Manipulation of mRNA translation elongation influences the fragmentation of a biotherapeutic Fc-fusion protein produced in CHO cells.

Mammalian cells, particularly Chinese hamster ovary cells, are the dominant system for the production of protein-based biotherapeutics, however, product degradation, particularly of Fc-fusion proteins, is sometimes observed that impacts the quality of the protein generated. Here, we identify the site of fragmentation of a model immunoglobulin G1 Fc-fusion protein, show that the observed clipping and aggregation are decreased by reduced temperature culturing, that the fragmentation/clipping is intracellular, and that reduced clipping at a lower temperature (<37°C) relates to mesenger RNA (mRNA) translation elongation. We subsequently show that reduced fragmentation can be achieved at 37°C by addition of chemical reagents that slow translation elongation. We then modified mRNA translation elongation speeds by designing different transcript sequences for the Fc-fusion protein based on alternative codon usage and improved the product yield at 37°C, and the ratio of intact to a fragmented product. Our data suggest that rapid elongation results in misfolding that decreases product fidelity, generating a region susceptible to degradation/proteolysis, whilst the slowing of mRNA translation improves the folding, reducing susceptibility to fragmentation. Manipulation of mRNA translation and/or the target Fc-fusion transcript is, therefore, an approach that can be applied to potentially reduce fragmentation of clipping-prone Fc-fusion proteins.

A proline metabolism selection system and its application to the engineering of lipid biosynthesis in Chinese hamster ovary cells.

Chinese hamster ovary (CHO) cells are the leading mammalian cell host employed to produce complex secreted recombinant biotherapeutics such as monoclonal antibodies (mAbs). Metabolic selection marker technologies (e.g. glutamine synthetase (GS) or dihydrofolate reductase (DHFR)) are routinely employed to generate such recombinant mammalian cell lines. Here we describe the development of a selection marker system based on the metabolic requirement of CHO cells to produce proline, and that uses pyrroline-5-carboxylase synthetase (P5CS) to complement this auxotrophy. Firstly, we showed the system can be used to generate cells that have growth kinetics in proline-free medium similar to those of the parent CHO cell line, CHOK1SV GS-KO™ grown in proline-containing medium. As we have previously described how engineering lipid metabolism can be harnessed to enhance recombinant protein productivity in CHO cells, we then used the P5CS selection system to re-engineer lipid metabolism by over-expression of either sterol regulatory element binding protein 1 (SREBF1) or stearoyl CoA desaturase 1 (SCD1). The cells with re-engineered proline and lipid metabolism showed consistent growth and P5CS, SCD1 and SREBF1 expression across 100 cell generations. Finally, we show that the P5CS and GS selection systems can be used together. A GS vector containing the light and heavy chains for a mAb was super-transfected into a CHOK1SV GS-KO™ host over-expressing SCD1 from a P5CS vector. The resulting stable transfectant pools achieved a higher concentration at harvest for a model difficult to express mAb than the CHOK1SV GS-KO™ host. This demonstrates that the P5CS and GS selection systems can be used concomitantly to enable CHO cell line genetic engineering and recombinant protein expression.

Selection of CHO host and recombinant cell pools by inhibition of the proteasome results in enhanced product yields and cell specific productivity.

Chinese hamster ovary (CHO) cells are the leading mammalian cell expression platform for biotherapeutic recombinant molecules yet some proteins remain difficult to express (DTE) in this, and other, systems. In recombinant cell lines expressing DTE proteins, cellular processes to restore proteostasis can be triggered when the folding and modification capabilities are exceeded, including the unfolded protein response and ER-associated degradation (ERAD) and proteasomal degradation. We therefore investigated whether the proteasome activity of CHO cells was linked to their ability to produce recombinant proteins. We found cell lines with diverse monoclonal antibody (mAb) productivity show different susceptibilities to inhibitors of proteasome activity. Subsequently, we applied selective pressure using proteasome inhibitors on mAb producing cells to determine the impact on cell growth and recombinant protein production, and to apply proteasome selective pressure above that of a metabolic selection marker during recombinant cell pool construction. The presence of proteasome inhibitors during cell pool construction expressing two different model molecules, including a DTE Fc-fusion protein, resulted in the generation of cell pools with enhanced productivity. The increased productivities, and ability to select for higher producing cells, has potential to improve clonal selection during upstream processes of DTE proteins.

Feedback control of two supplemental feeds during fed-batch culture on a platform process using inline Raman models for glucose and phenylalanine concentration.

