Optimization of fermentation conditions for enhancing extracellular production of L-asparaginase, an anti-leukemic agent, by newly isolated Streptomyces brollosae NEAE-115 using solid state fermentation

A sustainable green-approach for biofabrication of chitosan nanoparticles, optimization, characterization, its antifungal activity against phytopathogenic Fusarium culmorum and antitumor activity

Chitosan is a natural non-toxic, biocompatible, biodegradable, and mucoadhesive polymer. It also has a broad spectrum of applications such as agriculture, medical fields, cosmetics and food industries. In this investigation, chitosan nanoparticles were produced by an aqueous extract of Cympopogon citratus leaves as a reducing agent. According to the SEM and TEM micrographs, CNPs had a spherical shape, and size ranging from 8.08 to 12.01 nm. CNPs have a positively charged surface with a Zeta potential of + 26 mV. The crystalline feature of CNPs is determined by X-ray diffraction. There are many functional groups, including C꞊C, CH2-OH, C-O, C-S, N-H, CN, CH and OH were detected by FTIR analysis. As shown by the thermogravimetric study, CNPs have a high thermal stability. For the optimization of the green synthesis of CNPs, a Face centered central composite design (FCCCD) with 30 trials was used. The maximum yield of CNPs (13.99 mg CNPs/mL) was produced with chitosan concentration 1.5%, pH 4.5 at 40 °C, and incubation period of 30 min. The antifungal activity of CNPs was evaluated against phytopathogenic fungus; Fusarium culmorum. A 100% rate of mycelial growth inhibition was gained by the application of 20 mg CNPs/mL. The antitumor activity of the green synthesized CNPs was examined using 6 different cell lines, the viability of the cells reduced when the concentration of green synthesized CNPs increased, the IC50 dose of the green synthesized CNPs on the examined cell lines HePG-2, MCF-7, HCT-116, PC-3, Hela and WI-38 was 36.25 ± 2.3, 31.21 ± 2.2, 67.45 ± 3.5, 56.30 ± 3.3, 44.62 ± 2.6 and 74.90 ± 3.8; respectively.

Bionanofactory for green synthesis of collagen nanoparticles, characterization, optimization, in-vitro and in-vivo anticancer activities

Collagen nanoparticles (collagen-NPs) are promising biological polymer nanoparticles due to their exceptional biodegradability and biocompatibility. Collagen-NPs were bio-fabricated from pure marine collagen using the cell-free supernatant of a newly isolated strain, Streptomyces sp. strain NEAA-3. Streptomyces sp. strain NEAA-3 was identified as Streptomyces plicatus strain NEAA-3 based on its cultural, morphological, physiological properties and 16S rRNA sequence analysis. The sequence data has been deposited under accession number OR501412.1 in the GenBank database. The face-centered central composite design (FCCD) was used to improve collagen-NPs biosynthesis. The maximum yield of collagen-NPs was 9.33 mg/mL with a collagen concentration of 10 mg/mL, an initial pH of 7, an incubation time of 72 h, and a temperature of 35 °C. Using the desirability function approach, the collagen-NPs biosynthesis obtained after FCCD optimization (9.53 mg/mL) was 3.92 times more than the collagen-NPs biosynthesis obtained before optimization process (2.43 mg/mL). The TEM analysis of collagen-NPs revealed hollow sphere nanoscale particles with an average diameter of 33.15 ± 10.02 nm. FTIR spectra confirmed the functional groups of the collagen, collagen-NPs and the cell-free supernatant that are essential for the efficient capping of collagen-NPs. The biosynthesized collagen-NPs exhibited antioxidant activity and anticancer activity against HeP-G2, MCF-7 and HCT116 cell lines. Collagen-NPs assessed as an effective drug loading carrier with methotrexate (MTX), a chemotherapeutic agent. The TEM analysis revealed that the average size of MTX-loaded collagen-NPs was 35.4 ± 8.9 nm. The percentages of drug loading (DL%) and encapsulation efficiency (EE%) were respectively 22.67 and 45.81%.

