Application of metabolic modeling for targeted optimization of high seeding density processes.

Process intensification by application of perfusion mode in pre-stage bioreactors and subsequent inoculation of cell cultures at high seeding densities (HSD) has the potential to meet the increasing requirements of future manufacturing demands. However, process development is currently restrained by a limited understanding of the cell's requirements under these process conditions. The goal of this study was to use extended metabolite analysis and metabolic modeling for targeted optimization of HSD cultivations. The metabolite analysis of HSD N-stage cultures revealed accumulation of inhibiting metabolites early in the process and flux balance analysis led to the assumption that reactive oxygen species (ROS) were contributing to the fast decrease in cell viability. Based on the metabolic analysis an optimized feeding strategy with lactate and cysteine supplementation was applied, resulting in an increase in antibody titer of up to 47%. Flux balance analysis was further used to elucidate the surprisingly strong synergistic effect of lactate and cysteine, indicating that increased lactate uptake led to reduced ROS formation under these conditions whilst additional cysteine actively reduced ROS via the glutathione pathway. The presented results finally demonstrate the benefit of modeling approaches for process intensification as well as the potential of HSD cultivations for biopharmaceutical manufacturing.

The Less the Better: How Suppressed Base Addition Boosts Production of Monoclonal Antibodies With Chinese Hamster Ovary Cells.

Biopharmaceutical production processes strive for the optimization of economic efficiency. Among others, the maximization of volumetric productivity is a key criterion. Typical parameters such as partial pressure of CO2 (pCO2) and pH are known to influence the performance although reasons are not yet fully elucidated. In this study the effects of pCO2 and pH shifts on the phenotypic performance were linked to metabolic and energetic changes. Short peak performance of qmAb (23 pg/cell/day) was achieved by early pCO2 shifts up to 200 mbar but followed by declining intracellular ATP levels to 2.5 fmol/cell and 80% increase of qLac. On the contrary, steadily rising qmAb could be installed by slight pH down-shifts ensuring constant cell specific ATP production (qATP) of 27 pmol/cell/day and high intracellular ATP levels of about 4 fmol/cell. As a result, maximum productivity was achieved combining highest qmAb (20 pg/cell/day) with maximum cell density and no lactate formation. Our results indicate that the energy availability in form of intracellular ATP is crucial for maintaining antibody synthesis and reacts sensitive to pCO2 and pH-process parameters typically responsible for inhomogeneities after scaling up.

Perfusion cultures require optimum respiratory ATP supply to maximize cell-specific and volumetric productivities.

Perfusion processes are an emerging alternative to common fed-batch processes in the growing biopharmaceutical industry. However, the challenge of maintaining high cell-specific productivities remains. In this study, glucose limitation was applied to two perfusion steady states and compared with a third steady state without any detectable limitation. The metabolic phenotype was enhanced under glucose limitation with a decrease of 30% in glucose uptake and 75% in lactate formation. Cell-specific productivities were substantially improved by 50%. Remarkably, the productivities showed a strong correlation to respiratory adenosine triphosphate (ATP) supply. As less reduced nicotinamide adenine dinucleotide (NADH) remained in the cytosol, the ATP generation from oxidative phosphorylation was increased by almost 30%. Consequently, the efficiency of carbon metabolism and the resulting respiratory ATP supply was crucial for maintaining the highly productive cellular state. This study highlights that glucose limitation can be used for process intensification in perfusion cultures as ATP generation via respiration is significantly increased, leading to elevated productivities.

Towards robust cell culture processes - Unraveling the impact of media preparation by spectroscopic online monitoring.

Biopharmaceutical manufacturing processes can be affected by variability in cell culture media, e.g. caused by raw material impurities. Although efforts have been made in industry and academia to characterize cell culture media and raw materials with advanced analytics, the process of industrial cell culture media preparation itself has not been reported so far. Within this publication, we first compare mid-infrared and two-dimensional fluorescence spectroscopy with respect to their suitability as online monitoring tools during cell culture media preparation, followed by a thorough assessment of the impact of preparation parameters on media quality. Through the application of spectroscopic methods, we can show that media variability and its corresponding root cause can be detected online during the preparation process. This methodology is a powerful tool to avoid batch failure and is a valuable technology for media troubleshooting activities. Moreover, in a design of experiments approach, including additional liquid chromatography-mass spectrometry analytics, it is shown that variable preparation parameters such as temperature, power input and preparation time can have a strong impact on the physico-chemical composition of the media. The effect on cell culture process performance and product quality in subsequent fed-batch processes was also investigated. The presented results reveal the need for online spectroscopic methods during the preparation process and show that media variability can already be introduced by variation in media preparation parameters, with a potential impact on scale-up to a commercial manufacturing process.

A robust feeding strategy to maintain set-point glucose in mammalian fed-batch cultures when input parameters have a large error.

Industrial CHO cell cultures run under fed-batch conditions are required to be controlled in particular ranges of glucose, while glucose is constantly consumed and must be replenished by a feed. The most appropriate feeding rate is ideally stoichiometric and adaptive in nature to balance the dynamically changing rate of glucose consumption. However, high errors in biomass and glucose estimation as well as limited knowledge of the true metabolic state challenge the control strategy. In this contribution, we take these errors into account and simulate the output with uncertainty trajectories in silico in order to control glucose concentration. Other than many control strategies, which require parameter estimation, our assumptions are founded on two pillars: (i) first principles and (ii) prior knowledge about the variability of fed-batch CHO cell culture. The algorithm was exposed to an in-silico Design of Experiments (DoE), in which variations of parameters were changed simultaneously, such as clone-specific behavior, precision of equipment and desired control range used. The results demonstrate that our method achieved the target of holding the glucose concentration within an acceptable range. A robust and sufficient level of control could be demonstrated even with high errors for biomass or metabolic state estimation. In a time where blockbuster drugs are queuing up for time slots of their production, this transferable control strategy that is independent of tedious establishment runs may be a decisive advantage for rapid implementation during technology transfer and scale up and decrease in campaign change over time. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:317-336, 2017.

