It’s still not easy to engineer cells. Implementing even simple functions today requires serious optimization and tuning. Even then, unintended interactions within the complex and poorly understood cell environment mean that things still typically don’t work as desired.
In contrast, engineers in other fields routinely design systems that work with incredible control: rockets that can reach Mars, cars that can drive themselves, and skyscrapers that stand hundreds of meters tall, to name a few.
How do we get to routine cell engineering that simply works?
The history of routinization in engineering practice tells us that we need a combination of theory, modeling, and empiricism to design and build complete integrated systems. We can design rockets because we understand how to modulate propulsion and aerodynamics. We can build self-driving cars because we can reliably integrate engines, steering, and brakes with microprocessors equipped with specialized machine learning algorithms. We can construct skyscrapers because we know how all the necessary structural materials fit together to support enormous external forces. Under the hood, cells are fundamentally composed of many different molecules working together, suggesting a need for integrated design that captures total molecular behavior.
In our newly published Nature Communications article, we seek to establish such an integrated approach for cell engineering, introducing a framework for designing and building simple cellular systems with molecular resolution. We develop a molecular physics-based computer aided design (CAD) tool and method for constructing CAD-specified ensembles of molecules. Together, these make it possible to design and build simple cellular systems from scratch. We show we can build engineered cellular systems that simply work on the first try, offering a “design-build-work” framework for routinely engineering increasingly complex cellular systems.
Leveraging a physics modeling framework to design cells from scratch
Designing synthetic cellular systems from scratch means specifying exactly how many of each molecule should be present in any given system – for example, the number of tRNA, ribosomes, or any protein. In our prior work, we developed a physics modeling framework that can be used to construct and simulate the physical motion and chemical reactivity of ensembles of molecules in E. coli ; we found that representing the physical dynamics of molecules at the so-called “colloidal scale” is critical to predicting how quickly proteins are produced. In our new work, we built a CAD tool "Colloidal Dynamics-CAD", or CD-CAD, around our colloidal physics model to design and simulate the behavior of molecule ensembles in engineered cellular systems. To do so, we extended our physics model to predict the behavior of cellular systems with specified relative amounts of tRNA, developed new computational methods to speed up predictions by 100,000-fold, and wrapped an evolutionary algorithm around the improved model to systematically discover optimal molecule compositions.
Design to reality: an experimental method for building cells from scratch
The gold standard for fully defined cellular systems is the ‘PURE’ system, a set of 108 different molecules capable of transcription and translation . While the types of molecules in PURE can be fully specified, their relative numbers cannot: for example, the abundance of each tRNA is constrained to mimic that of natural E. coli because PURE uses tRNA that are extracted together in bulk. To connect our CAD-designed systems to experimental implementation, we expanded PURE to include specified amounts of each tRNA. Specifically, we extended PURE to work with individually synthesized and purified tRNA  and established a process for assembling ensembles of tRNA as specified by CD-CAD. We call this experimental method “Tunable Implementation of Nucleic Acids”, or TINA. TINA-built PURE provides a foundation for fully defined CAD-engineered systems built from scratch.
Designing and building new types of cellular systems
One power of designing cells from scratch is that we can deviate from fundamental rules of natural cells. For example, in our previous work we designed ‘Fail-Safe’ genetic codes in which each amino acid is encoded by only a single tRNA, making so-encoded genes evolve more slowly in theory . In our new work, we computationally recoded the entire E. coli transcriptome into a Fail-Safe code, then used CD-CAD to design molecule abundances with specified protein synthesis rates, achieving cell systems with 5% faster to 50% slower predicted protein synthesis rates compared to wild type. We also engineered molecule abundances for faster and slower protein synthesis of a single model Fail-Safe encoded gene, then built those faster and slower systems using TINA. We found that our experiments qualitatively matched our designs. Even small changes to protein synthesis rate can be powerful: for example, a cell that produces proteins even 10% slower will be outcompeted by neighboring cells within a few generations, enabling control over the propagation and lifespan of engineered cells.
Design-build-work as a framework for routinizing synthetic cell engineering
Our designed systems worked the first time without any need to fit our model or optimize our experimental setup, a unique experience in cell engineering. Our experience suggests that a “design-build-work” framework is not only possible, but also a promising path forward for routinely designing increasingly complex systems. For example, while our current work demonstrates “design-build-work” for one cell function – protein synthesis – the approach of coupled CAD and from-scratch systems engineering is modular and scalable to other essential cell processes. CD-CAD and TINA together now enable routine engineering based on modular control of 21 of the 108 molecules in PURE. Given that only 473 types of molecules are needed for at least one minimal cell , we’re excited to imagine a near future in which we can routinely design and build complete cells from scratch.
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