Probing metabolism in an E. coli-based cell-free system reveals a trade-off between transcription and translation

Abstract

Cell-free transcription-translation (TX-TL) systems have been used for diverse applications, from prototyping gene circuits to providing a platform for the development of synthetic life, but their performance is limited by issues such as batch-to-batch variability, poor predictability, and limited lifetime. These issues stem largely from the fact that cell lysate contains an active and complex metabolism whose effect on TX-TL has remained largely uncharacterized. Motivated by a minimal model of cell-free metabolism, this work explored the effects of energy molecules, which power TX-TL, and fuel molecules, which regenerate energy by harnessing core metabolism, on anE. coli-based TX-TL system. This work reports a compensatory interaction between TX-TL components Mg⁺² and 3-phosphoglyceric acid (3-PGA, used to regenerate ATP), where if one component’s concentration is increased, the other’s must likewise be increased to maintain optimal translation. Furthermore, maximum total mRNA and protein production occur in different and opposite concentration regimes of Mg⁺² and 3-PGA. To explore the observed phenomenon, transcription and translation were decoupled. Under translation inhibition, transcriptional output was uniform across Mg⁺² and 3-PGA concentrations, but in a translation-only system, maximum protein production occurred in the previously found optimal regime of Mg⁺² and 3-PGA, suggesting a TX-TL trade-off. Using alternative fuels to regenerate energy, this work found that the trade-off is universal across the different fuel sources, and that a system’s position along the trade-off is determined strongly by Mg⁺² and DNA concentrations. In systems where additional energy is supplied and where a fuel source is absent, the trade-off is absent, suggesting the trade-off arises from limitations in the regulation of translation and efficient energy regeneration. This work represents a significant advancement in understanding the effects of fuel and energy metabolism on TX-TL in cell-free systems and lays the foundation for improving TX-TL performance, lifetime, standardization, and prediction.