Assessing plant-microbe interactions in the rhizosphere using spatially resolved proteomics

Extensive spatial variability combined with analytical challenges associated with soil sampling complicate efforts to elucidate plant-microbe interactions within the rhizosphere, changes in these relationships over time, and the impacts of shifting microenvironmental conditions on microbial community membership and activity. Proteomics analysis of root or soil samples can provide insights to the taxonomy and functional capability of microbial populations and be used to augment various genomic and imaging techniques. Historically, however, proteomics relies on bulk level sampling by removing rhizosphere over relatively large lengths of root surface and is, therefore, neither spatially specific nor non-destructive. We are employing spatially resolved, non-destructive harvesting of mobile proteins onto a membrane to enable both two-dimensional protein mapping and proteomic analysis within rhizosphere while preserving the sample for either timeseries measurements or complementary, destructive techniques.

We are using rhizoboxes planted with switchgrass (variety Cave-in-rock) and constructed with natural soil (Kellogg Biological Station, Hickory Corners, Michigan, USA) to develop the approach. We are coupling membrane extraction with specialized sample digestion, purification, and analysis to enable proteomic interpretation. Through its non-destructive nature, this approach permits timeseries analyses for tracking specific taxa and, in some cases, functions associated with rhizosphere processes before and after a system perturbation or over plant growth phases during a growing season. The method’s high sensitivity enables spatial analysis at the up to two-millimeter diameter scale along the rhizobox sampling plane and samples can be manually selected based on proximity to specific root structure, metabolic hotspots, or other parameters of choice. We are using this analysis to track statistically significant shifts in plant and microbe contributions to rhizosphere proteome associated with roots at different growth stages. We are also linking this approach to a ¹³C tracer to identify specific taxonomic groups having the closest metabolic association with a host plant to identify shifts in plant-microbe interactions associated with nutrient availability. For instance, we are using a split root rhizobox approach to monitor the plasticity of plant-microbe C exchange associated with P availability. Combined, the spatial and ¹³C tracer components of this proteomic technique can help illuminate understanding of the complex inter-kingdom interactions within the rhizosphere and the implications these interactions have on driving C cycling and plant performance.