Elshami Nourhan H, El-Housseiny Ghadir S, Yassien Mahmoud A, Hassouna Nadia A
Department of Microbiology and Immunology, Faculty of Pharmacy, Ain Shams University, Organization of African Unity St., POB: 11566, Abbassia, Cairo, Egypt.
Bioresour Bioprocess. 2025 Apr 10;12(1):32. doi: 10.1186/s40643-025-00862-z.
β-Glucanases are a series of glycoside hydrolases (GHs) that are of special interest for various medical and biotechnological applications. Numerous β-glucanases were produced by different types of microorganisms. Particularly, bacterial β-glucanases have the privilege of being stable, easily produced, and suitable for large-scale production. This study aimed for finding potent β-glucanase producing bacterial strains and optimizing its production. Soil samples from Egyptian governorates were screened for such strains, and 96 isolates were collected. The β-glucanase activity was qualitatively assessed and quantitatively measured using 3,5-dinitrosalicylic acid (DNS) method. The highest β-glucanase producing strain (0.74 U/ml) was identified as Streptomyces albogriseolus S13-1. The optimum incubation period and temperature, determined one-variable at a time, were estimated as 4 d and 45 ͦ C, respectively. Similarly, yeast β-glucan and beef extract were selected as the best carbon and nitrogen sources, with enzymatic activities of 0.74 and 1.12 U/ml, respectively. Other fermentation conditions were optimized through response surface methodology (RSM); D-optimal design (DOD) with a total of 28 runs. The maximum experimental β-glucanase activity (1.3 U/ml) was obtained with pH 6.5, inoculum volume of 0.5% v/v, agitation speed of 100 rpm, carbon concentration of 1% w/v, and nitrogen concentration of 0.11% w/v. This was 1.76-fold higher compared to unoptimized conditions. Using the same experimental matrix, an artificial neural network (ANN) was built to predict β-glucanase production by the isolated strain. Predicted β-glucanase levels by RSM and ANN were 1.79 and 1.32 U/ml, respectively. Both models slightly over-estimated production levels, but ANN showed higher predictivity and better performance metrics. The enzyme was partially purified through acetone precipitation, characterized, and immobilized on chitosan-coated iron oxide microparticles. The optimal pH and temperature for enzyme activity were 5 and 50 °C, respectively. The immobilized enzyme showed superior characters such as higher stability at temperatures 50, 60, and 70 °C compared to the free enzyme, and satisfactory reusability, losing only 30% of activity after 6 cycles of reuse.
β-葡聚糖酶是一类糖苷水解酶(GHs),在各种医学和生物技术应用中具有特殊意义。不同类型的微生物可产生多种β-葡聚糖酶。特别是,细菌β-葡聚糖酶具有稳定性好、易于生产且适合大规模生产的优势。本研究旨在寻找高效产β-葡聚糖酶的细菌菌株并优化其生产。对埃及各省份的土壤样本进行了此类菌株的筛选,共收集到96株分离株。采用3,5-二硝基水杨酸(DNS)法对β-葡聚糖酶活性进行了定性评估和定量测定。产β-葡聚糖酶最高的菌株(0. 《74 U/ml)被鉴定为浅灰链霉菌S13-1。一次确定一个变量,确定的最佳培养时间和温度分别为4天和45℃。同样,酵母β-葡聚糖和牛肉提取物被选为最佳碳源和氮源,酶活性分别为0.74和1.12 U/ml。通过响应面法(RSM)对其他发酵条件进行了优化;采用D-最优设计(DOD),共进行28次实验。在pH 6.5、接种量0.5% v/v、搅拌速度100 rpm、碳浓度1% w/v和氮浓度0.11% w/v的条件下,获得了最大实验β-葡聚糖酶活性(1.3 U/ml)。与未优化条件相比,这提高了1.76倍。使用相同的实验矩阵,构建了一个人工神经网络(ANN)来预测分离菌株的β-葡聚糖酶产量。RSM和ANN预测的β-葡聚糖酶水平分别为1.79和1.32 U/ml。两个模型都略微高估了产量水平,但ANN显示出更高的预测性和更好的性能指标。通过丙酮沉淀对该酶进行了部分纯化,对其进行了表征,并固定在壳聚糖包被的氧化铁微粒上。该酶活性的最佳pH和温度分别为5和50℃。与游离酶相比,固定化酶表现出优异的特性,如在50、60和70℃的温度下具有更高的稳定性,以及令人满意的可重复使用性,在重复使用6个循环后仅损失30%的活性。