植物激素相关核酸和蛋白质二级数据库的构建与应用

以NCBI维护的一级数据库为数据源建立植物激素相关核酸和蛋白质二级数据库。将该二级数据库设计为基因、蛋白质和文献三部分,编写软件从上述数据源中采集数据,并以XML作为中间格式保存,通过解析提交到二级数据库中并集成部分生物信息学工具软件,初步实现了数据检索、统计分析、基于Web的本地化BLAST同源序列检索、序列的自动拼接以及蛋白质结构和功能位点的分析等功能。该二级数据库的构建为植物激素作用分子机理研究提供了高针对性的植物激素数据源和生物信息学辅助工具。     

生物信息学数据库研究文献引文与热点分析

以Web of Science为数据源,简要概括生物信息学数据库研究的发展趋势。利用Cite Space可视化工具展现生物信息学数据库研究的知识基础和研究热点图谱,为开展生物信息学数据库领域相关的理论研究和实践活动提供借鉴,以便推动生物信息学数据库研究的发展。研究表明：1990年Altschul SF发表的＂局部比对搜索工具——BLAST＂是生物信息学数据库研究的重要知识来源文献;热点主题集中在序列库、基因组数据库、分类数据库、蛋白质数据库、数据库更新、集成系统等。     

CXCL12-α基因编码区的克隆与生物信息学分析

目的:克隆人源CXCL12-α的成熟肽编码序列后进行生物信息学分析及其蛋白质结构与功能预测。方法:采用RTPCR方法从人骨髓组织中克隆CXCL12-α基因序列,并将编码其成熟蛋白的核酸片段插入原核表达载体pET-30a(+)中,转化Escherichia coli后进行酶切鉴定和DNA序列测定。利用在线网络生物信息学相关数据库和分析软件对测序结果进行分析,并对重组蛋白的一、二、三级结构及功能等进行验证和预测。结果:获得了基因序列为263 bp的人源CXCL12-α基因,与GenBank中公布序列一致。双酶切鉴定及DNA测序验证结果正确。生物信息学检索该基因编码蛋白的氨基酸序列与理化参数显示,蛋白无跨膜区,在第29位有一个Ser为蛋白激酶磷酸化位点,第1~21位可能为信号肽区域。ɑ-螺旋,无规则卷曲,延伸链和β-转角数量分别占总二级结构的44.94%、22.47%、21.35%、11.24%。同源建模预测信息可信度为0.68,该蛋白G-factor结构计分总平均为0.33,结构检验表明该蛋白属于正常范围内。二级结构和拓扑结构信息、蛋白质结合位点三维图和预测蛋白可能催化口袋及结合位点、三维结构模拟的可视化结构显示其空间结构稳定。结论:人源CXCL12-α分子克隆成功,网络数据库等生物信息学分析及结合蛋白质结构与功能预测可为深入研究CXCL12-α提供理论指导。     

基于生物信息学方法预测人线粒体转录终止因子3蛋白的结构与功能

目的:基于生物信息学预测人线粒体转录终止因子3(hMTERF3)蛋白的结构与功能。方法:利用GenBank、Uniprot、ExPASy、SWISS-PROT数据库资源和不同的生物信息学软件对hMTERF3蛋白进行系统研究,包括hMTERF3的理化性质、跨膜区和信号肽、二级结构功能域、亚细胞定位、蛋白质的功能分类预测、同源蛋白质多重序列比对、系统发育树构建、三级结构同源建模。结果:软件预测hMTERF3蛋白的相对分子质量为47.97×103,等电点为8.60,不具信号肽和跨膜区;二级结构分析显示主要为螺旋和无规则卷曲,包含6个MTERF基序,三级结构预测结果与二级结构预测结果相符;亚细胞定位分析结果显示该蛋白定位于人线粒体;功能分类预测其为转运和结合蛋白,参与基因转录调控;同源蛋白质多重序列比对和进化分析显示,hMTERF3蛋白与大鼠、小鼠等哺乳动物的MTERF3蛋白具有高度同源性,在系统发育树上聚为一类。结论:hMTERF3蛋白的生物信息学分析为进一步开展对该蛋白的结构和功能的实验研究提供了理论依据。     

