Scale-down Simulators Research Articles

Developing rational scale-down simulators for mimicking substrate heterogeneities based on cell lifelines in industrial-scale bioreactors

The influence of extracellular variations on the cellular metabolism and thereby the process performance at large-scale can be evaluated using the so-called scale-down simulators. Nevertheless, the major challenge is to design an appropriate scale-down simulator, which can accurately mimic the cell lifelines that record the flow paths and experiences of cells circulating in large-scale bioreactors. To address this, a dedicated SDSA (scale-down simulator application) was purposedly developed on the basis of black box model and process reaction model established for Penicillium chrysogenum strain as well as cell lifelines or trajectories information in an industrial-scale fermentor. Guided by the SDSA, the industrial-relevant metabolic regimes for substrate availability, i.e., excess, limitation and starvation, were successfully reproduced at laboratory-scale three-compartment scale-down (SD) system. In addition, such SDSA can also display individual process dynamics in each compartment, and demonstrate how individual factors influence the entire bioprocess performance, thus serving both educational and research purposes.

Scale-down cultivation in mammalian cell bioreactors—The effect of bioreactor mixing time on the response of CHO cells to dissolved oxygen gradients

Scale-down simulators have been widely applied to investigate the impact of various concentration gradients on the efficiency of industrial-scale fed-batch bioprocesses involving microbial cell factories. However, due to the general fragility and shear sensitivity of mammalian cells, these simulators, especially those with multiple compartments, have not been widely adopted to investigate the effects of similar concentration gradients on cell culture processes. In this work, we developed a multi-compartment scale-down simulator comprising a stirred tank bioreactor and a plug-flow reactor (PFR). CHO cells expressing a recombinant protein were recycled through the PFR whilst being subjected to dissolved oxygen gradients at varying residence times from 70 s to 120 s. The results show a clear cut switch in the metabolism of CHO cells, such that until a residence time of 90s was exceeded, the cells did not respond to the presence of dissolved oxygen gradients in the PFR. Beyond this residence time threshold, there was a marked accumulation of lactate and up to 15 % decline in viable cell density in the stationary phase, compared to the reference fed-batch process. Interestingly, the recombinant protein productivity was not affected by the dissolved oxygen gradients, although the purity of the product, measured as the concentration of host cell proteins in the supernatant was adversely affected. The response time threshold in the metabolism of the cells was used to propose a scale-up technique based on similar physiological indices between bioreactor scales. The demonstrated method is a possible tool for assessing the suitability of a process in a given large scale bioreactor with known mixing times.

Scale-down simulators for mammalian cell culture as tools to access the impact of inhomogeneities occurring in large-scale bioreactors.

During the scale‐up of a bioprocess, not all characteristics of the process can be kept constant throughout the different scales. This typically results in increased mixing times with increasing reactor volumes. The poor mixing leads in turn to the formation of concentration gradients throughout the reactor and exposes cells to varying external conditions based on their location in the bioreactor. This can affect process performance and complicate process scale‐up. Scale‐down simulators, which aim at replicating the large‐scale environment, expose the cells to changing environmental conditions. This has the potential to reveal adaptation mechanisms, which cells are using to adjust to rapidly fluctuating environmental conditions and can identify possible root causes for difficulties maintaining similar process performance at different scales. This understanding is of utmost importance in process validation. Additionally, these simulators also have the potential to be used for selecting cells, which are most robust when encountering changing extracellular conditions. The aim of this review is to summarize recent work in this interesting and promising area with the focus on mammalian bioprocesses, since microbial processes have been extensively reviewed.

Coupled metabolic-hydrodynamic modeling enabling rational scale-up of industrial bioprocesses.

