Statistical optimization for immobilized metal affinity purification of secreted human erythropoietin from Drosophila S2 cells.

We used a novel approach to affinity purify human erythropoietin (hEPO) following its secretion from Drosophila melanogaster S2 cells. Immobilized metal affinity purification of hEPO was optimized using a two-step serial statistical optimization strategy. After determining the elution conditions (based on preliminary batch-type purification experiments), the first optimization step considered three purification factors; resin, equilibrium, and washing. The results of this analysis showed that the resin amount was the major factor influencing yield and purity in both model equations and the washing factor lowered the confidence limits of the acquired model equations. The washing conditions were then set based on the results of the first step optimization and the second step then optimized three factors; resin, equilibrium, and elution. The yield and purity of hEPO were then compared following purification using three different approaches; batch-type purification based upon the conditions determined by serial statistical optimization, batch-type purification performed in preliminary experiments, and FPLC column chromatography-type purification. We found that the serial statistical optimization approach provided the best combination of yield and purity. These findings indicate that serial statistical optimization strategies can be successfully employed for immobilized metal affinity protein purification using either batch-type or column approaches.