Modeling of an integrated fermentation/membrane extraction process for the production of 2-phenylethanol and 2-phenylethylacetate

An unstructured model for an integrated fermentation/membrane extraction process for the production of the aroma compounds 2-phenylethanol and 2-phenylethylacetate by Kluyveromyces marxianus CBS 600 was developed. The extent to which this model, based only on data from the conventional fermentation and separation processes, provided an estimation of the integrated process was evaluated. The effect of product inhibition on specific growth rate and on biomass yield by both aroma compounds was approximated by multivariate regression. Simulations of the respective submodels for fermentation and the separation process matched well with experimental results. With respect to the in situ product removal (ISPR) process, the effect of reduced product inhibition due to product removal on specific growth rate and biomass yield was predicted adequately by the model simulations. Overall product yields were increased considerably in this process (4.0 g/L 2-PE+2-PEA vs. 1.4 g/L in conventional fermentation) and were even higher than predicted by the model. To describe the effect of product concentration on product formation itself, the model was extended using results from the conventional and the ISPR process, thus agreement between model and experimental data improved notably. Therefore, this model can be a useful tool for the development and optimization of an efficient integrated bioprocess.     

A multikinetic model approach to predict gluconic acid production in an airlift bioreactor

This paper uses a multikinetic approach to predict gluconic acid (GA) production performance in a 4.5 L airlift bioreactor (ALBR). The mathematical model consists of a set of simultaneous firstorder ordinary differential equations obtained from material balances of cell biomass, GA, glucose, and dissolved oxygen. Multikinetic models, namely, logistic and contois equations constitute kinetic part of the main model. The main model also takes into account the hydrodynamic and mass transfer parameters. These equations were solved using ODE solver of MATLAB v6.5 software. The mathematical model was validated with the experimental data available in the literature and is used to predict the effect of change in initial biomass and air sparging rate on the GA production. It is concluded that the mathematical model incorporated with multikinetic approach would be more efficient to predict the change in operating parameters on overall bioprocess of GA production in an ALBR.     

Prospective inference of bioprocess cell viability through chemometric modeling of fluorescence multiway data

In this investigation, the fermentation step of a standard mammalian cell-based industrial bioprocess for the production of a therapeutic protein was studied, with particular emphasis on the evolution of cell viability. This parameter constitutes one of the critical variables for bioprocess monitoring since it can affect downstream operations and the quality of the final product. In addition, when the cells experiment an unpredictable drop in viability, the assessment of this variable through classic off-line methods may not provide information sufficiently in advance to take corrective actions. In this context, Process Analytical Technology (PAT) framework aims to develop novel strategies for more efficient monitoring of critical variables, in order to improve the bioprocess performance. Thus, in this work, a set of chemometric tools were integrated to establish a PAT strategy to monitor cell viability, based on fluorescence multiway data obtained from fermentation samples of a particular bioprocess, in two different scales of operation. The spectral information, together with data regarding process variables, was integrated through chemometric exploratory tools to characterize the bioprocess and stablish novel criteria for the monitoring of cell viability. These findings motivated the development of a multivariate classification model, aiming to obtain predictive tools for the monitoring of future lots of the same bioprocess. The model could be satisfactorily fitted, showing the non-error rate of prediction of 100%.     

Biosurfactant production: emerging trends and promising strategies

Biosurfactants are economically most sought after biotechnological compounds of the 21st century. However, inefficient bioprocessing has mitigated the economical commercial production of these compounds. Although much work is being done on the use of low-cost substrates for their production, a paucity of literature exists on the upcoming bioprocess optimization strategies and their successes and potential for economical biosurfactant production. This review discusses some of the latest developments and most promising strategies to enhance and economize the biosurfactant production process. Recent market analysis, developments in the field of optimally formulated cost credit substrates for enhanced product formation and subsequent process economization are few of the critical aspects highlighted here. Use of nanoparticles and coproduction of biosurfactant along with other commercially important compounds like enzymes, are other upcoming bioprocess intensification strategies. The recent developments discussed here would not only give an overview of pertinent parameters for economic biosurfactant production but would also bring to fore multiple strategies that would open up new avenues of research on biosurfactant production. This would go a long way in making biosurfactants a commercially successful compound of the current century.     

