I have estabished a collaborative project with Dr. Amir Sitzenberg, Israel. We have published a paper on our preliminary data, and applied for funding.
The use of biocontrol agents to manage the many plant pathogens found in agricultural settings is very appealing to growers and consumers alike. Regrettably, the efficacy of promising candidates emerging from lab experiments is often several orders of magnitude lower in field conditions. Plants and soils harbor rich and very well adapted microbial communities. We propose that a main challenge to developing biological control is the protection of biocontrol microbes from the resident microbial community. This includes accounting for interactions between the biocontrol agent and members of the resident microbiota. To test this, we will build whole metagenome metabolic models to comprehensively describe the biochemical interactions within a microbial community. We will quantify the flux of metabolites as well as the growth and survival of microbes. Comprehensive microbial metabolic models of diseased plants and the soil they inhabit can promote the accurate identification of promising biocontrol-agent candidates, before they undergo costly and time consuming field trials. Microbial metabolic models can further pinpoint additives, in the form of biochemicals or co-cultures, that will support the novel biocontrol agent in field conditions. We have collected longitudinal DNA samples from the soil and root in two crops and sites, to characterise the microbial diversity of our study system (root-knot nematode infected plants). We will developing whole, metagenome metabolic models from the data, as a tool with which to assess biocontrol agents against root-knot nematodes, and improve their efficacy: model building is at the heart of this application. Whole genome metabolic models will be reconstructed by the Israeli partner and will be fine tuned by the American partner using their gene-expression and network expertise. Several nematicidal microbial isolates, both commercial and novel, will be scored by the models. The predictive power of the models will be established by comparing the performance of high scoring and low scoring isolates in a pot experiment based on root-knot nematode infested agricultural soil. The models will be made available online, in a graphic-user interface public system.