User: Minerai de Fer Québec, T2 Environnement, Tata Steel Minerals Canada, ViridisTerra Innovations Inc.
Experimental split-plot setups with boreal plant species inoculated with selected microbial strains will be established at two iron ore mine sites in Northern Québec. The performance of the inoculated plants will be evaluated using a phenomic approach, by measuring morpho-ecophysiological parameters (height, diameter, survival rate, photosynthesis, chlorophyll, respiration using the LICOR LI-6400XT Portable). The monitoring of inoculant strains in roots and soils, within a complex edaphic environment, will be carried out by a genomic approach (high-throughput sequencing of the complete genomes of inoculants). Bioinformatics analysis using the QIIME 2 pipeline will allow for the assembly, annotation and comparison of sequences, with the aim of developing unique biomarkers for species and strain identification in the environment. Different machine learning algorithms will be tested to improve the accuracy of identification. We will also test the new KoverMS machine learning algorithm, specifically designed for biomarker discovery in omics datasets of a complex telluric microbiome. Strain-specific primers, developed from genome analysis, will be used for ddPCR to quantify inoculants in roots and soils and assess their competitiveness in the consortium. This work will demonstrate the efficacy and specificity of this culture-independent approach, based on the use of strain-specific primers, allowing rapid and inexpensive detection of bioinoculants in the rhizosphere of plants, for monitoring and quantification purposes under non-sterile and uncontrolled conditions in the field.