Combining genetic engineering and bioprocess concepts for improved phenylpropanoid production

The group of natural aromatic compounds known as phenylpropanoids has diverse applications, but current methods of production which are largely based on synthesis from petrochemicals or extraction from agricultural biomass are unsustainable. Bioprocessing is a promising alternative, but improvements in production titers and rates are required to make this method profitable. Here the recent advances in genetic engineering and bioprocess concepts for the production of phenylpropanoids are presented for the purpose of identifying successful strategies, including adaptive laboratory evolution, enzyme engineering, in-situ product removal, and biocatalysis. The pros and cons of bacterial and yeast hosts for phenylpropanoid production are discussed, also in the context of different phenylpropanoid targets and bioprocess concepts. Finally, some broad recommendations are made regarding targets for continued improvement and areas requiring specific attention from researchers to further improve production titers and rates.     

Analysis of the regulation of noradrenaline secretion by autoadrenoreceptors and stimulation frequency

A mathematical model is presented which quantitatively describes the value of secreted mediator to each subsequent impulse in the series of presynaptic impulses. The model is constructed with the account taken of the role of presynaptic adrenoreceptors regulating noradrenaline secretion. An analysis of the model shows that the observed decrease and further stabilization of presynaptic responses in the series of presynaptic impulses observed in neurophysiological experiments can be connected with the work of alpha- and beta-autoadrenoreceptors. The increase of impulsation frequency affects the sensitivity of these receptors, which brings about an increase of concentration of secreted to each subsequent impulse mediator in the synaptic slit in the series of presynaptic impulses and stabilization of secretion at a higher level.     

Nomenclature and guideline to express the amount of a membrane protein synthesized in animal cells in view of bioprocess optimization and production monitoring

Studies of a bioprocess optimization and monitoring for protein synthesis in animal cells face a challenge on how to express in quantitative terms the system performance. It is possible to have a panel of calculated variables that fits more or less appropriately the intended goal. Each mathematical expression approach translates different quantitative aspects. We can basically separate them into two categories: those used for the evaluation of cell physiology in terms of product synthesis, which can be for bioprocess improvement or optimization, and those used for production unit sizing and for bioprocess operation. With these perspectives and based on our own data of kinetic S2 cells growth and metabolism, as well as on their synthesis of the transmembrane recombinant rabies virus glycoprotein, here indicated as P, we show and discuss the main characteristics of calculated variables and their recommended use. Mainly applied to a bioprocess improvement/optimization and that mainly used for operation definition and to design the production unit, we expect these definitions/recommendations would improve the quality of data produced in this field and lead to more standardized procedures. In turn, it would allow a better and easier comprehension of scientific and technological communications for specialized readers.     

Modeling and observer design for recombinant Escherichia coli strain

A mathematical model for recombinant bacteria which includes foreign protein production is developed. The experimental system consists of an Escherichia Coli strain and plasmid pIT34 containing genes for bioluminescence and production of a protein, β-galactosidase. This recombinant strain is constructed to facilitate on-line estimation and control in a complex bioprocess. Several batch experiments are designed and performed to validate the developed model. The design of a model structure, the identification of the model parameters and the estimation problem are three parts of a joint design problem. A nonlinear observer is designed and an experimental evaluation is performed on a batch fermentation process to estimate the substrate consumption.     

Microbial production of enzymes: Nonlinear state and kinetic reaction rates estimation

The nonlinearity of the biotechnological processes and the absence of cheap and reliable instrumentation require an enhanced modelling effort and estimation strategies for the state and the kinetic parameters. This work approaches nonlinear estimation strategies for microbial production of enzymes, exemplified by using a process of lipase production from olive oil by Candida rugosa. First, by using a dynamical mathematical model of this process, an asymptotic observer which reconstructs the unavailable state variables is proposed. The design of this kind of observers is based on mass and energy balances without the knowledge of kinetics being necessary; only minimal information concerning the measured concentrations is used. Second, a nonlinear high-gain observer is designed for the estimation of imprecisely known kinetics of the bioprocess. An important advantage of this high-gain estimator is that the tuning is reduced to the calibration of a single parameter. Numerical simulations in various scenarios are provided in order to test the behaviour and performances of the proposed nonlinear estimation strategies.     

