Impacts on product quality attributes of monoclonal antibodies produced in CHO cell bioreactor cultures during intentional mycoplasma contamination events.

A mycoplasma contamination event in a biomanufacturing facility can result in costly cleanups and potential drug shortages. Mycoplasma may survive in mammalian cell cultures with only subtle changes to the culture and penetrate the standard 0.2-µm filters used in the clarification of harvested cell culture fluid. Previously, we reported a study regarding the ability of Mycoplasma arginini to persist in a single-use, perfusion rocking bioreactor system containing a Chinese hamster ovary (CHO) DG44 cell line expressing a model monoclonal immunoglobulin G 1 (IgG1) antibody. Our previous work showed that M. arginini affects CHO cell growth profile, viability, nutrient consumption, oxygen use, and waste production at varying timepoints after M. arginini introduction to the culture. Careful evaluation of certain identified process parameters over time may be used to indicate mycoplasma contamination in CHO cell cultures in a bioreactor before detection from a traditional method. In this report, we studied the changes in the IgG1 product quality produced by CHO cells considered to be induced by the M. arginini contamination events. We observed changes in critical quality attributes correlated with the duration of contamination, including increased acidic charge variants and high mannose species, which were further modeled using principal component analysis to explore the relationships among M. arginini contamination, CHO cell growth and metabolites, and IgG1 product quality attributes. Finally, partial least square models using NIR spectral data were used to establish predictions of high levels (≥104 colony-forming unit [CFU/ml]) of M. arginini contamination, but prediction of levels below 104 CFU/ml were not reliable. Contamination of CHO cells with M. arginini resulted in significant reduction of antibody product quality, highlighting the importance of rapid microbiological testing and mycoplasma testing during particularly long upstream bioprocesses to ensure product safety and quality.

The ELISA Detectability and Potency of Pegfilgrastim Decrease in Physiological Conditions: Key Roles for Aggregation and Individual Variability.

PEGylated recombinant human granulocyte colony stimulating factor (pegfilgrastim) is used clinically to accelerate immune reconstitution following chemotherapy and is being pursued for biosimilar development. One challenge to overcome in pegfilgrastim biosimilar development is establishing pharmacokinetic (PK) similarity, which is partly due to the degree of PK variability. We herein report that commercially available G-CSF and PEG ELISA detection kits have different capacities to detect pegfilgrastim aggregates that rapidly form in vitro in physiological conditions. These aggregates can be observed using SDS-PAGE, size-exclusion chromatography, dynamic light scattering, and real-time NMR analysis and are associated with decreased bioactivity as reflected by reduced drug-induced cellular proliferation and STAT3 phosphorylation. Furthermore, individual variability in the stability and detectability of pegfilgrastim in human sera is also observed. Pegfilgrastim levels display marked subject variability in sera from healthy donors incubated at 37 °C. The stability patterns of pegfilgrastim closely match the stability patterns of filgrastim, consistent with a key role for pegfilgrastim's G-CSF moiety in driving formation of inactive aggregates. Taken together, our results indicate that individual variability and ELISA specificity for inactive aggregates are key factors to consider when designing and interpreting studies involving the measurement of serum pegfilgrastim concentrations.

Multivariate data analysis of growth medium trends affecting antibody glycosylation.

Use of multivariate data analysis for the manufacturing of biologics has been increasing due to more widespread use of data-generating process analytical technologies (PAT) promoted by the US FDA. To generate a large dataset on which to apply these principles, we used an in-house model CHO DG44 cell line cultured in automated micro bioreactors alongside PAT with four commercial growth media focusing on antibody quality through N-glycosylation profiles. Using univariate analyses, we determined that different media resulted in diverse amounts of terminal galactosylation, high mannose glycoforms, and aglycosylation. Due to the amount of in-process data generated by PAT instrumentation, multivariate data analysis was necessary to ascertain which variables best modeled our glycan profile findings. Our principal component analysis revealed components that represent the development of glycoforms into terminally galacotosylated forms (G1F and G2F), and another that encompasses maturation out of high mannose glycoforms. The partial least squares model additionally incorporated metabolic values to link these processes to glycan outcomes, especially involving the consumption of glutamine. Overall, these approaches indicated a tradeoff between cellular productivity and product quality in terms of the glycosylation. This work illustrates the use of multivariate analytical approaches that can be applied to complex bioprocessing problems for identifying potential solutions.

Real-time quantification and supplementation of bioreactor amino acids to prolong culture time and maintain antibody product quality.

