Large-scale genomic analyses reveal the population structure and evolutionary trends of Streptococcus agalactiae strains in Brazilian fish farms

• Published in: Scientific reports Vol. 7; no. 1; pp. 13538 - 10
• Main Authors: Barony, Gustavo M., Tavares, Guilherme C., Pereira, Felipe L., Carvalho, Alex F., Dorella, Fernanda A., Leal, Carlos A. G., Figueiredo, Henrique C. P.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 19.10.2017; Nature Publishing Group
• Subjects: 45/23; 45/43; 631/326/41/2529; 631/326/41/2530; 631/326/421; Aquaculture; Bayesian analysis; Comparative analysis; Farms; Fish farms; Genomes; Genomic analysis; Genomics; Genotypes; Humanities and Social Sciences; multidisciplinary; Multilocus sequence typing; Nucleotide sequence; Outbreaks; Population structure; Population studies; Science; Science (multidisciplinary); Strains (organisms); Streptococcus agalactiae; Streptococcus infections
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-017-13228-z

Streptococcus agalactiae is a major pathogen and a hindrance on tilapia farming worldwide. The aims of this work were to analyze the genomic evolution of Brazilian strains of S. agalactiae and to establish spatial and temporal relations between strains isolated from different outbreaks of streptococcosis. A total of 39 strains were obtained from outbreaks and their whole genomes were sequenced and annotated for comparative analysis of multilocus sequence typing, genomic similarity and whole genome multilocus sequence typing (wgMLST). The Brazilian strains presented two sequence types, including a newly described ST, and a non-typeable lineage. The use of wgMLST could differentiate each strain in a single clone and was used to establish temporal and geographical correlations among strains. Bayesian phylogenomic analysis suggests that the studied Brazilian population was co-introduced in the country with their host, approximately 60 years ago. Brazilian strains of S. agalactiae were shown to be heterogeneous in their genome sequences and were distributed in different regions of the country according to their genotype, which allowed the use of wgMLST analysis to track each outbreak event individually.