Details of Award
NERC Reference : NE/T010959/1
Reverse engineering the soil microbiome: detecting, modeling, and optimizing signal impacts on microbiome metabolic functions
Grant Award
- Principal Investigator:
- Professor E Takano, The University of Manchester, Chemistry
- Co-Investigator:
- Professor R Breitling, The University of Manchester, Chemistry
- Grant held at:
- The University of Manchester, Chemistry
- Science Area:
- Earth
- Overall Classification:
- Unknown
- ENRIs:
- Biodiversity
- Environmental Risks and Hazards
- Science Topics:
- Cell Signalling - Synbio
- Synthetic biology
- Soil science
- Soil ecosystems
- Abstract:
- 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.
- NERC Reference:
- NE/T010959/1
- Grant Stage:
- Awaiting Completion
- Scheme:
- Directed (RP) - NR1
- Grant Status:
- Active
- Programme:
- Signals in the Soil
This grant award has a total value of £859,366
FDAB - Financial Details (Award breakdown by headings)
| DI - Other Costs | Indirect - Indirect Costs | DA - Investigators | DA - Estate Costs | DI - Staff | DA - Other Directly Allocated | DI - T&S |
|---|---|---|---|---|---|---|
| £83,009 | £269,883 | £50,736 | £82,328 | £229,978 | £86,184 | £57,246 |
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