Forskning ved Københavns Universitet - Københavns Universitet


A 5' Nuclease Genotyping Assay for Identification of Macrolide-Resistant Mycoplasma genitalium in Clinical Specimens

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  • Gitte Qvist Kristiansen
  • Jan Gorm Lisby
  • Kristian Schønning

Rapid and sensitive detection of macrolide resistance in Mycoplasma genitalium is required for the guidance of adequate antimicrobial treatment. Previous studies have confirmed that single-base mutations at position 2058 or 2059 in domain V of the 23S rRNA gene of M. genitalium result in high-level macrolide resistance. Sequencing of PCR products remains the gold standard for the identification of mutations conferring resistance to macrolides but is laborious and time-consuming. The aim of the present study was to develop a 5' nuclease genotyping assay to detect single nucleotide polymorphisms in the 23S rRNA gene of Mycoplasma genitalium that are associated with macrolide resistance by combining PCR with hydrolysis probes and subsequent endpoint genotyping analysis. The 5' nuclease genotyping assay was used as a referral test to be used on M. genitalium-positive samples and was validated on 259 positive samples, of which 253 (97.7%) were successfully sequenced. With the newly developed assay, 237/259 (91.5%) investigated M. genitalium-positive samples were genotyped. The positive and the negative predictive values were 100% when evaluated on successfully genotyped samples. The newly developed assay discriminated macrolide-resistant M. genitalium in clinical specimens possessing A2058G, A2058C, A2058T, and A2059G mutations with a sensitivity of 94.4% (95% confidence interval [CI], 90.7% to 98.2%) and a specificity of 92.7% (95% CI, 87.8% to 97.6%) when evaluated on successfully sequenced samples. The assay can correctly guide antimicrobial treatment of M. genitalium infections.

TidsskriftJournal of Clinical Microbiology
Udgave nummer6
Sider (fra-til)1593-7
Antal sider5
StatusUdgivet - jun. 2016

ID: 176954319