Mathematical Modeling of Growth and Paclitaxel Biosynthesis in Corylus avellana Cell Culture Responding to Fungal Elicitors Using Multilayer Perceptron-Genetic Algorithm.
作者： Mina Salehi , Siamak Farhadi , Ahmad Moieni , Naser Safaie , Hamed Ahmadi
关键词: Intracellular 、 Biochemistry 、 Elicitor 、 Paclitaxel 、 Bacterial growth 、 Chemistry 、 Extracellular 、 Secondary metabolite 、 Biosynthesis 、 Cell culture
摘要: Paclitaxel is the top-selling anticancer medicine in world. In vitro culture of Corylus avellana has been made known as a promising and inexpensive strategy for producing paclitaxel. Fungal elicitors have named most efficient enhancing biosynthesis secondary metabolites plant cell culture. this study, endophytic fungal strain HEF17 was isolated from C. identified Camarosporomyces flavigenus. suspension (CSC) elicited with extract (CE) filtrate (CF) derived HEF17, either individually or combined treatment, mid late log phase processed modeling optimizing growth paclitaxel regarding CE CF concentration levels, elicitor adding day, CSC harvesting time using multilayer perceptron-genetic algorithm (MLP-GA). The results displayed higher accuracy MLP-GA models (0.89-0.95) than regression (0.56-0.85). great accordance between predicted observed values output variables (dry weight, intracellular, extracellular total yield paclitaxel, also portion) both training testing subsets supported excellent performance developed models. method presented tool selecting optimal conditions maximum biosynthesis. An Excel® estimator, HCC-paclitaxel, designed based on model an easy-to-use predicting responding to elicitors.
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