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Helmholtz-Zentrum für Umweltforschung GmbH - UFZ Leipzig
Njemačka
Technische Universiteit Delft, Department of Biotechnology
Nizozemska
University of Zagreb
Hrvatska
Agencia Estatal Consejo Superior de Investigaciones Científicas – CSIC
Španjolska
Evonik Rexim S.A.S
Francuska
RWTH Aachen
Njemačka
Short description of project
The potential of non-pathogenic Pseudomonas as a platform host for Industrial Biotechnology has been discussed for decades in Europe, mainly inspired by its metabolic versatility, ease of genetic programming and high solvent tolerance. These properties enable growth in the presence of a second phase of toxic solvents, such as styrene or octanol, or high concentrations of inherently toxic compounds originating from cheap renewable feedstocks (e.g., biomass hydrolysates), like furaldehydes. Furthermore, Pseudomonas displays an extensive enzymatic inventory (e.g., hydrocarbon degradation pathways), and the potential to regenerate redox cofactors at a high rate (Blank et al., FEBS J. 2008 275/20). On this background, it comes as a surprise that Pseudomonas strains are still a minor player as genomic and metabolic chassis for the Bio-Industry, where most key processes are still dominated by Bacillus, Corynebacterium glutamicum, and Escherichia coli. We argue that by tackling and overcoming the few molecular bottlenecks that still make non-pathogenic Pseudomonas less efficacious than bacterial alternatives, we can contribute to place European Bio- Industry into a prime position within the global Biotechnology scenario. Novel biocatalytic processes, must successfully overcome economic barriers before realization. This necessitates high solvent tolerance, a high rate of redox cofactor regeneration, carbon efficiency, and biocatalytic stability. Preferably, these parameters determining whole-cell biocatalyst performance are optimized simultaneously. Explicitly, this performance has to be transferable to industrial environments, including large scale fermenters, which will be a main focus of Pseudomonas 2.0. The transfer of excellent academic research findings into industrially useful technology will be achieved by truly cooperative work between the 6 academic partners and Rexim-Evonik and DSM, 2 of the major European chemical companies. The outcomes of the project Pseudomonas 2.0 will propel the development of Industrial Biotechnology in Europe, supporting a bio-refinery approach in the chemical industry on the basis of the European Lead Market Initiative.
Short description of the task performed by Croatian partner
Rational optimization of whole-cell (S)-styrene oxide epoxidation. To increase product yields and volumetric productivity, 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, while minimizing microbial stress. In bioprocess development, for each product, process and facility, suitable strategies have to be elaborated by a comprehensive and detailed process characterization, thereby identifying the most relevant process parameters influencing the product yield, volumetric productivity and product quality. Notably, the parameters identified at lab-scale should be highly relevant for the industrial scale. However, successful scale up in most cases is not the result of conclusive and straight-lined experimental strategies, but rather is the outcome of separate process developments and optimizations at different scales (Schmidt, 2005 Appl. Microbiol. BIotechnol. 68). The research objective in Pseudomonas 2.0 is the development of an efficient stereospecific epoxidation of styrene to enantiomerically pure (S)-styrene oxide by Pseudomonas and Pseudomonas 2.0. A commercially attractive fermentation process should be developed by incorporating limits given by the industrial process conditions. To achieve this aim, a close cooperation with partner 2 for production studies and partner 7 for scale-up will be realized. Experimental approach: Styrene epoxidation by whole cells of Pseudomonas will be studied in 1- and 2-L bioreactors for process conditions characterized by Partner 1, 2 (lab-scale) and 7 (pilot plant and industrial scale). Minimal growth requirement of Pseudomonas under full biocatalytic performance conditions as well as glucose requirements for sustainable production will be evaluated in lab-scale bioreactor having in mind all limitations present in the industrial production such as low power input and low oxygen transfer rate. Fermentation conditions, e.g., pH, temperature and medium composition for efficient (S)-styrene oxide production will be experimentally optimized. Different process strategies, e.g., (repetitive) batch, repetitive (fed-batch) and a continuous process will be considered at optimal fermentation conditions. The most important process parameters such as oxygen uptake rate, glucose uptake rate, and specific power consumption for efficient (S)-styrene oxide production will be indentified and used for scaling-up the process in collaboration with Partner 7. Modeling approach: Unstructured process models comprised of cell growth, glucose consumption and (S)-styrene oxide production based on the laboratory scale data will be developed and evaluated using data from independent experiments. Modeling and simulation of the process using lab-scale data should provide a sound basis for an economic and ecological evaluation that enables an integrated optimization of the process. The economic and ecological evaluation will be flanked by the expertise of partner 1, who recently showed that biocatalytic production of (S)-styrene oxide is more economically than chemical alternatives (Kuhn et al., 2010 Green Chem 12(5)). Developed models will be used for additional model based optimization of the process. Models based on the lab-scale data have a limited range of applicability or represent behavioral inconsistencies with industrial data. To overcome this shortcoming lab-scale and industrial scale data supplied by Partner 7 will be used as base for the development of knowledge based artificial neural network models. Neural networks were shown to be superior to mechanistic models in the description of bioprocesses in many lab-scale and industrial, real or simulated processes (Zelić et al, 2006 Bioprocess Biosyst. Eng. 29). The final model, after validation, will be used for both, estimation of biomass and product concentration, and for on-line control and optimization of (S)-styrene oxide production in an industrial production process.
Ovo web sjedište koristi tehnologiju "kolačića" (eng. cookie) da bi se korisnicima prikazao dinamičan i personaliziran sadržaj, te su oni nužni za ispravan rad. Ako nastavite pregledavati ove stranice, kolačići će biti korišteni u suradnji s vašim preglednikom Weba.
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