MIRA: Enzymology and Self-Resistance of Natural Product Biosynthesis
MIRA: Enzymology and Self-Resistance of Natural Product Biosynthesis
批准号:
10597896
负责人:
Yi Tang
金额:
$5.94万
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
未结题
起止时间:
2016-05-01 至 2026-03-31
关键词:
AddressAnabolismApplications GrantsAreaBiologicalChemical StructureCyclizationEnzymatic BiochemistryEnzymesFamilyFunding MechanismsGene ClusterGenomeGrantHumanInvestigationKnowledgeLeadLinkMetabolismMethodsMicrobial Genome SequencingMiningMoldsNatural ProductsNatural ResistanceNatureOrganismPathway interactionsPhenotypeProteinsRenaissanceResearchResearch ActivityResistanceResistance developmentStructureTherapeuticTimeVariantbasebioactive natural productsenzyme activitymicrobial genomeparent grantprogramsprotein transportresistance generesistance mechanismsynthetic biologytool
中文摘要
项目摘要/摘要
微生物基因组测序和合成生物学的最新进展创造了
天然产品发现的复兴。这种及时的组合提供了很大的希望来寻找
展示新结构和生物活性的天然产物。尽管如此
潜力,但仍然很难i)直接从生物合成基因预测产品结构
集群(BGC)。这是因为我们对天然产品中所含的酶的了解
生物合成仍然有限,特别是关于高度程序化的酶
真核生物,如丝状真菌;ii)优先考虑BGC,这可能导致新的
自然界的化学结构。这主要是由于该领域对研究充分的自然资源的关注。
产品系列和核心生物合成酶;以及iii)将生物活性与
BGC在基因组挖掘方面的努力。这代表了基因组挖掘与传统的
基于表型筛选的发现,其中天然产物分离是由生物学指导的
活动。这笔米拉拨款将通过一个全面的研究计划来解决这些限制
专注于真菌天然产物的发现和生物合成的研究。
这个Mira项目的第一个一般领域是获得对核心的基本了解
参与真菌天然产物生物合成的酶。特别是,我们将
重点了解真菌PKSS和NRPS的迭代编程规则。其他
核心酶编程规则的各个方面,包括环化和非正则结构域,将
被调查。我们还将调查真菌的异常剪裁酶活性。
生物合成途径,重点是PLP依赖酶和氧化酶。一批
将进行化合物驱动的生物合成研究。这方面的第二个一般领域
Mira项目是开发和改进基因组挖掘工具。最重要的研究
这一领域的活动是基于我们最近开发的抗病基因引导的靶基因组
挖掘,其中我们使用BGC中天然产品目标的共同聚集的、具有抗性的变体
作为发现所需生物活性的天然产物的指南。这一策略也可以
用于将生物活性赋予已知的天然产品。这里的目标有两个:
1)扩大可通过抗性基因识别的靶标列表,对酶和
蛋白质在中枢的教条、蛋白质的运输、新陈代谢等。在这里我们将进行基因组
挖掘和/或天然产品生物活性表征,以将代谢物与目标联系起来;以及2)
了解抵抗的机制,这将教会我们大自然是如何进化抵抗的
酶,并完善我们对如何克服潜在的耐药性的理解。
英文摘要
PROJECT SUMMARY/ABSTRACT
Recent progresses in microbial genome sequencing and synthetic biology have created
a renaissance in natural product discovery. This timely combination offers great promise to find
natural products displaying new structures and biological activities. Notwithstanding such
potential, it remains difficult to i) predict product structures directly from biosynthetic gene
clusters (BGCs). This is because our knowledge of enzymes that are involved in natural product
biosynthesis remains limited, especially with regard to the highly programmed enzymes from
eukaryotic organisms such as filamentous fungi; ii) prioritize BGCs that can lead to new-to-
nature chemical structures. This is primarily due to the focus of the field on well-studied natural
product families and core biosynthetic enzymes; and iii) connect the biological activity with
BGCs in genome mining efforts. This represents a gap between genome mining and traditional
phenotypical screen-based discovery in which natural product isolation is guided by biological
activity. This MIRA grant will address these limitations with a comprehensive research program
focused on fungal natural product discovery and biosynthetic investigation.
The first general area of this MIRA project is to gain fundamental understanding of core
enzymes that participate in the biosynthesis of fungal natural products. In particular, we will
focus on understanding the iterative programming rules of fungal PKSs and NRPSs. Other
aspects of core enzyme programming rules, including cyclization and noncanonical domains will
be investigated. We will also investigate the unusual tailoring enzyme activities of fungal
biosynthetic pathways, with emphasis on PLP-dependent and oxidative enzymes. A number of
compound driven biosynthetic investigations will be conducted. The second general area of this
MIRA project is to develop and refine tools for genome mining. The most important research
activity in this area is based on our recently developed resistance gene guided target genome
mining, in which we use a co-clustered, resistant variant of the natural product target in the BGC
as a guide to discover natural product of desired biological activity. This strategy can also be
used to assign biological activities to known natural products. The objectives here are two-fold:
1) to expand the list of targets that may be identified via resistance gene, to enzymes and
proteins in the central dogma, protein transport, metabolism, etc. Here we will perform genome
mining and/or natural product bioactivity characterization to link metabolites to targets; and 2) to
understand the mechanism of resistance, which will teach us how Nature evolves resistant
enzymes, and refine our understanding of how to overcome potential resistance.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
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海外基金