In vitro and in silico characterization of metagenomic soil-derived cellulases capable of hydrolyzing oil palm empty fruit bunch

Role of metagenomics in prospecting novel endoglucanases, accentuating functional metagenomics approach in second-generation biofuel production: a review

As the fossil fuel reserves are depleting rapidly, there is a need for alternate fuels to meet the day to day mounting energy demands. As fossil fuel started depleting, a quest for alternate forms of fuel was initiated and biofuel is one of its promising outcomes. First-generation biofuels are made from edible sources like vegetable oils, starch, and sugars. Second-generation biofuels (SGB) are derived from lignocellulosic crops and the third-generation involves algae for biofuel production. Technical challenges in the production of SGB are hampering its commercialization. Advanced molecular technologies like metagenomics can help in the discovery of novel lignocellulosic biomass-degrading enzymes for commercialization and industrial production of SGB. This review discusses the metagenomic outcomes to enlighten the importance of unexplored habitats for novel cellulolytic gene mining. It also emphasizes the potential of different metagenomic approaches to explore the uncultivable cellulose-degrading microbiome as well as cellulolytic enzymes associated with them. This review also includes effective pre-treatment technology and consolidated bioprocessing for efficient biofuel production.

Enzymatic hydrolysis of several pretreated lignocellulosic biomasses: Fractal kinetic modelling

Enzymatic hydrolysis of three pre-treated lignocellulosic biomasses -LCB- (wheat straw-WS-, corn stover-CSV- and cardoon stems -CS-) is studied. These biomasses were pre-treated by two methods: diluted sulfuric acid and acid ethanol-water extraction at six severity levels (H values). Pretreated solid fractions were hydrolyzed with commercial enzyme cocktails at standard conditions. A first-order kinetic fractal model was fitted to the experimental results. This model accurately describes the hydrolysis of all biomasses at all pre-treatment conditions studied. The results show that the formal first-order kinetic constant k depends on the biomass nature. The hydrolysis rate increases as the pre-treatment severity does, while the fractal exponent value h decreases. With these pre-treatments, and in terms of k and h, WS is highly reactive and, at medium H with EW pretreatment, highly accessible; CSV has a low reactivity and high accessibility and CS has the lowest reactivity and an increasing accessibility as severity rises.