Optimization of Medium Components Using Artificial Neural Networks
DOI:
https://doi.org/10.22100/ijhs.v3i1.182Keywords:
High cell density, Artificial neural networks, Culture medium, Optimization.Abstract
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 BL21. 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 K2HPO4, MgSO4, (NH4)2SO4 and NH4CL on maximum growth of bacteria BL21 after transforming BL21 with PET-32α 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 MgSO4 has dominant on high cell density other than salts if final concentration of MgSO4 is 25mg/ml. The best concentration each of salt be lower 30 mg/ml and critical total concentration of slats is 120 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. K2HPO4, MgSO4, (NH4)2SO4 and NH4CL) on cell density to reach high cell density, is effective and efficient.
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