Optimization of a feed medium for fed-batch culture of insect cells using a genetic algorithm

Insect cells have been cultured for over 30 years, but their application is still hampered by low cell densities in batch fermentations and expensive culture media. With respect to the culture method, the fed-batch culture mode is often found to give the best yields. However, optimization of the feed composition is usually a laborious task. In this report, the successful use of genetic algorithms (GAs) to optimize the growth of insect cells is described. A feed was developed from 11 different medium components, each used at a wide range of concentrations. The feed was optimized within four sets of 20 experiments. The optimized feed was tested in bioreactors and the addition scheme was further improved. The viable-cell density of HzAm1 (Helicoverpa zea) insect cells improved 550% to 19.5 x 10(6) cells/mL compared to a control fermentation in an optimized commercial medium. No accumulation of waste products was found, and none of the amino acids was depleted. Glucose was depleted, which suggests that even further improvement is possible. We show that GAs are a successful method to optimize a complex fermentation in a relatively short time frame and without the need of detailed information concerning the cellular physiology or metabolism.