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 Bacillus cereus strain produced acidic peptidase on binary-agro-industrial waste comprising yam peels and fish processing waste at pH 4.5 with high catalytic activity. A five-variable central composite rotatable design of a response surface methodology was used to model bioprocess conditions for improved peptidase production in solid-state fermentation. Data generated was leveraged as the basis for applying the novel Manta-ray foraging optimization-linked feed-forward artificial neural network to predict bioprocess conditions optimally. Results obtained from the optimization experiments revealed a significant coefficient of determination of 0.9885 with low-performance error. The bioprocess predicted a peptidase activity of 1035.32 U/mL under optimized conditions set as 54.8 g/100 g yam peels, 23.85 g/100 g fish waste, 0.31 g/100 g CaCl2, 47.54% (v/w) moisture content, and pH 2. Peptidase activity was improved 5-fold, and was stable for 240 min between pH 2.5 and 3.5. Michaelis-Menten kinetics revealed a Km of 0.119 mM and a catalytic efficiency of 45462.19 mM-1 min-1. The bioprocess holds promise for sustainable enzyme-driven applications.

Intracellular-to-extracellular localization switch of acidic lipase in Enterobacter cloacae: 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. Enterobacter cloacae produced naturally, acidic lipase with a 0.023:1 extracellular localization ratio. This research aimed to re-direct the localization of lipase to the extracellular milieu to reduce recovery costs using multi-objective response surface optimization (MO-RSM). The approach resulted in a 1:0.32 extracellular: intracellular lipase ratio, with product formation kinetics of Luedeking-Piret function showing a significant switch from a completely growth-associated intracellular production to a predominantly non-growth-associated extracellular localization. The enzyme was purified by an aqueous two-phase system which extracted 95.22% lipase with 72.36 purity. Characterization of the enzyme showed a molecular weight of 55.7 kDa, kcat of 68.59 s-1, and a Km of 0.63 mmol. Lipase activity occurred optimally at pH 2.5-3.5 and 50 °C, and was stable in most organic solvents tested. The acidic lipase demonstrated pH-dependent enantioselective esterification in resolving (R, S)-ibuprofen (E = 14, pH 4.5) and (R, S)-Naproxen (E = 13, pH 2.5), with an enantioselective preference for (S)-enantiomer in both drugs thus underpinning its potential for pharmaceutical applications.

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

The axenic culture of Aspergillus candidus (Asp-C) produced an anti-leukemic L-asparaginase while Aspergillus sydowii (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 Ile-Thr-Asp-C-180-K and Val-Asp-S-180-E stable mutants. Protoplast fusion of selected stable mutants generated fusant-09 with improved anti-leukemic activity, acrylamide reduction, higher temperature optimum and superior kinetic parameters. Submerged (SmF) and solid-state fermentation (SSF) types were compared; likewise batch, fed-batch and continuous fermentation modes; and fed-batch submerged fermentation was selected on the basis of impressive techno-economics. Fusant L-asparaginase was purified by PEG/Na+ citrate aqueous two-phase system and molecular exclusion chromatography to 69.96 and 146.21-fold, respectively, and characterized by molecular weight, specificity, activity and stability to chemical and physical agents. Michaelis-Menten kinetics, evaluated under optimum conditions gave Km, Vmax, Kcat, and Kcat/Km as 1.667 × 10-3 M, 1666.67 µmol min-1 mg-1 protein, 645.99 s-1 and 3.88 × 105 M-1 s-1 respectively. In-vitro cytotoxicity of HL-60 cell lines by fusant-09 L-asparaginase improved 3.00 and 18.71-folds from mutants Ile-Thr-Asp-C-180-K and Val-Asp-S-180-E, and from 5.73 and 32.55 from respective original strains. Free-radical scavenging and acrylamide reduction improvements were intermediate. Fusant-09 L-asparaginase is strongly recommended for sustainable economic anti-leukemic and food industry applications.