Process optimization for gold nanoparticles biosynthesis by Streptomyces albogriseolus using artificial neural network, characterization and antitumor activities

Gold nanoparticles (GNPs) are highly promising in cancer therapy, wound healing, drug delivery, biosensing, and biomedical imaging. Furthermore, GNPs have anti-inflammatory, anti-angiogenic, antioxidants, anti-proliferative and anti-diabetic effects. The present study presents an eco-friendly approach for GNPs biosynthesis using the cell-free supernatant of Streptomyces albogriseolus as a reducing and stabilizing agent. The biosynthesized GNPs have a maximum absorption peak at 540 nm. The TEM images showed that GNPs ranged in size from 5.42 to 13.34 nm and had a spherical shape. GNPs have a negatively charged surface with a Zeta potential of - 24.8 mV. FTIR analysis identified several functional groups including C-H, -OH, C-N, amines and amide groups. The crystalline structure of GNPs was verified by X-ray diffraction and the well-defined and distinct diffraction rings observed by the selected area electron diffraction analysis. To optimize the biosynthesis of GNPs using the cell-free supernatant of S. albogriseolus, 30 experimental runs were conducted using central composite design (CCD). The artificial neural network (ANN) was employed to analyze, validate, and predict GNPs biosynthesis compared to CCD. The maximum experimental yield of GNPs (778.74 μg/mL) was obtained with a cell-free supernatant concentration of 70%, a HAuCl4 concentration of 800 μg/mL, an initial pH of 7, and a 96-h incubation time. The theoretically predicted yields of GNPs by CCD and ANN were 809.89 and 777.32 μg/mL, respectively, which indicates that ANN has stronger prediction potential compared to the CCD. The anticancer activity of GNPs was compared to that of doxorubicin (Dox) in vitro against the HeP-G2 human cancer cell line. The IC50 values of Dox and GNPs-based treatments were 7.26 ± 0.4 and 22.13 ± 1.3 µg/mL, respectively. Interestingly, treatments combining Dox and GNPs together showed an IC50 value of 3.52 ± 0.1 µg/mL, indicating that they targeted cancer cells more efficiently.

Green synthesis of collagen nanoparticles by Streptomyces xinghaiensis NEAA-1, statistical optimization, characterization, and evaluation of their anticancer potential

Collagen nanoparticles (collagen-NPs) are promising biopolymeric nanoparticles due to their superior biodegradability and biocompatibility. The low immunogenicity and non-toxicity of collagen-NPs makes it preferable for a wide range of applications. A total of eight morphologically distinct actinomycetes strains were newly isolated from various soil samples in Egypt. The cell-free supernatants of these strains were tested for their ability. These strains' cell-free supernatants were tested for their ability to synthesize collagen-NPs. Five isolates had the ability to biosynthesize collagen-NPs. Among these, a potential culture, Streptomyces sp. NEAA-1, was chosen and identified as Streptomyces xinghaiensis NEAA-1 based on 16S rRNA sequence analysis as well as morphological, cultural and physiological properties. The sequence data has been deposited at the GenBank database under the accession No. OQ652077.1. Face-centered central composite design (FCCD) has been conducted to maximize collagen-NPs biosynthesis. Maximum collagen-NPs was 8.92 mg/mL under the condition of 10 mg/mL of collagen concentration, initial pH 7, incubation time of 48 h and temperature of 35 °C. The yield of collagen-NPs obtained via FCCD optimization (8.92 mg/mL) was 3.32-fold compared to the yield obtained under non-optimized conditions (2.5 mg/mL). TEM analysis of collagen-NPs showed hollow sphere nanoscale particles with mean of 32.63 ± 14.59 nm in diameter. FTIR spectra showed major peaks of amide I, amide II and amide III of collagen and also the cell-free supernatant involved in effective capping of collagen-NPs. The biosynthesized collagen-NPs exhibited anti-hemolytic, antioxidant and cytotoxic activities. The inhibitory concentrations (IC50) against MCF-7, HeP-G2 and HCT116 cell lines were 11.62 ± 0.8, 19.60 ± 1.2 and 41.67 ± 2.2 µg/mL; respectively. The in-vivo investigation showed that collagen-NPs can suppress Ehrlich ascites carcinoma (EAC) growth in mice. The collagen-NPs/DOX combination treatment showed considerable tumor growth suppression (95.58%). Collagen-NPs evaluated as nanocarrier with a chemotherapeutic agent, methotrexate (MTX). The average size of MTX loaded collagen-NPs was 42.73 ± 3.5 nm. Encapsulation efficiency percentage (EE %) was 48.91% and drug loading percentage (DL %) was 24.45%.

