Meta-exoproteomics identifies active plant-microbe interactions operating in the rhizosphere

The advance of DNA sequencing technologies has drastically changed our perception of the complexity and structure of the plant microbiome and its role in augmenting plant health. By comparison, our ability to accurately identify the metabolically active fraction of soil microbiota and their specific functional role is relatively limited. Here, we combined our recently developed protein extraction method and an iterative bioinformatics pipeline to enable the capture and identification of extracellular proteins (meta-exoproteomics) expressed in the rhizosphere of Brassica spp. First, we validated our method in the laboratory by successfully identifying proteins related to the host plant (Brassica rapa) and a bacterial inoculant, Pseudomonas putida BIRD-1, revealing the latter expressed numerous rhizosphere specific proteins linked to the acquisition of plant-derived nutrients. Next, we analysed natural field-soil microbial communities associated with Brassica napus L (Oil Seed rape). By combining deep-sequencing metagenomics with meta-exoproteomics, a total of 1882 proteins were identified in bulk and rhizosphere samples. Importantly, meta-exoproteomics identified a clear shift (p<0.001) in the metabolically active fraction of the soil microbiota responding to the presence of B. napus roots that was not apparent in the composition of the total microbial community (metagenome). This metabolic shift was associated with the stimulation of rhizosphere-specialised bacteria, such as Gammaproteobacteria, Betaproteobacteria and Flavobacteriia and the upregulation of plant beneficial functions related to phosphorus and nitrogen mineralisation. By providing the first meta-proteomic level assessment of the active plant microbiome at the field-scale, this study demonstrates the importance of moving past a genomic assessment of the plant microbiome in order to determine ecologically important plant: microbe interactions driving plant growth.