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Similar genomic patterns of clinical infective endocarditis and oral isolates of Streptococcus sanguinis and Streptococcus gordonii
Similar genomic patterns of clinical infective endocarditis and oral isolates of Streptococcus sanguinis and Streptococcus gordonii
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Similar genomic patterns of clinical infective endocarditis and oral isolates of Streptococcus sanguinis and Streptococcus gordonii
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Similar genomic patterns of clinical infective endocarditis and oral isolates of Streptococcus sanguinis and Streptococcus gordonii
Similar genomic patterns of clinical infective endocarditis and oral isolates of Streptococcus sanguinis and Streptococcus gordonii

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Similar genomic patterns of clinical infective endocarditis and oral isolates of Streptococcus sanguinis and Streptococcus gordonii
Similar genomic patterns of clinical infective endocarditis and oral isolates of Streptococcus sanguinis and Streptococcus gordonii
Journal Article

Similar genomic patterns of clinical infective endocarditis and oral isolates of Streptococcus sanguinis and Streptococcus gordonii

2020
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Overview
Streptococcus gordonii and Streptococcus sanguinis belong to the Mitis group streptococci, which mostly are commensals in the human oral cavity. Though they are oral commensals, they can escape their niche and cause infective endocarditis, a severe infection with high mortality. Several virulence factors important for the development of infective endocarditis have been described in these two species. However, the background for how the commensal bacteria, in some cases, become pathogenic is still not known. To gain a greater understanding of the mechanisms of the pathogenic potential, we performed a comparative analysis of 38 blood culture strains, S . sanguinis ( n  = 20) and S . gordonii ( n  = 18) from patients with verified infective endocarditis, along with 21 publicly available oral isolates from healthy individuals, S . sanguinis ( n  = 12) and S . gordonii (n  = 9). Using whole genome sequencing data of the 59 streptococci genomes, functional profiles were constructed, using protein domain predictions based on the translated genes. These functional profiles were used for clustering, phylogenetics and machine learning. A clear separation could be made between the two species. No clear differences between oral isolates and clinical infective endocarditis isolates were found in any of the 675 translated core-genes. Additionally, random forest-based machine learning and clustering of the pan-genome data as well as amino acid variations in the core-genome could not separate the clinical and oral isolates. A total of 151 different virulence genes was identified in the 59 genomes. Among these homologs of genes important for adhesion and evasion of the immune system were found in all of the strains. Based on the functional profiles and virulence gene content of the genomes, we believe that all analysed strains had the ability to become pathogenic.