Highly sensitive detection of influenza virus in saliva by real-time PCR method using sugar chain-immobilized gold nanoparticles; application to clinical studies.

Abstract A highly sensitive and convenient method for detecting influenza virus was developed using modified end-point melt curve analysis of a RT-qPCR SYBR Green method and influenza virus-binding sugar chain-immobilized gold-nanoparticles (SGNP). Because SGNPs capture influenza viruses, the virus-SGNP complex was separated easily by centrifugation. Viral RNA was detected at very low concentrations, suggesting that SGNP increased sensitivity compared with standard methods. This method was applied to clinical studies. Influenza viruses were detected in saliva of patients or inpatients who had been considered influenza-free by a rapid diagnostic assay of nasal swabs. Furthermore, the method was applied to a human trial of prophylactic anti-influenza properties of yogurt containing Lactobacillus acidophilus L-92. The incidence of influenza viruses in saliva of the L-92 group was found to be significantly lower compared to the control group. Thus, this method was useful for monitoring the course of anti-influenza treatment or preventive measures against nosocomial infection.