High-throughput characterization of an insect cell-free expression

Cell-free protein expression is a promising tool for improving protein-specific expression techniques. Despite their advantages, insect cell-free expression systems are not as well established as Escherichia coli cell-free systems. In most studies, characterization and optimization strategies are based on manual “one-factor-at-a-time” investigations that are expensive and time consuming. In this paper, two insect cell-free expression systems (Sf9 and High Five™) were reproducibly (CV = 2.9%) implemented on a robotic platform with integrated analytics. All experiments were planned by statistical design of experiments using central composite designs and analyzed by multivariate data analysis. Quadratic response surface models were fitted to the experimental data and model predictivity was validated successfully for both insect cell types. The characterization of the complete in vitro translation process included quantification and visualization of the parameter influences on the expression yield and the robustness of the systems. The results were compared to previous studies, which confirmed the applicability of the new method. In the future, yields from insect cell-free expression can be enhanced using a comprehensive system characterization based on optimally designed high-throughput screenings on robotic systems.