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ABSTRACT Recombinant adeno associated virus (rAAV) vectors have become popular delivery vehicles for in vivo gene therapies, but demand for rAAVs continues to outpace supply. Platform processes for rAAV production are being developed by many manufacturers, and transient chemical transfection of human embryonic kidney 293 (HEK293) cells is currently the most popular approach. However, the cutting edge nature of rAAV process development encourages manufacturers to keep cell culture media formulations, plasmid sequences, and other details proprietary, which creates hurdles for small companies and academic labs seeking to innovate in this space. To address this problem, we leveraged the resources of an academic‐industry consortium (Advanced Mammalian Biomanufacturing Innovation Center, AMBIC) to develop an rAAV production system based on transient transfection of suspension HEK293 cells adapted to an in‐house, chemically defined medium. We found that balancing iron and calcium levels in the medium were crucial for maintaining transfection efficiency and minimizing cell aggregation, respectively. A design of experiments approach was used to optimize the transient transfection process for batch rAAV production, and PEI:DNA ratio and cell density at transfection were the parameters with the strongest effects on vector genome (VG) titer. When the optimized transient process was transferred between two university sites, VG titers were within a twofold range. Analytical characterization showed that purified rAAV from the AMBIC process had comparable viral protein molecular weights versus vector derived from commercial processes, but differences in transducing unit (TU) titer were observed between vector preps. The developed media formulation, transient transfection process, and analytics for VG titer, capsid identity, and TU titer constitute a set of workflows that can be adopted by others to study fundamental problems that could improve product yield and quality in the nascent field of rAAV manufacturing. 

ABSTRACT miR-31 is a highly conserved microRNA that plays crucial roles in cell proliferation, migration and differentiation. We discovered that miR-31 and some of its validated targets are enriched on the mitotic spindle of the dividing sea urchin embryo and mammalian cells. Using the sea urchin embryo, we found that miR-31 inhibition led to developmental delay correlated with increased cytoskeletal and chromosomal defects. We identified miR-31 to directly suppress several actin remodeling transcripts, including β-actin, Gelsolin, Rab35 and Fascin. De novo translation of Fascin occurs at the mitotic spindle of sea urchin embryos and mammalian cells. Importantly, miR-31 inhibition leads to a significant a increase of newly translated Fascin at the spindle of dividing sea urchin embryos. Forced ectopic localization of Fascin transcripts to the cell membrane and translation led to significant developmental and chromosomal segregation defects, highlighting the importance of the regulation of local translation by miR-31 at the mitotic spindle to ensure proper cell division. Furthermore, miR-31-mediated post-transcriptional regulation at the mitotic spindle may be an evolutionarily conserved regulatory paradigm of mitosis. 

This review describes key milestones related to the production of biopharmaceuticals—therapies manufactured using recombinant DNA technology. The market for biopharmaceuticals has grown significantly since the first biopharmaceutical approval in 1982, and the scientific maturity of the technologies used in their manufacturing processes has grown concomitantly. Early processes relied on established unit operations, with research focused on process scale-up and improved culture productivity. In the early 2000s, changes in regulatory frameworks and the introduction of Quality by Design emphasized the importance of developing manufacturing processes to deliver a desired product quality profile. As a result, companies adopted platform processes and focused on understanding the dynamic interplay between product quality and processing conditions. The consistent and reproducible manufacturing processes of today's biopharmaceutical industry have set high standards for product efficacy, quality, and safety, and as the industry continues to evolve in the coming decade, intensified processing capabilities for an expanded range of therapeutic modalities will likely become routine. 

Glycosylation is a critical quality attribute of monoclonal antibody (mAb) therapeutics. Hydrophilic interaction liquid chromatography-mass spectrometry (HILIC-MS) is an invaluable technology for the characterization of protein glycosylation. HILIC/MS-based glycan analysis relies on the library search using Glucose Units (GU) and accurate mass (AM) as the primary search parameters for identification. However, GU-based identifications are gradient-dependent and are not suitable for applications where separation gradients need to be optimized to analyze complex samples or achieve higher throughput. Additionally, the workflow requires calibration curves (using dextran ladder) to be generated for each analysis campaign, which in turn, are used to derive the GU values of the separated glycan species. To overcome this limitation, we employed a two-step strategy for targeted glycan analysis of a mAb expressed in Chinese Hamster Ovary (CHO) cells. The first step is to create a custom library of the glycans of interest independent of GU values (thereby eliminating the need for a calibration curve) and instead uses AM and retention time (RT) as the primary search variables. The second step is to perform targeted glycan screening using the custom-built library. The developed workflow was applied for targeted glycan analysis of a mAb expressed in CHO for 1) cell line selection 2) characterizing the day-wise glycan evolution in a model mAb during a fed-batch culture, 3) assessing the impact of different media conditions on glycosylation, and 4) evaluating the impact of two different process conditions on glycosylation changes in a model mAb grown in a bioreactor. Taken together, the data presented in this study provides insights into the sources of glycan heterogeneity in a model mAb that are seen during its commercial manufacturing. 

