Bayesian Pairwise Compositional Lotka-Volterra Modeling Infers Potential Rhizosphere Microbial Suppressors of Ralstonia pseudosolanacearum.

Abstract

The Ralstonia solanacearum species complex (RSSC) is a major soil-borne pathogen of solanaceous crops. During a field experiment originally designed to monitor rhizosphere and episphere microbiomes in two pepper cultivars, a naturally emerging and asymptomatic Ralstonia dominance event was detected in the rhizosphere without visible wilt symptoms. This unexpected occurrence provided an opportunity to characterize asymptomatic RSSC dynamics and their microbial interactions under field conditions. Full-length 16S rRNA amplicon sequencing showed that one ASV (Sq_1) was nearly absent from the episphere but increased sharply in the rhizosphere from week 3 onward, dominating 20-80% of samples during weeks 7-10. Phylogenetic comparison with 93 historical Korean RSSC isolates placed Sq_1 within a 16S-defined lineage corresponding to pepper-associated R. pseudosolanacearum biovars 3 and 4. Sq_1 abundance accounted for a large portion of β-diversity turnover in the rhizosphere. After within-plot correlations were meta-analyzed, selected taxa were evaluated using a Bayesian pairwise compositional Lotka-Volterra (pcLV) model, which identified three taxa (Sq_272, TRA3-20; Sq_178, Bradyrhizobium; and Sq_124, Bryobacter) that consistently exerted inhibitory effects on Sq_1 per-interval growth. Supported by the longitudinal design and the high accuracy of PacBio full-length 16S sequencing, these findings highlight potential microbial suppressors of RSSC and demonstrate the utility of pcLV modeling for resolving directional interactions at the ASV level.