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From the early stages of the emergence of SARS-CoV-2, researchers have used real-time nanopore sequencing to generate and share genetic data critical to understanding the virus and informing public health responses to COVID-19. At London Calling 2021 online, scientists from around the world shared their findings and experiences.*
Nick Loman described how, early in 2020, he and his team at the University of Birmingham, UK, drew on their previous experience of using nanopore sequencing in outbreaks to rapidly track the spread of SARS-CoV-2. His colleague, Josh Quick, modified a method previously used to sequence Ebola, Zika, and yellow fever viruses. Released by the ARTIC Network, the open-source protocol uses a PCR tiling approach to amplify the SARS-CoV-2 genome from low sample amounts; this can then be sequenced, ensuring good coverage across the whole genome. Next, the ARTIC analysis pipeline generates viral consensus sequences and calls variants in real time, as sequencing progresses. The full, end-to-end workflow was made available in January 2020.
In March, the COVID-19 Genomics UK Consortium (COG-UK) was established: a decentralized network linking academia with public health agencies and sequencing labs. Nick’s team, who perform high-throughput SARS-CoV-2 sequencing on GridION and PromethION devices, are just one of many across the UK undertaking rapid sequencing and analysis of samples: as of May 2021, >460,000 SARS-CoV-2 genomes had been contributed and the data shared.
Using this genomic epidemiology data, potential transmission routes can be inferred–or ruled out–and clusters can be identified and investigated. By linking sequencing data with travel data, COG-UK were able to reveal >1,300 independent introductions of SARS-CoV-2 from mainland Europe into the UK in early March. Genomic epidemiology data also allows the identification and tracking of variants of concern in the viral genome, which may alter the nature of the disease caused and inform the development of future treatments or vaccines. Nick described how sequencing data revealed that a surge in cases in Kent, UK, in December 2020 was associated with a new lineage representing >50% of samples from the region. This lineage was later found to share a mutation with a lineage associated with a surge of cases in South Africa, and similar mutations to another that began to dominate in Brazil. Lastly, Nick highlighted the recent surge in cases in India, also thought to be associated with a new variant of the virus.
Lu Chen, based at Sichuan University in China, used the MinION device to sequence SARS-CoV-2 samples from cities across Sichuan Province and from Wuhan, China, from January to March 2020. Analysis of the sequencing data revealed >100 variants across the genome, with one—a deletion in Nsp—present in >20% of samples. Phylogenetic analysis revealed city-specific clusters, whilst further analysis also indicated wider transmission between multiple cities. Having identified 35 recurrent mutations in the SARS-CoV-2 samples from Sichuan Province, Lu then discovered 117 associations between these and clinical phenotypes. They also found that the Nsp1 deletion was associated with non-severe clinical phenotypes and correlated with significantly lower viral load and cytokine IFN-β levels.
George Githinji, a member of the KEMRI-Wellcome Trust Research Programme, described how he and his colleagues quickly scaled up their existing infrastructure for SARS-CoV-2 sequencing in Kenya through partnerships with GeMVi, ARTIC Network, and others. Utilising the ARTIC method and nanopore sequencing, they set up a rapid, end-to-end pipeline to analyze SARS-CoV-2 samples. Less than three weeks from the first COVID-19 case being reported in Kenya, the team sequenced their first SARS-CoV-2 samples, generating genomic epidemiology data early in the pandemic. This data provided insights into the introduction of SARS-CoV-2 into Kenya, revealing routes of transmission across the border, locally, and associated with travel.
George highlighted the critical need to expand sequencing capacity across Africa and discussed how they achieved this within Kenya working with other KEMRI institutes, and in other low-to-middle-income countries through their partnerships with Africa CDC and the WHO Regional Office for Africa.
In Düsseldorf, Germany, Alexander Dilthey and his team at Heinrich Heine University Düsseldorf set about integrating genomic surveillance with public health and contact tracing data across the city—noting that, using traditional tracing methods alone, the source of infection remained unknown in 40% of COVID-19 cases. Applying a mostly ARTIC-based approach, Alexander presented how they performed nanopore sequencing of SARS-CoV-2 samples and shared the results, including putative infection clusters, online in real time. Comparing post-hoc contact tracing and case information with these putative clusters pointed them to individual transmission chains “in each and every case”, enabling further, in-depth investigation. The data revealed some transmission chains were much more complex than previously recognized, highlighting the crucial role of sequencing data in informing containment and intervention strategies. He concluded that, with this data, “it is possible to track SARS-CoV-2 transmission chains through the population, even during periods of ongoing community transmission and very high incidences.”
The use of sequencing in COVID-19 research also extends to the investigation of how the human immune system responds to the SARS-CoV-2 virus. Rebekah Penrice-Randal, a member of the Hiscox Lab at the University of Liverpool, UK, used cDNA sequencing on GridION and MinION Mk1C to compare host transcriptomes of clinical research samples infected with either COVID-19 or influenza, alongside healthy controls. They identified hundreds of differentially expressed genes between the sample groups, including some distinguishing fatal vs non-fatal cases of COVID-19, suggesting their future potential as biomarkers of disease and its severity.
Meanwhile, Irina Chelysheva, of the Oxford Vaccine Group at the University of Oxford, UK, used high-throughput cDNA sequencing of human transcriptomes on PromethION to compare the host response to COVID-19 with that of typhoid fever. The symptoms of the two diseases are hard to distinguish, which can result in misdiagnosis. The team found differential expression between the samples taken at point of diagnosis and healthy controls and, beyond this, found specific genes to be upregulated only in COVID-19 or only in typhoid fever, representing potential biomarkers for each disease. Their work demonstrates the future potential to rapidly identify COVID-19, and distinguish it from other diseases, via the transcriptomic signatures of the infection visible in the host.
Nick Loman stressed that the more the virus is allowed to spread, the more chances it has to evolve combinations of mutations which can increase transmissibility and change antigenicity. He underlined that if the virus is able to circulate in areas that do not have sufficient public health measures in place to control it or access to vaccination, it is more likely SARS-CoV-2 will evolve increased transmissibility or immune evasion. Looking to the future, he emphasized the importance of further utilizing and optimizing SARS-CoV-2 sequencing across the globe: “We need to establish that principle of real-time data sharing worldwide, because everything is connected and we’re all in this together.”
* London Calling 2021 online conference, hosted by Oxford Nanopore Technologies; May 19–21, 2021.