Abstract
A systematic approach was developed to identify and optimize the essential amino acids in defined minimal medium for the production of recombinant human interleukin-3 (rHuIL-3) by Streptomyces lividans. Starvation trials were carried out initially to narrow down the number of probable essential amino acids from an initial number of twenty to eight. Then a screening mixture experiment was designed and performed with the eight identified amino acids and distance-based multivariate analysis was employed to rank the probable essential amino acids regarding both growth and product formation. Following this procedure, the search was narrowed to four amino acids (Asp, Leu, Met, and Phe). Finally, a mixture design experiment known as the simplex lattice design was carried out and the composition of the optimum minimal medium was found using both statistical and neural network models.
Keywords
- Neural Network Model
- Essential Amino Acid
- Mixture Design
- Mixture Experiment
- Sequential Quadratic Programming Algorithm
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Nowruzi, K., Elkamel, A., Scharer, J.M., Moo-Young, M. (2009). A Computational Intelligent Based Approach for the Development of a Minimal Defined Medium: Application to Human Interleukin-3 Production by Streptomyces lividans 66 . In: do Carmo Nicoletti, M., Jain, L.C. (eds) Computational Intelligence Techniques for Bioprocess Modelling, Supervision and Control. Studies in Computational Intelligence, vol 218. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01888-6_8
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