Application of sequential design for enhanced L-asparaginase synthesis from Ganoderma australe GPC191

With an increasing demand for L-asparaginase in pharmaceutical and food sectors for its cytostatic and acrylamide-reducing qualities, there's a need to discover novel, highly productive enzyme sources with improved pharmacokinetic profiles. Keeping this in mind, the present study aimed at maximizing the potential of Ganoderma australe GPC191 to produce L-asparaginase by fermentation medium optimization using statistical validation. Of the 11 physicochemical parameters evaluated under submerged fermentation conditions through one-factor-at-a-time approach and Plackett-Burman design, only four parameters (inoculum load, L-asparagine, soybean meal, and initial pH) influenced L-asparaginase production, significantly (p < 0.001). The optimal levels and interaction effects of these on the overall production were further evaluated by the central composite rotatable design of response surface methodology. Post-optimization, 27.34 U/mL was predicted as the maximum activity at pH 7 with 5n inoculum load and 15 g/L each of L-asparagine and soybean meal. Experimental validation yielded an activity of 28.52 U/mL, indicating an overall 18.17-fold increase from the unoptimized stage. To our knowledge, this is the first report signifying the L-asparaginase production aptitude of G. australe with sequential statistical validation using agricultural waste, which can serve as a model to enhance its yields, offering a sustainable and cost-effective solution for industrial application.

Artificial neural network approach for prediction of AuNPs biosynthesis by Streptomyces flavolimosus, characterization, antitumor potency in-vitro and in-vivo against Ehrlich ascites carcinoma

Gold nanoparticles (AuNPs) have emerged as promising and versatile nanoparticles for cancer therapy and are widely used in drug and gene delivery, biomedical imaging, diagnosis, and biosensors. The current study describes a biological-based strategy for AuNPs biosynthesis using the cell-free supernatant of Streptomyces flavolimosus. The biosynthesized AuNPs have an absorption peak at 530-535 nm. The TEM images indicate that AuNPs were spherical and ranged in size from 4 to 20 nm. The surface capping molecules of AuNPs are negatively charged, having a Zeta potential of - 10.9 mV. FTIR analysis revealed that the AuNPs surface composition contains a variety of functional groups as -OH, C-H, N-, C=O, NH3+, amine hydrochloride, amide group of proteins, C-C and C-N. The bioprocess variables affecting AuNPs biosynthesis were optimized by using the central composite design (CCD) in order to maximize the AuNPs biosynthesis. The maximum yield of AuNPs (866.29 µg AuNPs/mL) was obtained using temperature (35 °C), incubation period (4 days), HAuCl4 concentration (1000 µg/mL) and initial pH level 6. Comparison was made between the fitness of CCD versus Artificial neural network (ANN) approach based on their prediction and the corresponding experimental results. AuNPs biosynthesis values predicted by ANN exhibit a more reasonable agreement with the experimental result. The anticancer activities of AuNPs were assessed under both in vitro and in vivo conditions. The results revealed a significant inhibitory effect on the proliferation of the MCF-7 and Hela carcinoma cell lines treated with AuNPs with IC50 value of 13.4 ± 0.44 μg/mL and 13.8 ± 0.45 μg/mL for MCF-7 and Hela cells; respectively. Further, AuNPs showed potential inhibitory effect against tumor growth in tumor-bearing mice models. AuNPs significantly reduced the tumor volume, tumor weight, and decreased number of viable tumor cells in EAC bearing mice.

Green fabrication of chitosan nanoparticles using Lavendula angustifolia, optimization, characterization and in‑vitro antibiofilm activity

Chitosan nanoparticles (CNPs) are promising polymeric nanoparticles with exceptional physicochemical, antimicrobial and biological characteristics. The CNPs are preferred for a wide range of applications in the food industry, cosmetics, agriculture, medical, and pharmaceutical fields due to their biocompatibility, biodegradability, eco-friendliness, and non-toxicity. In the current study, a biologically based approach was used to biofabricate CNPs using an aqueous extract of Lavendula angustifolia leaves as a reducing agent. The TEM images show that the CNPs were spherical in shape and ranged in size from 7.24 to 9.77 nm. FTIR analysis revealed the presence of several functional groups, including C-H, C-O, CONH₂, NH₂, C-OH and C-O-C. The crystalline nature of CNPs is demonstrated by X-ray diffraction. The thermogravimetric analysis revealed that CNPs are thermally stable. The CNPs' surface is positively charged and has a Zeta potential of 10 mV. For optimising CNPs biofabrication, a face-centered central composite design (FCCCD) with 50 experiments was used. The artificial intelligence-based approach was used to analyse, validate, and predict CNPs biofabrication. The optimal conditions for maximum CNPs biofabrication were theoretically determined using the desirability function and experimentally verified. The optimal conditions that maximize CNPs biofabrication (10.11 mg/mL) were determined to be chitosan concentration 0.5%, leaves extract 75%, and initial pH 4.24. The antibiofilm activity of CNPs was evaluated in‑vitro. The results show that 1500 μg/mL of CNPs suppressed P. aeruginosa, S. aureus and C. albicans biofilm formation by 91.83 ± 1.71%, 55.47 ± 2.12% and 66.4 ± 1.76%; respectively. The promising results of the current study in biofilm inhibition by necrotizing biofilm architecture, reducing its significant constituents and inhibiting microbial cell proliferation encourage their use as natural biosafe and biocompatible anti-adherent coating in antibiofouling membranes, medical bandage/tissues and food packaging materials.

