Advancing Drug Development from Medicinal Plants using Transcriptomics and Metabo

利用转录组学和代谢促进药用植物药物开发

• 批准号: 7854387
• 负责人: Joe Chappell
• 金额: $ 302.76万
• 依托单位: UNIVERSITY OF KENTUCKY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7854387
• 关键词: Address; Agricultural Crops; Aliquot; Anabolism; Animal Model; Arabidopsis; Arts; Bioinformatics; Biological Factors; Biological Sciences; Bone callus; Communities; Custom; DNA Sequence; Data; Data Set; Databases; Deposition; Development; Flowers; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Genes; Genome; Genomics; Goals; Grant; Health; Human; Knowledge; Libraries; Link; Maize; Maps; Medicinal Plants; Messenger RNA; Metabolic; Metabolic Pathway; Metabolism; Methods; Molecular Profiling; Morphine; Organism; Paclitaxel; Pathway interactions; Pharmacologic Substance; Plant Genes; Plant Leaves; Plant Model; Plant Roots; Plants; Process; Production; Quality Control; RNA; Reading; Relative (related person); Research; Resources; Rice; Sampling; Sorghum; Technology; Time; Tissue Sample; Tissues; Titanium; Transcript; United States National Institutes of Health; Variant; Vincristine; Work; biological research; candidate identification; drug development; gene function; genome sequencing; improved; insight; knowledge base; metabolomics; next generation; novel; public health relevance; stem; tool; transcriptomics; user-friendly; virtual; web site; Address; Agricultural Crops; Aliquot; Anabolism; Animal Model; Arabidopsis; Arts; Bioinformatics; Biological Factors; Biological Sciences; Bone callus; Communities; Custom; DNA Sequence; Data; Data Set; Databases; Deposition; Development; Flowers; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Genes; Genome; Genomics; Goals; Grant; Health; Human; Knowledge; Libraries; Link; Maize; Maps; Medicinal Plants; Messenger RNA; Metabolic; Metabolic Pathway; Metabolism; Methods; Molecular Profiling; Morphine; Organism; Paclitaxel; Pathway interactions; Pharmacologic Substance; Plant Genes; Plant Leaves; Plant Model; Plant Roots; Plants; Process; Production; Quality Control; RNA; Reading; Relative (related person); Research; Resources; Rice; Sampling; Sorghum; Technology; Time; Tissue Sample; Tissues; Titanium; Transcript; United States National Institutes of Health; Variant; Vincristine; Work; biological research; candidate identification; drug development; gene function; genome sequencing; improved; insight; knowledge base; metabolomics; next generation; novel; public health relevance; stem; tool; transcriptomics; user-friendly; virtual; web site

DESCRIPTION (provided by applicant): Medicinal plants produce a wealth of pharmaceutical compounds such as taxol, vincristine, and morphine. Unfortunately, the specialized secondary metabolic pathways leading to such compounds remain poorly understood and progress in elucidating and manipulating these taxonomically restricted metabolic pathways has been correspondingly slow. This has been exacerbated by the limited development of "omics"-level resources for medicinal plants, which has meant that as a group, research in medicinal species have not benefited to the same extent from the genomics revolution, as have research in model plants and agronomic crop species. This proposal describes the combined use of state-of-the-art sequencing technologies, metabolomics capabilities, and bioinformatics to develop an unrestricted, public resource to address this growing gap in our knowledge base of species-specific plant metabolism and accelerate the identification and functional analysis of genes involved in natural product biosynthesis in 20 widely used medicinal plant species. This resource will provide the research community with user-friendly access to the DNA sequences and expression profiles of each plant's transcriptome and associated metabolome, which we anticipate will have a translational effect on drug development. To achieve this goal, we will utilize next generation sequencing approaches to determine the near-complete set of mRNAs encoded by each medicinal plant species. Transcriptome profiling of up to 20 chemically diverse tissues/treatments per species using the RNA-Seq method from Illumina will be performed and correlated with metabolite profiles generated through LC-TOF and GC-MS for these same samples. All sequence and gene expression data will be deposited into NCBI and made available, along with metabolite profiling data at medicinalplantgenomics.msu.edu, a custom website developed by the research consortium. Thus, this NIH Grand Opportunities Grant will provide searchable and downloadable databases for medicinal plant gene sequences, expression profiles and metabolites that can be accessed and utilized by the research community to facilitate discovery of the pathways and genes responsible for biosynthesis of key pharmaceuticals. High throughput sequencing of genomes and transcriptomes has revolutionized and accelerated the pace and progress of research across the life sciences and this proposal will for the first time extend these advances into the medicinal plant arena on a broad scale. PUBLIC HEALTH RELEVANCE: This proposal describes the combined use of state-of-the-art DNA sequencing technologies, metabolomics capabilities, and bioinformatics to develop an unrestricted, public resource to advance our knowledge base of species-specific plant metabolism and accelerate the identification and functional analysis of genes involved in natural product biosynthesis in 20 widely used medicinal plant species. This resource will provide the research community with user-friendly access to the DNA sequences and expression profiles of each plant's transcriptome and associated metabolome, which we anticipate will have a translational effect on drug development.

描述（由申请人提供）：药用植物生产大量的药物化合物，例如紫杉醇，vincristine和吗啡。不幸的是，导致此类化合物的专门二级代谢途径在阐明和操纵这些分类学限制的代谢途径方面的理解和进展仍然很慢。这对药用植物的“ OMICS”资源的有限发展加剧了这一点，这意味着，作为一个基因组革命的药物研究的研究并没有受益于基因组革命的程度，就像对模型植物和农艺农作物物种的研究一样。该建议描述了最先进的测序技术，代谢组学能力和生物信息学的综合使用，以开发一种不受限制的公共资源，以解决我们在我们的知识基础上越来越多的差距，并加速了对20种广泛使用的物种生物学物种物种的鉴定和功能分析，并加速了涉及的基因鉴定和功能分析。该资源将为研究社区提供对用户友好的访问，访问每种植物的转录组和相关代谢组的DNA序列和表达概况，我们预计这将对药物开发产生转化作用。为了实现这一目标，我们将利用下一代测序方法来确定每种药物植物物种编码的接近完整的mRNA集。使用来自Illumina的RNA-SEQ方法对每种物种的转录组分析将多达20种化学多样性的组织/处理，并将与这些样品通过LC-TOF和GC-MS产生的代谢物概况进行并相关。所有序列和基因表达数据都将存放到NCBI中，并在MedicinalPlantgenomics.msu.edu上提供了由研究财团开发的自定义网站上的代谢物分析数据。因此，这项NIH大机会赠款将为研究界可以访问和利用的药用植物基因序列，表达概况和代谢物提供可搜索和可下载的数据库，以促进发现关键药物生物合成的途径和基因。基因组和转录组的高通量测序彻底改变了整个生命科学的研究的步伐和进步，该建议将首次将这些进步扩展到广泛的药用植物领域。 公共卫生相关性：该提案描述了最先进的DNA测序技术，代谢组学能力和生物信息学的共同使用，以开发不受限制的公共资源，以促进我们对物种特异性植物代谢的知识库，并加速对基因在20种较大物种中使用的基因鉴定和功能分析。该资源将为研究社区提供对用户友好的访问，访问每种植物的转录组和相关代谢组的DNA序列和表达概况，我们预计这将对药物开发产生转化作用。