Unveiling the Functions of Two RpoNs in Bradyrhizobium sp. DOA9 During Free-Living Conditions: A Comprehensive and Comparative Analysis

In this study, we investigate two RpoN homologs in Bradyrhizobium sp. DOA9—chromosomal RpoNc and megaplasmid-borne RpoNp—and their roles in free-living conditions and nitrogen fixation. Phylogenetic analysis showed that RpoNc clusters with RpoN proteins from symbiotic nitrogen-fixing strains, whereas RpoNp forms a distinct clade, consistent with a function in stress responses. RpoNc proved essential for free-living conditions: ΔrpoNc mutants displayed severe growth defects that RpoNp could not compensate for. Transcriptomic comparisons between wild type and mutant RpoN identified 541 differentially expressed genes (DEGs) grouped into three clusters: 100 downregulated, 175 upregulated, and 254 moderately downregulated (with a fold change > 2, and a q-value (FDR, padj) < 0.05). Affected pathways involved nitrogen metabolism, motility, and environmental adaptation. RpoNc controlled major nitrogen fixation genes (nif and fix) along with core growth and stress response functions, while RpoNp mainly influenced stress-adaptation pathways. Genome-wide promoter motif analysis predicted 68 putative RpoNc targets, mainly associated with nitrogen fixation and metabolism, compared with only 22 predicted RpoNp targets, indicating a more restricted regulon. Electrophoretic mobility shift assays (EMSAs) further confirmed that both RpoN proteins directly bind σ54-dependent promoters identified from transcriptomic data, supporting their regulatory roles under free-living conditions. Two mutants (ΔrpoNc and ΔrpoNp::ΩrpoNc) showed broad transcriptional disruption across nitrogen fixation, metabolism, and stress responses, underscoring complementary regulation. Overall, RpoNc is the dominant regulator of nitrogen fixation and core metabolism during free-living conditions, whereas RpoNp fine-tunes stress responses, revealing new regulatory insights for DOA9 adaptation. These results clarify how RpoN systems optimize survival across fluctuating conditions.