SEED 2024
Upscaling Engineering of Synthetic Biomachines via Synthetic Cells
Richard M. Murray
California Institute of Technology
| Anton Jackson-Smith Zoila Jurado Zachary Martinez | b.next Build-A-Cell | |
| Ayush Pandey William Poole Yan Zhang | Imperial College London |
The goal of this project is to demonstrate a model for biological systems engineering that can serve as a starting point for a larger effort in systems engineering of biological systems. We are focused on proof-of-concept demonstrations in synthetic cells, a class of non-living biological machines, constructed from biological components such as lipids, amino acids, proteins, and DNA. Synthetic cells do not mutate or evolve, allowing more systematic and repeatable engineering, and also providing significant advantages in environments where it may not be desirable to deploy genetically engineered organisms. A major element of our work is the development of open source tools that help “routinize” the creation of synthetic cells. We anticipate that the methods we develop can also serve as a testbed for engineering methods in living organisms.
Links to additional resources
- BioCRNpyler - Biomolecular chemical reaction network compiler
- BioSCRAPE - Biological stochastic simulation of single cell reactions and parameter estimation
- Build-A-Cell - An open source, synthetic cell community
- Nucleus - Open source package for synthetic cell builders
- TRILL - Sandbox for creative protein engineering and discovery
- Vivarium - Simulation engine for composing and executing integrative multi-scale models
Papers and preprints
- Z. Jurado, A. Pandey, and R. M. Murray, A chemical reaction network model of PURE, bioRxiv, 2023.
- Z. A. Martinez, R. M. Murray, and M. Thomson, TRILL: Orchestrating Modular Deep-Learning Workflows for Democratized, Scalable Protein Analysis and Engineering, bioRxiv, 2023.
- W. Poole, A. Pandey, A. Shur, Z. A. Tuza, and R. M. Murray, BioCRNpyler: Compiling chemical reaction networks from biomolecular parts in diverse contexts, bioRxiv, 2022.
- Y. Zhang, Y. Qiu, M. Deveikis, Z. A. Martinez, T.-F. Chou, P. S. Freemont, and R. M. Murray, Optimizing protein expression in the One-Pot PURE System: Insights into reaction composition and translation efficiency, bioRxiv, 2024.
