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Original Article



Prevalence and population biology of mastitis-causing Streptococcus uberis using an MLST based approach

Aura Rahman, Arittra Bhattacharjee, Tahmina Tabassum, Mohammad Ariful Islam, Maqsud Hossain.




Abstract

Streptococcus uberis is a predominant pathogen in both clinical and subclinical varieties of bovine mastitis. The genetic and evolutionary relationships among S. uberis strains from different countries are poorly understood. In this paper we used S. uberisÂ’s multilocus sequence typing (MLST) method of genotyping to decipher the prevalence of sequence types (STs) and ST complexes by country and infection level, to delineate genetic relationships among prominent STs and ST complexes. Dataset collected from PubMLST database for S. uberis were subjected to clonal cluster and phylogenetic analyses using BURST, globally optimized eBURST (goeBURST) and neighborhood joining algorithm tools, respectively. Certain countries showed clear trends of strain prevalence whereas others had a more equally weighted, diverse population. Occurrence of different severities of disease varied among countries and displayed no direct correlation with sequence type (ST). Clonal cluster and phylogenetic analyses predicted the ancestral roles of certain prominent STs and indicated possible strain migration and reticulate and convergent evolution occurring within the S. uberis population at a global scale. Genome comparison of selected strains revealed the absence of SUB0822-SUB0826 response regulator proteins from ST-5 and ST-6 indicating their preference for contagious transmission. In conclusion, the findings of this study uncovered the global evolutionary dynamics of S. uberis and showed that the study of ST and ST complexes can be a useful technique in understanding prevalence patterns and clonal propagation of S. uberis isolates. Information generated from such studies would be crucial for monitoring infection outbreaks and directing further genomic investigations.

Key words: Streptococcus uberis, MLST, population genomics






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