Simultaneous detection and mutation surveillance of SARS-CoV-2 and multiple respiratory viruses by rapid field-deployable sequencing

Abstract

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 nanopore sequencing of isothermal rapid viral amplification for near real-time analysis (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 coronavirus disease 2019 (COVID-19). Additionally, NIRVANA could simultaneously detect SARS-CoV-2 and pepper mild mottle virus (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).

Keywords: SARS-CoV-2; adenovirus; co-infection; influenza; isothermal amplification; mutation surveillance; nanopore sequencing; real-time pathogen detection; variant virus sequencing; wastewater.

Graphical abstract

Figure 1

Multiplex RPA workflow for SARS-CoV-2 detection and Nanopore sequencing (A) Schematic representation of NIRVANA. RNA samples were subjected to reverse transcription, followed by multiplex RPA to amplify multiple regions of the SARS-CoV-2 genome. The amplicons were purified and prepared to the Nanopore library using an optimized barcoding library preparation protocol. In the end, the sequencing was performed in the pocket-sized Nanopore MinION sequencer and sequencing results were analyzed by our algorithm termed RTNano on the fly. Created with BioRender.com. (B) The RPA primers used in this study were plotted in the SARS-CoV-2 genome. The RPA amplicons are highlighted in red. The corresponding prevalent variants were labeled under the genome. (C) Agarose gel electrophoresis results of multiplex RPA. All of the five amplicons were shown in the gel with correct size (asterisks, note that pairs 5 and 13 have similar sizes). The no template control (NTC) showed a different pattern of non-specific amplicons. M, molecular size marker. (D) IGV plots showing Nanopore sequencing read coverage of the SARS-CoV-2 genome. All samples showed reads covering all of the targeted regions. (E) Pipeline of RTNano real-time analysis. RTNano monitors the Nanopore MinION sequencing output folder. Once newly generated fastq files are detected, it moves the files to the analyzing folder and makes a new folder for each sample. If the Nanopore demultiplexing tool guppy is provided, RTNano will do additional demultiplexing to make sure reads are correctly classified. The analysis will align reads to the SARS-CoV-2 reference genome, filter, and count alignment records and assign result mark (POS, NEG, or UNK) for each sample. As sequencing proceeds, RTNano will merge the newly analyzed results with existing ones to update the current sequencing statistics.

Figure 2

Agarose gel electrophoresis results of singleplex RPA (A) Agarose gel electrophoresis results of singleplex RPA with selected primers shown next a molecular size marker. The amplicons range from 194 bp to 466 bp. (B) Agarose gel electrophoresis results of restriction enzyme digestion. The amplicon of pair 5 was digested by SpeI although the others were digested by NlaIII. The digested DNA bands (asterisks) were of expected sizes. (C) Agarose gel electrophoresis results showing the sensitivity of RPA in amplifying the SARS-CoV-2 genome. Primer pair 4 was used in the experiment. Reliable amplification can be achieved with 1.4 copies (calculated from dilution) of the SARS-CoV-2 genome. (D) Agarose gel electrophoresis result of one-pot reverse transcription and RPA reaction using primer pair 4.

Figure 3

Real-time detection of multiple viral pathogens and mutational analysis of SARS-CoV-2 (A) Experimental design of multiple virus detection by one-pot NIRVANA. A mixture of SARS-CoV-2⁺ and Respiratory21⁺ samples was used as positive control to adjust the primer concentration. The final primer mix could amplify all targeted viral regions. Created with BioRender.com. (B) The sequencing throughput of 60 clinical samples (1–60) and NTC (61). A total of 6.3 million reads were acquired in a 24-h sequencing run. (C) CT values of potentially false-negative samples by RTNano analysis. The average CT value of the N1 assay was indicated by the blue line. (D) The average rRT-PCR CT values of SARS-CoV-2 RTNano⁺ samples (PCR⁺ of both N1 and N2 assays) of different confidence level using 9-amplicon NIRVANA. The sample number is shown in red under the graph. The error bars represent the standard deviation of CT values. RTNano confidence level inversely correlates with CT value. (E) IGV plots showing the read alignment to the SARS-CoV-2, ACTB, and FluA amplicon in sample 46 using 9-amplicon NIRVANA. (F) The SNVs detected in multiplex RPA sequencing and their position as shown in the Nextstrain data portal (https://nextstrain.org). A total of 16 SNVs were detected from 10 SARS-CoV-2-positive samples.