Just because a technology has a long history doesn’t mean it can’t be at the cutting edge. Consider cell-free protein synthesis. This technology appeared over 60 years ago, back when a pair of researchers at the National Institutes of Health showed that crude cell extracts could serve as in vitro life simulation systems.¹ These systems promise a range of advantages over cell-based expression systems, not the least of which is biosafety, given that cell-free systems avoid the replication and transmission risks associated with genetically engineered cells. Also, cell-free systems are free of the metabolic and operational overhead of keeping cells alive and productive.

These potential advantages, and others, came closer to being realized relatively recently, about 20 years ago, when a research team at the University of Tokyo introduced a defined system cell-based expression system, namely, the protein synthesis using recombinant elements (PURE) system.² Unlike systems based on crude extracts or lysates, the PURE system incorporates known components, all in known quantities.

One of the originators of PURE, Takuya Ueda, a researcher who is currently affiliated not only with the University of Tokyo, but also with Waseda University, will describe more than two decades’ worth of improvements to the PURE system when he speaks at SynBioBeta: The  Global Synthetic Biology Conference, which will be held May 5–8 in San Jose, CA. The conference will also include a developer of PURE systems, GeneFrontier, in its program. The company’s COO, Takashi Ebihara, will deliver a talk entitled “Beyond Cell, Beyond Life: Cell-Free Systems as the Architects of Synthetic Biology Advancement.”

Merits of Lysate-Based and Defined Systems

These presentations will no doubt provide an opportunity to consider the advantages of the PURE system over crude extract-based systems. Several such advantages have already been highlighted by researchers affiliated with Tsinghua University and Shenyang Normal University. In a recent review article,³ they offered the following: “First, the composition of the PURE system is precise. It generally includes 36 purified proteins, tRNAs, ribosome, and necessary factors. There is no polluting protease in the PURE system, which makes the PURE system stable and deterministic. Second, the composition of each element in the PURE system can be adjusted according to different experimental needs to achieve the maximum protein expression, making the PURE system flexible. Third, genetic code expansion or reprogramming is easier to be explored, and the manipulation of the translational machinery is easy in the PURE system.”

None of this should be taken to suggest that extract-based systems don’t also have a role to play in synthetic biology. Both extract-based systems and PURE systems are being commercialized. For example, systems of both types are available from New England Biolabs, which provides the NEBExpress Cell-free E. coli Protein Synthesis System and the PURExpress In Vitro Protein Synthesis Kit. The company indicates that each of the platforms is suitable for a range of applications, and that there are instances in which one or the other may be more suitable. For example, the NEBExpress option may scale up more easily and be preferred in certain labeling applications, such as those involving His-tagged proteins. And the PURExpress option may excel in fluorescent labeling and radiolabeling studies; in translational machinery, chaperone, and protein-folding studies; and in applications involving directed protein evolution.

Abstraction and Optimization

Both lysate-based approaches and defined approaches to cell-free technology are compatible with the general engineering approaches that underlie synthetic biology, approaches such as abstraction and optimization. Abstraction involves understanding complex systems as combinations of simpler systems that may interact with one another. 

Essentially, abstraction is modularization, which may allow the retention of some modules and the elimination of others, or even permit module combinations not seen in nature. Optimization may involve improving the interactions among modules or improving the performance of individual modules.

Since lysate-based systems and defined systems are both in vivo alternatives to cell-based systems, they can “abstract away” unnecessary life-support functions. They can also facilitate the addition of modules to improve familiar functions, such as protein folding, or introduce new functions, such as the incorporation of non-natural amino acids.

To advance the optimization of lysate-based systems and defined systems, scientists are exploring how artificial intelligence (AI) can be used to reduce batch-to-batch variability in lysate-based systems. For example, scientists affiliated with Université Paris-Saclay and the University of Manchester have used AI to determine how the concentrations of ribosomes, tRNAs, cofactors, enzymes, and other cell-derived components can be regulated to advantage.⁴

Using an active learning approach, the scientists explored a combinatorial space of about 4 million cell-free buffer compositions and reported that they achieved a 34-fold increase in protein production and identified critical parameters involved in cell-free productivity.

AI applications in cell-free protein synthesis are also being pursued by contract research organizations. One such organization, Asymchem Laboratories, asserts that it has established an “efficient cell-free synthesis and screening system for drug target membrane proteins, antibody proteins, cytokines, and toxic proteins.” The organization, which adds that its capabilities now encompass the rapid development of pharmaceutical-related proteins, will deliver a presentation at the upcoming SynBioBeta conference. The topic: integrating machine learning with cell-free protein synthesis to accelerate enzyme evolution.

