Next Generation Sequencing Methods for Simultaneous Detection of Chikungunya, Dengue, and Zika Viruses

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

Congreso; AABB 2022 Annual Meeting; 2022

AABB

BackgroundChikungunya (CHIKV), Dengue (DENV), and Zika (ZIKV) viruses are arboviruses responsible for multiple worldwide epidemics, demonstrate region co-occurrence, and exhibit similar clinical manifestations. Coinfection has been observed in regions where all three viruses are prevalent. Developing a method to differentiate arbovirus infection and identify coinfections may help to guide treatment and evaluate the blood supply in these regions. We utilized next generation sequencing (NGS) to identify and characterize CHIKV, DENV, and ZIKV individually and as a mixture of all three viruses to simulate coinfections. MethodsViral nucleic acids were extracted from cryopreserved CHIKV-, DENV-, and ZIKV-positive plasma samples. Copy number quantification of specimens was performed using RT-qPCR (Altona RealStar), with standards generated by serial dilution of CHIKV (ATCC VR-3246SD), DENV-4 (ATCC VR-3231SD) and ZIKV (ATCC VR-1838DQ) genomic RNA (specification range: 1x10^5 - 1x10^6 copies/µL) obtained from ATCC (American Type Culture Collection). Library preparation of isolated viral nucleic acids was conducted using Illumina Stranded Total RNA Prep with Ribo-Zero Plus with maximum input volume without ribosomal RNA depletion. Samples were normalized, pooled, and sequenced on an Illumina NextSeq 550. FASTQ files were analyzed using the cloud-based online classification tool Genome Detective (https://www.genomedetective.com/).ResultsAll RT-qPCR positive CHIKV, DENV, and ZIKV samples were correctly identified by NGS, with the lowest detectable level of 47, 119, and 70 copies/uL, respectively. All 3 viruses in the mixed sample were identified by NGS when present at high concentrations (CHIKV 2.24x10^6 copies/uL, DENV 1.03x10^5 copies/uL, ZIKV 2.73x10^3 copies/uL) and identified 2/3 viruses (ZIKV 736 copies/uL and DENV 119 copies/uL) when present at low concentrations (CHIKV not identified at 47 copies/uL). ConclusionsIn this study, we developed a simple workflow for isolation, library preparation, sequencing and genomic analysis for multiviral detection. Our workflow required no additional viral enrichment or amplification steps while maintaining high sensitivity and specificity, detecting CHIKV, DENV, and ZIKV individually at low concentrations and performing well in simulated coinfections. Genomic analysis was conducted using a web-based analysis tool requiring minimal advanced computing experience. Our results demonstrate the feasibility of easy to follow, highly sensitive NGS protocols as a tool for viral testing and blood screening.