The high cost of enzymes is a major bottleneck preventing the development of an economically viable lignocellulosic ethanol industry. Commercial enzyme cocktails for the conversion of plant biomass to fermentable sugars are complex mixtures containing more than 80 proteins of suboptimal activities and relative proportions. As a step toward the development of a more efficient enzyme cocktail for biomass conversion, we have developed a platform, called GENPLAT, that uses robotic liquid handling and statistically valid experimental design to analyze synthetic enzyme mixtures. Commercial enzymes (Accellerase 1000 +/- Multifect Xylanase, and Spezyme CP +/- Novozyme 188) were used to test the system and serve as comparative benchmarks. Using ammonia-fiber expansion (AFEX) pretreated corn stover ground to 0.5 mm and a glucan loading of 0.2%, an enzyme loading of 15 mg protein/g glucan, and 48 h digestion at 50 degrees C, commercial enzymes released 53% and 41% of the available glucose and xylose, respectively. Mixtures of three, five, and six pure enzymes of Trichoderma species, expressed in Pichia pastoris, were systematically optimized. Statistical models were developed for the optimization of glucose alone, xylose alone, and the average of glucose + xylose for two digestion durations, 24 and 48 h. The resulting models were statistically significant (P < 0.0001) and indicated an optimum composition for glucose release (values for optimized xylose release are in parentheses) of 29% (5%) cellobiohydrolase 1, 5% (14%) cellobiohydrolase 2, 25% (25%) endo-beta1,4-glucanase 1, 14% (5%) beta-glucosidase, 22% (34%) endo-beta1,4-xylanase 3, and 5% (17%) beta-xylosidase in 48 h at a protein loading of 15 mg/g glucan. Comparison of two AFEX-treated corn stover preparations ground to different particle sizes indicated that particle size (100 vs. 500 microm) makes a large difference in total digestibility. The assay platform and the optimized "core" set together provide a starting point for the rapid testing and optimization of alternate core enzymes from other microbial and recombinant sources as well as for the testing of "accessory" proteins for development of superior enzyme mixtures for biomass conversion.
Based on the analysis of its genome sequence, the ectomycorrhizal (ECM) basidiomycetous fungus Laccaria bicolor was shown to be lacking many of the major classes of secreted enzymes that depolymerize plant cell wall polysaccharides. To test whether this is also a feature of other ECM fungi, we searched a survey genome database of Amanita bisporigera with the proteins found in the secretome of Trichoderma reesei (syn. Hypocrea jecorina), a biochemically well-characterized industrial fungus. Additional proteins were also used as queries to compensate for major groups of cell-wall-degrading enzymes lacking in the secretome of T. reesei and to substantiate conclusions drawn from the T. reesei collection. By MS/MS-based "shotgun" proteomics, 80 proteins were identified in culture filtrates of T. reesei strain RUTC30 grown on corn cell walls and in a commercial "cellulase" preparation, Spezyme CP. The two T. reesei enzyme preparations were qualitatively and quantitatively similar, the most striking difference being the lack of at least five major peptidases from the commercial enzyme mixture. Based on our analysis of A. bisporigera, this ECM fungus is deficient in many major classes of cell-wall-degrading enzymes, including both glycosyl hydrolases and carbohydrate esterases. By comparison, the genomes of the saprophytic basidiomycetes Coprinopsis cinerea and Galerina marginata (using a genome survey sequence approximately equivalent in depth to that of A. bisporigera) have, like T. reesei, a much more complete complement of cell-wall-degrading enzymes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.