Acetic acid production by Acetogenium kivui in continuous culture — kinetic studies and computer simulations

Summary This work considers the continuous production of acetic acid by the homoacetogenic and thermophilic bacterium Acetogenium kivui. A mathematical model for the growth kinetics has been developed. The unstructured model for growth and product formation includes product and substrate inhibition as well as maintenance energy effects. The associated model parameters have been identified by non-linear optimization and evidenced experimentally in continuous culture as steady-state data. By using a mineral medium with glucose as the energy and carbon source for the bacteria proper carbon balances are available. The model permits good predictions of steady-state concentrations. Offprint requests to: J. von Eysmondt     

In situ product recovery (ISPR) by crystallization: basic principles, design, and potential applications in whole-cell biocatalysis

The removal of inhibiting or degrading product from a bioreactor as soon as the product is formed is an important issue in industrial bioprocess development. In this review, the potential of crystallization as an in situ product removal (ISPR) technique for the biocatalytic production of crystalline compounds is discussed. The emphasis of this review is on the current status of crystalline product formation by metabolically active cells for application in fine-chemicals production. Examples of relevant biocatalytic conversions are summarized, and some basic process options are discussed. Furthermore, a case study is presented in which two conceptual process designs are compared. In one process, product formation and crystallization are integrated by applying ISPR, whereas a second, nonintegrated process is based on a known conventional process equivalent for the production of 6R-dihydro-oxoisophorone. The comparison indicates that employing ISPR leads to significant advantages over the nonintegrated case in terms of increased productivity and yield with a corresponding decrease in the number of downstream processing steps, as well as in the quantity of waste streams. This leads to an economically more interesting process alternative. Finally, a general outlook on the various research aspects of ISPR by crystallization is given.     

Adsorptive bioconversion of ethylene glycol to glycolic acid by Gluconobacter oxydans DSM 2003

An integrated bioprocess for the production of glycolic acid from ethylene glycol with Gluconobacter oxydans DSM 2003 and in situ product removal were investigated. A slight substrate inhibition was observed as substrate concentration was above 20 g/l and the product inhibition was much stronger. Bioconversion of glycolic acid is an end-product-inhibited reaction. In order to increase the productivity of glycolic acid and reduce the end-product inhibition of bioconversion, an adsorptive bioconversion for glycolic acid production from ethylene glycol catalyzed by resting cells of G. oxydans DSM 2003, was developed by using anion exchange resin D315 as the adsorbent for selective removal of glycolic acid from the reaction mixture. This approach allowed the yield of glycolic acid to be increased to 93.2 g/l, compared to 74.5 g/l obtained from a conventional fed-batch mode.     

Substrate-limited co-culture for efficient production of propionic acid from flour hydrolysate

Propionic acid is presently mainly produced by chemical synthesis. For many applications, especially in feed and food industries, a fermentative production of propionic acid from cheap and renewable resources is of large interest. In this work, we investigated the use of a co-culture to convert household flour to propionic acid. Batch and fed-batch fermentations of hydrolyzed flour and a process of simultaneous saccharification and fermentation were examined and compared. Fed-batch culture with substrate limitation was found to be the most efficient process, reaching a propionic acid concentration of 30 g/L and a productivity of 0.33 g/L*h. This is the highest productivity so far achieved with free cells on media containing flour hydrolysate or glucose as carbon source. Batch culture and culture with controlled saccharification and fermentation delivered significantly lower propionic acid production (17–20 g/L) due to inhibition by the intermediate product lactate. It is concluded that co-culture fermentation of flour hydrolysate can be considered as an appealing bioprocess for the production of propionic acid.     

