Detection and identification of Candida spp. in human serum by LightCycler real-time polymerase chain reaction

Abstract

The aim of this work was to develop LightCycler real-time polymerase chain reaction method to allow rapid detection and identification of Candida spp. in human serum with panfungal primers (internal transcribed spacer [ITS] and L18). Melting-curve analysis of the ITS sequences showed that each amplicon presented a specific melting point and enabled identification of 5 Candida spp. After parameters optimization, 58 sera were preliminary analyzed from 23 patients. For L18 primers, the LightCycler system enabled detection of DNA in 92% of patients with positive blood culture. These primers were not able to differentiate between species of Candida. By using ITS primers, the LightCycler system enabled detection of DNA in sera from 76.9% of patients with positive blood culture. With ITS primers, the species responsible for the infection was identified for 11 patients. These data revealed the LightCycler as a potential tool for early detection and identification of Candida.