美洲大蠊新基因Parcxpwxxq01的分析及功能预测

为进一步研究已发现的美洲大蠊新基因Parcxpwxxq01,我们采用BLASTp,ORF Finder,ProtScale,ScanProsite和Tmpred Server等软件或数据库进行相似性比较、开放读码框预测和编码蛋白质的功能等生物信息学方法对该序列进行特征分析和功能预测,以获得该基因及其编码的蛋白质的更多功能提示。结果发现得到的Parcxpwxxq01序列是该基因的全长序列,该基因编码的蛋白质是一碱性跨膜蛋白,该蛋白质可能为美洲大蠊的药用有效成分,有进一步研究的价值。     

利用SWISS-PROT网上获取生物信息学资源

生物信息学是是采用数学、统计学和计算机方法对生物学数据信息进行采集、存储、传播、分析、归类、解释的科学[1].Internet网络是信息传输、检索、获取、交流的重要手段.当前,在Internet网上可以查询到大量的生物信息学数据库,其中SWISS-PROT蛋白质序列数据库是网上生物信息学最核心的3个数据库之一.通过该数据库,可以较完整地获得生物大分子的序列信息.同时,研究者也可以将测定的序列信息通过该数据库予以认定、发表、交流.本文主要探讨SWISS-PROT蛋白质序列数据库的特点、检索方法及利用Internet获取蛋白质序列信息.     

人溶菌酶基因的克隆和生物信息学分析

目的:克隆人溶菌酶基因并进行生物信息学分析及构建其原核表达载体方法:采用RT-PCR法扩增人溶菌酶基因,运用相关生物信息学软件对其理化性质、疏/亲水性、功能结构域及蛋白质二级结构等进行分析.将该基因克隆入载体pET32a,PCR、双酶切鉴定和核苷酸序列测定.结果:获得约400bp的人溶菌酶基因,其序列与GenBank中公布序列完全一致.生物信息学分析显示人溶菌酶基因编码130个氨基酸,分子量为14.7kDa,理论等电点为9.28,含有一个功能结构域,二级结构主要由α-螺旋、无规则卷曲、延伸链和β-转角组成.经PCR、双酶切鉴定和核苷酸序列测定,表明重级表达质粒构建成功.结论:该基因的克隆、生物信息学分析及原核表达质粒的构建为进一步研究其功能奠定了基础.     

利用SWISS-PROT网获取生物信息学资源

生物信息学是是采用数学、统计学和计算机方法对生物学数据信息进行采集、存储、传播、分析、归类、解释的科学[1] 。Ｉｎｔｅｒｎｅｔ网络是信息传输、检索、获取、交流的重要手段。当前 ,在Ｉｎｔｅｒｎｅｔ网上可以查询到大量的生物信息学数据库 ,其中ＳＷＩＳＳ ＰＲＯＴ蛋白质序列数据库是网上生物信息学最核心的 3个数据库之一。通过该数据库 ,可以较完整地获得生物大分子的序列信息。同时 ,研究者也可以将测定的序列信息通过该数据库予以认定、发表、交流。本文主要探讨ＳＷＩＳＳ ＰＲＯＴ蛋白质序列数据库的特点、检索方法及利用Ｉ…     

微生物基因组注释系统MGAP

利用生物信息学方法和工具开发了微生物基因组注释系统（Microbial genome annotation package, MGAP）,并用于蓝细菌PCC7002的基因组注释。该系统由基因组注释系统和基于Web的用户接口程序两部分组成。基因组注释系统整合多个基因识别、功能预测和序列分析软件;以及蛋白质序列数据库、蛋白质资源信息系统和直系同源蛋白质家族数据库等。用户接口程序包括基因组环状图展示、基因和开放读码框在染色体上的分布图,以及注释信息检索工具。该系统基于PC微机和Linux操作系统,用MySQL作数据库管理系统、用Apache作Web服务器程序,用Perl脚本语言编写应用程序接口,上述软件均可免费获得。     

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。     

Proteomic analysis of the lake trout (Salvelinus namaycush) heart and blood: The beginning of a comprehensive lake trout protein database