Artificial intelligence-based optimization for chitosan nanoparticles biosynthesis, characterization and in‑vitro assessment of its anti-biofilm potentiality

Chitosan nanoparticles (CNPs) are promising biopolymeric nanoparticles with excellent physicochemical, antimicrobial, and biological properties. CNPs have a wide range of applications due to their unique characteristics, including plant growth promotion and protection, drug delivery, antimicrobials, and encapsulation. The current study describes an alternative, biologically-based strategy for CNPs biosynthesis using Olea europaea leaves extract. Face centered central composite design (FCCCD), with 50 experiments was used for optimization of CNPs biosynthesis. The artificial neural network (ANN) was employed for analyzing, validating, and predicting CNPs biosynthesis using Olea europaea leaves extract. Using the desirability function, the optimum conditions for maximum CNPs biosynthesis were determined theoretically and verified experimentally. The highest experimental yield of CNPs (21.15 mg CNPs/mL) was obtained using chitosan solution of 1%, leaves extract solution of 100%, initial pH 4.47, and incubation time of 60 min at 53.83°C. The SEM and TEM images revealed that CNPs had a spherical form and varied in size between 6.91 and 11.14 nm. X-ray diffraction demonstrates the crystalline nature of CNPs. The surface of the CNPs is positively charged, having a Zeta potential of 33.1 mV. FTIR analysis revealed various functional groups including C-H, C-O, CONH2, NH2, C-OH and C-O-C. The thermogravimetric investigation indicated that CNPs are thermally stable. The CNPs were able to suppress biofilm formation by P. aeruginosa, S. aureus and C. albicans at concentrations ranging from 10 to 1500 µg/mL in a dose-dependent manner. Inhibition of biofilm formation was associated with suppression of metabolic activity, protein/exopolysaccharide moieties, and hydrophobicity of biofilm encased cells (r ˃ 0.9, P = 0.00). Due to their small size, in the range of 6.91 to 11.14 nm, CNPs produced using Olea europaea leaves extract are promising for applications in the medical and pharmaceutical industries, in addition to their potential application in controlling multidrug-resistant microorganisms, especially those associated with post COVID-19 pneumonia in immunosuppressed patients.

Production and optimization of l-asparaginase by Streptomyces koyangensis SK4 isolated from Arctic sediment

Actinomycetes isolated from the Arctic sediment were evaluated for the production of the enzyme l-asparaginase, an enzyme used to treat acute lymphoblastic leukemia. The most potent strain Streptomyces koyangensis SK4 was selected for l-asparaginase enzyme production by submerged fermentation. The effect of various fermentation parameters on enzyme production was analyzed statistically using the Plackett-Burman design and response surface method. Effects of eight parameters including temperature, pH, incubation time, inoculum size, agitation speed, the concentration of starch, l-asparagine, and yeast extract were studied on l-asparaginase production by the Arctic isolate S. koyangensis SK4. Factors such as temperature, pH, incubation time, agitation speed, and l-asparagine concentration were found to be important factors influencing  l-asparaginase production. Maximum enzyme activity of 136 IU/ml was obtained at 20°C on the seventh day of incubation in the asparagine dextrose broth maintained at pH 7.5, agitation speed 125 rpm, and l-asparagine concentration of 7.5 g/L. The statistical optimization method described in this study proved effective for increasing the l-asparaginase production by Arctic actinomycetes.

