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The article presents information about beta glucan, an enzyme that synthesizes a polysaccharide in plant cell walls. It is a major cell wall component in grains, including the barleys used in brewing. Its presence can not only negatively affect fermentation, but can also inhibit the filtration process, leaving beer with an unappealing haze. Thus, it is not surprising that plant breeders have sought to identify the genes that determine how much beta glucan is produced in barley. A region of genomic DNA that controls the production of this polysaccharide in barley grains has been mapped to chromosome 2. To identify the genes and proteins responsible for beta glucan biosynthesis, some researchers have taken advantage of this information and the conserved genome structure between barley and rice, whose genome has been completely sequenced. The cellulose synthase like genes were first identified in the model plant Arabidopsis thaliana and rice genomes. Sequence analyses indicate that the cellulose synthase superfamily contains multiple subfamilies.

Presents information on mixed-linked glucanases which are extracellular enzymes. What purpose they serve; Details on the role that they play in the body; Information on the chemical make up of the enzymes.

Enzymatic conversion of lignocellulosic materials to fermentable sugars is a limiting step in the production of biofuels from biomass. We show here that combining enzymes from different microbial sources is one way to identify superior enzymes. Extracts of the thermophilic fungus Sporotrichum thermophile (synonym Myceliophthora thermophila) gave synergistic release of glucose (Glc) and xylose (Xyl) from pretreated corn stover when combined with an 8-component synthetic cocktail of enzymes from Trichoderma reesei. The S. thermophile extracts were fractionated and an enhancing factor identified as endo-β1,4- glucanase (StCel5A or EG2) of subfamily 5 of Glycosyl Hydrolase family 5 (GH5_5). In multi-component optimization experiments using a standard set of enzymes and either StCel5A or the ortholog from T. reesei (TrCel5A), reactions containing StCel5A yielded more Glc and Xyl. In a five-component optimization experiment (i.e., varying four core enzymes and the source of Cel5A), the optimal proportions for TrCel5A vs. StCel5A were similar for Glc yields, but markedly different for Xyl yields. Both enzymes were active on lichenan, glucomannan, and oat β-glucan; however, StCel5A but not TrCel5A was also active on β1,4-mannan, two types of galactomannan, and β1,4-xylan. Phylogenetically, fungal enzymes in GH5_5 sorted into two clades, with StCel5A and TrCel5A belonging to different clades. Structural differences with the potential to account for the differences in performance were deduced based on the known structure of TrCel5A and a homology-based model of StCel5A, including a loop near the active site of TrCel5A and the presence of four additional Trp residues in the active cleft of StCel5A. The results indicate that superior biomass-degrading enzymes can be identified by exploring taxonomic diversity combined with assays in the context of realistic enzyme combinations and realistic substrates. Substrate range may be a key factor contributing to superior performance within GH5_5. [ABSTRACT FROM AUTHOR]

Background: Enzymes for plant cell wall deconstruction are a major cost in the production of ethanol from lignocellulosic biomass. The goal of this research was to develop optimized synthetic mixtures of enzymes for multiple pretreatment/substrate combinations using our high-throughput biomass digestion platform, GENPLAT, which combines robotic liquid handling, statistical experimental design and automated Glc and Xyl assays. Proportions of six core fungal enzymes (CBH1, CBH2, EG1, β-glucosidase, a GH10 endo-β1,4-xylanase, and β-xylosidase) were optimized at a fixed enzyme loading of 15 mg/g glucan for release of Glc and Xyl from all combinations of five biomass feedstocks (corn stover, switchgrass, Miscanthus, dried distillers' grains plus solubles [DDGS] and poplar) subjected to three alkaline pretreatments (AFEX, dilute base [0.25% NaOH] and alkaline peroxide [AP]). A 16-component mixture comprising the core set plus 10 accessory enzymes was optimized for three pretreatment/substrate combinations. Results were compared to the performance of two commercial enzymes (Accellerase 1000 and Spezyme CP) at the same protein loadings. Results: When analyzed with GENPLAT, corn stover gave the highest yields of Glc with commercial enzymes and with the core set with all pretreatments, whereas corn stover, switchgrass and Miscanthus gave comparable Xyl yields. With commercial enzymes and with the core set, yields of Glc and Xyl were highest for grass stovers pretreated by AP compared to AFEX or dilute base. Corn stover, switchgrass and DDGS pretreated with AFEX and digested with the core set required a higher proportion of endo-β1,4-xylanase (EX3) and a lower proportion of endo-β1,4-glucanase (EG1) compared to the same materials pretreated with dilute base or AP. An optimized enzyme mixture containing 16 components (by addition of α-glucuronidase, a GH11 endoxylanase [EX2], Cel5A, Cel61A, Cip1, Cip2, β-mannanase, amyloglucosidase, α-arabinosidase, and Cel12A to the core set) was determined for AFEX-pretreated corn stover, DDGS, and AP-pretreated corn stover. The optimized mixture for AP-corn stover contained more exo-β1,4-glucanase (i.e., the sum of CBH1 + CBH2) and less endo-β1,4-glucanase (EG1 + Cel5A) than the optimal mixture for AFEX-corn stover. Amyloglucosidase and β-mannanase were the two most important enzymes for release of Glc from DDGS but were not required (i.e., 0% optimum) for corn stover subjected to AP or AFEX. As a function of enzyme loading over the range 0 to 30 mg/g glucan, Glc release from AP-corn stover reached a plateau of 60-70% Glc yield at a lower enzyme loading (5-10 mg/g glucan) than AFEX-corn stover. Accellerase 1000 was superior to Spezyme CP, the core set or the 16-component mixture for Glc yield at 12 h, but the 16-component set was as effective as the commercial enzyme mixtures at 48 h. Conclusion: The results in this paper demonstrate that GENPLAT can be used to rapidly produce enzyme cocktails for specific pretreatment/biomass combinations. Pretreatment conditions and feedstock source both influence the Glc and Xyl yields as well as optimal enzyme proportions. It is predicted that it will be possible to improve synthetic enzyme mixtures further by the addition of additional accessory enzymes. [ABSTRACT FROM AUTHOR]