耐盐性谷氨酰胺酶在Bacillus subtilis 168中的整合表达

微生物质粒过表达外源基因,会由于质粒分离稳定性低、种子培养基中需添加抗生素等原因,限制其在工业生产中的应用。为了得到一株可用于工业生产谷氨酰胺酶的菌株,选择食品安全级Bacillus subtilis 168作为宿主,将来源于Micrococcus luteus K-3的编码耐高浓度盐的谷氨酰胺酶基因(Mglu)插入到其染色体上进行整合表达。选择了2个内源性蛋白酶基因作为整合表达位点,通过lox序列的重组消除抗性基因,得到无抗性基因的重组谷氨酰胺酶表达菌株。遗传稳定性研究表明,在不添加抗生素的条件下,通过连续传代重组菌株并测定发酵酶活,发现重组菌株连续传42代时,酶活基本不变。随后,采用5 L发酵罐对重组菌株进行分批补料发酵,最高酶活达到了41.5 U/mL。本研究对提高谷氨酰胺酶重组菌株遗传稳定性提供了借鉴。     

1株源自如皋火腿的产谷氨酰胺酶腐生葡萄球菌RG-2催化条件的优化

谷氨酰胺酶与发酵肉制品的鲜味形成有关,且能够降低产品的酸度,改善口感。利用从如皋火腿中分离得到的1株产谷氨酰胺酶的腐生葡萄球RG-2,通过单因素试验及响应曲面设计,研究pH、温度、NaCl浓度等因素对菌株RG-2的谷氨酰胺酶催化活力的影响。结果表明:最佳条件为pH6.7、温度43℃、NaCl浓度3.1%,此条件下谷氨酰胺酶酶活达到40.2 U/mL。     

Purification of Glutaminase from Zygosaccharomyces rouxii in Polyethylene Glycol– Sodium Sulphate Aqueous Two-Phase System

L-glutaminase (EC 3.5.1.2) produced from Zygosaccharomyces rouxii NRRL-Y 2547 was partitioned in an aqueous two phase system comprising PEG 2000 and sodium sulphate. The effects of tie line length (TLL), pH, broth loading (BL), volume ratio, and neutral salt concentration on enzyme partitioning and purification were investigated. The optimal condition for the partitioning of glutaminase was obtained through response surface methodology and obtained the partition coefficient and yield of 12.99 and 95.12%, respectively. The purification factor of 5.59 and selectivity of 6.52 were achieved at the optimal condition.     

Enrichment of glutaminase production by Bacillus subtilis RSP‐GLU in submerged cultivation based on neural network—genetic algorithm approach

BACKGROUND: Owing to the importance of glutaminase in biotech product production, its production with isolated Bacillus subtilis RSP‐GLU (MTCC 9727) was investigated. Fermentation factors play an important role in product enhancement. Hence, glutaminase production was optimized using an artificial neural network (ANN) coupled genetic algorithm (GA). RESULTS: A ‘6–12–1’ topology ANN was constructed to identify the nonlinear relationship between fermentation factors and enzyme yield. ANN‐predicted values were optimized for glutaminase production using a GA. The overall mean absolute predictive error (MAPE) and the mean square errors (MSE) were observed to be 0.00125 and 1.77 and 0.002 and 3.06 for training and testing, respectively. The goodness of neural network prediction (coefficient of R²) was found to be 0.996. The maximum interactive impact on glutaminase production was noted with rpm versus medium volume. The use of ANN–GA hybrid methodology resulted in a significant improvement (47%) in glutaminase yield. CONCLUSION: Five different optimum fermentation conditions out of 500 revealed maximum enzyme production. Glutaminase enzyme production in this Bacillus subtilis RSP‐GLU is strongly influenced by aeration of the fermentation. A hybrid ANN‐GA effectively identifies the different fermentation conditions for optimum production of enzyme in a given large set of conditions. Copyright © 2009 Society of Chemical Industry     

