Genetic diversity and sequence polymorphism of bacterial 16S rRNA isolates from beef tripe from Gaborone, Botswana

Beef tripe is a commonly consumed organ meat in many parts of the world, including Botswana, but its porous texture and microbial richness pose potential food safety risks. Despite its widespread consumption, limited studies have characterized the genetic diversity of tripe-associated microbial populations at the molecular level. This study aimed to assess the genetic polymorphism and evolutionary dynamics of microbial isolates recovered from beef tripe sold in butcheries in Gaborone, Botswana, using nucleotide sequence data and population genetic tools implemented in R. Population genetic statistics were applied as descriptive measures of sequence heterogeneity across multiple bacterial taxa rather than as strict intraspecific evolutionary tests. A total of 99 aligned nucleotide sequences were analyzed for nucleotide composition, polymorphism, haplotype structure, and genetic diversity. Sliding window analyses of nucleotide diversity (π) and Tajima’s D were conducted. Additional analyses included haplotype network construction, PCA, minor allele frequency profiling, mismatch distribution, and genetic distance heatmaps. High nucleotide diversity (mean π = 0.7006) as well as 99 unique haplotypes were observed, indicating a highly diverse microbial population. Polymorphism was widely distributed across the genome, with no hyper-conserved or hypervariable regions. PCA and genetic distance heatmaps revealed diffuse clustering, consistent with a non-clonal structure. Tajima’s D values hovered around zero, suggesting neutral evolution. A unimodal mismatch distribution indicated recent population expansion. Notably, rare alleles with low minor allele frequencies were present across multiple isolates. The findings reveal a genetically diverse, neutrally evolving microbial community in beef tripe, shaped by environmental exposure and stochastic colonization. This underscores the need for genomic surveillance in food safety systems to detect emerging antimicrobial-resistant or pathogenic variants. However, pathogenic potential cannot be inferred from 16S rRNA sequence data alone. These findings describe genetic diversity patterns among bacterial isolates but do not directly infer pathogenicity or public health risk.