Lake trout (Salvelinus namaycush) are a top-predator species in the Laurentian Great Lakes that are often used as bioindicators of chemical stressors in the ecosystem. Although many studies are done using these fish to determine concentrations of stressors like legacy persistent, bioaccumulative and toxic chemicals, there are currently no proteomic studies on the biological effects these stressors have on the ecosystem. This lack of proteomic studies on Great Lakes lake trout is because there is currently no complete, comprehensive protein database for this species. Here, we employed proteomics approaches to develop a lake trout protein database that could aid in future research on this fish, in particular exposomics and adductomics. The current study utilized heart tissue and blood from two lake trout. Our previous work using lake trout liver revealed 4194 potential protein hits in the NCBI databases and 3811 potential protein hits in the UniProtKB databases. In the current study, using the NCBI databases we identified 838 proteins for the heart and 580 proteins for the blood tissues in the biological replicate 1 (BR1) and 1180 potential protein hits for the heart and 561 potential protein hits for the blood in BR2. Similar results were obtained using the UniProtKB databases. This study builds on our previous work by continuing to build the first comprehensive lake trout protein database and provides insight into protein homology through evolutionary relationships. This data is available via the PRIDE partner repository with the dataset identifier PXD023970.     

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。     

Plant genome resources at the national center for biotechnology information

The National Center for Biotechnology Information (NCBI) integrates data from more than 20 biological databases through a flexible search and retrieval system called Entrez. A core Entrez database, Entrez Nucleotide, includes GenBank and is tightly linked to the NCBI Taxonomy database, the Entrez Protein database, and the scientific literature in PubMed. A suite of more specialized databases for genomes, genes, gene families, gene expression, gene variation, and protein domains dovetails with the core databases to make Entrez a powerful system for genomic research. Linked to the full range of Entrez databases is the NCBI Map Viewer, which displays aligned genetic, physical, and sequence maps for eukaryotic genomes including those of many plants. A specialized plant query page allow maps from all plant genomes covered by the Map Viewer to be searched in tandem to produce a display of aligned maps from several species. PlantBLAST searches against the sequences shown in the Map Viewer allow BLAST alignments to be viewed within a genomic context. In addition, precomputed sequence similarities, such as those for proteins offered by BLAST Link, enable fluid navigation from unannotated to annotated sequences, quickening the pace of discovery. NCBI Web pages for plants, such as Plant Genome Central, complete the system by providing centralized access to NCBI's genomic resources as well as links to organism-specific Web pages beyond NCBI.     

Facilities that make the PDB data collection more powerful

We describe a series of databases and tools that directly or indirectly support biomedical research on macromolecules, with focus on their applicability in protein structure bioinformatics research. DSSP, that determines secondary structures of proteins, has been updated to work well with extremely large structures in multiple formats. The PDBREPORT database that lists anomalies in protein structures has been remade to remove many small problems. These reports are now available as PDF‐formatted files with a computer‐readable summary. The VASE software has been added to analyze and visualize HSSP multiple sequence alignments for protein structures. The Lists collection of databases has been extended with a series of databases, most noticeably with a database that gives each protein structure a grade for usefulness in protein structure bioinformatics projects. The PDB‐REDO collection of reanalyzed and re‐refined protein structures that were solved by X‐ray crystallography has been improved by dealing better with sugar residues and with hydrogen bonds, and adding many missing surface loops. All academic software underlying these protein structure bioinformatics applications and databases are now publicly accessible, either directly from the authors or from the GitHub software repository.     

Parallelisation of the blast algorithm

Retrieving homologous DNA and protein sequences from existing databases is a fundamental routine in bioinformatics research. Programs of the NCBI BLAST family are widely used for this purpose. We evaluated paraBLAST, a parallelised version of the NCBI BLAST algorithm, using a Message Passing Interface (MPI) on a multi-node compute cluster. Here, we propose static and dynamic database-partitioning schemes based on the availability of the cluster. We evaluated the application of the algorithm in querying nucleotide sequences against a large-scale sequence database with different numbers of database partitions, and hence, different numbers of CPUs. Since the program's tasks are performed independently of each other, each available CPU can run its own copy of BLAST queries, resulting in reduced interference between processes and leading to a highly scalable solution.     

Tracker: continuous HMMER and BLAST searching

SUMMARY: Tracker is a web-based email alert system for monitoring protein database searches using HMMER and Blast-P, nucleotide searches using Blast-N and literature searches of the PubMed database. Users submit searches via a web-based interface. Searches are saved and run against updated databases to alert users about new information. If there are new results from the saved searches, users will be notified by email and will then be able to access results and link to additional information on the NCBI website. Tracker supports Boolean AND/OR operations on HMMER and BLASTP result sets to allow users to broaden or narrow protein searches. AVAILABILITY: The server is located at http://jay.bioinformatics.ku.edu/tracker/index.html. A distribution package including detailed installation procedure is freely available from http://jay.bioinformatics.ku.edu/download/tracker/.