Bioinformatics procedure.

To predict Zur-binding sites, 42 manually curated Zur-binding motifs from Rhizobiales, described on the RegPrecise website (65), were used as a training set, and then a weight matrix was constructed using the CONSENSUS algorithm (66) on the Regulatory Sequence Analysis Tools (RSAT) website (67). Then, we used this matrix to perform a genome-wide screening for putative Zur-binding sites in the CCBAU45436 genome. Six hits with scores above ten were added to the training set, resulting in a set of 48 curated Zur-binding motifs. This updated training set was then used for final prediction of Zur-binding sites in CCBAU45436 (score > 5). DNA sequence logos were generated by WebLogo (68). Protein sequence alignment was generated using ClustalW (69). A neighbor-joining phylogenetic tree was constructed using MEGA 7 (70). Protein structure homology modeling for Zip1 and Zip2 was performed on the SWISS-MODEL server (71), using two different Zn²⁺-substituted structures at 2.4 Å as the structural templates, and results are shown in Fig. 2B and Fig. 7. Core genomes of nine Sinorhizobium strains were defined by the bidirectional best-hit algorithm as described earlier (54). Two thousand one hundred sixty-six core genes were aligned with ClustalW (69) and trimmed using Gblocks (72). The trimmed alignment was used for the construction of a maximum likelihood phylogenic tree through MEGA 7 (70).