JBEI Develops AI and Biosensor Strategies to Rapidly Accelerate Synthetic Jet Fuel Production

BERKELEY, CA — Researchers at the Joint BioEnergy Institute (JBEI), managed by Lawrence Berkeley National Laboratory, have unveiled two complementary strategies aimed at significantly accelerating the production of high-performance synthetic jet fuels from plant material. These innovative methods, centered on the crucial precursor molecule isoprenol, integrate artificial intelligence, laboratory automation, and biosensor technology to engineer microbes more efficiently, offering a promising alternative to traditional petroleum-based aviation fuels.

Background on Synthetic Jet Fuels

The core objective of this research is to create sustainable synthetic alternatives to petroleum-based aviation fuels. This involves engineering microbes to produce fuel compounds derived from plant materials. Historically, the development of such bioproducts has been a slow and arduous process, largely due to the inherent complexities of biological systems and the reliance on extensive trial-and-error methodologies. The new approaches specifically focus on enhancing the microbial production of isoprenol, an alcohol identified as a vital precursor to the next-generation jet fuel DMCO.

AI and Automation for Strain Optimization

One of the groundbreaking strategies, spearheaded by Taek Soon Lee and Héctor García Martín, harnesses the power of artificial intelligence (AI) and lab automation to engineer Pseudomonas putida strains for increased isoprenol production. This method employs an automated pipeline featuring robotics to simultaneously generate and test hundreds of genetic designs. Machine learning algorithms then analyze the experimental outcomes, providing recommendations for subsequent genetic modifications.

"This AI-driven approach is accelerating the development process by an estimated 10 to 100 times compared to conventional techniques."

Key aspects of this advanced AI-driven approach include:

• A custom microfluidic electroporation device, specifically designed for the efficient insertion of genetic material into microbial strains.
• The application of CRISPR interference (CRISPRi) to fine-tune gene activity, allowing for the precise testing of subtle genetic combinations rather than complete deactivation.
• Systematic optimization conducted across six engineering cycles, which ultimately led to an impressive five-fold increase in isoprenol production compared to the initial strain.

Biosensor for Novel Pathway Discovery

A second, equally impactful strategy, led by Thomas Eng, involved the development of a sophisticated biosensor designed to identify and select high-producing microbial strains. This approach capitalizes on Pseudomonas putida's natural ability to consume isoprenol, indicating an existing molecular sensing system within the microbe. Researchers successfully rewired this natural system into a biosensor that activates proportionally to the amount of fuel produced by the cell.

This innovative biosensor was then integrated with genes essential for cell survival, establishing a unique selection mechanism. This mechanism ensures that only microbes producing higher levels of the target fuel compound can thrive.

"This method facilitated the rapid screening of millions of microbial variants, leading to the identification of strains that produced up to 36 times more isoprenol than the original."

Furthermore, this research uncovered previously uncharacterized metabolic adaptations in high-producing strains, such as their ability to utilize amino acids for production even when glucose levels were low, opening new avenues for understanding microbial metabolism.

Complementary Approaches and Future Applications

The two developed methods offer distinct yet complementary advantages. The AI-driven pipeline excels at optimizing combinations of known gene targets, providing systematic improvements. Conversely, the biosensor method is particularly effective for the discovery of novel gene targets and metabolic pathways, uncovering entirely new biological mechanisms.

Both research teams are actively working towards scaling their respective methods for industrial fermentation systems, with the ultimate goal of producing synthetic aviation fuel at commercially viable levels. They are also adapting these powerful approaches for use with other microbes and target molecules, envisioning a broader application across various biomanufacturing processes.

"Researchers suggest that widespread adoption of these strategies could significantly reduce the time required for developing new bioproducts, potentially shortening timelines from a decade to less than a year."

The Joint BioEnergy Institute is a Bioenergy Research Center that receives vital funding from the Department of Energy Office of Science.