基因芯片技术及其在寄生虫学研究中的应用

随着人类基因组计划(human genome project,HGP)和一些模式生物基因组计划的完成,基因序列数据正以前所未有的速度迅速增长,对基因组学的研究已从结构基因组学逐步转向了功能基因组学.由于基因芯片技术操作简便,获得的信息高度特异、稳定,在寄生虫学研究领域已得到广泛应用.随着寄生虫分子遗传学研究的进展和寄生虫基因芯片检测工具的开发应用,这一技术用于筛选寄生虫功能基因,探索寄生虫与宿主相互作用,研究寄生虫发病机制及筛选寄生虫诊断抗原、药物靶标和疫苗分子等,大大推动了寄生虫学领域的研究进程.该文主要介绍了基因芯片技术的分类,并就近几年来基因芯片技术在寄生虫学研究方面的应用作一综述.     

基因芯片技术及其在寄生虫学研究中的应用

随着人类基因组计划(human genome project,HGP)和一些模式生物基因组计划的完成,基因序列数据正以前所未有的速度迅速增长,对基因组学的研究已从结构基因组学逐步转向了功能基因组学.由于基因芯片技术操作简便,获得的信息高度特异、稳定,在寄生虫学研究领域已得到广泛应用.随着寄生虫分子遗传学研究的进展和寄生...     

表达序列标签在寄生虫功能基因组学研究中的应用

随着后基因组时代的到来，基因组学已从结构基因组学向功能基因组学领域拓展。表达序列标签（expressed sequence tags，EST）是一种快捷、高效地揭示基因组功能信息的方法。本文就EST在寄生虫功能基因组学研究中的应用作一综述。     

华支睾吸虫分子生物学研究进展

华支睾吸虫是危害人类和许多动物健康的一种重要的食源性寄生虫,寄生在宿主的胆管内,可引起多种消化道疾病,严重者可导致肿瘤的发生。随着人类基因组计划的开展,寄生虫基因组计划也被纳入到了其中,主要有恶性疟原虫、利什曼原虫、锥虫、丝虫和血吸虫等。近年来分子寄生虫学迅速发展起来,为生命科学和生物医药研究领域提供了新的视角,成为寄生虫学研究的热点。首尔国立大学医学院以及我国许多大学和科研机构都开展相关研究,多集中于功能基因组学,并且取得了一定的进展。特对华支睾吸虫的分子生物学研究进展,重点从基因表达谱、特殊的功能基因、遗传发育和进化等方面进行论述。     

吸虫排泄分泌产物成分及其功能的研究进展

吸虫是一类重要的人兽共患寄生虫,不仅影响水产业和家畜业的生产,还严重威胁人类的健康.吸虫的排泄分泌产物(excretory-secretory products,ESP)在虫体致病机制中发挥重要的作用,研究其组成成分和相应的功能对探讨虫体和宿主的相互关系有重要的意义.目前已开展通过蛋白质组学和基因组学的相关技术对ESP的成分进行分离、提纯、重组表达,并在体内、外探讨各生物活性分子的生物活性和免疫调节功能的研究.该文就吸虫排泄分泌产物及功能的国内外研究进展作一综述.     

吸虫排泄分泌产物成分及其功能的研究进展

吸虫是一类重要的人兽共患寄生虫,不仅影响水产业和家畜业的生产,还严重威胁人类的健康.吸虫的排泄分泌产物(excretory-secretory products,ESP)在虫体致病机制中发挥重要的作用,研究其组成成分和相应的功能对探讨虫体和宿主的相互关系有重要的意义.目前已开展通过蛋白质组学和基因组学的相关技术对ESP的成分进行分离、提纯、重组表达,并在体内、外探讨各生物活性分子的生物活性和免疫调节功能的研究.该文就吸虫排泄分泌产物及功能的国内外研究进展作一综述.     

重要绦虫功能基因组学研究进展

绦虫病是一类严重危害人类健康以及畜牧业生产的寄生虫病,其防治措施目前尚不完善。近年来,分子生物学技术发展迅速,已成为遏制绦虫病的有效手段。因此,研究绦虫基因的功能对于防治绦虫病意义重大。本文介绍了功能基因组学研究常用的几种技术,并对近年来一些重要绦虫的功能基因组学研究进展作一综述。     

基因识别的计算机方法及其在寄生虫基因组学研究中的应用

随着基因组学研究时代的到来,应用计算机方法进行基因识别分析愈来愈受到重视。 本文简要介绍了基因识别中常用的一些计算机方法和原理,并就应用其中的一些方法进行寄生虫 基因组学研究的进展情况作一概述。     