Real-time monitoring of cell cultures in bioreactors can enable expedited responses necessary to correct potential batch failure perturbations which may normally go undiscovered until the completion of the batch and result in failure. Currently, analytical technologies are dedicated to real-time monitoring of bioreactor parameters such as pH, dissolved oxygen, and temperature, nutrients such as glucose and glutamine, or metabolites such as lactate. Despite the importance of amino acids as the building blocks of therapeutic protein products, other than glutamine their concentrations are not commonly measured. Here, we present a study into amino acid monitoring, supplementation strategies, and how these techniques may impact the cell growth profiles and product quality. We used preliminary bioreactor runs to establish baselines by determining initial amino acid consumption patterns, the results of which were used to select a pool of amino acids which gets depleted in the bioreactor. These amino acids were combined into blends which were supplemented into bioreactors during a subsequent run, the concentrations of which were monitored using a mass spectrometry based at-line method we developed to quickly assess amino acid concentrations from crude bioreactor media. We found that these blends could prolong culture life, reversing a viable cell density decrease that was leading to batch death. Additionally, we assessed how these strategies might impact protein product quality, such as the glycan profile. The amino acid consumption data were aligned with the final glycan profiles in principal component analysis to identify which amino acids are most closely associated with glycan outcomes.

Relative Quantification of siRNA Strand Loading into Ago2 for Design of Highly Active siRNAs.

In RNA interference (RNAi), silencing is achieved through the interaction of double-stranded small interfering RNAs (siRNAs) with essential RNAi pathway proteins, including Argonaute 2 (Ago2). Based on these interactions, one strand of the siRNA is loaded into Ago2 forming the active RNA-induced silencing complex (RISC). Optimal siRNAs maximize RISC activity against the intended target and minimize off-target silencing. To achieve the desired activity and specificity, selection of the appropriate siRNA strand for loading into Ago2 is essential. Here, we provide a protocol to quantify the relative loading of individual siRNA strands into Ago2, one factor in determining the capacity of a siRNA to achieve silencing activity and target specificity.

Purification and Analytics of a Monoclonal Antibody from Chinese Hamster Ovary Cells Using an Automated Microbioreactor System.

Monoclonal antibodies (mAbs) are one of the most popular and well-characterized biological products manufactured today. Most commonly produced using Chinese hamster ovary (CHO) cells, culture and process conditions must be optimized to maximize antibody titers and achieve target quality profiles. Typically, this optimization uses automated microscale bioreactors (15 mL) to screen multiple process conditions in parallel. Optimization criteria include culture performance and the critical quality attributes (CQAs) of the monoclonal antibody (mAb) product, which may impact its efficacy and safety. Culture performance metrics include cell growth and nutrient consumption, while the CQAs include the mAb's N-glycosylation and aggregation profiles, charge variants, and molecular weight. This detailed protocol describes how to purify and subsequently analyze HCCF samples produced by an automated microbioreactor system to gain valuable performance metrics and outputs. First, an automated protein A fast protein liquid chromatography (FPLC) method is used to purify the mAb from harvested cell culture samples. Once concentrated, the glycan profiles are analyzed by mass spectrometry using a specific platform (refer to the Table of Materials). Antibody molecular weights and aggregation profiles are determined using size exclusion chromatography-multiple angle light scattering (SEC-MALS), while charge variants are analyzed using microchip capillary zone electrophoresis (mCZE). In addition to the culture performance metrics captured during the bioreactor process (i.e., culture viability, cell counts, and common metabolites including glutamine, glucose, lactate, and ammonia), spent media is analyzed to identify limiting nutrients to improve the feeding strategies and overall process design. Therefore, a detailed protocol for the absolute quantification of amino acids by liquid chromatography-mass spectrometry (LC-MS) of spent media is also described. The methods used in this protocol take advantage of high-throughput platforms that are compatible for large numbers of small-volume samples.

Use of High-Throughput Automated Microbioreactor System for Production of Model IgG1 in CHO Cells.

Automated microscale bioreactors (15 mL) can be a useful tool for cell culture engineers. They facilitate the simultaneous execution of a wide variety of experimental conditions while minimizing potential process variability. Applications of this approach include: clone screening, temperature and pH shifts, media and supplement optimization. Furthermore, the small reactor volumes are conducive to large Design of Experiments that investigate a wide range of conditions. This allows upstream processes to be significantly optimized before scale-up where experimentation is more limited in scope due to time and economic constraints. Automated microscale bioreactor systems offer various advantages over traditional small scale cell culture units, such as shake flasks or spinner flasks. However, during pilot scale process development significant care must be taken to ensure that these advantages are realized. When run with care, the system can enable high level automation, can be programmed to run DOE's with a higher number of variables and can reduce sampling time when integrated with a nutrient analyzer or cell counter. Integration of the expert-derived heuristics presented here, with current automated microscale bioreactor experiments can minimize common pitfalls that hinder meaningful results. In the extreme, failure to adhere to the principles laid out here can lead to equipment damage that requires expensive repairs. Furthermore, the microbioreactor systems have small culture volumes making characterization of cell culture conditions difficult. The number and amount of samples taken in-process in batch mode culture is limited as operating volumes cannot fall below 10 mL. This method will discuss the benefits and drawbacks of microscale bioreactor systems.

