| Literature DB >> 31624500 |
Vera Novy1,2, Fredrik Nielsen1,2, Bernhard Seiboth3,4, Bernd Nidetzky1,4.
Abstract
Biorefineries, designed for the production of lignocellulose-based chemicals and fuels, are receiving increasing attention from the public, governments, and industries. A major obstacle for biorefineries to advance to commercial scale is the high cost of the enzymes required to derive the fermentable sugars from the feedstock used. As summarized in this review, techno-economic studies suggest co-localization and integration of enzyme manufacturing with the cellulosic biorefinery as the most promising alternative to alleviate this problem. Thus, cultivation of Trichoderma reesei, the principal producer of lignocellulolytic enzymes, on the lignocellulosic biomass processed on-site can reduce the cost of enzyme manufacturing. Further, due to a complex gene regulation machinery, the fungus can adjust the gene expression of the lignocellulolytic enzymes towards the characteristics of the feedstock, increasing the hydrolytic efficiency of the produced enzyme cocktail. Despite extensive research over decades, the underlying regulatory mechanisms are not fully elucidated. One aspect that has received relatively little attention in literature is the influence the characteristics of a lignocellulosic substrate, i.e., its chemical and physical composition, has on the produced enzyme mixture. Considering that the fungus is dependent on efficient enzymatic degradation of the lignocellulose for continuous supply of carbon and energy, a relationship between feedstock characteristics and secretome composition can be expected. The aim of this review was to systematically collect, appraise, and aggregate data and integrate results from studies analyzing enzyme production by T. reesei on insoluble cellulosic model substrates and lignocellulosic biomass. The results show that there is a direct effect of the substrate's complexity (rated by structure, composition of the lignin-carbohydrate complex, and recalcitrance in enzymatic saccharification) on enzyme titers and the composition of specific activities in the secretome. It further shows that process-related factors, such as substrate loading and cultivation set-up, are direct targets for increasing enzyme yields. The literature on transcriptome and secretome composition further supports the proposed influence of substrate-related factors on the expression of lignocellulolytic enzymes. This review provides insights into the interrelation between the characteristics of the substrate and the enzyme production by T. reesei, which may help to advance integrated enzyme manufacturing of substrate-specific enzymes cocktails at scale.Entities:
Keywords: Gene regulation; Integrated enzyme manufacturing; Lignocellulose; On-site enzyme manufacturing; Productivity; Secretome; Transcriptome; Trichoderma reesei
Year: 2019 PMID: 31624500 PMCID: PMC6781402 DOI: 10.1186/s13068-019-1571-z
Source DB: PubMed Journal: Biotechnol Biofuels ISSN: 1754-6834 Impact factor: 6.040
Enzymes expressed and characterized in T. reesei for the degradation of hemicellulose and cellulose, grouped according to their functionality.
Adapted from Häkkinen et al. [127]
| Group | Functionality | Enzymes in | EC |
|---|---|---|---|
| Enzymes for the degradation of hemicellulose | |||
| Backbone cleaving enzymes | Degradation of the xylan backbone in arabinoxylan (hardwood) and arabinoglucoronoxylan (grasses) by endo- and exo-xylanases | Endo-β-1,4-xylanase | 3.2.1.8 |
| 1,4-β-Xylosidase | 3.2.1.37 | ||
| Xyloglucan-specific endo-β-1,4-glucanase | 3.2.1.151 | ||
| Degradation of the mannan backbone in galactoglucomannan (softwood) by endo- and exo-mannanases | Endo-1,4-β-mannosidase | 3.2.1.78 | |
| β-Mannosidase | 3.2.1.25 | ||
| 1,2-α-Mannosidase | 3.2.1.113 | ||
| β-Galactosidase | 3.2.1.23 | ||
| Side-chain cleaving hydrolytic enzymes | Cleaving off galactose moieties from galactoglucomannan (softwood) | α-Galactosidase | 3.2.1.22 |
| Cleaving off arabinose moieties from arabinoxylan (hardwood) and arabinoglucoronoxylan (grasses) | α- | 3.2.1.55 | |
| Cleaving off glucoronic moieties from arabinoxylan (hardwood) and arabinoglucoronoxylan (grasses) | α-Glucuronidase | 3.2.1.139 | |
| Side chain cleaving esterases | Cleaving off acetyl groups from glucuronoxylan (hardwood), arabinoglucoronoxylan (grasses), and galactoglucomannan (softwood) | Acetyl xylan esterase | 3.1.1.72 |
| Cleaving ester linkage between arabinose in hemicellulose and ferulic acid in lignin | Acetyl esterase | 3.1.1.6 | |
| Enzymes for degradation of cellulose | |||
| Concerted action of exo- and endo-cellulases and β-glucosidase | Endo-β-1,4-glucanase | 3.2.1.4 | |
| 1,4-β-Cellobiosidase | 3.2.1.91 | ||
| β-Glucosidase | 3.2.1.21 | ||
| Auxiliary activities | Cleavage of cellulose chains by oxidation of C1 or C4 | Lytic polysaccharide monooxygenases | 1.14.99.56 |
| Non-hydrolytic proteins | High binding affinity for hemicellulose and cellulose, unknown role in biomass degradation | Swollenin |
|
Fig. 1Box-and-whiskers plot for cellulase production in shake flask (n = 37) and bioreactor (n = 16) cultivations by T. reesei. Depicted are the min to max box plots in quartiles. The band inside the box represents the median
Fig. 2Metadata analysis on enzyme production by T. reesei on insoluble substrates. Depicted is the correlation between the substrate concentration and the FPA (a), the protein concentration and the FPA (b), and the hemicellulose content of the substrate and the xylanase activity (c). Data are summarized in Additional file 1: Table S1. The solid line represents the linear regression of the data points, the dotted line the 95% confidence interval
Fig. 3The influence of substrate type on FPA production (a), protein production (b), and C-source concentration utilized (c). The categories were ordered with ascending complexities from left to right, where the complexity is a function of the structural organization, the chemical composition, and the recalcitrance to deconstruction (as detailed in “Assessing and categorizing lignocellulosic biomass” section). Depicted are the min to max box plots in quartiles. The band inside the box represents the median. The raw data with the respective references can be found in Additional file 1: Table S1