植物蛋白电泳分析的方法学研究及技术改进

本文在采用多种方法进行植物蛋白质电泳分析的基础之上,对植物蛋白进行了电泳分析的方法学研究,论述了多种电泳技术的理论概要、关键步骤、实验要领及我们的一些改进。     

He—Ne激光对家蚕诱变效应的研究

采用一定剂量的ＨｅＮｅ激光辐照家蚕蛹,在子代与对照相比较,出现熟性、茧形、斑纹等多种变异,利用ＰＡＧＥ,进行血液蛋白质电泳分析结果,也产生谱带数目及活性的变化,首次证明ＨｅＮｅ激光对家蚕具有一定的诱变效应。     

电泳技术在细菌分类学中的应用

近年来,电泳技术在细菌分类学中得到了广泛的应用,通过对各类细菌的各种细胞组分的电泳分析,得到了许多有用的分类结果,发展了多种适于各种水平的分类技术。细菌细胞中有很多组分可以采用电泳分析,如完整的细胞,脂多糖,肽聚糖,蛋白质(包括酶),及核酸等。这些组分的分子依其电荷性质和电荷的多少,分子的大小和形状诸因素的不同而在电场中表现出不同性质的迁移和不同的迁移速率,从而使组分中不同的     

真菌的分子生物学鉴定方法研究进展

综述了真菌的分子生物学鉴定方法,包括DNA碱基组成分析,核酸分析技术,真菌核型的脉冲电泳分析。     

聚丙烯酰胺凝胶电泳中LPS样品制备方法的改进

为了对革兰阴性细菌的LPS进行快速分析,观察LPS的产量、分子量分布,进行菌种筛选和抗原传代稳定性研究,实验中对热酚法、酶水解法、冷酚法三种制备LPS的方法进行了比较。结果证明,改进的水饱和冷酚LPS提取方法,需要时间短、经济、方便,只须几个细菌菌落就可以提取LPS进行SDS-PAGE电泳分析,说明该方法有很好的实用性。     

西葫芦的单花粉蛋白电泳

对西葫芦（ＣｕｃｕｒｂｉｔａｐｅｐｏＬ．）的单花粉进行了蛋白电泳分析,结果表明在西葫芦花粉发育的不同阶段,其蛋白电泳图谱存在明显差异,结合细胞学观察结果,对这些差异进行了讨论。同时对同一杂合个体同一雄花相同发育阶段的不同花粉粒的蛋白电泳结果表明,它们之间也存在着差异。     

荧光假单胞菌鞭毛蛋白对黑松细胞的致死作用

采用细胞免疫荧光分析、细胞染色观察、电导率测定以及基因组DNA电泳分析技术,研究了松材线虫携带的荧光假单胞菌分泌的鞭毛蛋白对黑松愈伤组织细胞的作用及其致死方式。结果表明,鞭毛蛋白与黑松细胞之间存在直接的相互作用;鞭毛蛋白处理的细胞,细胞膜皱缩变形、细胞质浓缩、细胞核解体,形成若干小核,细胞质中的RNA降解;处理细胞的着色力增强,细胞培养液的电导率增加,说明鞭毛蛋白可增加处理细胞的细胞膜透性;基因组DNA的电泳分析证实,处理细胞的DNA发生了断裂,但无明显的梯子形成,推测鞭毛蛋白对黑松细胞的致死方式为非典型的细胞凋亡。     

Cry1Ac基因载体构建及其在枯草芽孢杆菌中的杀虫活性表达

根据苏云金芽孢杆菌Bacillus thuringiensis HD-73基因Cry1Ac和枯草芽孢杆菌Bacillus subtilis木糖诱导型启动子PxylR序列, 分别设计2对特异引物Cry1Ac F/R和Pxy F/R,扩增获得了完整的启动子PxylR和Cry1Ac基因序列,进一步以上述产物混合物为模板,以Pxy F/Cry1Ac R作引物进行重迭PCR,获得了载体PxylR-Cry1Ac,经SphⅠ和BamHⅠ完全酶切后,将PxylR-Cry1Ac插入大肠杆菌-苏云金芽孢杆菌穿梭载体pHT315,重组表达质粒pCry1Ac315转化枯草芽孢杆菌感受态细胞。工程菌株质粒酶切电泳分析、SDS-PAGE电泳分析和杀虫生物活性测定结果证实了Cry1Ac基因的导入及其在枯草芽孢杆菌JAAS01D中的有效表达。     