Promising Applications and Recent Announcements

Several review articles have summarized the applications that are being enabled with cell-free technology. For example, a review in Nature Review Genetics has cited “new approaches to the model-driven design of synthetic gene networks, the fast and portable sensing of compounds, on-demand biomanufacturing, building cells from the bottom up, and next-generation educational kits.”⁵

Platform providers are also projecting exciting applications. For example, GeneFrontier asserts that its PUREfrex kit can be used to synthesize antibodies (IgG, Fab, scFv), membrane proteins, glycoproteins, enzymes, and toxic proteins. “In addition,” the company continues, “PUREfrex can be used for various purposes such as display techniques such as mRNA display and ribosome display, introduction of unnatural amino acids, and translation mechanism research. PUREfrex is suitable for small-scale, high-throughput synthesis of a wide variety of proteins, and is also ideal for protein function evaluation platform for machine learning.”

In recent months, there has been conspicuous progress in biosensor applications. For example, a study from the Wyss Institute described how a cell-free system and an optimized genetic code expansion chemistry were used to expedite the discovery and evolution of nanosensors containing fluorogenic amino acids.⁶

“We have long worked on expanding the genetic code of cells to endow them with new capabilities to enable research, biotechnology, and medicine in different areas,” said Wyss Core Faculty member George Church, who led the study. “This novel synthetic biology platform solves many of the obstacles that stood in the way of upgrading proteins with new chemistries, as exemplified by more capable instant biosensors, and is poised to impact many biomedical areas.”

The Wyss team expects the platform to speed the design of low-cost fluorescent biosensors for real-time disease monitoring. “We can also incorporate synthetic amino acids with many other functionalities into all kinds of proteins to create new therapeutics, and a much broader range of research tools,” noted the study’s lead author, Erkin Kuru, a protein engineer at Wyss.

A recent study from Northwestern University that appeared in Nature Chemical Biology described how a cell-free system incorporated genetic circuits to expand the capabilities of an existing sensing platform, ROSALIND (named after famous chemist Rosalind Franklin and short for “RNA output sensors activated by ligand induction).⁷ The new circuitry essentially gave the platform a volume knob to “turn up” weak signals. When used to test water samples, the upgraded ROSALIND platform outperformed the previous version, detecting contaminants with 10-fold greater sensitivity.

“Biosensors repurposed from nature can, in principle, detect a whole spectrum of contaminants and human health markers, though they’re often not sensitive enough as is,” said the study’s corresponding author, Julius Lucks. “By adding genetic circuitry that acts like an amplifier, we can make this biosensing platform meet sensitivity levels needed for application in environmental and human health monitoring.”

Finally, according to an article in ACS Synthetic Biology, researchers at Ehime University, giant unilamellar vesicles were used to encapsulate a wheat germ extract and a riboswitch (a DNA template encoding an analyte-responsive regulatory RNA), resulting in an artificial-cell-based biosensor.⁸ “[We] utilized this method to successfully create three types of artificial cells, each of which responded to a specific, membrane-permeable analyte with wide-range, analyte-dose dependency and high sensitivity at ambient temperature,” the article’s authors wrote. “Finally, due to their orthogonality and robustness, we were able to mix a cocktail of these artificial cells to achieve simultaneous detection of the three analytes without significant barriers.”

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References

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3. Cui Y, Chen X, Wang Z, Lu Y. Cell-free pure system: Evolution and achievements. Biodes. Res. 2022; 9847014.
4. Borkowski O, Koch M, Zettor A, Pandi A, Batista AC, Soudier P, Faulon J-L. Large-scale active-learning-guided exploration for in vitro protein production optimization. Nat. Commun. 2020; 11: 1–8.
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6. Kuru E, Rittichier J, de Puig H, Flores A, Rout S, et al. Rapid discovery and evolution of nanosensors containing fluorogenic amino acids. Nat. Commun. 2024; 15(1): 7531.
7. Li Y, Lucci T, Dujovne MV, Jung JK, Capdevila DA, Lucks JB. A cell-free biosensor signal amplification circuit with polymerase strand recycling. Nat. Chem. Biol. 2025: Jan 13.
8. Takahashi H, Ikemoto Y, Ogawa A. Simultaneous Detection of Multiple Analytes at Ambient Temperature Using Eukaryotic Artificial Cells with Modular and Robust Synthetic Riboswitches. ACS Synth. Biol. 2024; 14(3): 771–780.