refinement-onepot-pure-crude-ribosome-production-for-reproducible

Refinement of OnePot PURE and Crude Ribosome Production for Reproducible Cell-free Protein Synthesis

Recent advances have enabled the Protein synthesis Using Recombinant Elements (PURE) cell-free system to be produced in individual laboratories ...

University of Edinburgh

Cell-free systems offer a promising approach to engineer biology since their open nature allows for well-controlled and characterized reaction conditions. In this review, we discuss the history and recent developments in engineering recombinant and crude extract systems, as well as breakthroughs in enabling technologies, that have facilitated increased throughput, compartmentalization, and spatial control of cell-free protein synthesis reactions. Combined with a deeper understanding of the cell-free systems themselves, these advances improve our ability to address a range of scientific questions. By mastering control of the cell-free platform, we will be in a position to construct increasingly complex biomolecular systems, and approach natural biological complexity in a bottom-up manner.

Bottom-Up Construction of Complex Biomolecular Systems With Cell-Free Synthetic Biology.

Cell-free gene expression systems present an alternative approach to synthetic biology, where biological gene expression is harnessed inside non-living,  biochemical reactions. Taking advantage of a plethora of recent experimental innovations, they easily overcome certain challenges for computer-aided biological design. For instance, their open nature renders all their components directly accessible, greatly facilitating model construction and validation. At the same time, these systems present their own unique difficulties, such as limited reaction lifetimes and lack of homeostasis. In this Perspective, I propose that cell-free systems are an ideal proving ground to test rational biodesign strategies, as demonstrated by a small but growing number of examples of model-guided, forward engineered cell-free biosystems. It is likely that advances gained from this approach will contribute to our efforts to more reliably and systematically engineer both cell-free as well as living cellular systems for useful applications.

Cell-Free Systems: A Proving Ground for Rational Biodesign.

Self-regeneration is a fundamental function of all living systems. Here we demonstrate partial molecular self-regeneration in a synthetic cell. By implementing a minimal transcription-translation system within microfluidic reactors, the system is able to regenerate essential protein components from DNA templates and sustain synthesis activity for over a day. By quantitating genotype-phenotype relationships combined with computational modeling we find that minimizing resource competition and optimizing resource allocation are both critically important for achieving robust system function. With this understanding, we achieve simultaneous regeneration of multiple proteins by determining the required DNA ratios necessary for sustained self-regeneration. This work introduces a conceptual and experimental framework for the development of a self-replicating synthetic cell.

A partially self-regenerating synthetic cell.

Cell-free synthetic biology offers an approach to building and testing gene circuits in a simplified environment free from the complexity of a living cell. Recent advances in microfluidic devices allowed cell-free reactions to run under nonequilibrium, steady-state conditions enabling the implementation of dynamic gene regulatory circuits in vitro. In this chapter, we present a detailed protocol to fabricate a microfluidic chemostat device which enables such an operation, detailing essential steps in photolithography, soft lithography, and hardware setup.

Steady-State Cell-Free Gene Expression with Microfluidic Chemostats.

We present a new method for the surface capture of proteins in cell-free protein synthesis (CFPS). We demonstrate the spontaneous self-assembly of the protein BslA into functionalizable surfaces on the surface of a CFPS reaction chamber. We show that proteins can be covalently captured by such surfaces, using "Catcher/Tag" technology. Importantly, proteins of interest can be captured either when synthesised  by CFPS above the BslA surfaces, or when added as pure protein. The simplicity and cost efficiency of this method suggest that it will find many applications in cell-free-based methods.

Self-Assembling Protein Surfaces for  Capture of Cell-Free-Synthesized Proteins.

In protein design, the ultimate test of success is that the designs function as desired. Here, we discuss the utility of cell free protein synthesis (CFPS) as a rapid, convenient and versatile method to screen for activity. We champion the use of CFPS in screening potential designs. Compared to in vivo protein screening, a wider range of different activities can be evaluated using CFPS, and the scale on which it can easily be used-screening tens to hundreds of designed proteins-is ideally suited to current needs. Protein design using physics-based strategies tended to have a relatively low success rate, compared with current machine-learning based methods. Screening steps (such as yeast display) were often used to identify proteins that displayed the desired activity from many designs that were highly ranked computationally. We also describe how CFPS is well-suited to identify the reasons designs fail, which may include problems with transcription, translation, and solubility, in addition to not achieving the desired structure and function.

Applications of cell free protein synthesis in protein design.

