植物蛋白质组学研究进展Ⅰ. 蛋白质组关键技术

随着模式植物拟南芥和水稻基因组测序相继完成, 使植物基因组学研究成功迈入到功能基因组学研究的时代。这为蛋白质组学产生及其发展奠定了坚实的基础。文章重点介绍了蛋白质组学的概念、产生背景和蛋白质组学的关键技术。蛋白质组学的关键技术包括双向电泳、高效液相色谱、蛋白芯片、质谱技术、蛋白质组学的相关数据库、定量蛋白组技术、蛋白复合体标签亲和纯化技术和酵母双杂交系统。同时对当前蛋白质组技术面临的挑战和发展前景进行了讨论。     

蛋白质组学在水稻与微生物互作研究中的应用

应用蛋白质组学方法揭示植物与微生物的互作机制是当前植物病理学研究的热点之一。结合水稻感染水稻条纹病毒后的蛋白质组学分析经验,综述了蛋白质组学在水稻与微生物互作研究中的应用,包括水稻与真菌、细菌、病毒互作的蛋白组学和突变体蛋白质组学。在总结研究现状的基础上,提出了水稻与微生物互作的蛋白质组学研究中存在的问题,并对该领域的发展前景进行展望。     

利用EST序列构建Mascot本地数据库

对蛋白质质谱数据进行数据库比对和鉴定是蛋白质组学研究技术中的一个重要步骤。由于公共数据库蛋白质数据信息不全,有些蛋白质质谱数据无法得到有效的鉴定。而利用相关物种的EST序列构建专门的质谱数据库则可以增加鉴定未知蛋白的几率。本文介绍了利用EST序列构建Mascot本地数据库的具体方法和步骤,扩展了Mascot检索引擎对蛋白质质谱数据的鉴定范围,从数据库层面提高了对未知蛋白的鉴别几率,为蛋白质组学研究提供了一种较为实用的生物信息学分析技术。     

蛋白质组学技术在植物类囊体膜蛋白研究中的应用

类囊体作为植物光合作用光反应的重要场所,在植物亚细胞蛋白质组学研究中倍受关注.介绍了植物蛋白质组学相关技术,包括双向凝胶电泳(2DE)、高效液相色谱(HPLC)、高效毛细管电泳(HPCE)、质谱(MS)和蛋白质组学数据库在植物类囊体膜蛋白研究中的应用.同时对类囊体膜蛋白质组学的研究趋势进行了探讨.     

快速构建蛋白质结构域克隆库的方法

对蛋白质组学的研究有许多不同的切入方法 .从研究的生物学意义和可行性考虑 ,提出从蛋白结构域入手进行蛋白质组学研究 .SH2 (Srchomology 2 )结构域是细胞信号转导中重要的元件之一 ,人SH2结构域共有约 12 0种 ,对其进行研究将深刻揭示细胞信号转导的规律 .为了得到人所有的SH2结构域序列及克隆 ,首先在公共数据库里检索出了人所有的SH2结构域序列 ,利用国际上现有的共享资源IMAGE(IntegratedMolecularAnalysisofGenomesandTheirExpression)克隆为PCR模板 ,解决了从cDNA文库中难以克隆低丰度结构域的问题 .利用有方向性的TOPO克隆技术提高克隆效率 ,从而快速高效地构建了包括 6 0个SH2结构域的克隆库 .克隆库可以方便地转换到GATEWAY系统具有各种用途的载体上 ,为SH2结构域的蛋白质组学研究奠定了坚实的基础     

生物信息学及其在蛋白质组学中的应用

随着基因组学和蛋白质组学的发展,生物信息学在数据处理中的应用已经越来越广泛。作为数据处理中越来越重要的分析手段,蛋白质组学数据库是蛋白质组学的主要内容之一。本文分别从生物信息学的蛋白质双向电泳数据库和基于蛋白质质谱结果的数据库两个方面,概述了发展中的蛋白质数据库的最新动态和有关信息,同时对主要的热门蛋白质组学数据库站点和资源进行了评价和分析。     

水稻矮缩病毒基因组数据库的构建

二级数据库的构建是生物信息学新的重要领域。目前部分生物的基因组序列测定完成后,正在进行广泛而深入的结构和功能研究,使二级数据库的重要性显得日益突出。水稻矮缩病毒是一种在日本、中国和东南亚感染水稻的病原微生物,给农业生产造成很大损失。根据国际和国内对水稻矮缩病毒基因组的研究,利用已有的基因序列和结构、功能等方面的数据,以计算机网络为载体,参考国际通用数据库的格式,尝试建立一个简洁的、友好的通用性好而且专用性强的二级数据库：水稻矮缩病毒基因组数据库。希望能够为研究普通水稻矮缩病毒的粒子结构、基因表达调控、致病机理和防治方法提供一个良好的工具,为从事水稻矮缩病理论和应用研究的工作者提供方便和帮助,并为探索二级数据库的构建积累经验。     

