Theoretical and experimental investigation of chaperone effects on soluble recombinant proteins in Escherichia coli: effect of free DnaK level on temperature-induced recombinant streptokinase production.

Modeling and analysis of genetic networks have become increasingly important in the investigation of cellular processes. The genetic networks involved in cellular stress response can have a critical effect on the productivity of recombinant proteins. In this work, it was found that the temperature-inducible expression system for the production of soluble recombinant streptokinase in Escherichia coli resulted in a lower productivity compared to the chemically-induced system. To investigate the effect of the induced cellular response due to temperature up-shift a model-based approach is adopted. The role played by the major molecular chaperone teams DnaK-DnaJ-GrpE and GroEL-GroES on the productivity of recombinant streptokinase was experimentally determined. Based on these investigations, a detailed mechanistic mathematical model was developed for the cellular response during the temperature-induced recombinant streptokinase production. The model simulations were found to have a good qualitative agreement with the experimental results. The mechanistic mathematical model was validated with the experiments conducted on a sigma(32) mutant strain. Detailed analysis of the parameter sensitivities of the model indicated that the level of free DnaK chaperone in the cell has the major effect on the productivity of recombinant streptokinase during temperature induction. Analysis of the model simulations also shows that down regulation or selective redirection of the heat shock proteins could be a better way of manipulating the cellular stress response than overexpression or deletion. In other words, manipulating the system properties resulting from the interaction of the components is better than manipulating the individual components. Although our results are specific to a recombinant protein (streptokinase) and the expression system (E. coli), we believe that such a systems-biological approach has several advantages over conventional experimental approaches and could be in principle extended to bigger genetic networks as well as other recombinant proteins and expression systems.