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Chae, B.

Publications and source records attributed to Chae, B..

2 recordsLinked to original sources

Automated, modular assembly of reconstituted cell-free systems from in vitro-produced components

High-performance cell-free protein synthesis has transformative potential for synthetic biology, yet the prohibitive costs of PURE kits and the labor intensity of in-house preparation have restricted accessibility and scalability. We developed i-POPFLEX (Purified components OPtimized for FLEXible protein expression), a modular cell-free protein synthesis system in which 34 translation factors, individually synthesized in vitro, are assembled using automated liquid handling. This workflow minimizes manual input and supports parallelized production, generating complete, ready-to-use systems within two days. i-POPFLEX achieves up to 5-fold higher protein yields and a 95 % cost reduction (20-fold lower cost) compared with commercial kits. Its flexible architecture also enables selective component inclusion for genetic code reprogramming and site-specific incorporation of non-canonical amino acids. By coupling modular design with automation, i-POPFLEX provides an accessible, customizable, and economically viable platform for next-generation biomanufacturing workflows. Technology readinessi-POPFLEX is a reconstituted cell-free system (CFS) composed of 34 translational components that are individually synthesized in vitro and assembled by automation. This system achieves up to 5-fold higher protein yields with a 95 % cost reduction (20-fold lower; <USD 0.06 {micro}L-1) compared with commercial PURE kits (USD 1.36 {micro}L-1) and reduces preparation time from four days to two. The workflow has been validated across diverse protein and peptide synthesis applications, including genetic code reprogramming and site-specific incorporation of non-canonical amino acids, and integrates seamlessly with benchtop automated liquid-handling platforms. These capabilities place i-POPFLEX at Technology Readiness Level (TRL) 4-5: integrated components validated in a laboratory setting and advancing toward pilot-scale readiness. For full-scale deployment, several key challenges remain. Matching crude lysate costs (USD 0.03 {micro}L-1) will require bulk reagent production, optimized procurement strategies, and specialized equipment for high-throughput component synthesis. Enabling milliliter- and liter-scale production will demand improvements in upstream synthesis, downstream purification, and quality control to ensure consistent performance at industrial throughput. Overcoming these barriers would enable production of thousands to millions of fully assembled i-POPFLEX systems for biofoundry-scale enzyme engineering, metabolic pathway prototyping, and large-scale variant screening, democratizing reconstituted CFS technology, and accelerating adoption in next-generation biomanufacturing pipelines.

synthetic biology↗

Resource-explicit interactions in spatial population models

Continuous-space population models can yield significantly different results from their panmictic counterparts when assessing evolutionary, ecological, or population-genetic processes. However, the computational burden of spatial models is typically much greater than that of panmictic models due to the overhead of determining which individuals interact with one another and how strongly they interact. Though these calculations are necessary to model local competition that regulates the population density, they can lead to prohibitively long runtimes. Here, we present a novel modeling method in which the resources available to a population are abstractly represented as an additional layer of the simulation. Instead of interacting directly with one another, individuals interact indirectly via this resource layer. We find that this method closely matches other spatial models, yet can dramatically increase the speed of the model, allowing the simulation of much larger populations. Additionally, models structured in this manner exhibit other desirable characteristics, including more realistic spatial dynamics near the edge of the simulated area, and an efficient route for modeling more complex heterogeneous landscapes.

ecology↗