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

Serratia marcescens 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 S. marcescens 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 1.71 for optimal prodigiosin production and WFD. Luedeking-Piret kinetics revealed a non-exclusive, non-growth-associated prodigiosin yield of 9.66 g/L from the degradation of 88.55% waste feather within 96 h. The polyethylene glycol (PEG) 6000/Na+ citrate aqueous two-phase system-purified serratiopeptidase demonstrated gelatinolytic and keratinolytic activities that were stable for 240 h at 55 °C and pH 9.0. In vitro evaluations revealed that the prodigiosin inhibited methicillin-resistant Staphylococcus aureus at IC50 of 4.95 µg/mL, the plant-pathogen, Sclerotinia sclerotiorum, at IC50 of 2.58 µg/mL, breast carcinoma at IC50 of 0.60 µg/mL and 2,2-diphenyl-1-picryl-hydrazyl hydrate (DPPH) free-radical at IC50 of 96.63 µg/mL). The pigment also demonstrated commendable textile dyeing potential of fiber and cotton fabrics. The technology promises cost-effective prodigiosin development through sustainable waste feather-waste frying oil co-management.

Production, characterization, and bio-ethanologenic potential of a novel tripartite raw starch-digesting amylase from Priestia flexa 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 Priestia flexa strain with α-, ß-, and gluco-amylolytic activities and its potential for bioethanol production. Response surface statistics was employed to develop a suitable medium for improved production of the tripartite enzyme by submerged fermentation. The bioprocess selected raw starch (4.36%) Ca2+(2.71 g/L) and Zn2+ (0.0177 g/L) as significant variables which demonstrated a total RSDA activity of 7208.23 U/mL in a 5-L batch bioreactor. SDS/Native-PAGE determined the molecular weights of the 27-fold purified product as 25.2 kDa, 57.3 kDa, and 90.1 kDa for α-, ß-, and gluco-amylases, respectively. Optimum temperature and pH for enzyme activity were respectively broad at 30-70 °C and 4-11. The enzyme mixture demonstrated digestibility above 90% against a variety of raw starches and simultaneous fermentation of digestate with Saccharomyces cerevisiae generated 71.69 g/L of bioethanol within 24 h suggesting great potential for bioethanologenesis.

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

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, Aspergillus sydowii strain UCCM 00124 produced an L-asparaginase with a baseline acrylamide reduction potential of 64.5% in sweet potato chips. Plasma mutagenesis at atmospheric pressure and room temperature (ARTP) was employed to improve L-asparaginase production while artificial neural network embedded with genetic algorithm (ANN-GA) and global sensitivity analysis were used to identify and optimize process conditions for improved acrylamide reduction in sweet potato chips. The ARTP mutagenesis generated a valine-deficient mutant, Val-Asp-S-180-L with 2.5-fold L-asparaginase improvement. The ANN-GA hybrid evolutionary intelligence significantly improved process efficiency to 98.18% under optimized conditions set as 118.6 °C, 726.37 g/L asparagine content, 9.92 µg/mL L-asparaginase, 4.54% NaCl, and soaking time of 15 h without significant changes in sensory properties. The sensitivity index revealed initial asparagine content as the most sensitive parameter to the bioprocess. The enzyme demonstrated significant thermo-stability with Arrhenius deactivation rate constant, Kd, of 0.00562 min-1 and half-life, t1/2, of 123.35 min at 338 K. These conditions are recommended for sustainable healthier, and safer sweet potato chips processing in the food industry. Supplementary Information: The online version contains supplementary material available at 10.1007/s13197-023-05757-5.

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. Logistic and modified Gompertz models revealed significant fits for biomass formation, total protein, and substrate consumption models. Maximum specific growth rate (µmax = 0.362 h-1) of the bacterium in the optimized medium did not differ significantly from those in Luria-Bertani and trypticase soy broths. The aqueous two-phase system-purified 45.7 kDa alkaline protease retained 83% activity which improved with increasing sodium dodecyl sulfate concentration thus highlighting potential laundry application. Maximum enzyme activity occurred at 75ºC and pH 10.5 but was inhibited by 5 mM phenyl-methyl-sulfonyl fluoride suggesting a serine-protease nature.

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. This research re-directed enzyme localization to the extracellular milieu to reduce recovery cost using multi-objective response surface optimization of medium parameters. Results revealed a 1:0.32 extracellular:intracellular lipase ratio. Product formation kinetics, modeled by the Luedeking-Piret function, showed a significant switch from a completely growth-associated intracellular production to a predominantly non-growth-associated extracellular localization through medium optimization. Aqueous two-phase system purification conditions extracted 95.22% lipase with 72.36 purity, a Vmax of 370.37 µmolmin-1, and a Km of 0.63 mmol. Enzyme activity was enhanced by K+ and Ca2+ ions, stable in many organic solvents, except acetone, and had pH and temperature optima at 2.5-3.5 and 50 °C, respectively.