Improvement of L-asparaginase, an Anticancer Agent of Aspergillus arenarioides EAN603 in Submerged Fermentation Using a Radial Basis Function Neural Network with a Specific Genetic Algorithm (RBFNN-GA)

The present study aimed to optimize the production of L-asparaginase from Aspergillus arenarioides EAN603 in submerged fermentation using a radial basis function neural network with a specific genetic algorithm (RBFNN-GA) and response surface methodology (RSM). Independent factors used included temperature (x1), pH (x2), incubation time (x3), and soybean concentration (x4). The coefficient of the predicted model using the Box–Behnken design (BBD) was R2 = 0.9079 (p < 0.05); however, the lack of fit was significant indicating that independent factors are not fitted with the quadratic model. These results were confirmed during the optimization process, which revealed that the standard error (SE) of the predicted model was 11.65 while the coefficient was 0.9799, at which 145.35 and 124.54 IU mL−1 of the actual and predicted enzyme production was recorded at 34 °C, pH 8.5, after 7 days and with 10 g L−1 of organic soybean powder concentrations. Compared to the RBFNN-GA, the results revealed that the investigated factors had benefits and effects on L-asparaginase, with a correlation coefficient of R = 0.935484, and can classify 91.666667% of the test data samples with a better degree of precision; the actual values are higher than the predicted values for the L-asparaginase data.

Green synthesis of chitosan nanoparticles, optimization, characterization and antibacterial efficacy against multi drug resistant biofilm-forming Acinetobacter baumannii

Chitosan nanoparticles (CNPs) are promising versatile cationic polymeric nanoparticles, which have received growing interest over last few decades. The biocompatibility, biodegradability, environmental safety and non-toxicity of the chitosan nanoparticles makes it preferred for a wide range of biological applications including agriculture, medical and pharmaceutical fields. In this study, CNPs were biosynthesized by aqueous extract of Eucalyptus globulus Labill fresh leaves as bio-reductant. Box-Behnken design in 29 experimental runs was used for optimization of different factors affecting the production of CNPs. The maximum yield of CNPs was 9.91 mg/mL at pH of 4.5, chitosan concentration of 1%, incubation time of 60 min and temperature of 50 °C. The crystallinity, particle size and morphology of the biosynthesized CNPs were characterized. The CNPs possess a positively charged surface of 31.1 mV. The SEM images of the CNPs confirms the formation of spherical form with smooth surface. The TEM images show CNPs were spherical in shape and their size range was between 6.92 and 10.10 nm. X-ray diffraction indicates the high degree of CNPs crystallinity. FTIR analysis revealed various functional groups of organic compounds including NH, NH2, C-H, C-O, C-N, O-H, C-C, C-OH and C-O-C. The thermogravimetric analysis results revealed that CNPs are thermally stable. The antibacterial activity of CNPs was determined against pathogenic multidrug-resistant bacteria, Acinetobacter baumannii. The diameters of the inhibition zones were 12, 16 and 30 mm using the concentrations of 12.5, 25 and 50 mg/mL; respectively. When compared to previous studies, the biosynthesized CNPs produced using an aqueous extract of fresh Eucalyptus globulus Labill leaves have the smallest particle sizes (with a size range between 6.92 and 10.10 nm). Consequently, it is a promising candidate for a diverse range of medical applications and pharmaceutical industries.

Statistical optimization for simultaneous removal of methyl red and production of fatty acid methyl esters using fresh alga Scenedesmus obliquus

Microalgae are a diverse group of microorganisms, the majority of which are photosynthetic in nature. Microalgae have different applications, the most important of which is the biological treatment of wastewater. Microalgae grow in various types of wastewater, such as wastewater polluted by Azo dyes, due to microalgae using wastewater as a culture medium, which contains many nutrients like nitrogen, phosphate, and carbon sources. Microalgae grow in various types of wastewater, such as wastewater polluted by Azo dyes, due to microalgae using wastewater as a culture medium, which contains many nutrients like nitrogen, phosphate, and carbon sources. So, microalgae are used for bioremediation of wastewater due to the efficiency of growing in wastewater and for the high production of lipids followed by trans-esterification to biodiesel. Face-centered central composite design (FCCCD) was used to determine the factors that have the most significant impact on the simultaneous decolorization of methyl red and lipid production by the fresh green alga Scenedesmus obliquus. The predicted results indicated that the alga decolorized 70.15% methyl red and produced 20.91% lipids by using 1 g/L nitrogen, an incubation time of 10 days, a pH of 8, and the concentration of methyl red is 17.65 mg/L. The dry biomasses of S. obliquus were also examined by SEM and FTIR before and after treatment with methyl red. SEM and FTIR showed that the properties of dry S. obliquus were altered after the biosorption of methyl red. According to GC-MS analysis of hexane extracts of S. obliquus, the lipid profile differed before and after methyl red decolorization. The results proved that it is possible to use S. obliquus to remove dyes and produce renewable fuels such as biodiesel. The novelty of this study is that this is the first time in which the effect of nitrogen concentrations in the medium used for algal growth on the removal of dye has been studied.

