Gemella bacteraemia characterised by 16S ribosomal RNA gene sequencing

Abstract

Aims: To define epidemiology, clinical disease, and outcome of gemella bacteraemia by 16S rRNA gene sequencing. To examine the usefulness of the Vitek, API, and ATB systems in identifying two gemella species.

Methods: All alpha haemolytic streptococci other than Streptococcus pneumoniae isolated from blood cultures during a six year period were identified by conventional biochemical methods, the Vitek system, and the API system. 16S rRNA gene sequencing was performed on all isolates identified by both kits as gemella with >or= 95% confidence or by either kit as any bacterial species with < 95% confidence. The ATB expression system was used to identify the two isolates that were defined as gemella species by 16S rRNA gene sequencing.

Results: Of the 302 alpha haemolytic streptococci other than S pneumoniae isolated, one was identified as Gemella morbillorum, and another as Gemella haemolysans by 16S rRNA gene sequencing. The patient with monomicrobial G morbillorum bacteraemia was a 66 year old man with community acquired infective endocarditis with septic thromboemboli. The patient with G haemolysans bacteraemia was a 41 year old woman with hospital acquired polymicrobial bacteraemia during the neutropenic period of an autologous bone marrow transplant for non-Hodgkin's lymphoma, the first case of its kind in the English literature. The API and ATB expression systems only identified the second strain as G haemolysans at 94% and 99% confidence, respectively, whereas the Vitek system identified none of the two strains correctly at > 70% confidence.

Conclusions: Gemella bacteraemia is uncommon. 16S rRNA gene sequencing is the method of choice for identification of gemella and gemella-like isolates.

Figure 1

Phylogenetic tree showing the relation of the two gemella isolates to other species. The tree was inferred from 16S rRNA sequencing data by the neighbour joining method. The scale bar indicates the estimated number of substitutions for each 100 bases using the Jukes-Cantor correction. Names and accession numbers are given as cited in the GenBank database.