Stabilization of D-Amino Acid Oxidase via Covalent Immobilization and Mathematical Model of D-Methionine Oxidative Deamination Catalyzed by Immobilized Enzyme

Porcine kidney D-amino acid oxidase was stabilized by covalent immobilization on spherical particles of Eupergit C because of its low stability in soluble form. The focus of this work was to evaluate operational stability of the immobilized enzyme. To evaluate D-amino acid oxidase’s operational stability during process conditions, repetitive batch reactor experiments of D-methionine oxidation reaction were carried out with continuous aeration for oxygen supply at air-flow rates of 5 and 10 dm3 h–1. Kinetic analysis of the immobilized enzyme was done as well. The mathematical model of D-methionine oxidative deamination catalyzed by the immobilized D-amino acid oxidase was developed and it described the data well. It enabled the estimation of operational stability decay rate constant. It was possible to achieve 100 % substrate conversion in all batch experiments

Modelingof the Biotransformation Processes

Modeling and simulation of biotransformation processes have a large potential in searching for optimal process conditions, development and process design, control, scale-up, identifying of the process cost structure, and comparing process alternatives. Modeling and simulation leads to better understanding and quantification of the investigated process and could lead to significant material and costs savings especially in the early phases of the process development. In this review modeling and simulation techniques are demonstrated on two basically different types of bioprocesses, enzymatic and microbial biotransformations. Acetophenone reduction catalyzed by ADH from Thermoanaerobacter sp., amino acid oxidation catalyzed by D-amino acid oxidase from Arthrobacter protophormiae, and L-DOPA oxidation catalyzed by L-amino acid oxidases from Crotalus adamanteus and Rhodococcus opacus are examples for modeling of enzymatic biotransformation processes. On the other hand, microbial biotransformation processes are shown for: production of alcohol dehydrogenase (ADH) in baker\u27s yeast growing cells, production of L-malic acid by permeabilized non-growing yeast cells, production of 2,5-diketo-D-gluconic acid using Pantoea citrea, and for Escherichia coli based pyruvate production

Modelling and Optimization of the (R)-(+)-3,4-dihydroxyphenyllactic Acid Production Catalyzed with D-lactate Dehydrogenase from Lactobacillus leishmannii Using Genetic Algorithm

A mathematical model for the enzymatic kinetics of the synthesis of (R)–(+)–3,4-dihydroxyphenyllactic acid (DHPL) was developed. The synthesis was catalyzed by D-lactate dehydrogenase from Lactobacillus leishmannii. Since this enzyme requires NADH as a coenzyme, formate dehydrogenase system was used for NADH regeneration. Kinetic constants of both enzymes were estimated independently from initial reaction rate experiments. The developed mathematical model was verified by the batch reactor experiment (volumetric productivity in this experiment was 4.76 g dm–3 d–1). Optimization of initial reaction conditions for DHPL synthesis was performed using the genetic algorithm (GA). The genetic algorithm as a flexible optimization tool had been used to obtain the experimental conditions where maximal volumetric productivity could be achieved. The optimal initial conditions were found in the investigated parameter area: c3,4-dihydroxyphenylpyruvic acid = 4.69 mmol dm–3, cNAD+= 4.95 mmol dm–3, cformate = 36.85 mmol dm–3, D-lactate dehydrogenase = 3 mg cm–3, formate dehydrogenase = 2.94mg cm–3 and the reaction time 8.5 min. At these conditions volumetric productivity of 93.06 g dm–3 d–1 can be achieved

Modelling and Optimization of the (R)-(+)-3,4-dihydroxyphenyllactic Acid Production Catalyzed with D-lactate Dehydrogenase from Lactobacillus leishmannii Using Genetic Algorithm

A mathematical model for the enzymatic kinetics of the synthesis of (R)–(+)–3,4-dihydroxyphenyllactic acid (DHPL) was developed. The synthesis was catalyzed by D-lactate dehydrogenase from Lactobacillus leishmannii. Since this enzyme requires NADH as a coenzyme, formate dehydrogenase system was used for NADH regeneration. Kinetic constants of both enzymes were estimated independently from initial reaction rate experiments. The developed mathematical model was verified by the batch reactor experiment (volumetric productivity in this experiment was 4.76 g dm–3 d–1). Optimization of initial reaction conditions for DHPL synthesis was performed using the genetic algorithm (GA). The genetic algorithm as a flexible optimization tool had been used to obtain the experimental conditions where maximal volumetric productivity could be achieved. The optimal initial conditions were found in the investigated parameter area: c3,4-dihydroxyphenylpyruvic acid = 4.69 mmol dm–3, cNAD+= 4.95 mmol dm–3, cformate = 36.85 mmol dm–3, D-lactate dehydrogenase = 3 mg cm–3, formate dehydrogenase = 2.94mg cm–3 and the reaction time 8.5 min. At these conditions volumetric productivity of 93.06 g dm–3 d–1 can be achieved

