Locked away inside the walls of plant cells lies a valuable source of energy: sugar. But to access that sugar - which could provide a domestic source of bioenergy that strengthens U.S. energy security - researchers must first break down cellulose, the structural component of plant cell walls.
A team at Lawrence Livermore National Laboratory (LLNL) has designed two high-throughput screening systems to test hundreds of enzymes for their ability to break down cellulose in various forms of agricultural byproducts and plant waste. The result could be used to identify the most efficient enzymes for different materials, transforming biomass into biofuel.
"For each biomass type, our platforms identify where the highest sugar yield lies, which enzyme system unlocks it most efficiently, and what energy inputs are required," said LLNL scientist Sankar Raju Narayanasamy. "This compresses what has historically been a months-long development cycle into a scalable, data-driven workflow."
Previously, Narayanasamy and colleagues developed a technique to watch and map how a single enzyme breaks down cellulose in real time at the microscale. They identified the areas where biomass is most amenable to sugar extraction, revealing conditions that can maximize yield and help match enzymes to materials.
By extending the method to simultaneously screen 80 samples using LLNL's SPOC platform and a newly established AutoMine Ultra-High Throughput Screening System, the team is capable of examining 5000 combinations of enzymes and biomass types per week.
"By utilizing picodroplet technology as discrete reaction vessels, the systems enable the rapid evaluation of millions of variants, including diverse microbial strains, engineered enzymes and novel catalysts, specifically identifying those with superior performance in converting biomass into target products," said Narayanasamy.
Such scale-up is critical, as each form of biomass, from corn stover to wheat straw to wood and beyond, has a different cell structure and chemistry. An enzyme that breaks down cellulose in one material may not work at all for another.
The scientists plan to process the large volume of data using LLNL's high-performance computing (HPC) resources.
"Traditional methods are bulk analysis, so they don't precisely tell when and where we get the maximum yield of sugar," said Narayanasamy. "This is where we come in, by combining high-resolution, spatial, temporal and chemical mapping and scaling that with the automation and HPC."
So far, the researchers have tested their screening methods with agricultural biomass, but the methodology can be extended to the entire spectrum of biomass material.
With this material-agnostic approach, the team aims to provide valuable data with short turnaround times. The result will improve inefficiencies, reduce wasted energy and lower production costs long associated with biofuels.
