Scientists unlock 36x bio-jet fuel yields with AI, microbial 'bad habit'

Scientists at the Joint BioEnergy Institute (JBEI) have developed two innovative methods that dramatically accelerate the engineering of microbes for bio-jet fuel production, cutting development times from years to weeks. One approach combines artificial intelligence (AI) with lab automation to rapidly design and test hundreds of genetic variants of Pseudomonas putida, achieving a five-fold increase in isoprenol production. The second method uses a genetic biosensor that exploits the microbe’s natural tendency to consume its own fuel product, enabling selection of strains with a 36-fold increase in fuel titers by linking fuel production to microbial survival. Together, these methods enable testing genetic designs 10 to 100 times faster than traditional manual techniques. The primary focus is on producing isoprenol, which can be converted into DMCO, a synthetic jet fuel with higher energy density than petroleum-based fuels, critical for aviation where battery energy density remains insufficient. The AI-driven approach uses robotics and machine learning to optimize gene combinations via