Immobilization of permeabilized cells of baker’s yeast for decomposition of H2O2 by catalase

Permeabilization is one of the effective tools, used to increase the accessibility of intracellular enzymes. Immobilization is one of the best approaches to reuse the enzyme. Present investigation use both techniques to obtain a biocatalyst with high catalase activity. At the beginning the isopropyl alcohol was used to permeabilize cells of baker’s yeast in order to maximize the catalase activity within the treated cells. Afterwards the permeabilized cells were immobilized in calcium alginate beads and this biocatalyst was used for the degradation of hydrogen peroxide to oxygen and water. The optimal sodium alginate concentration and cell mass concentration for immobilization process were determined. The temperature and pH for maximum decomposition of hydrogen peroxide were assigned and are 20°C and 7 respectively. Prepared biocatalyst allowed 3.35-times faster decomposition as compared to alginate beads with non permeabilized cells. The immobilized biocatalyst lost ca. 30% activity after ten cycles of repeated use in batch operations. Each cycles duration was 10 minutes. Permeabilization and subsequent immobilization of the yeast cells allowed them to be transformed into biocatalysts with an enhanced catalase activity, which can be successfully used to decompose hydrogen peroxide.

Neural Network Model to Estimate and Predict Cell Mass Concentration in Lipase Fermentation

Lipase is an industrially important enzyme with major use in food industries. The demand of lipase is increasing every year. An online prediction of cell mass concentration is of great value in real time process involving the production of lipase. In the current work, the use of a back-propagation multilayer neural network to predict cell mass during lipase production by Rhizopus delemar NRRL 1472 is targeted. Network training data with respect to time is generated by carrying out experiments in laboratory. The fungus is grown in erlenmeyer flasks at initial pH of 5.6, temperature of 30ºC, and at 150 rpm. During the experiments, readings for cell mass growth are collected in specific period of time. By the training data, an artificial neural network model programmed in MATLAB for Windows is trained and used for prediction of cell mass. The Levenberg-Marquardt algorithm with back-propagation is used in the network to get the optimized weights. The optimum network configuration with different activation function and the number of nodes in the hidden layer are identified by trial and error method. Sigmoid unipolar activation function is 2-5-1, whereas logarithmoid and sigmoid bipolar is 2-3-1. These are chosen according to the values of Sum of Square of Errors (SSE), Root Mean Square (RMS) training and testing. The sigmoid unipolar activation function gives a good fit for estimated value with network configuration 2-5-1, which could be used for generalization.

Immobilization of Erwinia sp. D12 Cells in Alginate-Gelatin Matrix and Conversion of Sucrose into Isomaltulose Using Response Surface Methodology

Isomaltulose is a noncariogenic reducing disaccharide and also a structural isomer of sucrose and is used by the food industry as a sucrose replacement. It is obtained through enzymatic conversion of microbial sucrose isomerase. An Erwinia sp. D12 strain is capable of converting sucrose into isomaltulose. The experimental design technique was used to study the influence of immobilization parameters on converting sucrose into isomaltulose in a batch process using shaken Erlenmeyer flasks. We assessed the effect of gelatin and transglutaminase addition on increasing the reticulation of granules of Erwinia sp. D12 cells immobilized in alginate. Independent parameters, sodium alginate concentration, cell mass concentration, CaCl2 concentration, gelatin concentration, and transglutaminase concentration had all a significant effect (P<0.05) on isomaltulose production. Erwinia sp. D12 cells immobilized in 3.0% (w/v) sodium alginate, 47.0% (w/v) cell mass, 0.3 molL-1 CaCl2, 1.7% (w/v) gelatin and 0.15% (w/v) transglutaminase presented sucrose conversion into isomaltulose, of around 50–60% in seven consecutive batches.