Integrated multi-omics analysis of root transcriptomic, metabolomic, and bacterial-community responses associated with rhizobial inoculation and cadmium exposure in Robinia pseudoacacia.

Abstract

Cadmium (Cd) contamination threatens soil ecosystems and food security. Robinia pseudoacacia is a potential candidate for phytoremediation, but the molecular responses and root-associated microbial responses accompanying rhizobial symbiosis under Cd exposure remain incompletely understood. We integrated root transcriptomic, internal-root metabolomic, and 16S rRNA gene sequencing data to characterize responses to Cd exposure and rhizobial inoculation in SX, the high shoot-Cd accumulator, and HB, the low shoot-Cd accumulator. SX and HB exhibited distinct transcriptional patterns and exploratory candidate-metabolite profiles. In SX, the transcriptional responses were associated with the greater shoot Cd translocation reported previously for this genotype. In HB, rhizobial inoculation under Cd exposure was associated with broader changes in candidate metal-transport and compartmentalization genes, consistent with its previously reported greater root Cd retention. Rhizobial inoculation was also associated with higher candidate abundances of leucine, trehalose, palmitic acid, thymine, and pantothenates in HB, whereas inoculated SX showed higher candidate abundances of leucine and isoleucine but lower internal L-malic acid. Cd exposure, rhizobial inoculation, and root compartment were associated with variation in bacterial community composition, including abundance patterns involving Pseudomonas, Devosia, and Rhizobium. Exploratory Spearman correlation analyses revealed compartment-specific patterns of covariation between candidate metabolites and bacterial genera; however, no metabolite-genus association remained statistically significant after Benjamini-Hochberg correction in the rhizoplane, endosphere, or rhizosphere. None of the compartment-specific Procrustes tests indicated significant overall concordance between bacterial community composition and root-metabolite profiles. Collectively, these findings identify candidate genes, metabolites, and bacterial taxa and provide testable hypotheses that could inform future genotype selection and microbiome-assisted phytoremediation strategies.