Use of Brevibacillus choshinensis for the production of biologically active brain-derived neurotrophic factor (BDNF).

Brain-derived neurotrophic factor (BDNF) is a member of the neurotrophin family critical for neuronal cell survival and differentiation, with therapeutic potential for the treatment of neurological disorders and spinal cord injuries. The production of recombinant, bioactive BDNF is not practical in most traditional microbial expression systems because of the inability of the host to correctly form the characteristic cystine-knot fold of BDNF. Here, we investigated Brevibacillus choshinensis as a suitable expression host for bioactive BDNF expression, evaluating the effects of medium type (2SY and TM), temperature (25 and 30 °C), and culture time (48-120 h). Maximal BDNF bioactivity (per unit mass) was observed in cultures grown in 2SY medium at extended times (96 h at 30 °C or >72 h at 25 °C), with resulting bioactivity comparable to that of a commercially available BDNF. For cultures grown in 2SY medium at 25 °C for 72 h, the condition that led to the greatest quantity of biologically active protein in the shortest culture time, we recovered 264 µg/L of BDNF. As with other microbial expression systems, BDNF aggregates did form in all culture conditions, indicating that while we were able to recover biologically active BDNF, further optimization of the expression system could yield still greater quantities of bioactive protein. This study provides confirmation that B. choshinensis is capable of producing biologically active BDNF and that further optimization of culture conditions could prove valuable in increasing BDNF yields.

Terminal Duplex Stability and Nucleotide Identity Differentially Control siRNA Loading and Activity in RNA Interference.

Efficient short interfering RNA (siRNA)-mediated gene silencing requires selection of a sequence that is complementary to the intended target and possesses sequence and structural features that encourage favorable functional interactions with the RNA interference (RNAi) pathway proteins. In this study, we investigated how terminal sequence and structural characteristics of siRNAs contribute to siRNA strand loading and silencing activity and how these characteristics ultimately result in a functionally asymmetric duplex in cultured HeLa cells. Our results reiterate that the most important characteristic in determining siRNA activity is the 5' terminal nucleotide identity. Our findings further suggest that siRNA loading is controlled principally by the hybridization stability of the 5' terminus (Nucleotides: 1-2) of each siRNA strand, independent of the opposing terminus. Postloading, RNA-induced silencing complex (RISC)-specific activity was found to be improved by lower hybridization stability in the 5' terminus (Nucleotides: 3-4) of the loaded siRNA strand and greater hybridization stability toward the 3' terminus (Nucleotides: 17-18). Concomitantly, specific recognition of the 5' terminal nucleotide sequence by human Argonaute 2 (Ago2) improves RISC half-life. These findings indicate that careful selection of siRNA sequences can maximize both the loading and the specific activity of the intended guide strand.

Brain derived neurotrophic factor release from layer-by-layer coated agarose nerve guidance scaffolds.

Agarose nerve guidance scaffolds (NGS) seeded with cells expressing brain derived neurotrophic factor (BDNF) have demonstrated robust nerve regeneration in the rat central nervous system. The purpose of this work was to explore whether agarose NGS coated with hydrogen-bonded layer-by-layer (HLbL) could provide an acellular method of delivering prolonged and consistent dosages of active BDNF. Our results show that HLbL-coated agarose NGS could release BDNF over 10days in consistent dosages averaging 80.5±12.5(SD)ng/mL. Moreover, the BDNF released from HLbL was confirmed active by in vitro cell proliferation assays. To our knowledge, this is the first report demonstrating that HLbL assembled onto a hydrogel can provide consistent, prolonged release of active BDNF in clinically relevant dosages.

Design of siRNA Therapeutics from the Molecular Scale.

While protein-based therapeutics is well-established in the market, development of nucleic acid therapeutics has lagged. Short interfering RNAs (siRNAs) represent an exciting new direction for the pharmaceutical industry. These small, chemically synthesized RNAs can knock down the expression of target genes through the use of a native eukaryotic pathway called RNA interference (RNAi). Though siRNAs are routinely used in research studies of eukaryotic biological processes, transitioning the technology to the clinic has proven challenging. Early efforts to design an siRNA therapeutic have demonstrated the difficulties in generating a highly-active siRNA with good specificity and a delivery vehicle that can protect the siRNA as it is transported to a specific tissue. In this review article, we discuss design considerations for siRNA therapeutics, identifying criteria for choosing therapeutic targets, producing highly-active siRNA sequences, and designing an optimized delivery vehicle. Taken together, these design considerations provide logical guidelines for generating novel siRNA therapeutics.