舌苔细菌PCR-DGGE分析条件的建立与优化

目的针对口腔舌苔细菌16S rDNA序列进行变性梯度凝胶电泳(denaturing gradient gel electrophoresis,DGGE)适用序列的筛选及电泳条件的优化。方法以DGGE图谱的高分辨率为指标,选择舌苔细菌DGGE分离最适的16S rDNA高变区、电泳电压和电泳时间,并采用优化的条件分析健康青年人舌苔细菌群落的分布。结果舌苔细菌16S rDNA V3高变区引物序列能获得更加丰富清晰的DGGE条带;基于该区,当变性剂浓度为30%～60%、电泳温度60℃、电压60 V和电泳时间14 h时能得到分辨率最佳的DGGE图谱。运用此优化条件对12个样本舌苔细菌群落的分析表明,舌苔微生物主要由厚壁菌门、梭杆菌门、拟杆菌门和变形菌门等组成。优化后的DGGE技术对舌苔细菌多样性的分析具有准确性、灵敏性和可重复性。结论 DGGE图谱显示,不同分析条件对图谱类型和细菌多样性指数均有所差异。利用优化的DGGE条件能有效分离舌苔细菌16S rDNA V3区序列,为口腔微生物群落结构分析提供可靠的技术支持,也为其他不同生态细菌的多样性分析提供参考。     

面向工业生物技术的系统生物学

工业生物技术是以微生物细胞工厂利用可再生的生物原料来生产能源、材料与化学品等的生物技术,在解决资源、能源与环境等问题方面起着越来越重要的作用。系统生物学是全面解析微生物细胞工厂及其发酵过程从"黑箱"到"白箱"的重要研究方法。系统生物学借助基因组、转录组、蛋白质组、代谢组以及代谢流组等多组学数据,可解析微生物细胞工厂在RNA、蛋白与代谢物等不同水平上的变化规律与调控机制。目前,系统生物学在微生物细胞工厂的设计创建与发酵工艺优化中起着越来越重要的指导作用,许多成功应用实例不断涌现,推动着工业生物技术的快速发展。文中重点综述基因组、转录组、蛋白质组、代谢组与代谢流组以及基因组规模的网络模型等各组学技术的最新发展及其在工业生物技术尤其是菌株改造与发酵优化中的应用,并就工业生物技术中系统生物学的未来发展方向进行展望。     

密码子优化策略在异源蛋白表达中的应用

酶在医疗和生物药物方面有着广泛的应用,不仅可以用来治疗各种疾病,还在临床诊断和人体健康等方面有着重要的影响。利用微生物来表达异源蛋白已经成为获取酶最简单快速的方法。为获得高浓度和高质量的异源蛋白,常用的方法是对基因序列进行密码子优化。传统的密码子优化策略主要基于密码子偏好性和GC含量,忽略了翻译动力学和代谢水平等复杂多样的变化因素。文中从基因水平、转录水平、翻译水平、翻译后水平以及代谢水平等多方面考虑出发,提供了一个较为全面的密码子优化策略,主要包括密码子偏好性、密码子协调性、密码子敏感性、调整基因序列结构以及一些其他影响因素。同时对每种策略的内容、理论支持以及应用范围等方面作了全面的总结,并将各策略的优缺点进行了系统的比较,为异源蛋白表达提供了全方位、多层次、多选择的优化策略,也为酶工业和生物药物等方面提供参考。     

不同碳源对须糖多孢菌生长发育及丁烯基多杀菌素生物合成的影响

本文研究了不同碳源对须糖多孢菌生长以及丁烯基多杀菌素生物合成的影响,通过寻找优势碳源优化发酵培养基配方,促进须糖多孢菌丁烯基多杀菌素的生物合成。试验共设11个处理,1个对照,通过单因素试验比较不同处理组菌体OD600值和丁烯基多杀菌素产量,筛选获得最优碳源及其发酵培养基配方。结果表明,除可溶性淀粉和木糖外,须糖多孢菌在9种碳源中都能进行生长,对不同构型碳源显示较好的利用率。在以半乳糖、葡萄糖、果糖和甘露糖作为碳源时具有较好的生长速率,而以甘露糖为碳源时能显著促进丁烯基多杀菌素的合成。选择甘露糖最佳添加浓度为5 g/L,须糖多孢菌最高菌体浓度和丁烯基多杀菌素产量分别是初始配方条件的1. 32倍和1. 78倍,显著提高了丁烯基多杀菌素的产量。上述结果为培养基碳源对丁烯基多杀菌素生物合成影响机制的研究及丁烯基多杀菌素大规模工业化发酵生产提供了科学依据和新的技术途径。     

