TY - JOUR
T1 - Streptococcus pseudopneumoniae
T2 - Use of Whole-Genome Sequences To Validate Species Identification Methods
AU - Jensen, Christian Salgård
AU - Iversen, Katrine Højholt
AU - Dargis, Rimtas
AU - Shewmaker, Patricia
AU - Rasmussen, Simon
AU - Christensen, Jens Jørgen
AU - Nielsen, Xiaohui Chen
N1 - Copyright © 2021 American Society for Microbiology.
PY - 2021/1/21
Y1 - 2021/1/21
N2 - A correct identification of
Streptococcus pseudopneumoniae is a prerequisite for investigating the clinical impact of the bacterium. The identification has traditionally relied on phenotypic methods. However, these phenotypic traits have been shown to be unreliable, with some
S. pseudopneumoniae strains giving conflicting results. Therefore, sequence-based identification methods have increasingly been used for identification of
S. pseudopneumoniae In this study, we used 64
S. pseudopneumoniae strains, 59
S. pneumoniae strains, 22
S. mitis strains, 24
S. oralis strains, 6
S. infantis strains, and 1
S. peroris strain to test the capability of three single genes (
rpoB,
gyrB, and
recA), two multilocus sequence analysis (MLSA) schemes, the single nucleotide polymorphism (SNP)-based phylogeny tool CSI phylogeny, a k-mer-based identification method (KmerFinder), average nucleotide identity (ANI) using fastANI, and core genome analysis to identify
S. pseudopneumoniae Core genome analysis and CSI phylogeny were able to cluster all strains into distinct clusters related to their respective species. It was not possible to identify all
S. pseudopneumoniae strains correctly using only one of the single genes. The MLSA schemes were unable to identify some of the
S. pseudopneumoniae strains, which could be misidentified. KmerFinder identified all
S. pseudopneumoniae strains but misidentified one
S. mitis strain as
S. pseudopneumoniae, and fastANI differentiated between
S. pseudopneumoniae and
S. pneumoniae using an ANI cutoff of 96%.
AB - A correct identification of
Streptococcus pseudopneumoniae is a prerequisite for investigating the clinical impact of the bacterium. The identification has traditionally relied on phenotypic methods. However, these phenotypic traits have been shown to be unreliable, with some
S. pseudopneumoniae strains giving conflicting results. Therefore, sequence-based identification methods have increasingly been used for identification of
S. pseudopneumoniae In this study, we used 64
S. pseudopneumoniae strains, 59
S. pneumoniae strains, 22
S. mitis strains, 24
S. oralis strains, 6
S. infantis strains, and 1
S. peroris strain to test the capability of three single genes (
rpoB,
gyrB, and
recA), two multilocus sequence analysis (MLSA) schemes, the single nucleotide polymorphism (SNP)-based phylogeny tool CSI phylogeny, a k-mer-based identification method (KmerFinder), average nucleotide identity (ANI) using fastANI, and core genome analysis to identify
S. pseudopneumoniae Core genome analysis and CSI phylogeny were able to cluster all strains into distinct clusters related to their respective species. It was not possible to identify all
S. pseudopneumoniae strains correctly using only one of the single genes. The MLSA schemes were unable to identify some of the
S. pseudopneumoniae strains, which could be misidentified. KmerFinder identified all
S. pseudopneumoniae strains but misidentified one
S. mitis strain as
S. pseudopneumoniae, and fastANI differentiated between
S. pseudopneumoniae and
S. pneumoniae using an ANI cutoff of 96%.
KW - Streptococcus
KW - mitis group
KW - identification
KW - methods
KW - whole-genome sequencing
KW - genotypic identification
U2 - 10.1128/jcm.02503-20
DO - 10.1128/jcm.02503-20
M3 - Article
C2 - 33208473
SN - 0095-1137
VL - 59
JO - Journal of Clinical Microbiology
JF - Journal of Clinical Microbiology
IS - 2
ER -