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Concentration gradients that occur in large industrial‐scale bioreactors due to mass transfer limitations have significant effects on process efficiency. Hence, it is desirable to investigate the response of strains to such heterogeneities to reduce the risk of failure during process scale‐up. Although there are various scale‐down techniques to study these effects, scale‐down strategies are rarely applied in the early developmental phases of a bioprocess, as they have not yet been implemented on small‐scale parallel cultivation devices. In this study, we combine mechanistic growth models with a parallel mini‐bioreactor system to create a high‐throughput platform for studying the response of Escherichia coli strains to concentration gradients. As a scaled‐down approach, a model‐based glucose pulse feeding scheme is applied and compared with a continuous feed profile to study the influence of glucose and dissolved oxygen gradients on both cell physiology and incorporation of noncanonical amino acids into recombinant proinsulin. The results show a significant increase in the incorporation of the noncanonical amino acid norvaline in the soluble intracellular extract and in the recombinant product in cultures with glucose/oxygen oscillations. Interestingly, the amount of norvaline depends on the pulse frequency and is negligible with continuous feeding, confirming observations from large‐scale cultivations. Most importantly, the results also show that a larger number of the model parameters are significantly affected by the scale‐down scheme, compared with the reference cultivations. In this example, it was possible to describe the effects of oscillations in a single parallel experiment. The platform offers the opportunity to combine strain screening with scale‐down studies to select the most robust strains for bioprocess scale‐up. [ABSTRACT FROM AUTHOR]

N-glycosylation in the endoplasmic reticulum is an essential protein modification and highly conserved in evolution from yeast to man. Defects of N-glycosylation in humans lead to congenital disorders. The pivotal step of this pathway is the transfer of the evolutionarily conserved lipid-linked core-oligosaccharide to the nascent polypeptide chain, catalysed by the oligosaccharyltransferase. One of its nine subunits, Ost2, has homology to DAD1, originally characterized in hamster cells as a efender against poptotic eath. Here we show that ost mutants, such as ost2 and wbp1-1, display morphological and biochemical features of apoptosis upon induction of the glycosylation defect. We observe nuclear condensation, DNA fragmentation as well as externalization of phosphatidylserine. We also demonstrate induction of caspase-like activity, both determined by flow cytometric analysis and in cell-free extracts. Similarly, the N-glycosylation inhibitor tunicamycin in combination with elevated temperature is able to challenge the apoptotic cascade. Heterologous expression of anti-apoptotic human Bcl-2 diminishes caspase activation, improves survival of cells and suppresses the temperature-sensitive growth defect of wbp1-1. Furthermore, accumulation of reactive oxygen species occurs in response to defective glycosylation. As deletion of the metacaspase YCA1 does not seem to abrogate glycosylation-induced apoptosis, we postulate a different proteolytic process to be involved in this death pathway. [ABSTRACT FROM AUTHOR]

Downstream processing in the manufacturing biopharmaceutical industry is a multistep process separating the desired product from process‐ and product‐related impurities. However, removing product‐related impurities, such as product variants, without compromising the product yield or prolonging the process time due to extensive quality control analytics, remains a major challenge. Here, we show how mechanistic model‐based monitoring, based on analytical quality control data, can predict product variants by modeling their chromatographic separation during product polishing with reversed phase chromatography. The system was described by a kinetic dispersive model with a modified Langmuir isotherm. Solely quality control analytical data on product and product variant concentrations were used to calibrate the model. This model‐based monitoring approach was developed for an insulin purification process. Industrial materials were used in the separation of insulin and two insulin variants, one eluting at the product peak front and one eluting at the product peak tail. The model, fitted to analytical data, used one component to simulate each protein, or two components when a peak displayed a shoulder. This monitoring approach allowed the prediction of the elution patterns of insulin and both insulin variants. The results indicate the potential of using model‐based monitoring in downstream polishing at industrial scale to take pooling decisions. [ABSTRACT FROM AUTHOR]