Systematic characterization of bioactive molecules from the human microbiome

人类微生物组生物活性分子的系统表征

基本信息

批准号：
10647770
负责人：
Mohamed Abou Donia
金额：
$ 68.25万
依托单位：
PRINCETON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-06-16 至 2027-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10647770
关键词：
Bacteria Binding Biological Biological Assay Cells Chemical Structure Chemicals Clostridium difficile Communities Complex Computer Analysis Data Diet Disease Ecology Family Funding Opportunities Future Gene Cluster Health Human Human Microbiome Hybrids In Vitro Individual Intervention Iron Mediating Metagenomics Metals Microbe Molecular Mus Nature Pathogenicity Pathway interactions Peptides Physiology Play Process Production Property Research Role Sampling Siderophores Structure Taxonomy Therapeutic Therapeutic Intervention Time genome editing gut microbiome host-microbe interactions human data in vivo knowledgebase member metagenomic sequencing microbial microbiome microbiome components microbiome research oral microbiome parallelization pathogen polyketides skin microbiome small molecule success synthetic biology tool treatment response

项目摘要

ABSTRACT A complex interplay exists between the human microbiome and the host, resulting in clear effects on human physiology and microbiome ecology. A promising avenue to dissect this interplay at a mechanistic level is through the study of microbiome-derived molecules that mediate important microbe-microbe and microbe-host interactions. In this application, we propose a hybrid computational- synthetic biology approach to discover, rationally prioritize and systematically characterize microbiome- derived molecules. We propose to apply this approach to three structurally diverse classes of bioactive molecules that are widely encoded by the human microbiome but remain severely understudied in terms of both structure and function. First, guided by the computational analysis of biosynthetic gene clusters in metagenomic sequencing data from the human microbiome of thousands of subjects, we will select specific members of the three molecular classes for experimental characterization. Second, we will use genome editing of native members of the microbiome and synthetic biology in a multi-host heterologous expression platform to characterize the selected pathways and their products. Finally, we will employ an array of in vitro, cell-based and mouse colonization assays to interrogate the role of the discovered molecules in mediating relevant host and microbiome functions. Taken together, our approach will unveil an undermined section of the interplay between the human microbiome and the host and provide diverse microbiome-derived bioactive molecules as tools for future mechanistic studies and therapeutic interventions.

抽象的人类微生物组和宿主之间存在复杂的相互作用，从而对人类生理学和微生物组生态学。一个有前途的途径，可以在机械水平是通过研究介导重要的微生物组衍生的分子的研究微生物微生物和微生物 - 宿主相互作用。在此应用中，我们提出了一个混合计算 - 合成生物学方法是发现，合理优先和系统地表征微生物组 - 派生的分子。我们建议将这种方法应用于三种结构上不同的生物活性类别由人类微生物组广泛编码但在结构和功能的术语。首先，在生物合成基因的计算分析的指导下来自数千名受试者的人类微生物组的宏基因组测序数据中的簇，我们将选择三个分子类别的特定成员进行实验表征。第二，我们将在多宿主中使用微生物组和合成生物学的本地成员的基因组编辑表征所选途径及其产品的异源表达平台。最后，我们将采用一系列体外，基于细胞和小鼠定植测定法来审问在介导相关宿主和微生物组函数中发现的分子。总的来说，我们的方法将揭示人类微生物组与宿主并提供多种微生物组衍生的生物活性分子作为未来机械的工具研究和治疗干预措施。