Spatially resolved proteomic analysis of the rhizosphere

Extensive spatial variability combined with small spatial scales complicate efforts to elucidate plant-microbe interactions within the rhizosphere, how these relationships change 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. Historically, however, proteomics relies on harvesting material from the rhizosphere in a method that is neither spatially specific (as it stretches over lengths of the rhizosphere) nor non-destructive. We are working to circumvent this challenge by employing spatially resolved, non-destructive harvesting of mobile proteins onto membranes while preserving their spatial distributions.

We are using rhizoboxes planted with switchgrass and constructed with natural soil (Kellogg Biological Station, Hickory Corners, Michigan, USA) to develop the spatially resolved proteomics 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 1-2 millimeter scale and samples can be manually selected based on proximity to specific root structure, metabolic hotspots, or other parameters of choice. We are exploring the use of spatial analysis to track taxonomic shifts within the rhizosphere associated with roots at different growth stages. We are also developing methods to employ a ¹³C tracer to identify specific taxonomic groups having the closest metabolic association with a host plant and are attempting use of a ¹³CO₂ tracer to identify initial consumers of root exudate from a host plant. Combined, the spatial, timeseries-enabled, and ¹³C tracer components of this approach can provide new insights to understanding the complex inter-kingdom interactions within the rhizosphere and the implications these interactions have on driving carbon cycling and plant performance.