DNA微阵列在结核分枝杆菌研究中的应用

高密度DNA微阵列技术可以通过一次杂交获得大量的基因组信息,广泛用于基因组结构和基因表达谱分析。本文简介DNA微阵列技术在结核分枝杆菌的功能基因组学,致病机理以及耐药机制,诊断等方面的应用。     

基因芯片技术及其在肿瘤基因组学中的应用

基因芯片又称DNA微阵列,分为cDNA微阵列和寡聚核苷酸微阵列。DNA微阵列技术是探索基因组功能的一种强有力工具。扼要介绍基因芯片、表达谱芯片技术和原理,以及基因芯片技术在肿瘤基因组学中的应用。     

分析植物应答环境因子的一种有效平台--DNA微阵列

随着植物基因组测序工程的迅速发展,大量的DNA序列不断地快速对外公布。如何把这庞大的核苷酸序列信息与植物的生命活动有机地联系起来?高通量的DNA微阵列技术是连接植物基因组序列信息和植物功能基因组的桥梁;而且,这一技术在分析基因表达谱和基因的功能上已经得到了应用。通过简要叙述DNA微阵列技术的几个特点,着重分析近几年来该技术在研究植物对环境胁迫的响应机制以及环境信号间相互作用方面的应用。     

DNA甲基化微阵列

DNA甲基化微阵列是近年发展起来的高通量分析基因组水平DNA甲基化状态和模式的新型技术,已成为肿瘤表观遗传学组研究的重要工具之一。利用DNA甲基化微阵列研究某种疾病状态下异常甲基化的基因有利于进一步明确该疾病的表观遗传学异常机制,发现与之相关的表观遗传学标志物。现有的DNA甲基化微阵列主要包括CpG岛微阵列和甲基化寡聚核苷探针微阵列,根据已有的文献资料,较为详细地阐述了上述技术的原理、特点和适用范围,对于研究者根据自己的研究目的选择适当的DNA甲基化微阵列技术具有一定的指导价值。     

微阵列计划(MICROARRAY PROJECT,μAP)

随着人类基因组(测序)计划(HGP)的完成,探明人类全部基因的结构功能及其表达调控已成为后基因组(功能基因组)时代的主要目标,DNA微阵列(又称基因芯片)技术的出现为此提供了光辉的前景。美国国立卫生研究院(NIH)不失时机地提出了微阵列计划(MicroarrayProject),率先运用微阵列技术进行人类功能基因组的研究。目前介绍微阵列制作原理、杂交信号检测原理及微阵列技术应用的文献已有不少,但涉及微阵列技术的实验操作、阵列机和阅读机的结构和性能、阵列图像分析及软件和数据库的设计开发的文献较少。本文分五个部分介绍了微阵列计划的最新的主要成果,分别是:微阵列计划简介、实验操作、阵列机和阅读机的结构和性能、图像分析及数据库设计和开发。     

微阵列计划(MICROARRAY PROJECT,μAP)

随着人类基因组 (测序 )计划 (HGP)的完成 ,探明人类全部基因的结构功能及其表达调控已成为后基因组 (功能基因组 )时代的主要目标 ,DNA微阵列 (又称基因芯片 )技术的出现为此提供了光辉的前景。美国国立卫生研究院 (NIH)不失时机地提出了微阵列计划 (MicroarrayProject) ,率先运用微阵列技术进行人类功能基因组的研究。目前介绍微阵列制作原理、杂交信号检测原理及微阵列技术应用的文献已有不少 ,但涉及微阵列技术的实验操作、阵列机和阅读机的结构和性能、阵列图像分析及软件和数据库的设计开发的文献较少。本文分五个部分介绍了微阵列计划的最新的主要成果 ,分别是 :微阵列计划简介、实验操作、阵列机和阅读机的结构和性能、图像分析及数据库设计和开发。     

基因芯片进入临床

医生现在可以使用一种新的检测工具——DNA微阵列测试工具来减少药物的并发症,帮助确定正确的剂量。这是FDA批准的第一种这类测试工具,病人的DNA在一个微阵列芯片（即“基因芯片”或“基因组芯片”）上化验,从而确定很多基础信息,帮助制定更有效的治疗计划。     

微阵列（microarrays）技术及其应用

微阵列分为cDNA微阵列和寡聚核苷酸微阵列,微阵列上“印”有大量已知部分序列的DNA探针,微阵列技术就是利用分子杂交原理,使同时被比较的标本（用同位素或荧光素标记）与微阵列杂交,通过检测杂交信号强度及数据处理,把他们转化成不同标本中特异基因的丰度,从而全国比较不同标本的基因表达水平的差异,微阵列技术是一种探索基因组功能的有力手段。     

