(326c) A Rational Method to Improve Bioseparation Via Proteomics

Purification of target proteins for analytical and therapeutic applications requires the use of several chromatographic steps to achieve desired level of purity (e.g. 99.5 or 99.8%). This constitutes the major fraction of the total cost of its production. In this talk we will show how proteome information can be used to minimize the number of steps and to recover column capacity through rational modification of both the host cell and affinity tail systems. Our model system focuses on the use of Immobilized Metal affinity Chromatography (IMAC) in bioseparation. Although the method detailed here uses IMAC to purify hexahistidine-tagged proteins, this basic platform can be used with many other tags and affinity systems.

This presentation will provide a perspective on our past and ongoing work to improve chromatographic separation through the development and use of bacterial hosts that express minimum contaminant pool. To date, we have identified several proteins of Escherichia coli genome that interact with IMAC media and represent putative contaminants during IMAC capture steps by 2-D electrophoresis and MALDI-TOF mass spectroscopy. A threefold approach has been developed to incorporate this information into a rational bioseparation design strategy. (1) Mutation to essential proteins (eg. triosephosphate isomerase, TPI) is used to alter the nature of contaminating proteins that are deemed essential or very important. (2) Deletion or repression (eg. alpha-galactosidase) is used to suppress proteins not essential. (3) Rational affinity tail design is used to move the elution of the target protein to a region with less contaminants.

We will present results that indicate the model protein Green Fluorescent Protein (GFP) can be expressed by, and recovered from E. coli strains that are engineered to minimize the contaminant pool. Metabolic consequences of changes to the strain (eg. yield, acetate accumulation), expression level, and purification ease will be discussed. This study therefore represents the interplay between protein identification, mutation, and metabolism.