Metabolic Control in Mammalian Fed-Batch Cell Cultures for Reduced Lactic Acid Accumulation and Improved Process Robustness.

Biomass and cell-specific metabolic rates usually change dynamically over time, making the "feed according to need" strategy difficult to realize in a commercial fed-batch process. We here demonstrate a novel feeding strategy which is designed to hold a particular metabolic state in a fed-batch process by adaptive feeding in real time. The feed rate is calculated with a transferable biomass model based on capacitance, which changes the nutrient flow stoichiometrically in real time. A limited glucose environment was used to confine the cell in a particular metabolic state. In order to cope with uncertainty, two strategies were tested to change the adaptive feed rate and prevent starvation while in limitation: (i) inline pH and online glucose concentration measurement or (ii) inline pH alone, which was shown to be sufficient for the problem statement. In this contribution, we achieved metabolic control within a defined target range. The direct benefit was two-fold: the lactic acid profile was improved and pH could be kept stable. Multivariate Data Analysis (MVDA) has shown that pH influenced lactic acid production or consumption in historical data sets. We demonstrate that a low pH (around 6.8) is not required for our strategy, as glucose availability is already limiting the flux. On the contrary, we boosted glycolytic flux in glucose limitation by setting the pH to 7.4. This new approach led to a yield of lactic acid/glucose (Y L/G) around zero for the whole process time and high titers in our labs. We hypothesize that a higher carbon flux, resulting from a higher pH, may lead to more cells which produce more product. The relevance of this work aims at feeding mammalian cell cultures safely in limitation with a desired metabolic flux range. This resulted in extremely stable, low glucose levels, very robust pH profiles without acid/base interventions and a metabolic state in which lactic acid was consumed instead of being produced from day 1. With this contribution, we wish to extend the basic repertoire of available process control strategies, which will open up new avenues in automation technology and radically improve process robustness in both process development and manufacturing.

A global RNA-seq-driven analysis of CHO host and production cell lines reveals distinct differential expression patterns of genes contributing to recombinant antibody glycosylation.

Boehringer Ingelheim uses two CHO-DG44 lines for manufacturing biotherapeutics, BI-HEX-1 and BI-HEX-2, which produce distinct cell type-specific antibody glycosylation patterns. A recently established CHO-K1 descended host, BI-HEX-K1, generates antibodies with glycosylation profiles differing from CHO-DG44. Manufacturing process development is significantly influenced by these unique profiles. To investigate the underlying glycosylation related gene expression, we leveraged our CHO host and production cell RNA-seqtranscriptomics and product quality database together with the CHO-K1 genome. We observed that each BI-HEX host and antibody producing cell line has a unique gene expression fingerprint. CHO-DG44 cells only transcribe Fut10, Gfpt2 and ST8Sia6 when expressing antibodies. BI-HEX-K1 cells express ST8Sia6 at host cell level. We detected a link between BI-HEX-1/BI-HEX-2 antibody galactosylation and mannosylation and the gene expression of the B4galt gene family and genes controlling mannose processing. Furthermore, we found major differences between the CHO-DG44 and CHO-K1 lineages in the expression of sialyl transferases and enzymes synthesizing sialic acid precursors, providing a rationale for the lack of immunogenic NeuGc/NGNA synthesis in CHO. Our study highlights the value of systems biotechnology to understand glycoprotein synthesis and product glycoprofiles. Such data improve future production clone selection and process development strategies for better steering of biotherapeutic product quality.

Versatile metabolic adaptations of Ralstonia eutropha H16 to a loss of PdhL, the E3 component of the pyruvate dehydrogenase complex.

A previous study reported that the Tn5-induced poly(3-hydroxybutyric acid) (PHB)-leaky mutant Ralstonia eutropha H1482 showed a reduced PHB synthesis rate and significantly lower dihydrolipoamide dehydrogenase (DHLDH) activity than the wild-type R. eutropha H16 but similar growth behavior. Insertion of Tn5 was localized in the pdhL gene encoding the DHLDH (E3 component) of the pyruvate dehydrogenase complex (PDHC). Taking advantage of the available genome sequence of R. eutropha H16, observations were verified and further detailed analyses and experiments were done. In silico genome analysis revealed that R. eutropha possesses all five known types of 2-oxoacid multienzyme complexes and five DHLDH-coding genes. Of these DHLDHs, only PdhL harbors an amino-terminal lipoyl domain. Furthermore, insertion of Tn5 in pdhL of mutant H1482 disrupted the carboxy-terminal dimerization domain, thereby causing synthesis of a truncated PdhL lacking this essential region, obviously leading to an inactive enzyme. The defined ΔpdhL deletion mutant of R. eutropha exhibited the same phenotype as the Tn5 mutant H1482; this excludes polar effects as the cause of the phenotype of the Tn5 mutant H1482. However, insertion of Tn5 or deletion of pdhL decreases DHLDH activity, probably negatively affecting PDHC activity, causing the mutant phenotype. Moreover, complementation experiments showed that different plasmid-encoded E3 components of R. eutropha H16 or of other bacteria, like Burkholderia cepacia, were able to restore the wild-type phenotype at least partially. Interestingly, the E3 component of B. cepacia possesses an amino-terminal lipoyl domain, like the wild-type H16. A comparison of the proteomes of the wild-type H16 and of the mutant H1482 revealed striking differences and allowed us to reconstruct at least partially the impressive adaptations of R. eutropha H1482 to the loss of PdhL on the cellular level.