Whole genome sequencing as a tool for phylogenetic analysis of clinical strains of Mitis group streptococci

Identification of Mitis group streptococci (MGS) to the species level is challenging for routine microbiology laboratories. Correct identification is crucial for the diagnosis of infective endocarditis, identification of treatment failure, and/or infection relapse. Eighty MGS from Danish patients wi...

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Published inEuropean journal of clinical microbiology & infectious diseases Vol. 35; no. 10; pp. 1615 - 1625
Main Authors Rasmussen, L. H., Dargis, R., Højholt, K., Christensen, J. J., Skovgaard, O., Justesen, U. S., Rosenvinge, F. S., Moser, C., Lukjancenko, O., Rasmussen, S., Nielsen, X. C.
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2016
Springer Nature B.V
Subjects
Biomedical and Life Sciences
Biomedicine
Cluster Analysis
Denmark
Endocarditis
Endocarditis - microbiology
Genes
Genetic Variation
Genome, Bacterial
Genomes
Humans
Identification
Internal Medicine
Laboratories
Medical Microbiology
Microbiology
Original Article
Phylogenetics
Phylogeny
Retrospective Studies
Sequence Analysis, DNA
Streptococcal Infections - microbiology
Streptococcus infections
Streptococcus mitis - classification
Streptococcus mitis - genetics
Denmark
Germany
Robustness Evaluation
Streptococcus Agalactiae
Monophyletic Cluster
Single Gene Analysis
Infective Endocarditis
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Summary:Identification of Mitis group streptococci (MGS) to the species level is challenging for routine microbiology laboratories. Correct identification is crucial for the diagnosis of infective endocarditis, identification of treatment failure, and/or infection relapse. Eighty MGS from Danish patients with infective endocarditis were whole genome sequenced. We compared the phylogenetic analyses based on single genes ( recA, sodA , gdh) , multigene (MLSA), SNPs, and core-genome sequences. The six phylogenetic analyses generally showed a similar pattern of six monophyletic clusters, though a few differences were observed in single gene analyses. Species identification based on single gene analysis showed their limitations when more strains were included. In contrast, analyses incorporating more sequence data, like MLSA, SNPs and core-genome analyses, provided more distinct clustering. The core-genome tree showed the most distinct clustering.
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ISSN:0934-9723
1435-4373
DOI:10.1007/s10096-016-2700-2