Optimization, Purification and Antitumor Activity of Kodamaea ohmeri ANOMY L-Asparaginase Isolated from Banana Peel

OBJECTIVE

L-Asparaginase is an important enzyme that converts L-asparagine to L-aspartate and ammonia. Microbial L-asparaginase has important applications as anticancer and food processing agents.

METHODS

This study reported the isolation, screening of a local yeast isolate from banana peel for L-asparaginase production using submerged fermentation, optimization of the production, purification, and anticancer assay of L-asparaginase. The yeast isolate was identified as Kodamaea ohmeri ANOMY based on the analysis of nuclear large subunit (26S) rDNA partial sequences. It was a promising L-asparaginase producer with a specific activity of 3059±193 U/mg in a non-optimized medium. The classical one-variable-at-a-time method was used to optimize the production medium components, and it was found that the elimination of K2HPO4 from the medium increased L-asparaginase specific activity (3100.90±180 U/mg).

RESULTS

Statistical optimization of L-asparaginase production was done using Plackett-Burman and Box-Behnken designs. The production medium for the maximum L-asparaginase specific activity (8500±578U/mg) was as follows (g/L): L-asparagine (7.50), NaNO3 (0.50), MgSO₄.7H₂O (0.80), KCl (0.80) associated with an incubation period of 5 days, inoculum size of 5.60 %, and pH (7.0). The optimization process increased L-asparaginase production by 2.78-fold compared to the non-optimized medium. L-Asparaginase was purified using ammonium sulphate precipitation followed by gel filtration on a Sephadex G-100 column. Its molecular weight was 66 KDa by SDS-PAGE analysis.

CONCLUSION

The cell morphology technique was used to evaluate the anticancer activity of L-asparaginase against three different cell lines. L-Asparaginase inhibited the growth of HepG-2, MCF-7, and HCT-116 cells at a concentration of 20, 50, and 60 μL, respectively.

A Comprehensive Review on Valorization of Agro-Food Industrial Residues by Solid-State Fermentation

Agro-food industrial residues (AFIRs) are generated in large quantities all over the world. The vast majority of these wastes are lignocellulosic wastes that are a source of value-added products. Technologies such as solid-state fermentation (SSF) for bioconversion of lignocellulosic waste, based on the production of a wide range of bioproducts, offer both economic and environmental benefits. The versatility of application and interest in applying the principles of the circular bioeconomy make SSF one of the valorization strategies for AFIRs that can have a significant impact on the environment of the wider community. Important criteria for SSF are the selection of the appropriate and compatible substrate and microorganism, as well as the selection of the optimal process parameters for the growth of the microorganism and the production of the desired metabolites. This review provides an overview of the management of AFIRs by SSF: the current application, classification, and chemical composition of AFIRs; the catalytic function and potential application of enzymes produced by various microorganisms during SSF cultivation on AFIRs; the production of phenolic compounds by SSF; and a brief insight into the role of SSF treatment of AFIRs for feed improvement and biofuel production.

Production and Characterization of L-Asparaginases of Streptomyces Isolated from the Arauca Riverbank (Colombia)

Introduction:

L-asparaginase, is known as an anti-cancer agent, mainly used in acute lymphoblastic leukemia, which prevents the proliferation of tumor cells. This study shows that there are unexplored regions in Colombia that can be sources of obtaining this enzyme and that the optimization of the production of L-asparaginase from native isolates can be determined in the search for alternatives to commercial drugs.

Materials and Methods:

Selection and identification ofStreptomycesamongActinobacteriaisolated from the Arauca riverbank for L-asparaginase producers are described. In addition, the effect of carbon and nitrogen sources, pH, temperature and agitation rate are studied for L-asparaginase activity in liquid culture using Plackett-Burman design and Taguchi methodology. Kinetic characterization of a purified L-asparaginase and its cytotoxic potential are evaluated too.

