Separation of recombinant human protein C from transgenic animal milk using immobilized metal affinity chromatography

Abstract

Protein C is an important serine protease due to its ability to proteolytically cleave activated Factors V and VIII. Excess coagulation and blood agglutination can lead to plugged capillaries, thereby reducing oxygen transport to interstitial tissues. To treat patients with hereditary and acquired protein C deficiency would require a greater amount of Protein C than that available from human plasma. However, the potential demand for this protein could be met by the production of human protein C from transgenic animal mammary glands. Thus, research into inexpensive, efficient methods to purify proteins from transgenic animal milk will be a critical area of study for the large scale production of protein C. Immobilized metal affinity chromatography (IMAC) is a novel method for the purification of protein C. A proposed method of purification is to take advantage of protein C's strong metal ion binding characteristics with IMAC to assist in the separation from transgenic animal milk. The separation procedure is benchmarked against current systems in use by the American Red Cross for purification of Protein C from transgenic porcine milk. Common problems in developing separation schemes for new therapeutics are the initial availability of the product (protein), and time-to-market concerns. Extensive experimental tests for scaleable purification schemes are often cost and time prohibitive. In order to optimize an IMAC protocol with minimal waste of time and resources, total quality management tools have been adopted. Initial experiments were designed to choose buffer conditions, eluents, immobilized valence metals, and flow rates using Taguchi experimental design, which is a total quality management (TQM) tool. One of the values of Taguchi methods lies in the use of Latin orthogonal sets. Through the use of the orthogonal sets, the total number of experiments may be reduced, shortening the focus time on optimal conditions.