The use of Raman models for glucose and phenylalanine concentrations to provide the signal for a control algorithm to continuously adjust the feed rate of two separate supplemental feeds during the fed-batch culture of a CHOK1SV GS-KO® cell line in a platform process was evaluated. Automated feed rate adjustment of the glucose feed using a Raman model for glucose concentration, maintained the glucose concentration within the desired target (average deviation ± 0.49 g/L). Automated feed rate adjustment of the nutrient feed using a Raman model for phenylalanine concentration, maintained phenylalanine concentrations within the target (average deviation ± 29.97 mg/L). The novel use of a Raman model for phenylalanine concentration, combined with a Raman model for glucose concentration, to maintain target glucose and phenylalanine concentrations through feed-rate adjustments, reduced the average cumulative glucose and nutrient feed additions (19% and 27% respectively) compared to manually adjusted cultures. Additionally, the proposed automation strategy led to lower osmolality during culture, maintained the nutrient environment more consistently, and achieved higher harvest product concentration (≈ 20% higher) compared to typical fed-batch process control for the cell line and platform process evaluated. Furthermore, the proposed feeding strategy yielded similar glycosylation and charge variant profiles compared to manually adjusted fed-batch process control. The ability to continuously adjust the feed rate addition of two separate feeds in this manner helps enable a shift away from the current daily offline sampling needed to control fed-batch mammalian cell culture during clinical and commercial manufacturing on platform processes.

Data for engineering lipid metabolism of Chinese hamster ovary (CHO) cells for enhanced recombinant protein production.

The data presented in this article relates to the manuscript entitled 'Engineering of Chinese hamster ovary cell lipid metabolism results in an expanded ER and enhanced recombinant biotherapeutic protein production', published in the Journal Metabolic Engineering [1]. In the article here, we present data examining the overexpression of the lipid metabolism modifying genes SCD1 and SREBF1 in CHO cells by densitometry of western blots and by using mass spectrometry to investigate the impact on specific lipid species. We also present immunofluorescence data at the protein level upon SCD1 and SREBF1 overexpression. The growth profile data during batch culture of control CHO cells and CHO cells engineered to overexpress SCD1 and SREBF1 during batch culture are also reported. Finally, we report data on the yields of model secretory recombinant proteins produced from control, SCD1 or SREBF1 engineered cells using a transient expression systems.

Engineering of Chinese hamster ovary cell lipid metabolism results in an expanded ER and enhanced recombinant biotherapeutic protein production.

Chinese hamster ovary (CHO) cell expression systems have been exquisitely developed for the production of recombinant biotherapeutics (e.g. standard monoclonal antibodies, mAbs) and are able to generate efficacious, multi-domain proteins with human-like post translational modifications at high concentration with appropriate product quality attributes. However, there remains a need for development of new CHO cell expression systems able to produce more challenging secretory recombinant biotherapeutics at higher yield with improved product quality attributes. Amazingly, the engineering of lipid metabolism to enhance such properties has not been investigated even though the biosynthesis of recombinant proteins is at least partially controlled by cellular processes that are highly dependent on lipid metabolism. Here we show that the global transcriptional activator of genes involved in lipid biosynthesis, sterol regulatory element binding factor 1 (SREBF1), and stearoyl CoA desaturase 1 (SCD1), an enzyme which catalyzes the conversion of saturated fatty acids into monounsaturated fatty acids, can be overexpressed in CHO cells to different degrees. The amount of overexpression obtained of each of these lipid metabolism modifying (LMM) genes was related to the subsequent phenotypes observed. Expression of a number of model secretory biopharmaceuticals was enhanced between 1.5-9 fold in either SREBF1 or SCD1 engineered CHO host cells as assessed under batch and fed-batch culture. The SCD1 overexpressing polyclonal pool consistently showed increased concentration of a range of products. For the SREBF1 engineered cells, the level of SREBF1 expression that gave the greatest enhancement in yield was dependent upon the model protein tested. Overexpression of both SCD1 and SREBF1 modified the lipid profile of CHO cells and the cellular structure. Mechanistically, overexpression of SCD1 and SREBF1 resulted in an expanded endoplasmic reticulum (ER) that was dependent upon the level of LMM overexpression. We conclude that manipulation of lipid metabolism in CHO cells via genetic engineering is an exciting new approach to enhance the ability of CHO cells to produce a range of different types of secretory recombinant protein products via modulation of the cellular lipid profile and expansion of the ER.

Improving the accuracy of flux balance analysis through the implementation of carbon availability constraints for intracellular reactions.

Constraint-based modeling methods, such as Flux Balance Analysis (FBA), have been extensively used to decipher complex, information rich -omics datasets to elicit system-wide behavioral patterns of cellular metabolism. FBA has been successfully used to gain insight in a wide range of applications, such as range of substrate utilization, product yields and to design metabolic engineering strategies to improve bioprocess performance. A well-known challenge associated with large genome-scale metabolic networks is that they result in underdetermined problem formulations. Consequently, rather than unique solutions, FBA and related methods examine ranges of reaction flux values that are consistent with the studied physiological conditions. The wider the reported flux ranges, the higher the uncertainty in the determination of basic reaction properties, limiting interpretability of and confidence in the results. Herein, we propose a new, computationally efficient approach that refines flux range predictions by constraining reaction fluxes on the basis of the elemental balance of carbon. We compared carbon constraint FBA (ccFBA) against experimentally-measured intracellular fluxes using the latest CHO GEM (iCHO1766) and were able to substantially improve the accuracy of predicted flux values compared with FBA. ccFBA can be used as a stand-alone method but is also compatible with and complimentary to other constraint-based approaches.

At-line raman spectroscopy and design of experiments for robust monitoring and control of miniature bioreactor cultures.