Metabolomics aims to address what and how regulatory mechanisms are coordinated to achieve flux optimality, different metabolic objectives as well as appropriate adaptations to dynamic nutrient availability. Recent decades have witnessed that the integration of metabolomics and fluxomics within the goal of synthetic biology has arrived at generating the desired bioproducts with improved bioconversion efficiency. Absolute metabolite quantification by isotope dilution mass spectrometry represents a functional readout of cellular biochemistry and contributes to the establishment of metabolic (structured) models required in systems metabolic engineering. In industrial practices, population heterogeneity arising from fluctuating nutrient availability frequently leads to performance losses, that is reduced commercial metrics (titer, rate, and yield). Hence, the development of more stable producers and more predictable bioprocesses can benefit from a quantitative understanding of spatial and temporal cell-to-cell heterogeneity within industrial bioprocesses. Quantitative metabolomics analysis and metabolic modeling applied in computational fluid dynamics (CFD)-assisted scale-down simulators that mimic industrial heterogeneity such as fluctuations in nutrients, dissolved gases, and other stresses can procure informative clues for coping with issues during bioprocessing scale-up. In previous studies, only limited insights into the hydrodynamic conditions inside the industrial-scale bioreactor have been obtained, which makes case-by-case scale-up far from straightforward. Tracking the flow paths of cells circulating in large-scale bioreactors is a highly valuable tool for evaluating cellular performance in production tanks. The "lifelines" or "trajectories" of cells in industrial-scale bioreactors can be captured using Euler-Lagrange CFD simulation. This novel methodology can be further coupled with metabolic (structured) models to provide not only a statistical analysis of cell lifelines triggered by the environmental fluctuations but also a global assessment of the metabolic response to heterogeneity inside an industrial bioreactor. For the future, the industrial design should be dependent on the computational framework, and this integration work will allow bioprocess scale-up to the industrial scale with an end in mind.

From industrial fermentor to CFD-guided downscaling: what have we learned?

Euler–Lagrange computational fluid dynamics simulations offer great potential for the integration of transport dynamics and metabolic dynamics in fermentation systems. Since the seminal work of Lapin et al. [1,2], progress has been made, mainly in the analysis of CFD data and translation to laboratory setup designs. Different large-scale processes require different analysis methods; in this paper we discuss which analysis methods are best suited for given reactor types, by reviewing prior simulation cases as well as introducing new test cases. Furthermore, we address challenges in the translation from Euler–Lagrange simulations to laboratory scale systems, and propose methods to work around these shortcomings. Based on the current state of the art, we propose guidelines for the selection of data analysis methods, and we discuss the design of rational scale-down simulators. We conclude with a brief discussion regarding the requirements and possibilities of next-generation scale-down simulators, such as microfluidic single-cell analysis, and possible ways to approximate cellular lifelines from invasive intra-cellular measurements.

Euler-Lagrange analysis towards representative down-scaling of a 22 m3 aerobic S. cerevisiae fermentation

With reaction timescales equal to or shorter than the circulation time, the ideal mixing assumption typically does not hold for large scale bioreactors. As a consequence large scale gradients in extra-cellular conditions such as the substrate concentration exist, which may significantly impact the metabolism of micro-organisms and thereby the process performance. The influence of extra-cellular variations on the organism can be tested using so-called scale-down simulators, laboratory scale setups where deliberate, controlled fluctuations are imposed in the extra-cellular environment.The major challenge associated with this scale-down philosophy is to design a scale-down simulator that resembles the extra-cellular environment of the industrial process. Previously, Euler-Lagrange CFD was explored to investigate the large scale environment from the microbial point of view (Haringa et al., 2016a), collecting statistics of the frequency and magnitude of environmental fluctuations that can serve as a basis for scale-down design. In this work, we apply this methodology to a validated CFD simulation of a 22m3 aerated fermentation of S. cerevisiae, and devise possible scale-down strategies based on this CFD data, both with fluctuating feed profiles and multiple compartments. All designs are deemed feasible within the limitations of current scale-down equipment.

Dynamics monitoring of industrial bioprocesses realized in scale-down simulators

Dynamics monitoring of industrial bioprocesses realized in scale-down simulators

Accumulation of amino acids deriving from pyruvate in <i>Escherichia coli</i> W3110 during fed-batch cultivation in a two-compartment scale-down bioreactor

Bioprocess scale-down simulators are used to investigate the phenomena occurring in industrial scale cultivations. The aim is to simulate the large-scale conditions, characterized by long mixing times introducing local gradients into the bioreactor, in laboratory scale bioreactor. We have expanded the current physiological knowledge about the consequences of such cultivation conditions from well-known mixed-acid fermentation to amino acid metabolism. Several interesting deviations were observed for amino acids derived from pyruvate when a STR-PFR scale-down simulator and a regular STR fed-batch cultivation were compared. In this article we show that the cultivation of Escherichia coli K-12 substrain W3110 in a scale-down two-compartment bioreactor has consequences on the free amino acid pools. Repeated occurrence of high glucose zones affects the biosynthesis of amino acids derived from pyruvate. This is interesting since the pyruvate based amino acids are precursors of the branched chain amino acid pathway, which is further disturbed by an unbalanced regulation caused by a frameshift mutation in the ilvG gene of E. coli K-12 strains. As a consequence the formation of non-typical amino acid norvaline was detected in the two compartment bioreactor cultivation.