Abstract
Leptospirosis is a globally distributed zoonosis of major public health and veterinary relevance, caused by pathogenic species of the genus Leptospira. Brazil is a hotspot for transmission due to its ecological diversity and complex host-environment interfaces. This study explored the genetic diversity and structure of circulating pathogenic Leptospira spp. in Brazil through a single-locus sequence typing (SLST) analysis based on the secY gene. A total of 531 sequences were retrieved from GenBank and subjected to phylogenetic and haplotype diversity analyses. Maximum likelihood reconstruction revealed strongly supported clades for seven species, with L. interrogans being the most prevalent and broadly distributed across hosts and regions. This species showed evidence of clonal expansion, with a dominant haplotype (n = 242) shared by humans, domestic animals, and wildlife. In contrast, L. santarosai and L. noguchii exhibited high haplotypic diversity and reticulated network structures, reflecting greater evolutionary variability. The species L. kirschneri and L. borgpetersenii displayed reduced haplotypic variation, the latter mainly associated with cattle, consistent with its host-adapted profile. Host- and biome-based haplotype networks revealed both the broad ecological adaptability of certain lineages and the exclusive presence of haplotypes restricted to specific environments, such as those found in marine mammals from the Atlantic Ocean. Genetic distance analyses confirmed the strong taxonomic resolution of the gene secY, which effectively distinguished closely related species while capturing intraspecific diversity. These findings provide a comprehensive molecular overview of pathogenic Leptospira in Brazil, highlighting ecological connectivity across hosts and biomes, as well as the contrasting evolutionary dynamics among species. Beyond describing genetic patterns, our analyses emphasize evolutionary processes, host-environment connectivity, and the implications for One Health. This integrative framework strengthens the basis for surveillance and control strategies in other endemic regions in the world.