Physiological responses to mixing in large scale bioreactors

The presence of spatial gradients in fundamental culture parameters, such as dissolved gases, pH, concentration of substrates, and shear rate, among others, is an important problem that frequently occurs in large-scale bioreactors. This problem is caused by a deficient mixing that results from limitations inherent to traditional scale-up methods and practical constraints during large-scale bioreactor design and operation. When cultured in a heterogeneous environment, cells are continuously exposed to fluctuating conditions as they travel through the various zones of a bioreactor. Such fluctuations can affect cell metabolism, yields, and quality of the products of interest. In this review, the theoretical analyses that predict the existence of environmental gradients in bioreactors and their experimental confirmation are reviewed. The origins of gradients in common culture parameters and their effects on various organisms of biotechnological importance are discussed. In particular, studies based on the scale-down methodology, a convenient tool for assessing the effect of environmental heterogene ities, are surveyed.

Living with heterogeneities in bioreactors: understanding the effects of environmental gradients on cells.

To increase product yields and to ensure consistent product quality, key issues of industrial fermentations, process optimization and scale up are aimed at maintaining optimum and homogenous reaction conditions minimizing microbial stress exposure and enhancing metabolic accuracy. For each individual product, process and facility, suitable strategies have to be elaborated by a comprehensive and detailed process characterization, identification of the most relevant process parameters influencing product yield and quality and their establishment as scale-up parameters to be kept constant as far as possible. Physical variables, which can only be restrictedly kept constant as single parameters, may be combined with other pertinent parameters to appropriate mathematical groups or dimensionless terms. Process characterization is preferably based on real-time or near real-time data collected by in situ and on-line measurements and may be facilitated by supportive approaches and tools like neural network based chemometric data analysis and modelling, clarification of the mixing and stream conditions through computational fluid dynamics and scale-down simulations. However, as fermentation facilities usually are not strictly designed according to scale-up criteria and the process conditions in the culture vessels thus may differ significantly and since any strategy and model can only insufficiently consider and reflect the highly complex interdependence and mutual interaction of fermentation parameters, successful scale up in most cases is not the result of a conclusive and straight-lined experimental strategy, but rather will be the outcome of a separate process development and optimization on each scale. This article gives an overview on the problems typically coming along with fermentation process optimization and scale up, and presents currently applied scale-up strategies while considering future technologies, with emphasis on Escherichia coli as one of the most commonly fermented organisms.

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Optimization and scale up of industrial fermentation processes

Scale-up methodologies for Escherichia coli and yeast fermentation processes

The combination of synthetic and systems biology is a powerful framework to study fundamental questions in biology and produce chemicals of immediate practical application such as biofuels, polymers, or therapeutics. However, we cannot yet engineer biological systems as easily and precisely as we engineer physical systems. In this review, we describe the path from the choice of target molecule to scaling production up to commercial volumes. We present and explain some of the current challenges and gaps in our knowledge that must be overcome in order to bring our bioengineering capabilities to the level of other engineering disciplines. Challenges start at molecule selection, where a difficult balance between economic potential and biological feasibility must be struck. Pathway design and construction have recently been revolutionized by next-generation sequencing and exponentially improving DNA synthesis capabilities. Although pathway optimization can be significantly aided by enzyme expression characterization through proteomics, choosing optimal relative protein expression levels for maximum production is still the subject of heuristic, non-systematic approaches. Toxic metabolic intermediates and proteins can significantly affect production, and dynamic pathway regulation emerges as a powerful but yet immature tool to prevent it. Host engineering arises as a much needed complement to pathway engineering for high bioproduct yields; and systems biology approaches such as stoichiometric modeling or growth coupling strategies are required. A final, and often underestimated, challenge is the successful scale up of processes to commercial volumes. Sustained efforts in improving reproducibility and predictability are needed for further development of bioengineering.

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Synthetic and systems biology for microbial production of commodity chemicals.

A heterogeneous micro-environment was identified in a 12 m3 bioreactor with a height-to-diameter ratio of 2.5. The reactor was aerated by a ring sparger and stirred by three Rushton turbines. E. coli cells were cultivated in minimal medium to a cell density in the order of 30 g/l. Samples of glucose, the growth limiting component fed to the process, were taken at three levels in the bioreactor (top/middle/bottom). These showed that glucose concentration declined away from the feedpoint. The gradients depended on the mixing characteristics of the feedpoint, and concentrations of up to 400 times the mean value were found when feed was added to a relatively stagnant mixing zone. This resulted in up to 20% lower biomass yield compared to the bench scale. Gradients also affected the by-product formation, resulting in acetate formation in the large-scale bioreactor. IPTG induction of a recombinant protein was shown to influence important cell parameters and considerably increased the yield of carbon dioxide per glucose added, indicating an increased maintenance. The product formation rate was, however, not notably affected by the scale-up.

Substrate gradient formation in the large-scale bioreactor lowers cell yield and increases by-product formation

A large bioreactor is heterogeneous with respect to concentration gradients of substrates fed to the reactor such as oxygen and growth limiting carbon source. Gradient formation will highly depend on the fluid dynamics and mass transfer capacity of the reactor, especially in the area in which the substrate is added. In this study, some production-scale (12 m3 bioreactor) conditions of a recombinant Escherichia coli process were imitated on a laboratory scale. From the large-scale cultivations, it was shown that locally high concentration of the limiting substrate fed to the process, in this case glucose, existed at the level of the feedpoint. The large-scale process was scaled down from: (i) mixing time experiments performed in the large-scale bioreactor in order to identify and describe the oscillating environment and (ii) identification of two distinct glucose concentration zones in the reactor. An important parameter obtained from mixing time experiments was the residence time in the feed zone of about 10 seconds. The size of the feed zone was estimated to 10%. Based on these observations the scale-down reactor with two compartments was designed. It was composed of one stirred tank reactor and an aerated plug flow reactor, in which the effect of oscillating glucose concentration on biomass yield and acetate formation was studied. Results from these experiments indicated that the lower biomass yield and higher acetate formation obtained on a large scale compared to homogeneous small-scale cultivations were not directly caused by the cell response to the glucose oscillation. This was concluded since no acetate was accumulated during scale-down experiments. An explanation for the differences in results between the two reactor scales may be a secondary effect of high glucose concentration resulting in an increased glucose metabolism causing an oxygen consumption rate locally exceeding the transfer rate. The results from pulse response experiments and glucose concentration measurements, at different locations in the reactor, showed a great consistency for the two feeding/pulse positions used in the large-scale bioreactor. Furthermore, measured periodicity from mixing data agrees well with expected circulation times for each impeller volume. Conclusions are drawn concerning the design of the scale-down reactor.

F. Bylund

Papers

Substrate gradient formation in the large-scale bioreactor lowers cell yield and increases by-product formation

Scale down of recombinant protein production: a comparative study of scaling performance