Efficient and Precise Protein Synthesis in a Cell-Free System Using a Set of In Vitro Transcribed tRNAs with Nucleotide Modifications.

Reconstitution of a complicated system with a minimal set of components is essential for understanding the mechanisms of how the input is reflected in the output, which is fundamental for further engineering of the corresponding system. We have recently developed a reconstituted cell-free protein synthesis system equipped only with 21 in vitro transcribed tRNAs, one of the minimal systems for understanding the genetic code decoding mechanisms. Introduction of several nucleotide modifications to the transcribed tRNAs showed improvement of both protein synthesis efficiency and its fidelity, suggesting various combinations of tRNAs and their modifications can be evaluated in the developed system. In this chapter, we describe how to prepare this minimal system. Methods for preparing the transcribed tRNAs, their modifications, and the protein production using the set of prepared tRNAs are shown.

Reconstituted cell-free protein synthesis using in vitro transcribed tRNAs.

Entire reconstitution of tRNAs for active protein production in a cell-free system brings flexibility into the genetic code engineering. It can also contribute to the field of cell-free synthetic biology, which aims to construct self-replicable artificial cells. Herein, we developed a system equipped only with in vitro transcribed tRNA (iVTtRNA) based on a reconstituted cell-free protein synthesis (PURE) system. The developed system, consisting of 21 iVTtRNAs without nucleotide modifications, is able to synthesize active proteins according to the redesigned genetic code. Manipulation of iVTtRNA composition in the system enabled genetic code rewriting. Introduction of modified nucleotides into specific iVTtRNAs demonstrated to be effective for both protein yield and decoding fidelity, where the production yield of DHFR reached about 40% of the reaction with native tRNA at 30°C. The developed system will prove useful for studying decoding processes, and may be employed in genetic code and protein engineering applications.