Engineering tRNA abundances for synthetic cellular systems

• Published in: Nature communications 2023-07, Vol.14 (1), p.4594-11, Article 4594
• Main Authors: Maheshwari, Akshay J., Calles, Jonathan, Waterton, Sean K., Endy, Drew
• Format: Article
• Language: English
• Subjects: 38; 38/35; 631/553/2695; 631/553/552; 631/61/185; 82/80; Algorithms; Artificial Cells; Biology; CAD; Computer aided design; Evolutionary algorithms; First principles; Genetic Engineering; Humanities and Social Sciences; multidisciplinary; Physics; Protein biosynthesis; Protein synthesis; Proteins; Qualitative analysis; RNA, Transfer - genetics; Science; Science (multidisciplinary); Synthetic Biology; Transcription; Transfer RNA; tRNA
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-023-40199-9

Routinizing the engineering of synthetic cells requires specifying beforehand how many of each molecule are needed. Physics-based tools for estimating desired molecular abundances in whole-cell synthetic biology are missing. Here, we use a colloidal dynamics simulator to make predictions for how tRNA abundances impact protein synthesis rates. We use rational design and direct RNA synthesis to make 21 synthetic tRNA surrogates from scratch. We use evolutionary algorithms within a computer aided design framework to engineer translation systems predicted to work faster or slower depending on tRNA abundance differences. We build and test the so-specified synthetic systems and find qualitative agreement between expected and observed systems. First principles modeling combined with bottom-up experiments can help molecular-to-cellular scale synthetic biology realize design-build-work frameworks that transcend tinker-and-test. Mature fields of engineering use physics-based models to design systems that work reliably the first time. Here the authors show how a similar approach can be used to design and build a cellular-scale system, protein synthesis, from scratch.