宏蛋白质组学信息分析的基本策略及其挑战

宏蛋白质组学是一门新型科学,它运用质谱技术规模化地采集自然界微生物种群的蛋白质信息,并结合多种组学数据,开展微生物种群的遗传特征及其生物功能的研究.宏蛋白质组学的信息分析与传统蛋白质组学方法有较大的不同,亟需拓展新的分析思路.由于宏蛋白质组的研究对象是复杂度极高的微生物样品,因此,需要构建尽可能囊括样本中所含微生物的基因组信息的物种数据库.面对庞大的数据库,必须考虑到分析过程中所消耗的计算资源和鉴定结果的质控标准,因此,需要高度优化库容量、搜库、假阳性控制等参数.鉴于宏蛋白质组数据中广泛存在复杂的同源蛋白质序列,因此,需要充分利用NCBI数据库中的分类信息进行匹配,并运用LCA算法过滤处理才能将蛋白质有效地归组到物种.本文立足于宏蛋白质组学信息分析,从宏蛋白质组的数据库建立、蛋白质归并、生物学意义发掘等几个方面着手,对该领域的发展现状、面临挑战以及未来研究方向进行了评述.     

植物膜蛋白质组学研究技术现状

植物膜蛋白质组学是当前植物科学研究的热点领域。本文概论了蛋白质组学在植物膜蛋白研究中的应用,包括双向电泳前膜蛋白样品的制备以及植物质膜、液泡膜和其他膜蛋白组分的蛋白质组学研究进展,并介绍了植物膜蛋白质组学相关的数据库,最后对其发展作了展望。     

试论蛋白质组学的专利保护

蛋白质组学是后基因组时代的新兴学科,是当今生命科学领域新的增长点.蛋白质组学的研究为药物筛选、新药开发、临床诊断及新陈代谢途径研究等提供理论依据和研究基础.对蛋白质组学领域中涉及的蛋白质药物、数据库及检测分离设备等的专利保护现状和策略进行了初步探讨,并强调了加强我国蛋白质组学知识产权保护特别是专利保护的重要性.     

Update and challenges on proteomics in rice

Rice is not only an important agricultural resource but also a model plant for biological research. Our previous review highlighted different aspects of the construction of rice proteome database, cataloguing rice proteins of different tissues and organelle, differential proteomics using 2-DE and functional characterization of some of the proteins identified (Komatsu, S., Tanaka, N., Proteomics 2005, 5, 938-949). In this review, the powerfulness and weaknesses of proteomic technologies as a whole and limitations of the currently used techniques in rice proteomics are discussed. The information obtained from these techniques regarding proteins modification, protein-protein interaction and the development of new methods for differential proteomics will aid in deciphering more precisely the functions of known and/or unknown proteins in rice.     

植物响应病原菌胁迫的蛋白质组学研究进展

随着拟南芥、水稻等模式植物基因组测序的完成,植物基因组学的研究重点已经转变为功能基因组学研究。蛋白质组学成为后基因组时代的重要研究手段,它有助于从分子水平上了解植物功能。主要介绍了双向电泳技术、生物质谱、蛋白质质谱数据的生物信息学分析等蛋白质组学研究的主要技术手段及植物应答病原菌胁迫的蛋白质组学研究进展,并对蛋白质组学在研究植物抗病机制方面的应用前景做出展望。     

Rice proteome analysis: a step toward functional analysis of the rice genome

The technique of proteome analysis using 2-DE has the power to monitor global changes that occur in the protein complement of tissues and subcellular compartments. In this review, we describe construction of the rice proteome database, the cataloging of rice proteins, and the functional characterization of some of the proteins identified. Initially, proteins extracted from various tissues and organelles were separated by 2-DE and an image analyzer was used to construct a display or reference map of the proteins. The rice proteome database currently contains 23 reference maps based on 2-DE of proteins from different rice tissues and subcellular compartments. These reference maps comprise 13 129 rice proteins, and the amino acid sequences of 5092 of these proteins are entered in the database. Major proteins involved in growth or stress responses have been identified by using a proteomics approach and some of these proteins have unique functions. Furthermore, initial work has also begun on analyzing the phosphoproteome and protein-protein interactions in rice. The information obtained from the rice proteome database will aid in the molecular cloning of rice genes and in predicting the function of unknown proteins.     