Targeting Glutamine Induces Apoptosis: A Cancer Therapy Approach

Glutamine metabolism has been proved to be dysregulated in many cancer cells, and is essential for proliferation of most cancer cells, which makes glutamine an appealing target for cancer therapy. In order to be well used by cells, glutamine must be transported to cells by specific transporters and converted to glutamate by glutaminase. There are currently several drugs that target glutaminase under development or clinical trials. Also, glutamine metabolism restriction has been proved to be effective in inhibiting tumor growth both in vivo and vitro through inducing apoptosis, growth arrest and/or autophagy. Here, we review recent researches about glutamine metabolism in cancer, and cell death induced by targeting glutamine, and their potential roles in cancer therapy.     

大豆分离蛋白的谷氨酰胺酶水解及其产物抗氧化性的研究

利用谷氨酰胺酶(EC3.2.1.5)对大豆分离蛋白进行限制性脱酰胺和水解处理,以SDS-PAGE及排阻色谱分析评价产物的蛋白质降解情况,并制备具有较低脱酰胺度的脱酰胺大豆分离蛋白产物。在大豆分离蛋白浓度5%(w/v)、谷氨酰胺酶添加量400U/kg酪蛋白、37℃的条件下分别反应12、24、36h,制得脱酰胺度分别为3.5%、5.6%、6.6%,水解度分别为0.9%、2.7%、3.5%的脱酰胺大豆分离蛋白。评价这3种脱酰胺大豆分离蛋白产物对Fe2+的螯合能力以及DPPH自由基的清除能力,结果表明,脱酰胺大豆分离蛋白产物对Fe2+的螯合能力以及对DPPH自由基的清除能力高于大豆分离蛋白,并随着脱酰胺度的增加而提高。     

厚味γ-Glu-Ile肽的谷氨酰胺酶酶法合成

Glu-Ile可通过解淀粉芽孢杆菌源谷氨酰胺酶酶法合成。结果表明:反应得最佳底物浓度比Gln∶Ile为100∶200(mmol/L∶mmol/L),最适pH值在9~10之间,最适温度为37℃,反应时间为10h,最大产量为21.58mmol/L。γ-Glu-Ile可以增加鸡汤、牛肉汤和酱油的鲜味、厚味、酸味和甜味,且γ-Glu-Ile在鸡汤、牛肉汤和酱油中的厚味阈值分别为(0.62±0.20),(0.83±0.37),(0.91±0.29)mmol/L。商用解淀粉芽孢杆菌源谷氨酰胺酶可用于γ-Glu-Ile的酶法合成,γ-Glu-Ile因能增加鸡汤、牛肉汤和酱油中的呈味感受而作为呈味添加剂。     

基于谷氨酰胺代谢抗肿瘤药物的研究进展

谷氨酰胺作为多种肿瘤的条件性必需氨基酸,对肿瘤的发生发展影响巨大。近年来有关谷氨酰胺代谢的研究进展迅速,涉及的相关药物已有多个处于临床前及临床研究。谷氨酰胺参与肿瘤细胞内能量生成、维持氧化还原平衡、促进大分子合成、传递信号等,其转运体和代谢酶是潜在的肿瘤治疗靶点。本文基于谷氨酰胺代谢抗肿瘤药物的研究进行综述,旨在为相关新药的研发提供参考。     

硝基还原假单胞菌谷氨酰胺酶的分离纯化及酶学性质

采用离子交换层析和凝胶过滤层析等方法,分离纯化硝基还原假单胞菌(Pseudomonas nitroreducens)SK16.004所产的谷氨酰胺酶,并进一步研究该酶的酶学性质及反应动力学参数。结果表明,该酶的最适反应温度为55℃,最适pH为9.0,温度稳定范围为37～60℃,pH稳定范围为5.0～11.0;Cu2+对促进酶活提高作用最大,而Fe3+会抑制该酶的转移活力。谷氨酰胺酶对底物谷氨酰胺的亲和力最强,其Km值为0.72 mmol/L,Vmax为0.55μmol/(min.mL)。