Engineering tRNA abundances for synthetic cellular systems.

Area of Science:

• Synthetic Biology
• Molecular Engineering
• Computational Biology

Background:

• Routinizing synthetic cell engineering necessitates precise control over molecular quantities.
• Current physics-based tools for predicting molecular abundances in whole-cell synthetic biology are lacking.

Purpose of the Study:

• To develop physics-based predictive tools for synthetic cell engineering.
• To investigate the impact of transfer RNA (tRNA) abundances on protein synthesis rates.
• To engineer synthetic translation systems with predictable speed variations based on tRNA levels.

Main Methods:

• Utilized a colloidal dynamics simulator to model tRNA abundance effects on protein synthesis.
• Employed rational design and direct RNA synthesis to create 21 synthetic tRNA surrogates.
• Applied evolutionary algorithms within a computer-aided design framework to engineer translation systems.

Main Results:

• Demonstrated qualitative agreement between predicted and experimentally observed synthetic system behaviors.
• Successfully engineered synthetic translation systems with tunable protein synthesis rates.
• Validated the impact of specific tRNA abundances on protein production.

Conclusions:

• First principles modeling combined with bottom-up experimentation advances synthetic biology design-build-test frameworks.
• Developed a computational approach to guide the engineering of synthetic cells with predictable molecular dynamics.
• This work provides a foundation for more robust and predictable synthetic cell construction.