Point-of-Care Analyte Quantification and Digital Readout via Lysate-Based Cell-Free Biosensors Interfaced with Personal Glucose Monitors

Optimizing Protein Production in the One-Pot PURE System: Insights into Reaction Composition and Expression Efficiency

The One-Pot PURE (Protein synthesis Using Recombinant Elements) system simplifies the preparation of traditional PURE systems by coculturing and purifying 36 essential proteins for gene expression in a single step, enhancing accessibility and affordability for widespread laboratory adoption and customization. However, replicating this protocol to match the productivity of traditional PURE systems can take considerable time and effort due to uncharacterized variability. In this work, we observed unstable PURE protein expression in the original One-Pot PURE strains, E. coli M15/pREP4 and BL21(DE3), and addressed this issue using glucose-mediated catabolite repression to minimize burdensome background expression. We also identified several limitations making the M15/pREP4 strain unsuitable for PURE protein expression, including coculture incompatibility with BL21(DE3) and uncharacterized proteolytic activity. We showed that consolidating all expression vectors into a protease-deficient BL21(DE3) strain minimized proteolysis, led to more uniform coculture cell growth at the time of induction, and improved the stoichiometry of critical translation initiation factors in the final PURE mixture for efficient cell-free protein production. In addition to optimizing the One-Pot PURE protein composition, we found that variations in commercial energy solution formulations could compensate for suboptimal PURE protein stoichiometry. Notably, altering the source of E. coli tRNAs in the energy solution alone led to significant differences in the expression capacity of cell-free reactions, highlighting the importance of tRNA codon usage in influencing protein expression yield. Taken together, this work systematically investigates the proteome and biochemical factors influencing the One-Pot PURE system productivity, offering insights to enhance its robustness and adaptability across laboratories.

Metabolic Perturbations to an Escherichia coli-based Cell-Free System Reveal a Trade-off between Transcription and Translation

Cell-free transcription-translation (TX-TL) systems have been used for diverse applications, but their performance and scope are limited by variability and poor predictability. To understand the drivers of this variability, we explored the effects of metabolic perturbations to anEscherichia coli (E. coli) Rosetta2 TX-TL system. We targeted three classes of molecules: energy molecules, in the form of nucleotide triphosphates (NTPs); central carbon "fuel" molecules, which regenerate NTPs; and magnesium ions (Mg2+). Using malachite green mRNA aptamer (MG aptamer) and destabilized enhanced green fluorescent protein (deGFP) as transcriptional and translational readouts, respectively, we report the presence of a trade-off between optimizing total protein yield and optimizing total mRNA yield, as measured by integrating the area under the curve for mRNA time-course dynamics. We found that a system's position along the trade-off curve is strongly determined by Mg2+ concentration, fuel type and concentration, and cell lysate preparation and that variability can be reduced by modulating these components. Our results further suggest that the trade-off arises from limitations in translation regulation and inefficient energy regeneration. This work advances our understanding of the effects of fuel and energy metabolism on TX-TL in cell-free systems and lays a foundation for improving TX-TL performance, lifetime, standardization, and prediction.

Rapid and Finely-Tuned Expression for Deployable Sensing Applications

Organisms from across the tree of life have evolved highly efficient mechanisms for sensing molecules of interest using biomolecular machinery that can in turn be quite valuable for the development of biosensors. However, purification of such machinery for use in in vitro biosensors is costly, while the use of whole cells as in vivo biosensors often leads to long sensor response times and unacceptable sensitivity to the chemical makeup of the sample. Cell-free expression systems overcome these weaknesses by removing the requirements associated with maintaining living sensor cells, allowing for increased function in toxic environments and rapid sensor readout at a production cost that is often more reasonable than purification. Here, we focus on the challenge of implementing cell-free protein expression systems that meet the stringent criteria required for them to serve as the basis for field-deployable biosensors. Fine-tuning expression to meet these requirements can be achieved through careful selection of the sensing and output elements, as well as through optimization of reaction conditions via tuning of DNA/RNA concentrations, lysate preparation methods, and buffer conditions. Through careful sensor engineering, cell-free systems can continue to be successfully used for the production of tightly regulated, rapidly expressing genetic circuits for biosensors.

Low-cost, point-of-care biomarker quantification

Low-cost, point-of-care (POC) devices that allow fast, on-site disease diagnosis could have a major global health impact, particularly if they can provide quantitative measurement of molecules indicative of a diseased state (biomarkers). Accurate quantification of biomarkers in patient samples is already challenging when research-grade, sophisticated equipment is available; it is even more difficult when constrained to simple, cost-effective POC platforms. Here, we summarize the main challenges to accurate, low-cost POC biomarker quantification. We also review recent efforts to develop and implement POC tools beyond qualitative readouts, and we conclude by identifying important future research directions.

Advances, Challenges and Future Trends of Cell-Free Transcription-Translation Biosensors

In recent years, the application of cell-free protein synthesis systems in biosensing has been developing rapidly. Cell-free synthetic biology, with its advantages of high biosafety, fast material transport, and high sensitivity, has overcome many defects of cell-based biosensors and provided an abiotic substitute for biosensors. In addition, the application of freeze-drying technology has improved the stability of such systems, making it possible to realize point-of-care application of field detection and broadening the application prospects of cell-free biosensors. However, despite these advancements, challenges such as the risk of sample interference due to the lack of physical barriers, maintenance of activity during storage, and poor robustness still need to be addressed before the full potential of cell-free biosensors can be realized on a larger scale. In this review, current strategies and research results for improving the performance of cell-free biosensors are summarized, including a comprehensive discussion of the existing challenges, future trends, and potential investments needed for improvement.