Application of genetic algorithm in modelling and optimization of cellulase production

Synergistic effect of two bacterial strains promoting anaerobic digestion of rice straw to produce methane

A large amount of agricultural waste causes global environmental pollution. Biogas production by microbial pretreatment is an important way to utilize agricultural waste resources. In this study, Sporocytophaga CG-1 (A, cellulolytic strain) was co-cultured with Bacillus clausii HP-1 (B, non-cellulolytic strain) to analyze the effect of pretreatment of rice straw on methanogenic capacity of anaerobic digestion (AD). The results showed that weight loss rate of filter paper of co-culture combination is 53.38%, which is 29.37% higher than that of A. The synergistic effect of B on A can promote its degradation of cellulose. The cumulative methane production rate of the co-culture combination was the highest (93.04 mL/g VS substrate), which was significantly higher than that of A, B and the control group (82.38, 67.28 and 67.70 mL/g VS substrate). Auxiliary bacteria can improve cellulose degradation rate by promoting secondary product metabolism. These results provide data support for the application of co-culture strategies in the field of anaerobic digestion practices.

Improved deinking and biobleaching efficiency of enzyme consortium from Thermomyces lanuginosus VAPS25 using genetic Algorithm-Artificial neural network based tools

The present study reports the combined enzymatic production efficiency of thermophilic fungus Thermomyces lanuginosus VAPS25 using a combinatory artificial intelligence-based tool, resulting in 2.7 IU/ml, 5.2 IU/ml, and 18.85 U/ml activity of endoglucanase, amylase, and lipase, respectively with good thermostability at 90 °C (pH 8-10). Interestingly, the metal ions viz. Cu²⁺ and Mg²⁺ increased the endoglucanase activity to 5 folds, i.e.,5.6 IU/ml compared to control. Further, the amylase and lipase activity was also enhanced by Fe²⁺ and Co²⁺ to 5.4 IU/ml and 19.57 U/ml, respectively. Additionally, the deinking efficiency was improved by 68.9%, 42.7%, and 52.8% by endoglucanase, amylase, and lipase, respectively, while the consortium increased the deinking efficiency to 72.7%. The bio-bleached paper strength parameters such as burst index, breaking length, tear index, and tensile index of sheets were significantly improved by 1.38%, 13.54%, 7.54%, and 20.88%, respectively. These enzymes at an industrial scale would help develop an economical paper recycling process.

Microbial cellulases - An update towards its surface chemistry, genetic engineering and recovery for its biotechnological potential

The inherent resistance of lignocellulosic biomass makes it impervious for industrially important enzymes such as cellulases to hydrolyze cellulose. Further, the competitive absorption behavior of lignin and hemicellulose for cellulases, due to their electron-rich surfaces augments the inappropriate utilization of these enzymes. Hence, modification of the surface charge of the cellulases to reduce its non-specific binding to lignin and enhance its affinity for cellulose is an urgent necessity. Further, maintaining the stability of cellulases by the preservation of their secondary structures using immobilization techniques will also play an integral role in its industrial production. In silico approaches for increasing the catalytic activity of cellulase enzymes is also significant along with a range of substrate specificity. In addition, enhanced productivity of cellulases by tailoring the related genes through the process of genetic engineering and higher cellulase recovery after saccharification seems to be promising areas for efficient and large-scale enzyme production concepts.

Modelling of fermentative bioethanol production from indigenous Ulva prolifera biomass by Saccharomyces cerevisiae NFCCI1248 using an integrated ANN-GA approach

Third generation biomass (marine macroalgae) has been projected as a promising alternative energy resource for bioethanol production due to its high carbon and no lignin composition. However, the major challenge in the technologies of production lies in the fermentative bioconversion process. Therefore, in the present study the predictive ability of an integrated artificial neural network with genetic algorithm (ANN-GA) in the modelling of bioethanol production was investigated for an indigenous marine macroalgal biomass (Ulva prolifera) by a novel yeast strain, Saccharomyces cerevisiae NFCCI1248 using six fermentative parameters, viz., substrate concentration, fermentation time, inoculum size, temperature, agitation speed and pH. The experimental model was developed using one-variable-at-a-time (OVAT) method to analyze the effects of the fermentative parameters on bioethanol production and the obtained regression equation was used as a fitness function for the ANN-GA modelling. The ANN-GA model predicted a maximum bioethanol production at 30 g/L substrate, 48 h fermentation time, 10% (v/v) inoculum, 30 °C temperature, 50 rpm agitation speed and pH 6. The maximum experimental bioethanol yield obtained after applying ANN-GA was 0.242 ± 0.002 g/g RS, which was in close proximity with the predicted value (0.239 g/g RS). Hence, the developed ANN-GA model can be applied as an efficient approach for predicting the fermentative bioethanol production from macroalgal biomass.

Engineering interventions in enzyme production: Lab to industrial scale

Commercial enzyme production has gained popularity due to its extensive applications in traditional and modern industrial sectors. Rigorous research activities are being conducted worldwide to make the enzyme production system more efficient, cost-effective and hence, sustainable. To overcome the lacunae in earlier enzyme production methods, new engineering interventions are being introduced to meet the growing demand for industrial enzymes. This review focuses initially on the current global scenario of the enzyme market followed by a discussion on different bioreactor design approaches. The use of novel membrane based, airlift and reciprocating plate bioreactors along with the emergence of micro-reactors have also been discussed. Further, the review covers different modelling and optimization strategies for the enzyme production process including advanced techniques like neural networks, adaptive neuro-fuzzy inference systems and genetic algorithms. Finally, the required thrust areas in the enzyme production sector have been highlighted with directions for future research.

Large-scale production of enzymes for biotechnology uses

Enzymes are biocatalysts that speed up the chemical reaction to obtain the final valuable product/s. Biotechnology has revolutionized the use of traditional enzymes to be applicable in industries such as food, beverage, personal and household care, agriculture, bioenergy, pharmaceutical, and various other segments. With respect to the exponential growth of enzymes in biotech industries, it becomes important to highlight the advancements and impact of enzyme technology over recent years. In this review article, we discuss the existing and emerging production approaches, applications, developments, and global need for enzymes. Special emphasis is given to the predominantly utilized hydrolytic microbial enzymes in industrial bioprocesses.

Microbial dynamics for lignocellulosic waste bioconversion and its importance with modern circular economy, challenges and future perspectives

An extensive use of microbial dynamics for utilizing the lignocellulosic wastes has been attributed to their efficiency in bioenergy and bioproducts development as a cost effective high nutritional value. The integration of lignocellulosic waste into the circular economy can scaleup the sustainable bioproducts and bioenergy development. In this review paper, the aim is to describe the existing research efforts on organic lignocellulosic waste, cellulase producing microbes, their potential enzyme, modern circular economy with associated challenges and future perspectives. Presently, it has been reviewed that microbial cellulases have provided treasure bioproducts visions into industrial bioproducts marvels unveiled through lignocellulosic waste cutting-edge microbial explorations. Furthermore, the review focused on new insights of the growing circular economy of lignocellulosic waste used for many bioproducts and bioenergy dealings and explored the emergent lignocellulosic biorefinery approaches which could then be applied to review industrial-scale sustainable economic models for upgraded bioproducts and other production associated problems.