A detailed metabolic network of more than 280 biochemical reactions and transport processes for 137 metabolites distributed among three compartments (cytoplasm, mitochondrion and peroxisome) was developed for Aspergillus niger. A unique aspect of the metabolic network was that it included carbohydrates and amino acids in both degradative and biosynthetic reactions. The general applicability of the methodology was evaluated by establishing commonality to optimize recombinant HEWL production. Experimental results indicated that HEWL production was growth associated. Linear programming was used for the optimization of the specific growth rates in combination with 37 measured input and output fluxes of the key metabolites to evaluate corresponding intracellular flux distributions throughout the batch fermentations. The importance of the implemented experimental results as constraints was proved to be necessary for having realistic results. Logarithmic sensitivity analysis and the experimental observations revealed that the addition of proline, alanine, glutamate, and tyrosine benefited growth in the defined media. In a series of preliminary nutritional experiments with extra amount of the identified amino acids contribution to growth enhancement was found to be 46% for proline, 23% for glutamate, and 22% for tyrosine. The addition of four amino acids (proline, glutamate, alanine, and tyrosine) in batch and fed-batch fermentations in a 7 liter bioreactor resulted in a 44% improvement in biomass and 41% improvement in recombinant protein production. The experiments also confirmed the model prediction that extra amount of amino acids besides the identified ones would not significantly enhance biomass and the recombinant protein production. These observations revealed that when the important organic nitrogen sources were supplied in excess, the higher concentration of glucose had a positive significant effect both in biomass and recombinant protein production. The experimental observations and simulation results presented could be used for some genetic manipulation processes

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