基于基因组关联数据识别阿尔茨海默病相关通路

阿尔茨海默病又称老年性痴呆,是一种复杂的中枢神经系统退行性疾病,本文选取一套阿尔茨海默病全基因组关联分析(GWAS)数据,利用Proxy Gene LD软件进行基因水平上的检验,利用Web Gestalt数据库进行遗传通路分析,识别出320个显著(P0.05)的阿尔茨海默病相关基因、8个显著的KEGG通路和41个显著的GO功能类,这些研究结果对进一步揭示阿尔茨海默病潜在的发病机制具有重要意义。     

水稻功能基因组学研究

水稻是迄今为止第一个被测序的农作物。随着水稻基因组测序计划的完成,以功能基因组学研究为标志的后基因组时代已经到来。综述了水稻功能基因组学的工作进展与方法,主要包括:表达序列标签(EST)c、DNA微阵列和DNA芯片、蛋白质组学、生物信息学和反向遗传学等新方法。     

DNA microarrays--perspective of application for drug effectivity and safety evaluation

Microarray technology provides a unique tool for the determination of gene expression at the level of messenger RNA (mRNA). Microarray has been successfully applied to the high throughput simultaneous expression of many thousands of genes in a single experiment. One important application of DNA microarray technology, within the context of drugs effectiveness and safety evaluation studies, is its use as a screening tool for the identification of biochemical pathways, potential targets for novel molecular therapeutics, for the identification of molecular mechanisms of toxicity and to understand and predict individual drug sensitivity and resistance. The purpose of this review is presentation of the utility of DNA microarray technology in all phases of the drug discovery process.     

快速老化小鼠海马差异表达cDNA芯片的制作

老年性痴呆(Alzheimer’s disease,AD)是老年人群中最普遍的痴呆类型,是一种神经退行性紊乱疾病,目前临床上还没有有效的治疗方法。快速老化小鼠亚系P8(senescence-accelerated mouse prone8,SAMP8)是研究增龄相关性认知缺陷机制以及研究脑老化机制的良好动物,同时也是研究AD较为理想的实验动物模型之一。cDNA芯片技术可以同时规模研究成千上万个基因的表达,尤其适于AD这种多机制、多靶标、多途径的复杂疾病的研究,为了揭示AD的发病机制,发现用于治疗AD的药物靶标,以SAMP8和SAMR1海马抑制消减cDNA文库中的cDNA片段为材料,以β-actin和G3PDH为内参,设计了16×(1×14)点阵方案,并点制了含有3136个点的SAM海马差异表达cDNA芯片。芯片背景均匀一致,点的大小均一,排列规则整齐。在靶分子与探针杂交过程中,进行了杂交条件和洗涤芯片的优化。将杂交结果进行统计分析,选择差异表达的cDNA进行测序并进行生物信息学分析,用实时定量RT-PCR对部分基因的表达进行了验证,检测了芯片筛选结果的可靠性。该芯片的成功制备为进一步进行差异表达基因的筛选和研究提供了良好的手段,并将成为揭示SAMP8脑老化和AD发病机制的有力手段。     

The application of gene expression microarray technology to kinetoplastid research

Protozoan parasites in the order Kinetoplastida cause severe disease primarily in tropical and subtropical areas. Vaccines to control these diseases have shown some promise, but none are in active clinical use. Drug treatments are available for all of the acute infections, but the emergence of resistance and an unresponsive chronic phase are current problems. Rapid advances in genomic technology open the possibility of discovering new genes that can contribute to vaccine initiatives or serve as targets for development of new drugs. The DNA microarray is a genomic technology, which is being applied to new gene discovery in kinetoplastid parasites. Both cDNA and genomic microarrays for Leishmania major have identified a number of new genes that are expressed in a stage-specific fashion and preliminary results from a L. donovani genomic microarray also demonstrated new gene discovery. A microarray of Trypanosoma brucei genomic fragments identified new genes whose expression differs between the insect borne stage and the human infectious stage of the parasite. The next few years, building on this foundational work, should witness the most exciting stage as microarrays are applied to questions such as the basis of drug resistance, post kala azar dermal leishmaniasis, the regulation of differentiation to infectious stages, linking coordinately regulated pathways of genes and development of genetically defined parasites that may have potential as live attenuated vaccines.     

Use of gene networks for identifying and validating drug targets

We propose a new method for identifying and validating drug targets by using gene networks, which are estimated from cDNA microarray gene expression profile data. We created novel gene disruption and drug response microarray gene expression profile data libraries for the purpose of drug target elucidation. We use two types of microarray gene expression profile data for estimating gene networks and then identifying drug targets. The estimated gene networks play an essential role in understanding drug response data and this information is unattainable from clustering methods, which are the standard for gene expression analysis. In the construction of gene networks, we use the Bayesian network model. We use an actual example from analysis of the Saccharomyces cerevisiae gene expression profile data to express a concrete strategy for the application of gene network information to drug discovery.     

