TY - JOUR
T1 - Whole genome sequencing as a tool for phylogenetic analysis of clinical strains of Mitis group streptococci
AU - Rasmussen, Louise Hesselbjerg
AU - Dargis, Rimtas
AU - Højholt, Katrine
AU - Christensen, Jens Jørgen
AU - Skovgaard, Ole
AU - Justesen, Ulrik S.
AU - Rosenvinge, Flemming S.
AU - Moser, Claus
AU - Lukjancenko, Oksana
AU - Rasmussen, Simon
AU - Nielsen, Xiaohui Chen
PY - 2016/6/20
Y1 - 2016/6/20
N2 - 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.
AB - 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.
U2 - 10.1007/s10096-016-2700-2
DO - 10.1007/s10096-016-2700-2
M3 - Journal article
SN - 0934-9723
VL - 35
SP - 1615
EP - 1625
JO - European Journal of Clinical Microbiology & Infectious Diseases
JF - European Journal of Clinical Microbiology & Infectious Diseases
IS - 10
ER -