Neural networks enable the processing of large, complex data sets with applications in disease diagnosis, cell profiling, and drug discovery. Beyond electronic computers, neural networks have been implemented using programmable biomolecules such as DNA; this confers unique advantages, such as greater portability, electricity-free operation, and direct analysis of patterns of biomolecules in solution. Analogous to bottlenecks in electronic computers, the computing power of DNA-based neural networks is limited by the ability to add more computing units, i.e., neurons. This limitation exists because current architectures require many nucleic acids to model a single neuron. Each additional neuron compounds existing problems such as long assembly times, high background signal, and cross-talk between components. Here, we test three strategies to solve this limitation and improve the scalability of DNA-based neural networks: (i) enzymatic synthesis for high-purity neurons, (ii) spatial patterning of neuron clusters based on their network position, and (iii) encoding neuron connectivity on a universal single-stranded DNA backbone. We show that neurons implemented via these strategies activate quickly, with a high signal-to-background ratio and process-weighted inputs. We rewired our modular neurons to demonstrate basic neural network motifs such as cascading, fan-in, and fan-out circuits. Finally, we designed a prototype two-layer microfluidic device to automate the operation of our circuits. We envision that our proposed design will help scale DNA-based neural networks due to its modularity, simplicity of synthesis, and compatibility with various neural network architectures. This will enable portable computing power for applications in portable diagnostics, compact data storage, and autonomous decision making for lab-on-a-chips.

Rewireable Building Blocks for Enzyme-Powered DNA Computing Networks.

The "Protein synthesis Using Recombinant Elements" ("PURE") system is a minimal biochemical system capable of carrying out cell-free protein synthesis using defined enzymatic components. This study extends PURE by integrating an ATP regeneration system based on pyruvate oxidase, acetate kinase, and catalase. The new pathway generates acetyl phosphate from pyruvate, phosphate, and oxygen, which is used to rephosphorylate ATP . Successful ATP regeneration requires a high initial concentration of ∼10 mM phosphate buffer, which surprisingly does not affect the protein synthesis activity of PURE. The pathway can function independently or in combination with the existing creatine-based system in PURE; the combined system produces up to 233 μg/mL of mCherry, an enhancement of 78% compared to using the creatine system alone. The results are reproducible across multiple batches of homemade PURE and importantly also generalize to commercial systems such as PURExpress from New England Biolabs. These results demonstrate a rational bottom-up approach to engineering PURE, paving the way for applications in cell-free synthetic biology and synthetic cell construction.

ATP Regeneration from Pyruvate in the PURE System.

Machine learning (ML) tools have revolutionized protein structure prediction, engineering, and design, but the best ML tool is only as good as the training data it learns from. To obtain high-quality structural or functional data, protein purification is typically required, which is both time and resource consuming, especially at the scale required to train ML tools. Here, we showcase cell-free protein synthesis as a straightforward and fast tool for screening and scoring the activity of protein variants in ML workflows. We demonstrate the utility of the system by improving the kinetic qualities of a protease. By rapidly screening just 48 random variants to initially sample the fitness landscape, followed by 32 more targeted variants, we identified several protease variants with improved kinetic properties.

Article	Year
Bottom-Up Construction of Complex Biomolecular Systems With Cell-Free Synthetic Biology. Frontiers in bioengineering and biotechnology\| PubMed ID: 32266240	2020
Cell-Free Systems: A Proving Ground for Rational Biodesign. Frontiers in bioengineering and biotechnology\| PubMed ID: 32793570	2020
A partially self-regenerating synthetic cell. Nature communications\| PubMed ID: 33311509	2020
Steady-State Cell-Free Gene Expression with Microfluidic Chemostats. Methods in molecular biology (Clifton, N.J.)\| PubMed ID: 33405223	2021
Self-Assembling Protein Surfaces for Capture of Cell-Free-Synthesized Proteins. Frontiers in bioengineering and biotechnology\| PubMed ID: 35875503	2022
Applications of cell free protein synthesis in protein design. Protein science : a publication of the Protein Society\| PubMed ID: 39180484	2024
Rewireable Building Blocks for Enzyme-Powered DNA Computing Networks. Journal of the American Chemical Society\| PubMed ID: 39255470	2024
ATP Regeneration from Pyruvate in the PURE System. ACS synthetic biology\| PubMed ID: 39754602	2025
Cell-Free Protein Synthesis as a Method to Rapidly Screen Machine Learning-Generated Protease Variants. ACS synthetic biology\| PubMed ID: 40304425	2025

Nadanai Laohakunakorn

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