银耳二型态细胞差异性的初步研究

以银耳的担孢子、节孢子和菌丝体为材料,通过显微观察和电泳分析揭示银耳二型态细胞间的差异性。显微形态及核相观察表明:节孢子直径略大于担孢子,担孢子为单核细胞,节孢子绝大多数为单核细胞,少数为双核细胞,菌丝体为双核细胞并具有典型的锁状联合结构。总蛋白及同工酶电泳分析表明:菌丝相总蛋白谱带多于酵母相,过氧化物及酯酶与酵母相存在一定差异,而多酚氧化酶基本相同。因此,伴随银耳二型态细胞两相形态的转变,细胞代谢水平发生了相应变化。     

植物叶片蛋白质的双向电泳分析

本文介绍一种提取植物叶片蛋白质的方法及电泳分析条件,可以很好地用来分析绿色组织中的全蛋白质组分。     

Identifying the proteome: software tools

The interest in proteomics has recently increased dramatically and proteomic methods are now applied to many problems in cell biology. The method of choice in proteomics for identifying and characterizing proteins is mass spectrometry combined with database searching. Software tools have been improved to increase the sensitivity of protein identification and methods for evaluating the search results have been incorporated     

CMASA: an accurate algorithm for detecting local protein structural similarity and its application to enzyme catalytic site annotation

Background  

The rapid development of structural genomics has resulted in many "unknown function" proteins being deposited in Protein Data Bank (PDB), thus, the functional prediction of these proteins has become a challenge for structural bioinformatics. Several sequence-based and structure-based methods have been developed to predict protein function, but these methods need to be improved further, such as, enhancing the accuracy, sensitivity, and the computational speed. Here, an accurate algorithm, the CMASA (Contact MAtrix based local Structural Alignment algorithm), has been developed to predict unknown functions of proteins based on the local protein structural similarity. This algorithm has been evaluated by building a test set including 164 enzyme families, and also been compared to other methods.     

三种花生幼胚蛋白质提取方法比较研究

植物组织(或细胞)的蛋白质提取效率与效果直接影响蛋白质双向凝胶电泳等实验的结果。为探索建立适用于花生幼胚蛋白质(双向凝胶电泳用)提取的最佳条件,尝试了磷酸缓冲液直接提取法、改良的荔枝胚胎蛋白提取法和Trizol(附加)提取法等3种提取方法,根据蛋白提取得率、试剂成本、双向电泳图谱的质量(蛋白质斑点的丰度、分布特点)进行初步评价。结果表明,磷酸缓冲液直接提取法简单但总体效果较差,改良的荔枝胚胎蛋白提取法综合评价最好,与双向凝胶电泳条件更兼容。     

Iteration method for predicting essential proteins based on orthology and protein-protein interaction networks

ABSTRACT: BACKGROUND: Identification of essential proteins plays a significant role in understanding minimal requirements for the cellular survival and development. Many computational methods have been proposed for predicting essential proteins by using the topological features of protein-protein interaction (PPI) networks. However, most of these methods ignored intrinsic biological meaning of proteins. Moreover, PPI data contains many false positives and false negatives. To overcome these limitations, recently many research groups have started to focus on identification of essential proteins by integrating PPI networks with other biological information. However, none of their methods has widely been acknowledged. RESULTS: By considering the facts that essential proteins are more evolutionarily conserved than nonessential proteins and essential proteins frequently bind each other, we propose an iteration method for predicting essential proteins by integrating the orthology with PPI networks, named by ION. Differently from other methods, ION identifies essential proteins depending on not only the connections between proteins but also their orthologous properties and features of their neighbors. ION is implemented to predict essential proteins in S. cerevisiae. Experimental results show that ION can achieve higher identification accuracy than eight other existing centrality methods in terms of area under the curve (AUC). Moreover, ION identifies a large amount of essential proteins which have been ignored by eight other existing centrality methods because of their low-connectivity. Many proteins ranked in top 100 by ION are both essential and belong to the complexes with certain biological functions. Furthermore, no matter how many reference organisms were selected, ION outperforms all eight other existing centrality methods. While using as many as possible reference organisms can improve the performance of ION. Additionally, ION also shows good prediction performance in E.Coli K-12. CONCLUSIONS: The accuracy of predicting essential proteins can be improved by integrating the orthology with PPI networks.     