基因识别的计算机方法及其在寄生虫基因组学研究中的应用

随着基因组学研究时代的到来,应用计算机方法进行基因识别分析愈来愈受到重视。本简要介绍了基因识别中常用的一些计算机方法和原理,并就应用其中的一些方法进行寄生虫基因组学研究的进展情况作一概述。     

辅助T细胞表位预测及其在抗寄生虫疫苗研发中的应用

细胞免疫在防御外来病原感染、自身免疫及肿瘤等疾病中发挥重要作用。随着分子免疫学研究的不断发展,对T淋巴细胞免疫分子机制的阐释,大量T细胞表位信息以及功能基因组学资料的积累,使得基于数据驱动的预测T细胞表位的研究受到重视,可能成为疫苗研发的重要工具之一。本文概述辅助T细胞表位预测的理论和方法及其在寄生虫疫苗研发中的应用,并讨论未来的研究方向。     

Toward the structural genomics of complexes: crystal structure of a PE/PPE protein complex from Mycobacterium tuberculosis

The developing science called structural genomics has focused to date mainly on high-throughput expression of individual proteins, followed by their purification and structure determination. In contrast, the term structural biology is used to denote the determination of structures, often complexes of several macromolecules, that illuminate aspects of biological function. Here we bridge structural genomics to structural biology with a procedure for determining protein complexes of previously unknown function from any organism with a sequenced genome. From computational genomic analysis, we identify functionally linked proteins and verify their interaction in vitro by coexpression/copurification. We illustrate this procedure by the structural determination of a previously unknown complex between a PE and PPE protein from the Mycobacterium tuberculosis genome, members of protein families that constitute approximately 10% of the coding capacity of this genome. The predicted complex was readily expressed, purified, and crystallized, although we had previously failed in expressing individual PE and PPE proteins on their own. The reason for the failure is clear from the structure, which shows that the PE and PPE proteins mate along an extended apolar interface to form a four-alpha-helical bundle, where two of the alpha-helices are contributed by the PE protein and two by the PPE protein. Our entire procedure for the identification, characterization, and structural determination of protein complexes can be scaled to a genome-wide level.     

Structural genomics of the Thermotoga maritima proteome implemented in a high-throughput structure determination pipeline

Structural genomics is emerging as a principal approach to define protein structure-function relationships. To apply this approach on a genomic scale, novel methods and technologies must be developed to determine large numbers of structures. We describe the design and implementation of a high-throughput structural genomics pipeline and its application to the proteome of the thermophilic bacterium Thermotoga maritima. By using this pipeline, we successfully cloned and attempted expression of 1,376 of the predicted 1,877 genes (73%) and have identified crystallization conditions for 432 proteins, comprising 23% of the T. maritima proteome. Representative structures from TM0423 glycerol dehydrogenase and TM0449 thymidylate synthase-complementing protein are presented as examples of final outputs from the pipeline.     

Functional implications from crystal structures of the conserved Bacillus subtilis protein Maf with and without dUTP

Three-dimensional structures of functionally uncharacterized proteins may furnish insight into their functions. The potential benefits of three-dimensional structural information regarding such proteins are particularly obvious when the corresponding genes are conserved during evolution, implying an important function, and no functional classification can be inferred from their sequences. The Bacillus subtilis Maf protein is representative of a family of proteins that has homologs in many of the completely sequenced genomes from archaea, prokaryotes, and eukaryotes, but whose function is unknown. As an aid in exploring function, we determined the crystal structure of this protein at a resolution of 1.85 A. The structure, in combination with multiple sequence alignment, reveals a putative active site. Phosphate ions present at this site and structural similarities between a portion of Maf and the anticodon-binding domains of several tRNA synthetases suggest that Maf may be a nucleic acid-binding protein. The crystal structure of a Maf-nucleoside triphosphate complex provides support for this hypothesis and hints at di- or oligonucleotides with either 5'- or 3'-terminal phosphate groups as ligands or substrates of Maf. A further clue comes from the observation that the structure of the Maf monomer bears similarity to that of the recently reported Methanococcus jannaschii Mj0226 protein. Just as for Maf, the structure of this predicted NTPase was determined as part of a structural genomics pilot project. The structural relation between Maf and Mj0226 was not apparent from sequence analysis approaches. These results emphasize the potential of structural genomics to reveal new unexpected connections between protein families previously considered unrelated.     