Overview on Reactions with Multi-enzyme Systems

Production of special chemicals and pharmaceuticals includes multi-step procedures that are still carried out in the traditional way: by isolating the intermediary product of each step and using it as a substrate for the next step, which is money and time consuming. These are also procedures that require many chemicals, energy and labour. Over the last couple of decades scientists have been working on new, integrated processes that require fewer resources and are more close to nature, as they produce less waste. These kinds of processes are discussed in this paper. The advantages of enzyme catalyzed reactions are well documented and numerous. Enzyme reactions are carried out at mild reaction conditions. The enzymes are enantioselective and stereoselective, which is important particularly for the pharmaceutical industry. By combining the action of different enzymes we can imitate the processes in the living cells and produce the desired compounds. Enzyme catalyzed reactions can also be combined with chemical reactions in one-pot chemo-enzymatic synthesis. The progress in the development of these reactions will be presented

Operational Stability of Glucoamylase in Continuously Operated Ultrafiltration Membrane Reactor – Experimental Methods and Mathematical Model

Operational stability of glucoamylase was studied at 45, 60 and 70 °C in the reaction of maltose hydrolysis. The experiments were carried out in a continuously operated ultrafiltration membrane reactor (UFMR) at constant residence time of 176.5 minutes. The rate of enzyme operational stability decay increased with temperature. This could be quantitatively observed from the measurements of volume activity during the experiments, which were used to estimate enzyme operational stability decay rate constants. The results have shown that stationary conditions in UFMR can be maintained if sufficiently high enzyme concentration is used in the reactor, regardless of the enzyme operational stability decay that occurs. This was shown by the experiment carried out at 45 °C where it was proved that the enzyme operational decay occurs even though maltose conversion was at maximum during the entire experiment. Thus, the operational stability decay can be masked

Isolation and Kinetic Characterization of Fumarase from Baker\u27s Yeast

U radu je opisan postupak pročišćavanja enzima fumaraze (fumarat-hidrataza, EC 4.2.1.2) iz pekarskog kvasca. Stanice kvasca su razbijane s pomoću tri metode: staklenim kuglicama, ultrazvukom te kombinacijom ovih dviju metoda. Frakcioniranje proteina provedeno je taloženjem s pomoću amonijeva sulfata, a fino pročišćavanje gel-filtracijskom kromatografijom na kolonama punjenim gelovima Sephadex G-50 i G-100. Primijenjenim tehnikama protein je pročišćen s ukupnim iskorištenjem od približno 25%. Provedena je kinetička karakterizacija dobivenog enzima, te se pokazalo da su Michaelisove konstante za fumarnu i L-jabučnu kiselinu 5,52 i 2,00 mmoldm-3. Biotransformacija fumarne kiseline u L-jabučnu kiselinu katalizirana pročišćenom fumarazom provedena je u kotlastom reaktoru, gdje je postignuta ravnotežna konverzija 76,5% fumarne kiseline. Razvijen je matematički model procesa koji je dobro opisao eksperimentalne podatke. Utvrđeno je da tijekom ovog eksperimenta dolazi do deaktivacije enzima. Brzina deaktivacije opisana je modelom reakcije prvoga reda. Procijenjena konstanta deaktivacije fumaraze iznosi 0,0031 min-1.Isolation and purification of fumarase (fumarate hydratase EC 4.2.1.2) from baker’s yeast was carried out. Yeast cells were disrupted by three methods: glass beads, ultrasound, and the combination of these two methods. Cell disruption methods were compared in their efficiency in Fig. 1. Protein fractionation was carried out by precipitation with ammonium sulphate. The concentrations of ammonium sulphate necessary for fumarase precipitation were found experimentally and are presented in Fig. 2. After precipitation, fumarase samples were purified by gel filtration chromatography on columns filled with Sephadex G50 and Sephadex G100. Examples of the elution curve of one protein suspension sample on both columns are presented in Fig. 3 and Fig. 4. Only the samples having high fumarase activity were used in the next purifying step. Table 1 presents the collective results of the fumarase purification procedure. The techniques used enabled purification of fumarase with a yield of 25 %. The purified enzyme was employed in the hydration of fumaric acid to L-malic acid. Kinetic constants of fumarase were estimated and are presented in Table 2. They were determined from the experimental data measured by the initial reaction rate method. The hydration of fumaric acid to L-malic acid was carried out in a batch reactor and the results are presented in Fig. 5. The kinetic model was developed on the basis of kinetic data and reaction scheme, as presented by equations 1 and 2. It was combined with the mass balances in the batch reactor presented by equations 3 and 4. Considering that fumarase deactivation occurs, it was proposed that the activity loss could be described by a first-order kinetic model (equation 5). Fumarase activity was followed during the batch experiment by the enzyme assay and it was found that activity decay occurs. Deactivation constant was estimated from the independent experimental results and found to be 0.0031 min–1