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. Volumetric biosurfactant production reached significantly high levels during prolonged stationary growth and specific urease activity. This suggests that glycolipopeptide biosynthesis may proceed through stationary phase transpeptidation of the glycolipid base. A high cross-correlation coefficient of 0.950 confirmed that substrate consumption and glycolipopeptide production occurred contemporaneously during the 66-h fermentation. The maximum biosurfactant concentration of 132.52 g/L, µmax of 0.292 h-1, qp of 1.674 g/gDCW/h, rp of 2.008 g/(Lh) and Yp/x of 4.413 g/g predicted by the selected logistic model and a unit cost of €0.57/g glycolipopeptide in the optimized medium may lead to technical and economic benefits.

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. Protoplast fusion of the wild strains generated Fusant-06 with improved anti-leukemic and acrylamide reduction potentials. Submerged fed-batch fermentation was preferred to batch and continuous modes on the basis of impressive techno-economics. Fusant-06 L-ASNase was purified by PEG/Na+ citrate aqueous two-phase system (ATPS) to 146.21-fold and global sensitivity analysis report revealed polymer molecular weight and citrate concentration as major determinants of yield and purification factor, respectively. The enzyme was characterized by molecular weight, amino acid profile, activity and stability to chemical agents. Michaelis-Menten kinetics, evaluated under optimum conditions gave Km, Vmax, Kcat, and Kcat/Km as 6.67 × 10-5 M, 1666.67 µmolmin-1 mg-1 protein, 3.88 × 104 min-1 and 5.81 × 108 M-1.min-1 respectively. In-vitro cytotoxicity of HL-60 cell lines by Fusant-06 L-ASNase improved significantly from their respective wild strains. Stability of Fusant-06 L-ASNase over a wide range of pH, temperature and NaCl concentration, coupled with its micromolar Km value, confers commercial and therapeutic value on the product. Free-radical scavenging and acrylamide reduction activities were intermediate and the conferred thermo-halo-stability could be exploited for sustainable clinical and food industry applications.

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

A strain of Stenotrophomonas acidaminiphila, 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. Kinetics of production by selected mutant modeled by logistic and modified Gompertz functions revealed higher specific growth rate in mutant than in the parent strain, likewise volumetric and specific productivities. Purification by PEG/Na+ citrate aqueous two-phase system recovered 73.87% yield and 52.55-fold of protease. Its activity was stable at 5-35% NaCl, 45-75°C, and was significantly enhanced by 1-15 mM sodium dodecyl sulfate (SDS). The protease was inhibited by low concentrations of phenyl-methyl-sulfonyl fluoride but was activated by 1-5 mM Mn2+ suggesting a manganese-dependent serine­protease. The 45.7 kDa thermo-halo-stable alkaline protease demonstrated keratinolytic and blood-stain removal potentials showing prospects in textile and detergent industries, respectively.

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. Consequently, this study was designed to characterise hepatitis B virus infection among outpatients in selected tertiary hospitals in the region. Methodology: Between June and August 2017, consenting nine hundred asymptomatic out-patients were enrolled and initially screened for HBV infection using one step Hepatitis B surface antigen (HBsAg) strip and subsequently re-tested using HBsAg and Hepatitis B core total antibody (anti-HBc) specific Enzyme-Linked Immunosorbent Assay (ELISA). Blood serum with detectable HBsAg were subsequently subjected to DNA extraction, S-gene amplification using a nested polymerase chain reaction (PCR) protocol, gel electrophoresis, sequencing and phylogenetic analysis. Results: Seroprevalence of HBsAg was 4.6% (95% CI 2.5-7.1) and anti-HBc was 10.1% (95% confidence interval (CI) 6.1-15.3). Of the 41 HBsAg positive samples subjected to DNA extraction and HBV S-gene specific PCR, only 6 (14.6%) yielded the expected ∼408bp band. Phylogenetic analysis based on HBV pre-S/S sequences identified all six typable samples as genotype E, subtype ayw4 of the West African clade. Conclusion: Results of the study confirm the presence and circulation of HBV genotype-E in the Niger-Delta region of Nigeria, thus corroborating the inclusion of the country in the Genotype E crescent. The authors advocate value-added HBV intervention in the region and the country at large.