Performance criteria for generating predictive optimal control simulations of bicycle pedaling

The purpose of this study was to identify one or more performance-based criteria that may be used to generate predictive optimal control simulations of submaximal pedaling. Two-legged pedaling simulations were generated based on minimizing muscle activation, muscle stress, metabolic energy, time derivative of muscle force, and minimizing metabolic energy while pedaling smoothly. The simulations based on minimizing muscle activation and muscle stress most closely matched experimental pedaling data, with the activation criterion better matching experimental muscle activation timing. We conclude that predictive simulations of submaximal pedaling may be generated using a cost function based on minimizing muscle activation.     

大肠杆菌角鲨烯合成途径的构建与调控

角鲨烯因其具有良好的抗氧化功能而被广泛应用于食品、医药、化妆品、工业应用等领域。本实验在大肠杆菌中构建角鲨烯合成途径,通过对其合成途径中关键限速酶(1-脱氧-D-木酮糖-5-磷酸合酶和异戊烯基二磷酸异构酶)过表达的方法进行初步调控,使角鲨烯的产量提升了近三倍。之后采用单因素试验对其发酵培养基和培养条件进行优化,以此来提高角鲨烯的产量。优化发酵条件后,使用最优发酵培养基——TB培养基,在最佳发酵条件:37℃,220r/min培养至OD600约为1.2时加入终浓度为0.1mmol/L的IPTG诱导剂,25℃条件下诱导48h,角鲨烯产量可达73.88mg/L。     

Optimizing interstitial photodynamic therapy with custom cylindrical diffusers

Interstitial photodynamic therapy (iPDT) has shown promise recently as a minimally invasive cancer treatment, partially due to the development of non‐toxic photosensitizers in the absence of activation light. However, a major challenge in iPDT is the pre‐treatment planning process that specifies the number of diffusers needed, along with their positions and allocated powers, to confine the light distribution to the target volume as much as possible. In this work, a new power allocation algorithm for cylindrical light diffusers including those that can produce customized longitudinal (tailored) emission profiles is introduced. The proposed formulation is convex to guarantee the minimum over‐dose possible on the surrounding organs‐at‐risk. The impact of varying the diffuser lengths and penetration angles on the quality of the plan is evaluated. The results of this study are demonstrated for different photosensitizers activated at different wavelengths and simulated on virtual tumors modeling virtual glioblastoma multiforme cases. Results show that manufacturable cylindrical diffusers with tailored emission profiles can significantly outperform those with conventional flat profiles with an average damage reduction on white matter of 15% to 55% and on gray matter of 23% to 58%.      

Hybrid optimization of preparative chromatography for a ternary monoclonal antibody mixture

In the purification of monoclonal antibodies, ion-exchange chromatography is typically used among the polishing steps to reduce the amount of product-related impurities such as aggregates and fragments, whilst simultaneously reducing HCP, residual Protein A and potential toxins and viruses. When the product-related impurities are difficult to separate from the products, the optimization of these chromatographic steps can be complex and laborious. In this paper, we optimize the polishing chromatography of a monoclonal antibody from a challenging ternary feed mixture by introducing a hybrid approach of the simplex method and a form of local optimization. To maximize the productivity of this preparative bind-and-elute cation-exchange chromatography, wide ranges of the three critical operational parameters—column loading, the initial salt concentration, and gradient slope—had to be considered. The hybrid optimization approach is shown to be extremely effective in dealing with this complex separation that was subject to multiple constraints based on yield, purity, and product breakthrough. Furthermore, it enabled the generation of a large knowledge space that was subsequently used to study the sensitivity of the objective function. Increased design space understanding was gained through the application of Monte Carlo simulations. Hence, this work proposes a powerful hybrid optimization method, applied to an industrially relevant process development challenge. The properties of this approach and the results and insights gained, make it perfectly suited for the rapid development of biotechnological unit operations during early-stage bioprocess development.