Microarray-Based Multiplexing Platform for Detecting and Serotyping Dengue Virus Infection

BAUMANN, R; ZHOU, H; HENNING, A; BARÉ P; DE GIORGI V

Congreso; 2021 AABB Virtual Annual Meeting; 2021

Microarray-Based Multiplexing Platform for Detecting and Serotyping Dengue Virus InfectionRyan Baumann1, Huizhi Zhou1, Amanda Henning1, Patricia Bare 2, Valeria De Giorgi11 Department of Transfusion Medicine, Clinical Center, National Institute of Health, Bethesda, MD2 Instituto de Investigaciones Hematologicas, Instituto de Medicina Experimental, CONICET, Academia Nacional de Medicina, Buenos Aires, ArgentinaBackgroundDengue Virus (DENV) is one of the most prevalent arboviruses infections in humans. DENV is a single-stranded RNA virus with four serotypes (DENV-1 to DENV-4). DENV infection may result in mild to severe clinical outcomes. Infection with one serotype does not confer immunity to other serotypes, and secondary infection with another serotype may increase disease severity. This has led to complications of vaccination efforts in individuals with previous DENV exposure. Understanding the serotype?s circulating during outbreaks may improve clinical outcomes and vaccination efforts. Currently, available detection methods for DENV are unable to simultaneously detect and serotype infection. We utilized an in house developed microarray-based pathogen chip, already validated for the detection of up16 RNA viruses including DENV 1-4, to investigate the platform performance to detect and serotype DENV in specimens collected in real epidemiological context Methods Nucleic acids were extracted from 24 cryopreserved plasma samples collected in Argentina during the 2016 outbreak. DENV positive specimens were quantified using the Altona RealStar RT-qPCR kit. Serial dilutions DENV (ATCC VR-3231SD), quantitative genomic RNA (specification range: 1x105 - 1x106 copies/µL) obtained from ATCC (American Type Culture Collection Manassas, VA) were prepared to generate a standard curve for copy number quantification. cDNA from random-primed, reverse-transcribed total RNA was performed and cDNA was labeled with Cy3. Labeled cDNA was purified and hybridized to 8x15000 format oligo arrays. Arrays were washed and scanned on an Agilent SureScan G4900DA microarray scanner using 5-µm resolution. Microarray images were analyzed using Agilent Feature Extraction software (Agilent Technologies, Inc., Santa Clara, CA) with default protocols and settings. Results All tested samples (24/24) were confirmed positive for DENV by RT-PCR with copy numbers ranging from 119-253,748 genome copies/uL. The Microarray was able not only to detect all positive DENV samples but also to differentiate the serotype. 24/24 samples were identified as DENV-1, which was the predominant serotype during Argentina 2016 outbreak. No coinfections with other RNA viruses were observed in our analysis. Conclusion In this study, we reported the feasibility of using a microarray-based platform for multiplexed detection of RNA viruses, specifically, for the simultaneous identification of all four serotypes of DENV in a single reaction. The platform showed a high specificity and sensitivity, whit a limit of detection of 119 genome copies/uL. The diagnosis of DENV infection and the typing of DENV serotypes as well as the differentiation of primary and secondary infections are essential for patient management and for the implementation of public health measures in the Dengue endemic area.