RESULTS: Mechanical disruption by sonication, which yielded 1.99 U/mg of GAD, was by far the most effective cell disintegration method compared with the other extraction procedures examined. In contrast, the second most effective method, freeze grinding followed by 10% v/v toluene permeabilization at 25°C for 120 min, yielded only 1.17 U/mg of GAD, which is 170% lower than the sonication method. Optimized enzymatic lysis with 3 mg/ml Yatalase® at 60°C for 30 min was the least effective. It yielded only 0.70 U/mg of GAD. Extraction using sonication was further optimized using a one-variable-at-a-time approach (OVAT). Results obtained show that the yield of GAD increased 176% from 1.99 U/mg to 3.50 U/mg.
CONCLUSION: Of the techniques used to extract GAD from A. oryzae NSK, sonication was found to be the best. Under optimized conditions, about 176% of GAD was recovered compared to recovery under non optimized conditions. The high production level of GAD in this strain offers an opportunity to conduct further studies on GABA production at a larger scale.
RESULTS: Different production media were tested for lipase production by a newly isolated thermophilic Geobacillus sp. strain ARM (DSM 21496 = NCIMB 41583). The maximum production was obtained in the presence of peptone and yeast extract as organic nitrogen sources, olive oil as carbon source and lipase production inducer, sodium and calcium as metal ions, and gum arabic as emulsifier and lipase production inducer. The best models for optimization of culture parameters were achieved by multilayer full feedforward incremental back propagation network and modified response surface model using backward elimination, where the optimum condition was: growth temperature (52.3 degrees C), medium volume (50 ml), inoculum size (1%), agitation rate (static condition), incubation period (24 h) and initial pH (5.8). The experimental lipase activity was 0.47 Uml(-1) at optimum condition (4.7-fold increase), which compared well to the maximum predicted values by ANN (0.47 Uml(-1)) and RSM (0.476 Uml(-1)), whereas R2 and AAD were determined as 0.989 and 0.059% for ANN, and 0.95 and 0.078% for RSM respectively.
CONCLUSION: Lipase production is the result of a synergistic combination of effective parameters interactions. These parameters are in equilibrium and the change of one parameter can be compensated by changes of other parameters to give the same results. Though both RSM and ANN models provided good quality predictions in this study, yet the ANN showed a clear superiority over RSM for both data fitting and estimation capabilities. On the other hand, ANN has the disadvantage of requiring large amounts of training data in comparison with RSM. This problem was solved by using statistical experimental design, to reduce the number of experiments.