Saccharification and co-fermentation of lignocellulosic biomass by a cockroach-gut bacterial symbiont and yeast cocktail for bioethanol production.

Background: The eco-friendly transformation of agro-industrial wastes through microbial bioconversion could address sustainability challenges in line with the United Nations' Sustainable Development Goals. The bulk of agro-industrial waste consists of lignocellulosic materials with fermentable sugars, predominantly cellulose and hemicellulose. A number of pretreatment options have been employed for material saccharification toward successful fermentation into second-generation bioethanol.

Production, characterization, and bio-ethanologenic potential of a novel tripartite raw starch-digesting amylase from UCCM 00132.

The biological conversion of agro-waste biomass into value-added metabolites is one of the trendy biotechnological research areas in recent times. One of the major drawbacks of the bioprocess is the saccharification potential of the amylolytic enzyme that releases reducing sugar from complex biomass to serve as substrate for fermentation. The present study reports the production of a novel tripartite raw starch-digesting amylase (RSDA) by an indigenous strain with α-, β-, and gluco-amylolytic activities and its potential for bioethanol production.

Strain improvement, artificial intelligence optimization, and sensitivity analysis of asparaginase-mediated acrylamide reduction in sweet potato chips.

Unlabelled: In recent times, L-asparaginase has emerged as a potential anti-carcinogen through hydrolysis of L-asparagine in the blood for anti-leukemic application, and in carbohydrate-based foods, for acrylamide reduction applications. In this study, strain UCCM 00124 produced an L-asparaginase with a baseline acrylamide reduction potential of 64.5% in sweet potato chips.

Application of the novel manta-ray foraging algorithm to optimize acidic peptidase production in solid-state fermentation using binary agro-industrial waste.

Peptidases, which constitute about 20% of the global enzyme market, have found applications in detergent, food and pharmaceutical industries, and could be produced on a large scale using low-cost agro-industrial waste. An acidophilic strain produced acidic peptidase on binary-agro-industrial waste comprising yam peels and fish processing waste at pH 4.5 with high catalytic activity.

Production, characterization and techno-economic evaluation of Aspergillus fusant L-asparaginase.

Protoplast fusion is one of the most reliable methods of introducing desirable traits into industrially-promising fungal strains. It harnesses the entire genomic repertoire of fusing microorganisms by routing the natural barrier and genetic incompatibility between them. In the present study, the axenic culture of a thermo-halotolerant strain of Aspergillus candidus (Asp-C) produced an anti-leukemic L-asparaginase (L-ASNase) while a xylan-degrading strain of Aspergillus sydowii (Asp-S) produced the acrylamide-reduction type.

Interspecific protoplast fusion of atmospheric and room-temperature plasma mutants of generates an L-asparaginase hyper-producing hybrid with techno-economic benefits.

The axenic culture of (Asp-C) produced an anti-leukemic L-asparaginase while (Asp-S) produced the acrylamide-reduction type. Upon mutagenesis by atmospheric and room-temperature plasma (ARTP), their individual L-asparaginase activities improved 2.3-folds in each of IleThrAsp-C-180-K and ValAsp-S-180-E stable mutants.

Stochastic modeling and meta-heuristic multivariate optimization of bioprocess conditions for co-valorization of feather and waste frying oil toward prodigiosin production.

strain UCCM 00009 produced a mixture of gelatinase and keratinase to facilitate feather degradation but concomitant production of prodigiosin could make waste feather valorization biotechnologically more attractive. This article describes prodigiosin fermentation through co-valorization of waste feather and waste frying peanut oil by UCCM 00009 for anticancer, antioxidant, and esthetic applications. The stochastic conditions for waste feather degradation (WFD), modeled by multi-objective particle swarm-embedded-neural network optimization (ANN-PSO), revealed a gelatinase/keratinase ratio of 1.

Intracellular-to-extracellular localization switch of acidic lipase in Enterobacter cloacae through multi-objective medium optimization: aqueous two-phase purification and activity kinetics.

As physiological impairments that require replacement therapy continue to increase, so also does the need for improved production of acidic lipase from new microbial sources. Enterobacter cloacae strain UCCM 00116 produced a novel acidic lipase in kernel oil-processing waste-basal broth with 0.023:1 extracellular: intracellular localization ratio.

