Using an artificial neural network to predict the optimal conditions for enzymatic hydrolysis of apple pomace.

The enzymatic degradation of lignocellulosic biomass such as apple pomace is a complex process influenced by a number of hydrolysis conditions. Predicting optimal conditions, including enzyme and substrate concentration, temperature and pH can improve conversion efficiency. In this study, the production of sugar monomers from apple pomace using commercial enzyme preparations, Celluclast 1.5L, Viscozyme L and Novozyme 188 was investigated. A limited number of experiments were carried out and then analysed using an artificial neural network (ANN) to model the enzymatic hydrolysis process. The ANN was used to simulate the enzymatic hydrolysis process for a range of input variables and the optimal conditions were successfully selected as was indicated by the R 2 value of 0.99 and a small MSE value. The inputs for the ANN were substrate loading, enzyme loading, temperature, initial pH and a combination of these parameters, while release profiles of glucose and reducing sugars were the outputs. Enzyme loadings of 0.5 and 0.2 mg/g substrate and a substrate loading of 30% were optimal for glucose and reducing sugar release from apple pomace, respectively, resulting in concentrations of 6.5 g/L glucose and 28.9 g/L reducing sugars. Apple pomace hydrolysis can be successfully carried out based on the predicted optimal conditions from the ANN.

Time dependence of enzyme synergism during the degradation of model and natural lignocellulosic substrates.

Cellulosic ethanol production relies on the biochemical (enzymatic) conversion of lignocellulose to fermentable sugars and ultimately to bioethanol. However, the cost of lignocellulolytic enzymes is a limiting factor in the commercialisation of this technology. This therefore necessitates the optimisation of lignocellulolytic enzyme cocktails through the elucidation of synergistic interactions between enzymes so as to improve lignocellulose hydrolysis and also lower protein loadings in these reactions. However, many factors affect the synergism that occurs between these lignocellulolytic enzymes, such as enzyme ratios, substrate characteristics, substrate loadings, enzyme loadings and time. This review examines the effect of time on the synergistic dynamics between lignocellulolytic enzymes during the hydrolysis of both complex (true) lignocellulosic substrates and model substrates. The effect of sequential and simultaneous application of the lignocellulolytic enzymes on the synergistic dynamics during the hydrolysis of these substrates is also explored in this review. Finally, approaches are further proposed for efficient and synergistic hydrolysis of both complex lignocellulosic substrates and model substrates. With respect to the synergistic enzymatic hydrolysis of lignocellulosic biomass, this review exposed knowledge gaps that should be covered in future work in order to fully understand how enzyme synergism works: e.g. elucidating protein to protein interactions that exist between these enzymes in establishing synergy; and the effect of lignocellulose degradation products of one enzyme on the behaviour of the other enzyme and ultimately their synergistic relationship.

A review of the enzymatic hydrolysis of mannans and synergistic interactions between ß-mannanase, ß-mannosidase and α-galactosidase.

Mannan is an important polysaccharide found in softwoods and many other plant sources. Mannans from various sources display large differences in composition, structure and complexity. To hydrolyse mannan into its monomer sugars requires a number of enzymes working in synergy. This review examines mannan structure and the enzymes required for its hydrolysis. Several studies have investigated the effect of supplementing ß-mannanases with ß-mannosidases and α-galactosidases in binary and ternary combinations. Synergistic enhancement of hydrolysis has been found in some, but not all cases. In the case of mannosidases, they sometimes display an anti-synergistic effect with mannanases, most likely due to competition for binding sites. Most importantly, in the case of α-galactosidases, the same enzyme from different families display differences in synergistic interactions due to different specificities. An improved understanding of enzyme interactions will aid in achieving enhanced hydrolysis of mannans and higher sugar yields. This review highlights areas which require further research in order to gain a better understanding of mannan hydrolysis and utilisation. Such knowledge is very important as this can be used in the optimisation of commercial or purified enzyme mixtures to improve the economic viability of the conversion of high mannan-containing biomass such as softwoods into fermentable sugars for bioethanol production.

Optimisation of enzymatic hydrolysis of apple pomace for production of biofuel and biorefinery chemicals using commercial enzymes.

Apple pomace, a waste product from the apple juice industry is a potential feedstock for biofuel and biorefinery chemical production. Optimisation of hydrolysis conditions for apple pomace hydrolysis using Viscozyme L and Celluclast 1.5L was investigated using 1 L reaction volumes. The effects of temperature, pH, ß-glucosidase supplementation and substrate feeding regimes were determined. Hydrolysis at room temperature using an unbuffered system gave optimal performance. Reactors in batch mode resulted in a better performance (4.2 g/L glucose and 16.8 g/L reducing sugar, 75 % yield for both) than fed-batch (3.2 g/L glucose and 14.6 g/L reducing sugar, 65.5 and 73.1 % yield respectively) in 72 h. The addition of Novozyme 188 to the core mixture of Viscozyme L and Celluclast 1.5L resulted in the doubling of glucose released. The main products (yield %) released from apple pomace hydrolysis were galacturonic acid (78 %), glucose (75 %), arabinose (90 %) and galactose (87 %). These products are potential raw materials for biofuel and biorefinery chemical production.

