Abstract
The rhizosphere, a 2-10 mm region surrounding the root surface, is colonized by numerous microorganisms, known as the rhizosphere microbiome. These microorganisms interact with each other, leading to emergent properties that affect plant fitness. Mapping these interactions is crucial to understanding microbial ecology in the rhizosphere and predicting and manipulating plant health. However, current methods do not capture the chemistry of the rhizosphere environment, and common plant-microbe interaction study setups do not map bacterial interactions in this niche. Additionally, studying bacterial interactions may require the creation of transgenic bacterial lines with markers for antibiotic resistance/fluorescent probes and even isotope labeling. Here, we describe a protocol for both in silico prediction and in vitro validation of bacterial interactions that closely recapitulate the major chemical constituents of the rhizosphere environment using a widely used Murashige & Skoog (MS)-based gnotobiotic plant growth system. We use the auto-fluorescent Pseudomonas, abundantly found in the rhizosphere, to estimate their interactions with other strains, thereby avoiding the need for the creation of transgenic bacterial strains. By combining artificial root exudate medium, plant cultivation medium, and a synthetic bacterial community (SynCom), we first simulate their interactions using genome-scale metabolic models (GSMMs) and then validate these interactions in vitro, using growth assays. We show that the GSMM-predicted interaction scores correlate moderately, yet significantly, with their in vitro validation. Given the complexity of interactions among rhizosphere microbiome members, this reproducible and efficient protocol will allow confident mapping of interactions of fluorescent Pseudomonas with other bacterial strains within the rhizosphere microbiome. Key features • This method builds upon the widely used MS-based gnotobiotic system for growing plants and a synthetic bacterial community (SynCom) for plant-microbe interaction studies. • It considers the chemical composition of plant growth media (MS) and root exudates to map bacterial interactions. • It provides a method to both predict and validate interactions of fluorescent Pseudomonas with other strains within a SynCom. • This method is scalable for any bacterial pair with distinguishing markers (e.g., fluorescence, antibiotic resistance).