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Optimization of Medium Components Using Artificial Neural Networks

عنوان مقاله: Optimization of Medium Components Using Artificial Neural Networks
شناسه ملی مقاله: JR_IJHS-3-1_002
منتشر شده در در سال 1396
مشخصات نویسندگان مقاله:

Mohamad Hosein Aghajani۱* - ۱. Dept. of Nanotechnology, The Persian Gulf Nuclear Medicine Research Center, The Persian Gulf Biomedical Sciences Institute, Bushehr University of Medical Sciences, Bushehr, Iran.
Hemat Aghagolzadeh haji۲ - ۲. School of Medicine, Shahroud University of Medical Sciences, Shahroud, Iran.
Mostafa Mir ۳ - ۳. Research Committee, Babol University of Medical Sciences, Iran.
Mahdi Aghajani ۴** - ۴. School of Advanced Medical Technology, Golestan University of Medical Sciences, Gorgan, Iran.

خلاصه مقاله:
Background: Achieving high cell density is an important goal in recombinant proteins production. Optimization of medium components to achieve high cell density and consequently high yield recombinant protein is a common practice in the biotechnology industry. We could not find an article that just examine the effects of salt on growht transformed BL۲۱. On the other hand, salt is a critical component of medium that can be made up in a medium optimization.Methods: Here, we separately investigated effect of K۲HPO۴, MgSO۴, (NH۴)۲SO۴ and NH۴CL on maximum growth of bacteria BL۲۱ after transforming BL۲۱ with PET-۳۲α that containing para thyroid hormones gene. Then, the salts were combined and added to the culture medium for optimization of their effects on high cell density using artificial neural network modelling (ANNs).Results: After ANN modeling, the obtained model showed that MgSO۴ has dominant on high cell density other than salts if final concentration of MgSO۴ is ۲۵mg/ml. The best concentration each of salt be lower ۳۰ mg/ml and critical total concentration of slats is ۱۲۰ mg/ml that inhibitory effect was seen after a critical concentration.Conclusions: In current study, ANN modeling shows that in prediction of effects of salts (i.e. K۲HPO۴, MgSO۴, (NH۴)۲SO۴ and NH۴CL) on cell density to reach high cell density, is effective and efficient.Background: Achieving high cell density is an important goal in recombinant proteins production. Optimization of medium components to achieve high cell density and consequently high yield recombinant protein is a common practice in the biotechnology industry. We could not find an article that just examine the effects of salt on growht transformed BL۲۱. On the other hand, salt is a critical component of medium that can be made up in a medium optimization. Methods: Here, we separately investigated effect of K۲HPO۴, MgSO۴, (NH۴)۲SO۴ and NH۴CL on maximum growth of bacteria BL۲۱ after transforming BL۲۱ with PET-۳۲α that containing para thyroid hormones gene. Then, the salts were combined and added to the culture medium for optimization of their effects on high cell density using artificial neural network modelling (ANNs). Results: After ANN modeling, the obtained model showed that MgSO۴ has dominant on high cell density other than salts if final concentration of MgSO۴ is ۲۵mg/ml. The best concentration each of salt be lower ۳۰ mg/ml and critical total concentration of slats is ۱۲۰ mg/ml that inhibitory effect was seen after a critical concentration. Conclusions: In current study, ANN modeling shows that in prediction of effects of salts (i.e. K۲HPO۴, MgSO۴, (NH۴)۲SO۴ and NH۴CL) on cell density to reach high cell density, is effective and efficient.

کلمات کلیدی:
High cell density, Artificial neural networks, Culture medium, Optimization.

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1915333/