基因芯片技术及应用研究进展

采用高速打印或光刻合成技术可在硅片、玻璃或尼龙膜上制造ＤＮＡ微阵列。样品ＤＮＡ／ＲＮＡ通过ＰＣＲ扩增、体外转录等技术掺入荧光标记分子,与微阵列杂交后通过荧光扫描仪器扫描及计算机分析即可获得样品中大量基因序列及表达的信息。该技术可应用于高通量基因表达平行分析、大规模基因发现及序列分析、基因多态性分析和基因组研究等 。     

Low expression of the IL-23/Th17 pathway in atopic dermatitis compared to psoriasis

The classical Th1/Th2 paradigm previously defining atopic dermatitis (AD) and psoriasis has recently been challenged with the discovery of Th17 T cells that synthesize IL-17 and IL-22. Although it is becoming evident that many Th1 diseases including psoriasis have a strong IL-17 signal, the importance of Th17 T cells in AD is still unclear. We examined and compared skin biopsies from AD and psoriasis patients by gene microarray, RT-PCR, immunohistochemistry, and immunofluorescence. We found a reduced genomic expression of IL-23, IL-17, and IFN-gamma in AD compared with psoriasis. To define the effects of IL-17 and IL-22 on keratinocytes, we performed gene array studies with cytokine-treated keratinocytes. We found lipocalin 2 and numerous other innate defense genes to be selectively induced in keratinocytes by IL-17. IFN-gamma had no effect on antimicrobial gene-expression in keratinocytes. In AD skin lesions, protein and mRNA expression of lipocalin 2 and other innate defense genes (hBD2, elafin, LL37) were reduced compared with psoriasis. Although AD has been framed by the Th1/Th2 paradigm as a Th2 polar disease, we present evidence that the IL-23/Th17 axis is largely absent, perhaps accounting for recurrent skin infections in this disease.     

Mining bacterial genomes for antimicrobial targets

The elucidation of whole-genome sequences is expected to have a revolutionary impact on the discovery of novel medicines. With the availability of complete genome sequences of more than 30 different species, the field of antimicrobial drug discovery has the opportunity to access a remarkable diversity of genomic information. In this review, I summarize how microbial genomics has changed strategies of drug discovery by applying bioinformatics, novel genetic approaches and genomics-based technologies, including analysis of gene expression using DNA microarrays.     

Building Disease-Specific Drug-Protein Connectivity Maps from Molecular Interaction Networks and PubMed Abstracts

The recently proposed concept of molecular connectivity maps enables researchers to integrate experimental measurements of genes, proteins, metabolites, and drug compounds under similar biological conditions. The study of these maps provides opportunities for future toxicogenomics and drug discovery applications. We developed a computational framework to build disease-specific drug-protein connectivity maps. We integrated gene/protein and drug connectivity information based on protein interaction networks and literature mining, without requiring gene expression profile information derived from drug perturbation experiments on disease samples. We described the development and application of this computational framework using Alzheimer''s Disease (AD) as a primary example in three steps. First, molecular interaction networks were incorporated to reduce bias and improve relevance of AD seed proteins. Second, PubMed abstracts were used to retrieve enriched drug terms that are indirectly associated with AD through molecular mechanistic studies. Third and lastly, a comprehensive AD connectivity map was created by relating enriched drugs and related proteins in literature. We showed that this molecular connectivity map development approach outperformed both curated drug target databases and conventional information retrieval systems. Our initial explorations of the AD connectivity map yielded a new hypothesis that diltiazem and quinidine may be investigated as candidate drugs for AD treatment. Molecular connectivity maps derived computationally can help study molecular signature differences between different classes of drugs in specific disease contexts. To achieve overall good data coverage and quality, a series of statistical methods have been developed to overcome high levels of data noise in biological networks and literature mining results. Further development of computational molecular connectivity maps to cover major disease areas will likely set up a new model for drug development, in which therapeutic/toxicological profiles of candidate drugs can be checked computationally before costly clinical trials begin.     

Microarray analysis in Alzheimer's disease and normal aging

The purpose of this study was to investigate gene expression in Alzheimer's disease (AD), the most common form of senile dementia. We utilized the microarray technology to simultaneously compare the expression profile of 12,000 human genes in cerebral cortex of AD and normal aging. To identify gene expression related to neurodegeneration, beside the presence of amyloid deposition, we used control brains with abundant amyloid plaques, derived from cognitively normal elderly subjects. The microarray analysis indicated that 314 genes were differentially expressed in AD cerebral cortex, with differences greater than 5 folds in 25 genes. RT-PCR performed on a selected group of genes confirmed the increased expression of the interferon-induced protein 3 in AD brain. This protein, which is highly inducible by both type I and type II interferons, was not previously associated with the neurodegenerative disease.