1. |
- Cavero-Olguin, Victor Hugo, et al.
(författare)
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Propionic acid production from glycerol in immobilized cell bioreactor using an acid-tolerant strain of Propionibacterium acidipropionici obtained by adaptive evolution
- 2021
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Ingår i: Process Biochemistry. - : Elsevier BV. - 1359-5113. ; 110, s. 223-230
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Tidskriftsartikel (refereegranskat)abstract
- Propionic acid (PA) production from agro-industrial residues using propionibacteria has gained interest as an alternative to fossil-based process. Microbial production is however characterized by product inhibition, lowering the product titers and productivity. In this study, Propionibacterium acidipropionici DSMZ4900 was subjected to adaptive evolution to tolerate higher acid concentrations. The strain adapted to growth in medium spiked with 20 g/L PA exhibited improved product titer (16.8 vs 8.72 g/L) and productivity (0.52 vs 0.17 g/L·h) with glycerol as carbon source in batch fermentations. It was immobilized on polyethyleneimine coated recycled glass beads Poraver® and used for fermentations in recycle batch mode with increasing glycerol concentration and decreasing pH, respectively. Doubling yeast extract concentration raised PA yield and productivity by >1.5 fold. Glycerol at 100 g/L was completely consumed to give ∼58 g/L PA at yield of 0.64 mol/mol and productivity of 0.28 g/L·h at pH 6.5. Decreasing fermentation pH to 5.0 increased PA productivity to 0.23 g/L·h from 0.14 g/L·h at pH 6.0 with 20 g/L glycerol, while immobilized cells exhibited no growth. The study shows combination of adaptive evolution and immobilization of cells to result in a robust system for PA fermentation at high glycerol concentration and lower pH.
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2. |
- Rahimpour, Farshad, et al.
(författare)
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Optimizing refolding and recovery of active recombinant Bacillus halodurans xylanase in polymer-salt aqueous two-phase system using surface response analysis
- 2007
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Ingår i: Journal of Chromatography A. - : Elsevier BV. - 0021-9673. ; 1141:1, s. 32-40
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Tidskriftsartikel (refereegranskat)abstract
- An experimental design was used to determine optimal conditions for refolding of a recombinant thermostable and alkaline active xylanase from Bacillus halodurans in PEG-phosphate two-phase system. The influence of different experimental variables on the enzyme recovery has been evaluated. To build the mathematical model and minimize the number of experiments for the design parameters, response surface methodology with a face-centered central composite design (CCF) was defined based on the conditions found by preliminary tests that resulted in the highest refolding yield. The adequacy of the calculated model for the response was confirmed by means of variance analysis and additional experiments. Analysis of contours of constant response as a function of pH, polyethylene glycol (PEG) molecular weight and concentration, and salt concentration for different enzyme loads revealed different effects of these five factors on the studied parameters. Recovery of more than 92% active xylanase was predicted for a system with 18.3% (w/w) PEG 1000, 14.4% (w/w) phosphate at pH 8.5, and enzyme load corresponding to a protein concentration of about 0.05 mg/g system. The yield of the refolded enzyme was found to be optimal at 22 degrees C. The validity of the response model was verified by a good agreement between predicted and experimental results. (c) 2006 Elsevier B.V. All rights reserved.
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3. |
- Rahimpour, Farshad, et al.
(författare)
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Purification of plasmid DNA with polymer-salt aqueous two-phase system: Optimization using response surface methodology
- 2006
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Ingår i: Biotechnology and Bioengineering. - : Wiley. - 1097-0290 .- 0006-3592. ; 95:4, s. 627-637
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Tidskriftsartikel (refereegranskat)abstract
- An experimental design was used to optimize plasmid purification from an alkaline lysate of Escherichia coli cells using PEG-sodium citrate aqueous two-phase systems (ATIPS), and to evaluate the influence of pH, PEG molecular weight, tie line length, phase volume ratio, and lysate load. To build the mathematical model and minimize the number of experiments for the design parameters, response surface methodology (RMS) with an orthogonal rotatable central composite design was defined based on the conditions found for the highest purification by preliminary tests. The adequacy of the calculated models for the plasmid recovery and remaining RNA were confirmed by means of variance analysis and additional experiments. Analysis of contours of constant response as a function of pH, PEG molecular weight, tie line length, and cell lysate load for three different phase volume ratios revealed different effects of these five factors on the studied parameters. Plasmid recovery of 99% was predicted for a system with PEG 400, pH 6.9, tie line length of 38.7%, phase volume ratio of 1.5, and lysate load of 10% MO. Under these conditions the predicted RNA removal was 68%. (c) 2006 Wiley Periodicals, Inc.
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4. |
- Rahimpour, Farshad, et al.
(författare)
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Response surface methodology and artificial neural network modeling of an aqueous two-phase system for purification of a recombinant alkaline active xylanase
- 2016
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Ingår i: Process Biochemistry. - : Elsevier BV. - 1359-5113. ; 51:3, s. 452-462
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Tidskriftsartikel (refereegranskat)abstract
- A two-stage polyethylene glycol (PEG)-phosphate aqueous two-phase system was used for purification of a highly thermostable and alkaline active recombinant xylanase. Response surface methodology (RSM) and artificial neural network (ANN) have been used to develop predictive models for simulation and optimization of purification process. Effects of pH, PEG molecular weight, concentrations of phosphate, PEG and NaCl on the partitioning of the target enzyme and the contaminants were studied using a central composite design of experiments. The best first stage purification was achieved using 6% PEG 6000, 20% phosphate and pH 6. The optimum back extraction stage system consist of 10% phosphate, 10% NaCl, pH 10 and the first stage separation top phase. After the two stage phase separations, about 78% of the original enzyme activity was recovered and the specific activity of the purified enzyme was increased by a factor of 6.7. Also, the aqueous two-phase system was scaled-up 100 times. After back-extraction, the specific activity increased 6.56 times with 72% total yield. A similar design was also used to obtain a training set for ANN. A comparison between the model results and experimental data gave high correlation coefficient (R2) and showed that both models were able to predict the partitioning behavior. The results demonstrated a higher prediction accuracy of ANN compared to RSM. This superiority of ANN over other multi factorial approaches could make this estimation technique a very helpful tool for purification process.
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