Characterization of Xyn30A and Axh43A of Bacillus licheniformis SVD1 identified by its genomic analysis.

The genome sequence of Bacillus licheniformis SVD1, that produces a cellulolytic and hemi-cellulolytic multienzyme complex, was partially determined, indicating that the glycoside hydrolase system of this strain is highly similar to that of B. licheniformis ATCC14580. All of the fifty-six genes encoding glycoside hydrolases identified in B. licheniformis ATCC14580 were conserved in strain SVD1. In addition, two new genes, xyn30A and axh43A, were identified in the B. licheniformis SVD1 genome. The xyn30A gene was highly similar to Bacillus subtilis subsp. subtilis 168 xynC encoding for a glucuronoarabinoxylan endo-1,4-ß-xylanase. Xyn30A, produced by a recombinant Escherichia coli, had high activity toward 4-O-methyl-D-glucurono-D-xylan but showed definite activity toward oat-spelt xylan and unsubstituted xylooligosaccharides. Recombinant Axh43A, consisting of a family-43 catalytic module of the glycoside hydrolases and a family-6 carbohydrate-binding module (CBM), was an arabinoxylan arabinofuranohydrolase (α-L-arabinofuranosidase) classified as AXH-m23 and capable of releasing arabinosyl residues, which are linked to the C-2 or C-3 position of singly substituted xylose residues in arabinoxylan or arabinoxylan oligomers. The isolated CBM polypeptide had an affinity for soluble and insoluble xylans and removal of the CBM from Axh43A abolished the catalytic activity of the enzyme, indicating that the CBM plays an essential role in hydrolysis of arabinoxylan.

Lime pretreatment of sugar beet pulp and evaluation of synergy between ArfA, ManA and XynA from Clostridium cellulovorans on the pretreated substrate.

Sugar beet pulp (SBP) is a waste product from the sugar beet industry and could be used as a potential biomass feedstock for second generation biofuel technology. Pretreatment of SBP with 'slake lime' (calcium hydroxide) was investigated using a 2(3) factorial design and the factors examined included lime loading, temperature and time. The pretreatment was evaluated for its ability to enhance enzymatic degradation using a combination of three hemicellulases, namely ArfA (an arabinofuranosidase), ManA (an endo-mannanase) and XynA (an endo-xylanase) from C. cellulovorans to determine the conditions under which optimal activity was facilitated. Optimal pretreatment conditions were found to be 0.4 g lime/g SBP, with 36 h digestion at 40 °C. The synergistic interactions between ArfA, ManA and XynA from C. cellulovorans were subsequently investigated on the pretreated SBP. The highest degree of synergy was observed at a protein ratio of 75% ArfA to 25% ManA, with a specific activity of 2.9 U/g protein. However, the highest activity was observed at 4.2 U/g protein at 100% ArfA. This study demonstrated that lime treatment enhanced enzymatic hydrolysis of SBP. The ArfA was the most effective hemicellulase for release of sugars from pretreated SBP, but the synergy with the ManA indicated that low levels of mannan in SBP were probably masking the access of the ArfA to its substrate. XynA displayed no synergy with the other two hemicellulases, indicating that the xylan in the SBP was not hampering the access of ArfA or ManA to their substrates and was not closely associated with the mannan and arabinan in the SBP.

Review on the use of enzymes for the detection of organochlorine, organophosphate and carbamate pesticides in the environment.

Pesticides are released intentionally into the environment and, through various processes, contaminate the environment. Three of the main classes of pesticides that pose a serious problem are organochlorines, organophosphates and carbamates. While pesticides are associated with many health effects, there is a lack of monitoring data on these contaminants. Traditional chromatographic methods are effective for the analysis of pesticides in the environment, but have limitations and prevent adequate monitoring. Enzymatic methods have been promoted for many years as an alternative method of detection of these pesticides. The main enzymes that have been utilised in this regard have been acetylcholinesterase, butyrylcholinesterase, alkaline phosphatase, organophosphorus hydrolase and tyrosinase. The enzymatic methods are based on the activation or inhibition of the enzyme by a pesticide which is proportional to the concentration of the pesticide. Research on enzymatic methods of detection, as well as some of the problems and challenges associated with these methods, is extensively discussed in this review. These methods can serve as a tool for screening large samples which can be followed up with the more traditional chromatographic methods of analysis.