Reverse engineering the soil microbiome: detecting, modeling, and optimizing signal impacts on microbiome metabolic functions

概述：我们的项目将提供对信号在调节土壤微生物生态和抑制植物病害中的作用的基本见解。这项工作为精准农业工程功能土壤微生物群的研究奠定了基础。我们的团队由来自英国和美国的土壤生态学、基因工程、代谢组学和群落建模方面的专家组成。目标：1)开发和测试遗传记录器(GR)菌株，以‘倾听和报告’土壤中调节链霉菌初级和次级代谢途径的信号。从抑制疾病的土壤中分离出来；2)建立和测试依赖初级和次生代谢诱导的物种-物种相互作用如何影响多物种群落；以及3)发现潜在信号对链霉菌代谢的影响，并利用信号来优化土壤中的微生物功能。方法：1)我们将利用丝氨酸整合酶介导的重组，创建GRs来检测土壤微生物中感兴趣的基因/通路的激活。GRS将由未知的化学、物理和生物信号触发，以产生可以使用下一代测序技术轻松量化的状态变化。使用这些GR，我们将能够在单个高通量实验中同时记录数百种代谢活动的激活，跨越不同的微生物物种。2)我们将利用基因组规模的代谢模型、转录组学和代谢组学将信号与功能联系起来。我们将扩展现有的代谢建模平台，纳入新的功能，以了解信号将如何影响单个细菌的生理，并改变新兴的生态系统动态。转录组和代谢组数据将用于验证和扩展当前关于外源代谢物在系统行为中的作用的知识，并促进对土壤微生物群的系统水平的理解。3)我们将在体外筛选潜在的信号对链霉菌的抗生素抑制和营养利用表型的直接影响。我们将使用GRs来筛选它们在介导链霉菌初级和次级代谢活动中的假定信号，提供一个信号发现平台和与表型数据的直接比较。我们将创造信号优化的分离组合或分离/信号组合，并测试它们减少土壤中小麦和萝卜幼苗上植物病害的能力。最后，我们将测试GRS在复杂土壤群落中检测信号的有效性。智力优势：拟议的研究将促进对信号在调节复杂土壤微生物群落组装、动态和功能行为中所起作用的基础理解；为研究体内信号动力学提供新的工具，有可能作为土壤微生物活动的传感器；增强对微生物群落内初级和次生代谢活动的系统水平的理解和建模；以及测试信号优化接种剂提高土壤系统中植物健康和生产力的能力。全球可持续种植制度。

Overview: Our project will provide fundamental insights into the roles of signals in mediating the ecology of soil microbes and suppression of plant diseases. This work establishes a foundation for engineering functional soil microbiomes for precision agriculture. Our team consists of experts in soil ecology, genetic engineering, metabolomics, and community modeling from the UK and USA.Objectives: 1) Develop and test genetic recorder (GR) strains to 'listen and report' on signals in the soil that regulate primary and secondary metabolic pathways in Streptomyces spp. isolated from disease suppressive soils; 2) Model and test how species-species interactions that rely on primary and secondary metabolic induction impact multi-species communities; and 3) Discover effects of potential signals on Streptomyces metabolism and harness signals to optimize microbial functional capacities in soil.Methods: 1) We will create GRs to detect the activation of genes/pathways of interest in soil microbes using serine integrase-mediated recombination. The GRs will be triggered by yet unknown chemical, physical, and biological signals to produce a state change that can be easily quantified using Next-Generation Sequencing technology. Using these GRs, we will be able to simultaneously record the activation of hundreds of metabolic activities, across diverse microbial species, in a single high-throughput experiment. 2) We will utilize genome-scale metabolic models, transcriptomics, and metabolomics to connect signals to functions. We will extend existing metabolic modeling platforms to incorporate novel functionality to understand how signals will influence the physiology of individual bacteria and alter emergent ecosystem dynamics. Transcriptomic and metabolomic data will be used to validate and extend current knowledge of exo-metabolite roles in system behavior and advance systems-level understanding of soil microbiomes. 3) We will screen potential signals for their direct effects on Streptomyces antibiotic inhibitory and nutrient use phenotypes in vitro. We will use the GRs to screen presumptive signals for their role in mediating Streptomyces primary and secondary metabolic activities, providing both a signal discovery platform and a direct comparison with phenotypic data. We will create signal-optimized isolate combinations or isolate/signal combinations and test their capacities to reduce plant diseases on wheat and radish seedlings in soil. Finally, we will test the effectiveness of the GRs in detecting signals in complex soil communities.Intellectual Merit: The proposed research will advance fundamental understanding of the roles of signals in mediating the assembly, dynamics, and functional behaviors of complex soil microbiomes; provide novel tools for studying signaling dynamics in vivo, with potential to serve as sensors of microbial activities in soil; enhance systems-level understanding and modeling of primary and secondary metabolic activities within microbiomes; and test the capacity of signal-optimized inoculants to enhance plant health and productivity in soil systems. sustainable cropping systems worldwide.