Abstract BackgroundTo select the most complete, continuous, and accurate assembly for an organism of interest, comprehensive quality assessment of assemblies is necessary. We present a novel tool, called Evaluation of De Novo Assemblies (EvalDNA), which uses supervised machine learning for the quality scoring of genome assemblies and does not require an existing reference genome for accuracy assessment. ResultsEvalDNA calculates a list of quality metrics from an assembled sequence and applies a model created from supervised machine learning methods to integrate various metrics into a comprehensive quality score. A well-tested, accurate model for scoring mammalian genome sequences is provided as part of EvalDNA. This random forest regression model evaluates an assembled sequence based on continuity, completeness, and accuracy, and was able to explain 86% of the variation in reference-based quality scores within the testing data. EvalDNA was applied to human chromosome 14 assemblies from the GAGE study to rank genome assemblers and to compare EvalDNA to two other quality evaluation tools. In addition, EvalDNA was used to evaluate several genome assemblies of the Chinese hamster genome to help establish a better reference genome for the biopharmaceutical manufacturing community. EvalDNA was also used to assess more recent human assemblies from the QUAST-LG study completed in 2018, and its ability to score bacterial genomes was examined through application on bacterial assemblies from the GAGE-B study. ConclusionsEvalDNA enables scientists to easily identify the best available genome assembly for their organism of interest without requiring a reference assembly. EvalDNA sets itself apart from other quality assessment tools by producing a quality score that enables direct comparison among assemblies from different species. 

Chinese hamster ovary (CHO) cells are the primary mammalian cell lines utilized to produce monoclonal antibodies (mAbs). The upsurge in biosimilar development and the proven health benefits of mAb treatments reinforces the need for innovative methods to generate robust CHO clones and enhance production, while maintaining desired product quality attributes. Among various product titer-enhancing approaches, the use of histone deacetylase inhibitors (HDACis) such as sodium butyrate (NaBu) has yielded promising results. The titer-enhancing effect of HDACi treatment has generally been observed in lower producer cell lines but those studies are typically done on individual clones. Here, we describe a cell line development (CLD) platform approach for creating clones with varying productivities. We then describe a method for selecting an optimal NaBu concentration to evaluate potential titer-enhancing capabilities in a fed-batch study. Finally, a method for purifying the mAb using protein A chromatography, followed by glycosylation analysis using mass spectrometry, is described. The proposed workflow can be applied for a robust CLD process optimization to generate robust clones, enhance product expression, and improve product quality attributes. 

Abstract The ambr250 high-throughput bioreactor platform was adopted to provide a highly-controlled environment for a project investigating genome instability in Chinese hamster ovary (CHO) cells, where genome instability leads to lower protein productivity. Development of the baseline (control) and stressed process conditions highlighted the need to control critical process parameters, including the proportional, integral, and derivative (PID) control loops. Process parameters that are often considered scale-independent, include dissolved oxygen (DO) and pH; however, these parameters were observed to be sensitive to PID settings. For many bioreactors, control loops are cascaded such that the manipulated variables are adjusted concurrently. Conversely, for the ambr250 bioreactor system, the control levels are segmented and implemented sequentially. Consequently, each control level must be tuned independently, as the PID settings are independent by control level. For the CHO cell studies, it was observed that initial PID settings did not resulted in a robust process, which was observed as elevated lactate levels; which was caused by the pH being above the setpoint most of the experiment. After several PID tuning iterations, new PID settings were found that could respond appropriately to routine feed and antifoam additions. Furthermore, these new PID settings resulted in more robust cell growth and increased protein productivity. This work highlights the need to describe PID gains and manipulated variable ranges, as profoundly different outcomes can result from the same feeding protocol. Additionally, improved process models are needed to allow process simulations and tuning. Thus, these tuning experiments support the idea that PID settings should be fully described in bioreactor publications to allow for better reproducibility of results. 

Chinese hamster ovary (CHO) cell cultures in industry are most commonly conducted as fed-batch cultures in computer-controlled bioreactors, though most preliminary studies are conducted in fed-batch shake flasks. To improve comparability between bioreactor studies and shake flask studies, shake flask studies should be conducted as fed-batch. However, the smaller volumes and reduced control in shake flasks can impact pH and aeration, which leads to performance differences. Planning and awareness of these vessel and control differences can assist with experimental design as well as troubleshooting. This method will highlight several of the configuration and control issues that should be considered during the transitions from batch to fed-batch and shake flasks to bioreactors, as well as approaches to mitigate the differences. Furthermore, if significant differences occur between bioreactor and shake flask studies, approaches will be presented to isolate the main contributors for these differences.