Circulation of hepatitis B virus genotype-E among outpatients in tertiary hospitals in the Niger-Delta region of Nigeria.

Introduction: Hepatitis B virus (HBV) infection continues to be a significant public health challenge globally, with higher disease burden in developing countries. HBV genotypes are associated with different geographical regions and clinical outcomes. Limited information exists on epidemiology of HBV in the Niger-Delta region (South-South) of Nigeria.

Intracellular-to-extracellular localization switch of acidic lipase in : evaluation of production kinetics and enantioselective esterification potential for pharmaceutical applications.

Downstream processing is a significant part of a production process and accounts for 50-90% of the production cost of biotechnological products. Post-fermentation localization of a microbial metabolite contributes significantly to the recovery cost of the product. produced naturally, acidic lipase with a 0.

A novel strain of Stenotrophomonas acidaminiphila produces thermostable alkaline peptidase on agro-industrial wastes: process optimization, kinetic modeling and scale-up.

Bacterial alkaline peptidases, especially from Bacillus species, occupy the frontline in global enzyme market, albeit with poor production economics. Here, we report the deployment of response surface methodology approximations to optimize fermentation parameters for enhanced yield of alkaline peptidase by the non-Bacillus bacterium; Stenotrophomonas acidaminiphila. Shake flask production under optimized conditions was scaled up in a 5-L bench-scale bioreactor.

Overproduction of a thermo-stable halo-alkaline protease on agro-waste-based optimized medium through alternate combinatorial random mutagenesis of .

A strain of , isolated from fermenting bean-processing wastewater, produced alkaline protease in pretreated cassava waste-stream, but with low yield. Strain improvement by alternate combinatorial random mutagenesis and bioprocess optimization using comparative statistical and neural network methods enhanced yield by 17.8-fold in mutant kGy-04-UV-25.

Kinetic modeling and quasi-economic analysis of fermentative glycolipopeptide biosurfactant production in a medium co-optimized by statistical and neural network approaches.

This study presents the kinetics of production of a glycolipopeptide biosurfactant in a medium previously co-optimized by response surface and neural network methods to gain some insight into its volumetric and specific productivities for possible scale-up towards industrial production. Significant kinetic parameters including maximum specific growth rate, µmax, specific substrate consumption rate, qs and specific biosurfactant yield, Yp/x were determined from logistic model parameters after comparison with other kinetic models. Results showed that bio-catalytic rates of lipase and urease reached exponential values within the first 12 h of fermentation leading to high specific rates of substrate consumption and bacterial growth.

Bioprocess Optimization of Nutritional Parameters for Enhanced Anti-leukemic L-Asparaginase Production by UCCM 00117: A Sequential Statistical Approach.

Sequential optimization of bioprocess nutritional conditions for production of glutaminase-near-free L-asparaginase by UCCM 00117 was conducted under shake flask laboratory conditions. Catalytic and anti-cancer activities of the poly-peptide were evaluated using standard in vitro biochemical methods. Medium nutrients were selected by one-factor-at-a-time (OFAT) approach while Plackett-Burman design (PBD) screened potential factors for optimization.

Statistical and Artificial Neural Network Approaches to Modeling and Optimization of Fermentation Conditions for Production of a Surface/Bioactive Glyco-lipo-peptide.

A freshwater alkaliphilic strain of grown on waste frying oil-basal medium, produced a surface-active metabolite identified as glycolipopeptide. Bioprocess conditions namely temperature, pH, agitation and duration were comparatively modeled using statistical and artificial neural network (ANN) methods to predict and optimize product yield using the matrix of a central composite rotatable design (CCRD). Response surface methodology (RSM) was the statistical approach while a feed-forward neural network, trained with Levenberg-Marquardt back-propagation algorithm, was the neural network method.

Plackett-Burman Design and Response Surface Optimization of Medium Trace Nutrients for Glycolipopeptide Biosurfactant Production.

Background: A glycolipopeptide biosurfactant produced by Pseudomonas aeruginosa strain IKW1 reduced the surface tension of fermentation broth from 71.31 to 24.62 dynes/cm at a critical micelle concentration of 20.