水稻抗旱耐盐蛋白质组学研究进展

抗旱耐盐是水稻抗逆研究的重要方向。水稻抗旱耐盐蛋白质组学研究通过观察水稻在干旱和盐胁迫条件下的蛋白质组表达情况,动态分析水稻的蛋白质组变化,使研究的结果和性状联系更紧密,相对于从基因组水平上研究更具实际意义。简要介绍了水稻蛋白质组研究的基本方法和技术并重点叙述了水稻抗旱耐盐蛋白质组研究取得的成果。     

适于蛋白双向电泳的水稻叶片样品提取方法初探

在水稻基因组测序完成后,利用蛋白质组学技术揭示水稻基因功能的研究,已成为水稻分子生物学研究的热点之一。水稻叶片作为DNA研究的便利材料被经常使用,但对蛋白质研究来说,占叶片全蛋白50%～60%的核酮糖二磷酸羧化酶（RuBP羧化酶）对低丰度蛋白常常造成掩盖。以水稻叶片为材料,用不同浓度的聚乙二醇（PEG）去除叶片中RuBP羧化酶。通过SDS-PAGE垂直电泳比较发现,浓度为17%的PEG对去除RuBP羧化酶效果最好,所获得的蛋白质样品可以得到质量较高的双向电泳图谱。     

Use of proteomics to understand seed development in rice

Rice is an important cereal crop and has become a model monocot for research into crop biology. Rice seeds currently feed more than half of the world's population and the demand for rice seeds is rapidly increasing because of the fast‐growing world population. However, the molecular mechanisms underlying rice seed development is incompletely understood. Genetic and molecular studies have developed our understanding of substantial proteins related to rice seed development. Recent advancements in proteomics have revolutionized the research on seed development at the single gene or protein level. Proteomic studies in rice seeds have provided the molecular explanation for cellular and metabolic events as well as environmental stress responses that occur during embryo and endosperm development. They have also led to the new identification of a large number of proteins associated with regulating seed development such as those involved in stress tolerance and RNA metabolism. In the future, proteomics, combined with genetic, cytological, and molecular tools, will help to elucidate the molecular pathways underlying seed development control and help in the development of valuable and potential strategies for improving yield, quality, and stress tolerance in rice and other cereals. Here, we reviewed recent progress in understanding the mechanisms of seed development in rice with the use of proteomics.     

Proteomics characterization of different bran proteins between aromatic and nonaromatic rice (Oryza sativa L. ssp. indica)

Proteomic approach is applied for the analysis of seed brans of 14 rice varieties (Oryza sativa L. ssp. indica) which can classify to five aromatic rice and nine nonaromatic rice. The two-dimensional electrophoresis (2-DE) protein patterns for 14 rice varieties were similar within pH ranges of 3-10 and 4-7. To characterize aromatic group-specific proteins, we compared 2-D gels of aromatic rice to nonaromatic rice using PDQUEST image analysis. Four out of six differential spots were identified as hypothetical proteins, but one (SSP 7003) was identified by matrix assisted laser desoption/ionization-quardrupole-time of fight (MALDI-Q-TOF) as prolamin with three matching peptides based on NCBI database. Prolamin is a class of storage proteins with three different polypeptides of 10, 13, and 16 kDa. Spot SSP7003 was identified as a 13 kDa polypeptide of prolamin by combination of mass spectroscopy and N-terminal sequence analyses. In contrast, one sulfur-rich 16 kDa polypeptide of prolamin was found in extremely high intensity in brans of deep-water rice compared to nondeep-water rice. Our results suggest that proteomics is a powerful step to open the way for the identification of rice varieties.     

YPED:An Integrated Bioinformatics Suite and Database for Mass Spectrometry-based Proteomics Research

We report a significantly-enhanced bioinformatics suite and database for proteomics research called Yale Protein Expression Database(YPED) that is used by investigators at more than 300 institutions worldwide. YPED meets the data management, archival, and analysis needs of a high-throughput mass spectrometry-based proteomics research ranging from a singlelaboratory, group of laboratories within and beyond an institution, to the entire proteomics community. The current version is a significant improvement over the first version in that it contains new modules for liquid chromatography–tandem mass spectrometry(LC–MS/MS) database search results, label and label-free quantitative proteomic analysis, and several scoring outputs for phosphopeptide site localization. In addition, we have added both peptide and protein comparative analysis tools to enable pairwise analysis of distinct peptides/proteins in each sample and of overlapping peptides/proteins between all samples in multiple datasets. We have also implemented a targeted proteomics module for automated multiple reaction monitoring(MRM)/selective reaction monitoring(SRM) assay development. We have linked YPED's database search results and both label-based and label-free fold-change analysis to the Skyline Panorama repository for online spectra visualization. In addition, we have built enhanced functionality to curate peptide identifications into an MS/MS peptide spectral library for all of our protein database search identification results.