Desenvolvimento e avaliação de uma plataforma de diagnóstico para meningoencefalites virais por PCR em tempo real

• Ano de defesa: 2015
• Autor(a) principal: Danilo Bretas de Oliveira
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais
• Palavras-chave em Português: Microbiologia; Reação em cadeia da polimerase em tempo real; Meningoencefalite; Sistema nervoso central; Viroses
• Link de acesso: https://hdl.handle.net/1843/BUBD-ABZGBW

Infections on central nervous system (CNS) have a global distribution, affecting people worldwide. Viral infections are the main cause of infection in the CNS. In Brazil, on average, 11,500 cases/year of meningitis/meningoencephalitis with probable viral etiology are reported. However, most cases there are no identification of the etiologic agent. The objective of this work was the use of real time PCR (qPCR) for development and evaluation of a platform of diagnostic for meningoencephalitis caused by viruses. Viruses were used to obtain plasmids for control and standardization of qPCR. Specific primers were designed to detect each virus or viral groups. All reactions were standardized and presented efficiency of: ENTV 110%; FLAV 92%; HHV-1/2 114%; HHV-3 113%; SLEV 94%; YFV 96%; 97% JEV; 98% WNV. All tests were specific in the target detection and analytical sensitivities were equal or less to 10 copies/ml. The developed tests showed coefficient of variation less than 5% in reproducibility and repeatability assays. In addition to qPCR assays pre-analytical steps were standardized to improve viral detection efficiency. Finally, the qPCR platform was applied on clinical samples of cerebrospinal liquid (CSF), and it was able to detect the virus in 62.9% of samples from patients with suspected viral meningoencephalitis. ENTVs were detected (70%), HHV-3 (13%), DENVs (11%), HSV-1/2 and HHV-5 (2%). The amplified DNAs in qPCR positive samples were sequenced and the results were confirmed. Viruses were also detected in samples of patients with bacterial meningitis. So the developed platform showed high efficiency for diagnosis of infections in CNS and has a potential use in health system.