Dynamic metabolic engineering for increasing bioprocess productivity

Yield and productivity are critical for the economics and viability of a bioprocess. In metabolic engineering, the main objective is the increase of a target metabolite production through genetic engineering. However, genetic manipulations usually result in lower productivity due to growth impairment. Previously, it has been shown that the dynamic control of metabolic fluxes can increase the amount of product formed in an anaerobic batch fermentation of Escherichia coli. In order to apply this control strategy, the genetic toggle switch is used to manipulate key fluxes of the metabolic network. We have designed and analyzed an integrated computational model for the dynamic control of gene expression. This controller, when coupled to the metabolism of E. coli, resulted in increased bioprocess productivity.     

Mathematical model of microporous hollow-fiber membrane extractive fermentor

A mathematical model is presented for a microporous hollow-fiber membrane extractive fermentor (HFEF). The model is based on the continuous flow of the aqueous nutrient phase and cells through the shell space of the fermentor where the fermentation reaction occurs. The product diffuses from the shell space through the hollow-fiber membrane where it is continuously removed by solvent flowing concurrently through the fiber lumen. Results for ethanol production show that the HFEF has a volumetric productivity significantly higher than that possible using conventional methods. The model predicts the existence of an optimum volume fraction of hollow fibers in the fermentor that maximizes the total volumetric productivity. This optimum is the result of a classic trade-off between the volume fraction of the fermentor required for fermentation and that required for efficient removal of the ethanol product to minimize product inhibition.     

In situ magnetic separation for extracellular protein production

A new approach for in situ product removal from bioreactors is presented in which high-gradient magnetic separation is used. This separation process was used for the adsorptive removal of proteases secreted by Bacillus licheniformis. Small, non-porous bacitracin linked magnetic adsorbents were employed directly in the broth during the fermentation, followed by in situ magnetic separation. Proof of the concept was first demonstrated in shake flask culture, then scaled up and applied during a fed batch cultivation in a 3.7 L bioreactor. It could be demonstrated that growth of B. licheniformis was not influenced by the in situ product removal step. Protease production also remained the same after the separation step. Furthermore, degradation of the protease, which followed first order kinetics, was reduced by using the method. Using a theoretical modeling approach, we could show that protease yield in total was enhanced by using in situ magnetic separation. The process described here is a promising technique to improve overall yield in bio production processes which are often limited due to weak downstream operations. Potential limitations encountered during a bioprocess can be overcome such as product inhibition or degradation. We also discuss the key points where research is needed to implement in situ magnetic separation in industrial production.     

Bioprocess monitoring by marker gene analysis

The optimization and the scale up of industrial fermentation processes require an efficient and possibly comprehensive analysis of the physiology of the production system throughout the process development. Furthermore, to ensure a good quality control of established bioprocesses, on-line analysis techniques for the determination of marker gene expression are of interest to monitor the productivity and the safety of bioprocesses. A prerequisite for such analyses is the knowledge of genes, the expression of which is critical either for the productivity or for the performance of the bioprocess. This work reviews marker genes that are specific indicators for stress- and nutrient-limitation conditions or for the physiological status of the bacterial production hosts Bacillus subtilis, Bacillus licheniformis and Escherichia coli. The suitability of existing gene expression analysis techniques for bioprocess monitoring is discussed. Analytical approaches that enable a robust and sensitive determination of selected marker mRNAs or proteins are presented.     

Modelling of growth and product formation of Porphyridium purpureum

In this contribution experimental data and simulations of growth and product formation of the unicellular microalgae Porphyridium purpureum are presented. A mathematical model has been developed for a better understanding of growth and product formation in production plants. The model has been refined with the results of several cultivations in a new photobioreactor designed especially for the study of microalgal kinetics under highly defined illumination conditions. In this photobioreactor light is generated by an external light source and then distributed by means of optical fibres into an internal draft tube which also serves as irradiation element. All cultivations were performed in turbidostate mode. The influence of different light intensity changes, including stepwise change and light-dark cycles in the range from millisecond to second, has been investigated and the results were integrated into the mathematical model. The structured mathematical model consists of three levels: metabolic flux, control of macromolecules and the reactor level. A new linear optimization approach has been realized, enabling the model to describe even very different cultivation conditions. Output variables are among others the commercially interesting macromolecules of the microalgae, e.g. polysaccharides, pigments and polyunsaturated fatty acids. Thus, reliable predictions of the specific production rates of these products are possible for the production in a larger scale.