Results:

Seven of seventy-eight actinobacterial strains were selected as L-asparaginase producingStreptomycesshowing a high L-asparaginase/L-glutaminase ratio in liquid culture with lactose as substrate. The strain 112 identified asStreptomyces lacticiproducenswas chosen for L-asparaginase production at these culture conditions: lactose 0.25%, L-asparagine 0,015%, malt extract 0,015%, pH 7.36, 32°C and 130 rpm. Enzymatic studies of the purified L-asparaginase showed that the optimal pH and temperature were 6 and 37.5°C, respectively. This purified enzyme had an IC50of 36.74 µg/mL on THP-1 cells.

Conclusion:

S. lacticiproducensisolated from the Arauca riverbank is a new source for the production of a high activity L-asparaginase, creating expectation of its availability as a drug for the acute lymphoblastic leukemia treatment.

The Statistical Optimisation of Recombinant β-glucosidase Production through a Two-Stage, Multi-Model, Design of Experiments Approach

β-glucosidases are a class of enzyme that are widely distributed in the living world, with examples noted in plants, fungi, animals and bacteria. They offer both hydrolysis and synthesis capacity for a wide range of biotechnological processes. However, the availability of native, or the production of recombinant β-glucosidases, is currently a bottleneck in the widespread industrial application of this enzyme. In this present work, the production of recombinant β-glucosidase from Streptomyces griseus was optimised using a Design of Experiments strategy, comprising a two-stage, multi-model design. Three screening models were comparatively employed: Fractional Factorial, Plackett-Burman and Definitive Screening Design. Four variables (temperature, incubation time, tryptone, and OD600 nm) were experimentally identified as having statistically significant effects on the production of S.griseus recombinant β-glucosidase in E. coli BL21 (DE3). The four most influential variables were subsequently used to optimise recombinant β-glucosidase production, employing Central Composite Design under Response Surface Methodology. Optimal levels were identified as: OD600 nm, 0.55; temperature, 26 °C; incubation time, 12 h; and tryptone, 15 g/L. This yielded a 2.62-fold increase in recombinant β-glucosidase production, in comparison to the pre-optimised process. Affinity chromatography resulted in homogeneous, purified β-glucosidase that was characterised in terms of pH stability, metal ion compatibility and kinetic rates for p-nitrophenyl-β-D-glucopyranoside (pNPG) and cellobiose catalysis.

The Goldilocks Approach: A Review of Employing Design of Experiments in Prokaryotic Recombinant Protein Production

The production of high yields of soluble recombinant protein is one of the main objectives of protein biotechnology. Several factors, such as expression system, vector, host, media composition and induction conditions can influence recombinant protein yield. Identifying the most important factors for optimum protein expression may involve significant investment of time and considerable cost. To address this problem, statistical models such as Design of Experiments (DoE) have been used to optimise recombinant protein production. This review examines the application of DoE in the production of recombinant proteins in prokaryotic expression systems with specific emphasis on media composition and culture conditions. The review examines the most commonly used DoE screening and optimisation designs. It provides examples of DoE applied to optimisation of media and culture conditions.

Protease production by the keratinolytic Bacillus sp. CL18 through feather bioprocessing

Bacillus sp. CL18 was investigated to propose a bioprocess for protease production using feathers as organic substrate. In feather broth (FB), containing feathers as sole organic substrate (1-100 g l^-1), maximal protease production was observed at 30 g l^-1 (FB30) after 6 days of cultivation, whereas increased feather concentrations negatively affected protease production and feather degradation. Protease production peaks were always observed earlier during cultivations than maximal feather degradation. In FB30, 80% of initial feathers mass were degraded after 7 days. Addition of glucose, sucrose, starch, yeast extract (2 g l^-1), CaCl₂, or MgCl₂ (10 mmol l^-1) to FB30 decreased protease production and feather degradation. FB30 supplementation with NH₄Cl (1 g l^-1) resulted in less apparent negative effects on protease production, whereas peptone (2 g l^-1) increased protease yields earlier during cultivations (3 days). Through a central composite design employed to investigate the effects of peptone and NH₄Cl (0.5-4.5 g l^-1) on protease production and feather degradation, FB30 supplementation with peptone and NH₄Cl (0.5-1.1 g l^-1) increased protease production within a shorter cultivation time (5 days) and hastened complete feather degradation (6 days). Feather bioconversion concurs with sustainable production of value-added products.