High Throughput Analysis Platform for Optimization of Enzyme Mixtures for Lignocellulosic Feedstocks

Scientists from the United States Department of Energy (US-DOE) Great Lakes Bioenergy Research Center and Department of Energy Plant Research Laboratory, Michigan State University, report a "high-throughput analysis platform, called GENPLAT, for the analysis and optimization of enzyme mixtures in the saccharification step of cellulose ethanol production.

Cellulose ethanol production technology uses lignocellulosic feedstocks, which undergo three major processing steps: (1) pretreatment, for removal of lignin and liberating the cellulose/hemicelluloses molecules in the biomass, (2) saccaharification, for the conversion of cellulose/hemicelluloses into simple sugars (mainly glucose and xylose), and (3) fermentation of simple sugars to ethanol. The saccharification step presents a major challenge. Lignocellulosic feedstock sources are highly diverse (from grasses, to agricultural residues, or fast growing trees), and it is possible that the enzyme mixtures used in the saccharification step may not be optimized for a particular feedstock.

The enzyme cocktail usually contains different types of cellulose-degrading, hemicelluloses-degrading enzymes, and possibly, other "accessory enzymes". The Michigan State University scientists attempted to "optimize synthetic mixtures of enzymes for multiple pretreatment/substrate combinations using a high-throughput biomass digestion platform, GENPLAT". The analysis platform reportedly combines robotic liquid handling, statistical experimental design and automated [glucose] and [xylose] assays. The results were compared to the performance of two commercial enzymes at the same protein loadings. The authors were able to demonstrate that GENPLAT can be used to rapidly produce enzyme cocktails for specific pretreatment/biomass combinations. The results of their findings are published in the free access journal, Biotechnology for Biofuels (URL above).