Quantification of the dynamics of population heterogeneities in CHO cultures with stably integrated fluorescent markers

Use of qPCR for the analysis of population heterogeneity and dynamics during Lactobacillus delbrueckii spp. bulgaricus batch fculture

Direct molecular methods such as real-time polymerase chain reaction (qPCR) and propidium monoazide (PMA)-qPCR have been successfully used for quantifying viable microorganisms in the food industry. This study attempted to use qPCR and PMA-qPCR for quantifying Lactobacillus delbrueckii spp. bulgaricus sp1.1 physiological states. The qPCR standards of the 16S rRNA gene were employed to calibrate the qPCR assay, which contributed to an amplification efficiency of 98.42%. The number of copies of the 16S rRNA gene was linearly related to cell density, and this linear relationship was used to construct a quantitative curve (R² =0.9981) with a detection limit of 15.1 colony-forming units mL^-1·reaction^-1. qPCR in combination with an optimal PMA concentration (60 μM) helped in discriminating and quantifying the viable cells, without any interference by heat-killed cells. Compared with the conventional methods, the population heterogeneity of viable, culturable, dormant-like and membrane-permeabilized cells were well identified and quantified using qPCR during L. delbrueckii spp. bulgaricus sp1.1 batch culture. Despite the restriction in the enumeration of lysed cells, qPCR-based methods facilitated reliable identification and quantification of bacterial physiological states and provided additional knowledge on the dynamics of L. delbrueckii spp. bulgaricus sp1.1 physiological states.

Regulation of pyruvate dehydrogenase complex related to lactate switch in CHO cells

The metabolism of Chinese hamster ovary (CHO) cell lines is typically characterized by high rates of aerobic glycolysis with increased lactate formation, known as the "Warburg" effect. Although this metabolic state can switch to lactate consumption, the involved regulations of the central metabolism have only been partially studied so far. An important reaction transferring the lactate precursor, pyruvate, into the tricarboxylic acid cycle is the decarboxylation reaction catalyzed by the pyruvate dehydrogenase enzyme complex (PDC). Among other mechanisms, PDC is mainly regulated by phosphorylation-dephosphorylation at the three sites Ser232, Ser293, and Ser300. In this work, the PDC phosphorylation in antibody-producing CHO DP-12 cell culture is investigated during the lactate switch. Batch cultivations were carried out with frequent sampling (every 6 h) during the transition from lactate formation to lactate uptake, and the PDC phosphorylation levels were quantified using a novel indirect flow cytometry protocol. Contrary to the expected activation of PDC (i.e., reduced PDC phosphorylation) during lactate consumption, Ser293 and Ser300 phosphorylation levels were 33% higher compared to the phase of glucose excess. At the same time, the relative phosphorylation level of Ser232 increased steadily throughout the cultivation (66% increase overall). The intracellular pyruvate was found to accumulate only during the period of high lactate production, while acetyl-CoA showed nearly no accumulation. These results indicate a deactivation of PDC and reduced oxidative metabolism during lactate switch even though the cells undergo a metabolic transition to lactate-based cell growth and metabolism. Overall, this study provides a unique view on the regulation of PDC during the lactate switch, which contributes to an improved understanding of PDC and its interaction with the bioprocess.

Model-assisted DoE software: optimization of growth and biocatalysis in Saccharomyces cerevisiae bioprocesses

Bioprocess development and optimization are still cost- and time-intensive due to the enormous number of experiments involved. In this study, the recently introduced model-assisted Design of Experiments (mDoE) concept (Möller et al. in Bioproc Biosyst Eng 42(5):867, https://doi.org/10.1007/s00449-019-02089-7 , 2019) was extended and implemented into a software ("mDoE-toolbox") to significantly reduce the number of required cultivations. The application of the toolbox is exemplary shown in two case studies with Saccharomyces cerevisiae. In the first case study, a fed-batch process was optimized with respect to the pH value and linearly rising feeding rates of glucose and nitrogen source. Using the mDoE-toolbox, the biomass concentration was increased by 30% compared to previously performed experiments. The second case study was the whole-cell biocatalysis of ethyl acetoacetate (EAA) to (S)-ethyl-3-hydroxybutyrate (E3HB), for which the feeding rates of glucose, nitrogen source, and EAA were optimized. An increase of 80% compared to a previously performed experiment with similar initial conditions was achieved for the E3HB concentration.

Model-based workflow for scale-up of process strategies developed in miniaturized bioreactor systems

Miniaturized bioreactor (MBR) systems are routinely used in the development of mammalian cell culture processes. However, scale-up of process strategies obtained in MBR- to larger scale is challenging due to mainly non-holistic scale-up approaches. In this study, a model-based workflow is introduced to quantify differences in the process dynamics between bioreactor scales and thus enable a more knowledge-driven scale-up. The workflow is applied to two case studies with antibody-producing Chinese hamster ovary cell lines. With the workflow, model parameter distributions are estimated first under consideration of experimental variability for different scales. Second, the obtained individual model parameter distributions are tested for statistical differences. In case of significant differences, model parametric distributions are transferred between the scales. In case study I, a fed-batch process in a microtiter plate (4 ml working volume) and lab-scale bioreactor (3750 ml working volume) was mathematically modeled and evaluated. No significant differences were identified for model parameter distributions reflecting process dynamics. Therefore, the microtiter plate can be applied as scale-down tool for the lab-scale bioreactor. In case study II, a fed-batch process in a 24-Deep-Well-Plate (2 ml working volume) and shake flask (40 ml working volume) with two feed media was investigated. Model parameter distributions showed significant differences. Thus, process strategies were mathematically transferred, and model predictions were simulated for a new shake flask culture setup and confirmed in validation experiments. Overall, the workflow enables a knowledge-driven evaluation of scale-up for a more efficient bioprocess design and optimization.