Core-directed protein design

For various reasons, it seems sensible to redesign or design proteins from the inside out. Past approaches in this field have involved iterations of mutagenesis and characterisation to 'evolve' designs. Increasingly, combinatorial approaches are being taken to select 'fit' sequences from libraries of variant proteins. In particular, in silico methods have been used to good effect. More recently, experimental methods have been developed and improved. We are now in a position to redesign stability and function into natural protein frameworks confidently and to attempt de novo designs for more ambitious targets.     

筛选差异表达基因和蛋白质的方法进展

分离和鉴定差异表达基因和蛋白质不仅有助于发现基因和蛋白质的功能,更有助于揭示某些疾病的发生机理.目前筛选差异表达基因的方法主要有差异显示PCR方法(differential display RT-PCR,DDRT-PCR)、消减杂交法(subtractive hybridization,SH)、基因芯片技术(DNA chip technique)和基因表达的系统分析(serial analysis of gene expression,SAGE)等,其中消减杂交法中又先后建立了代表性差异分析技术(representational difference analysis,RDA)、抑制消减杂交法(suppression subtractive hybridization,SSH)和获得全长基因的消减杂交法(full-length-gene-obtainable subtractive hybridization).筛选差异表达蛋白质的方法主要有双向电泳技术(two-dimentional gel electrophoresis)和噬菌体全套抗体库技术(phage display antibody repertoire library technique).这些方法各有特点,各有利弊,研究者可根据自己的需要选择适合于自己的方法.     

Amyloid fibrillogenesis: themes and variations

Recent progress has improved our knowledge of how proteins form amyloid fibrils. Both 'natively unfolded' and globular proteins have been shown to initiate fibrillization by adopting a partially structured conformation. Oligomeric prefibrillar intermediates have been extensively characterized with respect to their morphology and temporal evolution. Three-dimensional models obtained using biophysical and computational methods have provided information about fibril structure. All of these advances suggest common features of self-assembly pathways, with subtle variations accounting for differences among distinct amyloid fibrils.     

Optimization of protein expression systems for modern drug discovery

The expression of high levels of stable and functional proteins remains a bottleneck in many scientific endeavors, including the determination of structures in a high-throughput fashion or the screening for novel active compounds in modern drug discovery. Recently, numerous developments have been made to improve the production of soluble and active proteins in heterologous expression systems. These include modifications to the expression constructs, the introduction of new and/or improved pro- and eukaryotic expression systems, and the development of improved cell-free protein synthesis systems. The introduction of robotics has enabled a massive parallelization of expression experiments, thereby vastly increasing the throughput and, hopefully, the output of such experiments. In addition, the big challenges of recombinant overexpression of membrane and secreted proteins are tackled, and some new methods are reviewed.     

2DE-MS中膜蛋白质组的研究进展

2-维凝胶电泳(2DE)具有高分辨率、高通量等特点,已被广泛地用于蛋白质组的研究.然而,2DE-MS在膜蛋白质组学研究方面却有其局限性,主要因为:膜蛋白具有低丰度、难溶、等电点时易沉淀、难酶解等特点.然而随着亚细胞分离技术和直接的生化方法富集等技术的发展,低丰度问题得到了极大的改善;增溶剂(尿素,硫脲),新的两性离子和非离子去垢剂,以及有机溶剂等的利用极大地改善了膜蛋白质组的溶解性能;同时,一些新的2DE技术的利用扩大了常规2DE的分离范围.在膜蛋白裂解方面,将酶解法与化学法(CNBr)相结合,另外先进的质谱技术的发展使得膜蛋白质组的研究在最近几年取得了较大的发展.现对2DE-MS途径中,膜的富集、膜蛋白的提取、分离、酶解、鉴定方面的进展进行综述.