of how 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

Integration of Time-Series Transcriptomic Data with Genome-Scale CHO Metabolic Models for mAb Engineering

Chinese hamster ovary (CHO) cells are the most commonly used cell lines in biopharmaceutical manufacturing. Genome-scale metabolic models have become a valuable tool to study cellular metabolism. Despite the presence of reference global genome-scale CHO model, context-specific metabolic models may still be required for specific cell lines (for example, CHO-K1, CHO-S, and CHO-DG44), and for specific process conditions. Many integration algorithms have been available to reconstruct specific genome-scale models. These methods are mainly based on integrating omics data (i.e., transcriptomics, proteomics, and metabolomics) into reference genome-scale models. In the present study, we aimed to investigate the impact of time points of transcriptomics integration on the genome-scale CHO model by assessing the prediction of growth rates with each reconstructed model. We also evaluated the feasibility of applying extracted models to different cell lines (generated from the same parental cell line). Our findings illustrate that gene expression at various stages of culture slightly impacts the reconstructed models. However, the prediction capability is robust enough on cell growth prediction not only across different growth phases but also in expansion to other cell lines

Integration of Time-Series Transcriptomic Data with Genome-Scale CHO Metabolic Models for mAb Engineering

Chinese hamster ovary (CHO) cells are the most commonly used cell lines in biopharmaceutical manufacturing. Genome-scale metabolic models have become a valuable tool to study cellular metabolism. Despite the presence of reference global genome-scale CHO model, context-specific metabolic models may still be required for specific cell lines (for example, CHO-K1, CHO-S, and CHO-DG44), and for specific process conditions. Many integration algorithms have been available to reconstruct specific genome-scale models. These methods are mainly based on integrating omics data (i.e., transcriptomics, proteomics, and metabolomics) into reference genome-scale models. In the present study, we aimed to investigate the impact of time points of transcriptomics integration on the genome-scale CHO model by assessing the prediction of growth rates with each reconstructed model. We also evaluated the feasibility of applying extracted models to different cell lines (generated from the same parental cell line). Our findings illustrate that gene expression at various stages of culture slightly impacts the reconstructed models. However, the prediction capability is robust enough on cell growth prediction not only across different growth phases but also in expansion to other cell lines.</jats:p

Prediction of N-linked Glycoform Profiles of Monoclonal Antibody with Extracellular Metabolites and Two-Step Intracellular Models

Monoclonal antibodies (mAbs) are commonly glycosylated and show varying levels of galactose attachment. A set of experiments in our work showed that the galactosylation level of mAbs was altered by the culture conditions of hybridoma cells. The uridine diphosphate galactose (UDP-Gal) is one of the substrates of galactosylation. Based on that, we proposed a two-step model to predict N-linked glycoform profiles by solely using extracellular metabolites from cell culture. At the first step, the flux level of UDP-Gal in each culture was estimated based on a computational flux balance analysis (FBA); its level was found to be linear with the galactosylation degree on mAbs. At the second step, the glycoform profiles especially for G0F (agalactosylated), G1F (monogalactosylated) and G2F (digalactosylated) were predicted by a kinetic model. The model outputs well matched with the experimental data. Our study demonstrated that the integrated mathematical approach combining FBA and kinetic model is a promising strategy to predict glycoform profiles for mAbs during cell culture processes.</jats:p

Comparison of Permissive Hypotension vs. Conventional Resuscitation Strategies in Adult Trauma Patients with Hemorrhagic Shock: An Updated Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Abstract BackgroundThere is still an ongoing battle against the Permissive Hypotension (PH) through Conventional Resuscitation Strategies (CR). Active fluid resuscitation in patients with traumatic shock can bring many problems, as it is known that standard high-volume resuscitation can exacerbate the lethal triad of acidemia, hypothermia, and coagulopathy. As a part of damage control resuscitation strategy, it can reduce mortality and shorten hospital stay, compared with the use of standard liquids. Moreover, its application is gradually receiving wider attention (1) . This review evaluated the effectiveness and safety of permissive hypotension resuscitation in adult patients with traumatic hemorrhagic shock.MethodsThe systematic review and meta-analysis were conducted according to PRISMA guidelines. We searched PubMed, EMBASE and Cochrane databases for randomized controlled trials (RCTs) from the beginning to March 2021 to compare the therapeutic effects of controlled fluid resuscitation and conventional fluid resuscitation on patients with traumatic hemorrhagic shock. Two reviewers independently conducted screening, data extraction and bias assessment. Data analysis was performed using Cochrane Collaboration Software Revman 5.2. The primary outcome was 30-day or in-hospital mortality. Secondary outcomes included blood routine index, coagulation function, resuscitation fluid use, complications, and length of hospital stay. Pooling was performed with a random-effects model.Results8 randomized controlled trials were screened out of 898 studies and 1593 patients were evaluated. The target blood pressure of the intervention group ranged from 50-90 mmHg in systolic pressure or mean arterial pressure ≥ 50 mmHg, while that of the control group was 65-110 mmHg systolic pressure or mean arterial pressure ≥ 60 mmHg. Only patients with penetrating injuries were evaluated in two studies, while the remaining six included blunt injuries. A statistically significant reduction in mortality was observed in the intervention group (RR = 0.70; 95%CI= 0.58-0.84; P &lt; 0.05). Small heterogeneity was observed in the included articles (χ2 = 8.9; P = 0.18; I2 = 33%). The loss of platelet (PLT), hemoglobin (Hb) and body fluid was properly protected, the amount of resuscitation fluid was reduced, and the incidence of some adverse events was effectively reduced. There was no significant difference in coagulation time and hospital stay between the two groups.ConclusionsThis meta-analysis reveals the survival benefits of hypotension resuscitation in patients with traumatic hemorrhagic shock. The significant advantage is to promote the recovery of patients' physical function and reduce the incidence of treatment-related complications such as acute respiratory distress syndrome (ARDS), acute kidney injury (AKI) and multiple organ dysfunction syndrome (MODS), which reduces the mortality. Convincing evidences are provided based on these results, but larger, multicenter, randomized trials are needed to confirm the findings.</jats:p