The biopharmaceutical industry is moving toward a more quality by design (QbD) approach that seeks to increase product and process understanding and process control. Miniature bioreactor systems offer a high-throughput method enabling the assessment of numerous process variables in a controlled environment. However, the number of off/at-line samples that can be taken is restricted due to the small working volume of each vessel. This limitation may be resolved through the use of Raman spectroscopy due to its ability to obtain multianalyte data from small sample volumes fast. It can, however, be challenging to implement this technique for this application due to the complexity of the sample matrix and that analytes are often present in low concentration. Here, we present a design of experiments (DOE) approach to generate samples for calibrating robust multivariate predictive models measuring glucose, lactate, ammonium, viable cell concentration (VCC) and product concentration, for unclarified cell culture that improves the daily monitoring of each miniature bioreactor vessel. Furthermore, we demonstrate how the output of the glucose and VCC models can be used to control the glucose and main nutrient feed rate within miniature bioreactor cultures to within qualified critical limits set for larger scale vessels. The DOE approach used to generate the calibration sample set is shown to result in models more robust to process changes than by simply using samples taken from the "typical" process. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 35: e2740, 2019.

Development of generic raman models for a GS-KOTM CHO platform process.

The monitoring and control of bioprocesses is of the utmost importance in order to provide a consistent, safe, and high-quality product for consumers. Current monitoring and control schemes rely on infrequent and time consuming offline sampling methods, which inherently leads to some variability in the process which may impact the product quality profile. As part of Lonza's dedication to process analytical technology (PAT) initiatives this study evaluated the ability to generate generic calibration models, which are independent of the cell line, using Raman probes to monitor changes in glucose, lactate, glutamate, ammonium, viable cell concentration (VCC), total cell concentration (TCC) and product concentration. Calibration models were developed from cell culture using two different CHOK1SV GS-KOTM cell lines producing different monoclonal antibodies (mAbs). Developed predictive models, measured changes in glucose, lactate, ammonium, VCC, and TCC with average prediction errors of 0.44, 0.23, 0.03 g L-1 , 1.90 × 106 cells mL-1 , and 1.85 × 106 cells mL-1 , respectively over the course of cell culture with minimal cell line dependence. The development of these generic models allows the application of spectroscopic PAT techniques in clinical and commercial manufacturing environments, where processes are typically run once or twice in GMP manufacturing based on a common platform process. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:730-737, 2018.

Extraction of indirectly captured information for use in a comparison of offline pH measurement technologies.

Understanding the causes of discrepancies in pH readings of a sample can allow more robust pH control strategies to be implemented. It was found that 59.4% of differences between two offline pH measurement technologies for an historical dataset lay outside an expected instrument error range of ±0.02pH. A new variable, OsmoRes, was created using multiple linear regression (MLR) to extract information indirectly captured in the recorded measurements for osmolality. Principal component analysis and time series analysis were used to validate the expansion of the historical dataset with the new variable OsmoRes. MLR was used to identify variables strongly correlated (p<0.05) with differences in pH readings by the two offline pH measurement technologies. These included concentrations of specific chemicals (e.g. glucose) and OsmoRes, indicating culture medium and bolus feed additions as possible causes of discrepancies between the offline pH measurement technologies. Temperature was also identified as statistically significant. It is suggested that this was a result of differences in pH-temperature compensations employed by the pH measurement technologies. In summary, a method for extracting indirectly captured information has been demonstrated, and it has been shown that competing pH measurement technologies were not necessarily interchangeable at the desired level of control (±0.02pH).

Comparison of spectroscopy technologies for improved monitoring of cell culture processes in miniature bioreactors.

Cell culture process development requires the screening of large numbers of cell lines and process conditions. The development of miniature bioreactor systems has increased the throughput of such studies; however, there are limitations with their use. One important constraint is the limited number of offline samples that can be taken compared to those taken for monitoring cultures in large-scale bioreactors. The small volume of miniature bioreactor cultures (15 mL) is incompatible with the large sample volume (600 µL) required for bioanalysers routinely used. Spectroscopy technologies may be used to resolve this limitation. The purpose of this study was to compare the use of NIR, Raman, and 2D-fluorescence to measure multiple analytes simultaneously in volumes suitable for daily monitoring of a miniature bioreactor system. A novel design-of-experiment approach is described that utilizes previously analyzed cell culture supernatant to assess metabolite concentrations under various conditions while providing optimal coverage of the desired design space. Multivariate data analysis techniques were used to develop predictive models. Model performance was compared to determine which technology is more suitable for this application. 2D-fluorescence could more accurately measure ammonium concentration (RMSECV 0.031 g L-1 ) than Raman and NIR. Raman spectroscopy, however, was more robust at measuring lactate and glucose concentrations (RMSECV 1.11 and 0.92 g L-1 , respectively) than the other two techniques. The findings suggest that Raman spectroscopy is more suited for this application than NIR and 2D-fluorescence. The implementation of Raman spectroscopy increases at-line measuring capabilities, enabling daily monitoring of key cell culture components within miniature bioreactor cultures. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:337-346, 2017.