On the 14th, senior researcher Lee Seung-gu and the research team at the Korea Research Institute of Bioscience and Biotechnology (KRIBB) National Biofoundry Program Office said they succeeded in building and demonstrating an automated experimental system that can convert methane into eco-friendly bio-based materials.
A biofoundry repeats a cycle of design, build, test, and learn to collect data and analyzes it with artificial intelligence (AI) to propose better experimental methods and gene designs. Because it can quickly and easily gather large volumes of biological data, it enables efficient development of bio-based products such as new materials, pharmaceuticals, and eco-friendly chemicals.
The research team believed that methane, a representative greenhouse gas whose concentration in the atmosphere is rapidly increasing, could be turned into a useful resource using the biofoundry. Methane causes a greenhouse effect more than 84 times stronger than carbon dioxide, but natural sinks that can reduce it are very limited.
In this study, the research team built a scalable semi-automated experimental system. Like assembling Lego blocks, experimental steps can be flexibly combined, allowing rapid execution of large-scale experiments numbering in the thousands or more. By introducing automated equipment, they achieved up to 36 times faster experimental speed from sample preparation to gene assembly and microbial introduction.
Based on this approach, they improved isoprene-synthesizing enzymes used across industries such as tires, adhesives, and fuel additives. When the improved enzymes were applied to methane-eating microorganisms, productivity in converting methane, a greenhouse gas, into isoprene increased significantly. Conventional isoprene-synthesizing enzymes were difficult to commercialize due to poor expression or low activity, but data-driven automated design increased enzymatic reaction efficiency by up to 4.5 times and improved thermal stability.
Senior researcher Lee Seung-gu said, "The significance of this study is great in that we presented a scalable workflow that integrates computational design, automated experiments, and large-scale data analysis into one," and added, "High-quality data accumulated through this system will make AI-based design more precise and accelerate the era of digital biomanufacturing."
The research was carried out through a joint study with the Agile BioFoundry, a public biofoundry under the U.S. Department of Energy (DOE) with world-class automation and data analysis capabilities. The results were published on Sep. 13 in the international journal "Trends in Biotechnology."
References
Trends in Biotechnology (2025), DOI: https://doi.org/10.1016/j.tibtech.2025.08.007