Simultaneous Detection and Mutation Surveillance of SARS-CoV-2 and co-infections of multiple respiratory viruses by Rapid field-deployable sequencing

Bi, Chongwei; Ramos-Mandujano, Gerardo; Tian, Yeteng; Hala, Sharif; Xu, Jinna; Mfarrej, Sara; Esteban, Concepcion Rodriguez; Delicado, Estrella Nuñez; Alofi, Fadwa S.; Khogeer, Asim; Hashem, Anwar M.; Almontashiri, Naif A.M.; Pain, Arnab; Izpisua Belmonte, Juan Carlos; Li, Mo

Background Strategies for monitoring the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are crucial for combating the pandemic. Detection and mutation surveillance of SARS-CoV-2 and other respiratory viruses require separate and complex workflows that rely on highly-specialized facilities, personnel, and reagents. To date, no method can rapidly diagnose multiple viral infections and determine variants in a high-throughput manner. Methods We describe a method for multiplex isothermal amplification-based sequencing and real-time analysis of multiple viral genomes, termed NIRVANA. It can simultaneously detect SARS-CoV-2, influenza A, human adenovirus, and human coronavirus, and monitor mutations for up to 96 samples in real-time. Findings NIRVANA showed high sensitivity and specificity for SARS-CoV-2 in 70 clinical samples with a detection limit of 20 viral RNA copies per μl of extracted nucleic acid. It also detected the influenza A co-infection in two samples. The variant analysis results of SARS-CoV-2 positive samples mirror the epidemiology of COVID-19. Additionally, NIRVANA could simultaneously detect SARS-CoV-2 and PMMoV (an omnipresent virus and water quality indicator) in municipal wastewater samples. Conclusions NIRVANA provides high-confidence detection of both SARS-CoV-2 and other respiratory viruses and mutation surveillance of SARS-CoV-2 on the fly. We expect it to offer a promising solution for rapid field-deployable detection and mutational surveillance of pandemic viruses. Funding M.L. is supported by KAUST Office of Sponsored Research (BAS/1/1080-01). This work is supported by KAUST Competitive Research Grant (URF/1/3412-01-01, M.L. and J.C.I.B.) and Universidad Catolica San Antonio de Murcia (J.C.I.B.). A.M.H. is supported by Saudi Ministry of Education (project 436).