Bioremediation Kinetics of Pharmaceutical Industrial Effluent

U radu je istražena bioremedijacija otpadne vode iz proizvodnje farmaceutika tvrtke Pliva Hrvatska d.o.o. pomoću aktivnog mulja i bioaugmentiranog aktivnog mulja s izoliranom mješovitom bakterijskom kulturom. Pokusi su provedeni šaržno u submerznim uvjetima s početnom koncentracijom organske tvari u otpadnoj vodi γS0 = 5,01 g dm−3, izraženoj kao vrijdnost KPK te s različitim početnim koncentracijama biomase, γX0, u rasponu od 1,16 do 3,54 g dm−3. Endo-Haldaneova jednadžba odabrana je za matematički opis procesa biorazgradnje farmaceutika. Procijenjene vrijednosti biokinetičkih parametara μmax, Ks, Ki, Y i kd iznosile su 1,66 d−1; 46,2 g dm−3; 131,2 g dm−3; 0,23 gg−1; 0,002 d−1 za pokus s aktivnim muljem i 1,69 d−1; 44,3 g dm−3; 132,0 g dm−3; 0,22 gg−1; 0,001 d−1 za pokus s bioaugmentiranim aktivnim muljem. Bioaugmentacijom aktivnog mulja skratilo se vrijeme obrade otpadne vode za 24 sata. Učinkovitost procesa bioremedijacije u prosjeku je iznosila 64,8 % za sve provedene pokuse.In recent years, concerns about the occurrence and fate of pharmaceuticals that could be present in water and wastewater has gained increasing attention. With the public’s enhanced awareness of eco-safety, environmentally benign methods based on microorganisms have become more accepted methods of removing pollutants from aquatic systems. This study investigates bioremediation of pharmaceutical wastewater from pharmaceutical company Pliva Hrvatska d.o.o., using activated sludge and bioaugmented activated sludge with isolated mixed bacterial culture. The experiments were conducted in a batch reactor in submerged conditions, at initial concentration of organic matter in pharmaceutical wastewater, expressed as COD, 5.01 g dm–3 and different initial concentrations of activated sludge, which ranged from 1.16 to 3.54 g dm–3. During the experiments, the COD, pH, concentrations of dissolved oxygen and biomass were monitored. Microscopic analyses were performed to monitor the quality of activated sludge. Before starting with the bioremediation in the batch reactor, toxicity of the pharmaceutical wastewater was determined by toxicity test using bacteria Vibrio fischeri. The obtained results showed that the effective concentration of the pharmaceutical wastewater was EC50 = 17 % and toxicity impact index was TII50 = 5.9, meaning that the untreated pharmaceutical industrial effluent must not be discharged into the environment before treatment. The results of the pharmaceutical wastewater bioremediation process in the batch reactor are presented in Table 1. The ratio γXv ⁄ γX maintained high values throughout all experiments and ranged from 0.90 and 0.95, suggesting that the concentrations of biomass remained unchanged during the experiments. The important kinetic parameters required for performance of the biological removal process, namely μmax, Ks, Ki, Y and kd were calculated from batch experiments (Table 2). Figs. 1 and 2 show the experimental results of changes in concentrations of substrate γS0 = 5.01 g dm–3 for different initial concentrations of activated sludge in comparison to Endo-Haldane model. Changes in concentrations of activated sludge during four days of experiments P1 and P2 are presented in Figs. 4 and 5, respectively. These results suggest that the bioremediation process is well described by the selected model. Process efficiency of pharmaceutical wastewater treatment was approximately 64.8 % (Fig. 3), while in experiment P2 with bioaugmented activated sludge (Fig. 2), the same efficiency was obtained 24 hours earlier than in experiment P1 (Fig.1). Microscopic examination of the activated sludge (Fig. 6) showed that bioaugmentation has no effect on formation of the flocs, but increases efficiency of the bioremediation in a way that the pharmaceutical wastewater treatment is faster and more efficient with bioaugmented activated sludge (Table 3, Fig. 2)