Physiological state as transferable operating criterion to improve recombinant protein production in Pichia pastoris through oxygen limitation

BACKGROUND: The yeast Pichia pastoris is widely used as a production platform for secreted recombinant protein. The application of oxygen-limiting conditions leads to an important increase in protein specific productivity driven by the GAP promoter. RESULTS: The physiological and metabolic adaptation of the host to a wide range of oxygen availability has been systematically studied in glucose-limited chemostat cultivations producing an antibody fragment (Fab). A weighty increase of up to 3-fold of the specific Fab production rate (qFab) and Fab yield (YPX) has been achieved for the optimal conditions. Besides the remarkable increase on both Fab yield and productivity, as a consequence of the metabolic shift from respiratory to respiro-fermentative pathways, a decrease on biomass yield and generation of several secreted by-products have been observed. CONCLUSION: The accurate system characterization achieved throughout the bioprocess specific rates and the monitoring of cell physiology allowed the determination of the optimal conditions to enhance bioprocess efficiency. This work also presents a versatile approach based on the physiological state of the yeast that can be used to implement the desired oxygen-limiting conditions to fermentations set-ups with different oxygen transfer capacities, alternative operating modes, and even for the production of other proteins of interest

Ultrasound-enhanced attenuated total reflection mid-infrared spectroscopy in-line probe: Acquisition of cell spectra in a bioreactor

This article presents a novel method for selective acquisition of Fourier transform infrared (FT-IR) spectra of microorganisms in-line during fermentation, using Saccharomyces cerevisiae as an example. The position of the cells relative to the sensitive region of the attenuated total reflection (ATR) FT-IR probe was controlled by combing a commercially available ATR in-line probe with contact-free, gentle particle manipulation by ultrasonic standing waves. A prototype probe was successfully constructed, assembled, and tested in-line during fed-batch fermentations of S. cerevisiae. Control over the position of the cells was achieved by tuning the ultrasound frequency: 2.41 MHz was used for acquisition of spectra of the cells (pushing frequency fp) and 1.87 MHz, for retracting the cells from the ATR element, therefore allowing spectra of the medium to be acquired. Accumulation of storage carbohydrates (trehalose and glycogen) inside the cells was induced by a lack of a nitrogen source in the feed medium. These changes in biochemical composition were visible in the spectra of the cells recorded in-line during the application of fp and could be verified by reference spectra of dried cell samples recorded off-line with a FT-IR microscope. Comparison of the cell spectra with spectra of trehalose, glycogen, glucose, and mannan, i.e., the major carbohydrates present in S. cerevisiae, and principal components analysis revealed that the changes observed in the cell spectra correlated well with the bands specific for trehalose and glycogen. This proves the applicability and capability of ultrasound-enhanced in-line ATR mid-IR spectroscopy as a real-time PAT method for the in situ monitoring of cellular biochemistry during fermentation

A control strategy to investigate the relationship between specific productivity and high-mannose glycoforms in CHO cells

The final publication is available at Springer via https://doi.org/10.1007/s00253-016-7380-4.The integration of physiological knowledge into process control strategies is a cornerstone for the improvement of biopharmaceutical cell culture technologies. The present contribution investigates the applicability of specific productivity as a physiological control parameter in a cell culture process producing a monoclonal antibody (mAb) in CHO cells. In order to characterize cell physiology, the on-line oxygen uptake rate (OUR) was monitored and the time-resolved specific productivity was calculated as physiological parameters. This characterization enabled to identify the tight link between the deprivation of tyrosine and the decrease in cell respiration and in specific productivity. Subsequently, this link was used to control specific productivity by applying different feeding profiles. The maintenance of specific productivity at various levels enabled to identify a correlation between the rate of product formation and the relative abundance of high-mannose glycoforms. An increase in high mannose content was assumed to be the result of high specific productivity. Furthermore, the high mannose content as a function of cultivation pH and specific productivity was investigated in a design of experiment approach. This study demonstrated how physiological parameters could be used to understand interactions between process parameters, physiological parameters, and product quality attributes

Propagation of measurement accuracy to biomass soft-sensor estimation and control quality

Part of the following topical collections "Process Analytics in Science and Industry".The final publication is available at Springer via https://doi.org/10.1007/s00216-016-9711-9.In biopharmaceutical process development and manufacturing, the online measurement of biomass and derived specific turnover rates is a central task to physiologically monitor and control the process. However, hard-type sensors such as dielectric spectroscopy, broth fluorescence, or permittivity measurement harbor various disadvantages. Therefore, soft-sensors, which use measurements of the off-gas stream and substrate feed to reconcile turnover rates and provide an online estimate of the biomass formation, are smart alternatives. For the reconciliation procedure, mass and energy balances are used together with accuracy estimations of measured conversion rates, which were so far arbitrarily chosen and static over the entire process. In this contribution, we present a novel strategy within the soft-sensor framework (named adaptive soft-sensor) to propagate uncertainties from measurements to conversion rates and demonstrate the benefits: For industrially relevant conditions, hereby the error of the resulting estimated biomass formation rate and specific substrate consumption rate could be decreased by 43 and 64 %, respectively, compared to traditional soft-sensor approaches. Moreover, we present a generic workflow to determine the required raw signal accuracy to obtain predefined accuracies of soft-sensor estimations. Thereby, appropriate measurement devices and maintenance intervals can be selected. Furthermore, using this workflow, we demonstrate that the estimation accuracy of the soft-sensor can be additionally and substantially increased.Austrian research funding association (FFG) COME