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 Pseudomonas aeruginosa, 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. Glycolipopeptide model was predicted by a significant (P < 0.001, R 2 of 0.9923) quadratic function of the RSM with a mean squared error (MSE) of 3.6661. The neural network model, on the other hand, returned an R 2 value of 0.9964 with an MSE of 1.7844. From all error metrics considered, ANN glycolipopeptide model significantly (P < 0.01) outperformed RSM counterpart in predictive modeling capability. Optimization of factor levels for maximum glycolipopeptide concentration produced bioprocess conditions of 32 °C for temperature, 7.6 for pH, agitation speed of 130 rpm and a fermentation time of 66 h, at a combined desirability function of 0.872. The glycosylated lipid-tailed peptide demonstrated significant anti-bacterial activity (MIC = 8.125 µg/mL) against Proteus vulgaris, dose-dependent anti-biofilm activities against Escherichia coli (83%) and Candida dubliniensis (90%) in 24 h and an equally dose-dependent cytotoxic activity against human breast (MCF-7: IC50 = 65.12 µg/mL) and cervical (HeLa: IC50 = 16.44 µg/mL) cancer cell lines. The glycolipopeptide compound is recommended for further studies and trials for application in human cancer therapy.

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

Sequential optimization of bioprocess nutritional conditions for production of glutaminase-near-free L-asparaginase by Aspergillus candidus 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. Path of steepest ascent (PSA) and response surface methodology (RSM) of a Min-Run-Res V fractional factorial of a central composite rotatable design (CCRD) were employed to optimize factor levels towards improved enzyme activity. A multi-objective approach using desirability function generated through predictor importance and weighted coefficient methodology was adopted for optimization. The approach set optimum bioprocess conditions as 49.55 g/L molasses, 64.98% corn steep liquor, 44.23 g/L asparagine, 1.73 g/L potassium, 0.055 g/L manganese and 0.043 g/L chromium (III) ions, at a composite desirability of 0.943 and an L-asparaginase activity of 5216.95U. The Sephadex-200 partially-purified polypeptide had a specific activity of 476.84 U/mg; 0.087U glutaminase activity, 36.46% yield and 20-fold protein purification. Anti-cancer activity potentials of the catalytic poly-peptide were dose-dependent with IC50 (µg/mL): 4.063 (HL-60), 13.75 (HCT-116), 15.83 (HeLa), 11.68 (MCF-7), 7.61 (HepG-2). The therapeutic enzyme exhibited 15-fold more cytotoxicity to myeloid leukemia cell line than to normal (HEK 238 T) cell. Optimum temperature and pH for activity were within physiological range. However, significant interactions between exposure time and levels of each of temperature and pH made interpretations of residual enzyme activities difficult. The manganese-dependent L-asparaginase from Aspergillu s candidus UCCM 00117 is recommended for further anticancer drug investigations.

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 20.80 mg/L. The compound proved suitable for applications in emulsion stabilization in food, as well as in cosmetic and pharmaceutical formulations. Method: In the present study, Plackett-Burman design (PBD) and response surface method (RSM) were employed to screen and optimize concentrations of trace nutrients in the fermentation medium, to increase surfactant yield. Results: The PBD selected 5 out of the 12 screened significant trace nutrients. The RSM, on the other hand, resulted in the production of 84.44 g glycolipopeptide/L in the optimized medium containing 1.25 mg/L nickel, 0.125 mg/L zinc, 0.075 mg/L iron, 0.0104 mg/L boron, and 0.025 mg/L copper. Conclusion: Significant second-order quadratic models for biomass (P<0.05; adjusted R2=94.29%) and biosurfactant (R2=99.44%) responses suggest excellent goodness-of-fit of the models. However, their respective non-significant lack-of-fit (Biomass: F=1.28; P=0.418; Biosurfactant: F=1.20; P=0.446) test results indicate their adequacy to explain data variations in the experimental region. The glycolipopeptide is recommended for the formulation of inexpensive pharmaceutical products that require surface-active compounds.