Diagnostic testing in hepatitis C virus infection: viral kinetics and genomics

Virological tools play a major role in the diagnosis of hepatitis C virus (HCV) infection and in ongoing decision-making based on the patient's virological response to therapy. Virological tools used to assess viral kinetics and viral genomics can also be applied to clinical and translational research, especially in studies aimed at understanding the mechanisms underlying HCV treatment failure. Viral kinetics studies are based on quantification of HCV RNA at prescribed intervals during treatment and mathematical modeling of HCV RNA dynamics. These studies require sensitive and specific HCV RNA assays with an extended dynamic range of quantification. Viral genomics methods are useful to correlate viral kinetics with the intrinsic genomic characteristics of the HCV infecting strain. The interpretation of results utilizing various viral genomics tools is difficult, however, and must include predictive structural and functional genomic analyses. These approaches will be particularly useful in studying the mechanisms of HCV treatment failure with new HCV inhibitors currently under development.     

DNA shuffling as a tool for protein crystallization

The success of structural studies performed on an individual target in small scale or on many targets in the system-wide scale of structural genomics depends critically on three parameters: (i) obtaining an expression system capable of producing large quantities of the macromolecule(s) of interest, (ii) purifying this material in soluble form, and (iii) obtaining diffraction-quality crystals suitable for x-ray analysis. The attrition rate caused by these constraints is often quite high. Here, we present a strategy that addresses each of these three parameters simultaneously. Using DNA shuffling to introduce functional sequence variability into a protein of interest, we screened crude lysate supernatants for soluble variants that retain enzymatic activity. Crystallization trials performed on three WT and eight shuffled enzymes revealed two variants that crystallized readily. One of these was used to determine the high-resolution structure of the enzyme by x-ray analysis. The sequence diversity introduced through shuffling efficiently samples crystal packing space by modifying the surface properties of the enzyme. The approach demonstrated here does not require guidance as to the type of mutation necessary for improvements in expression, solubility, or crystallization. The method is scaleable and can be applied in situations where a single protein is being studied or in high-throughput structural genomics programs. Furthermore, it should be readily applied to structural studies of soluble proteins, membrane proteins, and macromolecular complexes.     

Predicting protein function from structure: unique structural features of proteases

We have noted consistent structural similarities among unrelated proteases. In comparison with other proteins of similar size, proteases have smaller than average surface areas, smaller radii of gyration, and higher C(alpha) densities. These findings imply that proteases are, as a group, more tightly packed than other proteins. There are also notable differences in secondary structure content between these two groups of proteins: proteases have fewer helices and more loops. We speculate that both high packing density and low alpha-helical content coevolved in proteases to avoid autolysis. By using the structural parameters that seem to show some separation between proteases and nonproteases, a neural network has been trained to predict protease function with over 86% accuracy. Moreover, it is possible to identify proteases whose folds were not represented during training. Similar structural analyses may be useful for identifying other classes of proteins and may be of great utility for categorizing the flood of structures soon to flow from structural genomics initiatives.     

A time-invariant principle of genome evolution

Uncovering general principles of genome evolution that are time-invariant and that operate in germ and somatic cells has implications for genome-wide association studies (GWAS), gene therapy, and disease genomics. Here we investigate the relationship between structural alterations (e.g., insertions and deletions) and single-nucleotide substitutions by comparing the following genomes that diverged at different times across germ- and somatic-cell lineages: (i) the reference human and chimpanzee genome (in million years), (ii) the reference human and personal genomes (in tens of thousands of years), and (iii) structurally altered regions in cancer and genetically engineered cells (in days). At the species level, genes with structural alteration in nearby regions show increased single-nucleotide changes and tend to evolve faster. In personal genomes, the single-nucleotide substitution rate is higher near sites of structural alteration and decreases with increasing distance. In human cancer cell populations and in cells genetically engineered using zinc-finger nucleases, single-nucleotide changes occur frequently near sites of structural alterations. We present evidence that structural alteration induces single-nucleotide changes in nearby regions and discuss possible molecular mechanisms that contribute to this phenomenon. We propose that the low fidelity of nonreplicative error-prone repair polymerases, which are used during insertion or deletion, result in break-repair-induced single-nucleotide mutations in the vicinity of structural alteration. Thus, in the mutational landscape, structural alterations are linked to single-nucleotide changes across different time scales in both somatic- and germ-cell lineages. We discuss implications for genome evolution, GWAS, disease genomics, and gene therapy and emphasize the need to investigate both types of mutations within a single framework.     

Educational Websites — Bioinformatics Tools II

In this issue, the highlighted websites are a continuation of a series of educational websites; this one in particular from a couple of years ago, Bioinformatics Tools [Pancreatology 2005;5:314–315]. These include sites that are valuable resources for many research needs in genomics and proteomics. Bioinformatics has become a laboratory tool to map sequences to databases, develop models of molecular interactions, evaluate structural compatibilities, describe differences between normal and disease-associated DNA, identify conserved motifs within proteins, and chart extensive signaling networks, all in silico.