Leveraging Active Learning to Establish Efficient In Vitro Transcription and Translation from Bacterial Chromosomal DNA.

Abstract

Gene expression is a fundamental aspect in the construction of a minimal synthetic cell, and the use of chromosomes will be crucial for the integration and regulation of complex modules. Expression from chromosomes in vitro transcription and translation (IVTT) systems presents limitations, as their large size and low concentration make them far less suitable for standard IVTT reactions. Here, we addressed these challenges by optimizing lysate-based IVTT systems at low template concentrations. We then applied an active learning tool to adapt IVTT to chromosomes as template DNA. Further insights into the dynamic data set led us to adjust the previous protocol for chromosome isolation and revealed unforeseen trends pointing at limiting transcription kinetics in our system. The resulting IVTT conditions allowed a high template DNA efficiency for the chromosomes. In conclusion, our system shows a protein-to-chromosome ratio that moves closer to in vivo biology and represents an advancement toward chromosome-based synthetic cells.