ABSTRACT
The ARTIC protocol uses a multiplexed PCR approach with two primer pools tiling the entire SARS-CoV-2 genome. Primer pool updates are necessary for accurate amplicon sequencing of evolving SARS-CoV-2 variants with novel mutations. The suitability of the ARTIC V4 and updated V4.1 primer scheme was assessed using whole genome sequencing of Omicron from clinical samples using Oxford Nanopore Technology. Analysis of Omicron BA.1 genomes revealed that 93.22% of clinical samples generated improved genome coverage at 50x read depth with V4.1 primers when compared to V4 primers. Additionally, the V4.1 primers improved coverage of BA.1 across amplicons 76 and 88, which resulted in the detection of the variant defining mutations G22898A, A26530G and C26577G. The Omicron BA.2 sub-variant (VUI-22JAN-01) replaced BA.1 as the dominant variant by March 2022, and analysis of 168 clinical samples showed reduced coverage across amplicons 15 and 75. Upon further interrogation of primer binding sites, a mutation at C4321T (present in 163/168, 97% of samples) was identified as a possible cause of complete dropout of amplicon 15. Furthermore, two mutations were identified within the primer binding regions for amplicon 75: A22786C (present in 90% of samples) and C22792T (present in 12.5% of samples). Together, these mutations may result in reduced coverage of amplicon 75 and further primer updates would allow the identification of the two BA.2 defining mutations present in amplicon 75; A22688G and T22679C. This work highlights the need for ongoing surveillance of primer matches as circulating variants evolve and change.
ABSTRACT
ObjectiveTo determine how the severity of successively dominant SARS-CoV-2 variants changed over the course of the COVID-19 pandemic. DesignRetrospective cohort analysis. SettingCommunity- and hospital-sequenced COVID-19 cases in the NHS Greater Glasgow and Clyde (NHS GG&C) Health Board. ParticipantsAll sequenced non-nosocomial adult COVID-19 cases in NHS GG&C infected with the relevant SARS-CoV-2 lineages during analysis periods. B.1.177/Alpha: 1st November 2020 - 30th January 2021 (n = 1640). Alpha/Delta: 1st April - 30th June 2021 (n = 5552). AY.4.2 Delta/non-AY.4.2 Delta: 1st July - 31st October 2021 (n = 9613). Non-AY.4.2 Delta/Omicron: 1st - 31st December 2021 (n = 3858). Main outcome measuresAdmission to hospital, ICU, or death within 28 days of positive COVID-19 test ResultsFor B.1.177/Alpha, 300 of 807 B.1.177 cases were recorded as hospitalised or worse, compared to 232 of 833 Alpha cases. After adjustment, the cumulative odds ratio was 1.51 (95% CI: 1.08-2.11) for Alpha versus B.1.177. For Alpha/Delta, 113 of 2104 Alpha cases were recorded as hospitalised or worse, compared to 230 of 3448 Delta cases. After adjustment, the cumulative odds ratio was 2.09 (95% CI: 1.42-3.08) for Delta versus Alpha. For non-AY.4.2 Delta/AY.4.2 Delta, 845 of 8644 non-AY.4.2 Delta cases were recorded as hospitalised or worse, compared to 101 of 969 AY.4.2 Delta cases. After adjustment, the cumulative odds ratio was 0.99 (95% CI: 0.76-1.27) for AY.4.2 Delta versus non-AY.4.2 Delta. For non-AY.4.2 Delta/Omicron, 30 of 1164 non-AY.4.2 Delta cases were recorded as hospitalised or worse, compared to 26 of 2694 Omicron cases. After adjustment, the median cumulative odds ratio was 0.49 (95% CI: 0.22-1.06) for Omicron versus non-AY.4.2 Delta. ConclusionsThe direction of change in disease severity between successively emerging SARS-CoV-2 variants of concern was inconsistent. This heterogeneity demonstrates that severity associated with future SARS-CoV-2 variants is unpredictable.
ABSTRACT
The scale of data produced during the SARS-CoV-2 pandemic has been unprecedented, with more than 5 million sequences shared publicly at the time of writing. This wealth of sequence data provides important context for interpreting local outbreaks. However, placing sequences of interest into national and international context is difficult given the size of the global dataset. Often outbreak investigations and genomic surveillance efforts require running similar analyses again and again on the latest dataset and producing reports. We developed civet (cluster investigation and virus epidemiology tool) to aid these routine analyses and facilitate virus outbreak investigation and surveillance. Civet can place sequences of interest in the local context of background diversity, resolving the query into different catchments and presenting the phylogenetic results alongside metadata in an interactive, distributable report. Civet can be used on a fine scale for clinical outbreak investigation, for local surveillance and cluster discovery, and to routinely summarise the virus diversity circulating on a national level. Civet reports have helped researchers and public health bodies feedback genomic information in the appropriate context within a timeframe that is useful for public health.
ABSTRACT
The SARS-CoV-2 ARTIC amplicon protocol is the most widely used genome sequencing method for SARS-CoV-2, accounting for over 43% of publicly-available genome sequences. The protocol utilises 98 primers to amplify [~]400bp fragments of the SARS-CoV-2 genome covering all 30,000 bases. Understanding the analytical performance metrics of this protocol will improve how the data is used and interpreted. Different concentrations of SARS-CoV-2 control material were used to establish the limit of detection (LoD) of the ARTIC protocol. Results demonstrated the LoD was a minimum of 25-50 virus particles per mL. The sensitivity of ARTIC was comparable to the published sensitivities of commercial diagnostics assays and could therefore be used to confirm diagnostic testing results. A set of over 3,600 clinical samples from three UK regions were then evaluated to compare the protocols performance to clinical diagnostic assays (Roche Lightcycler 480 II, AusDiagnostics, Roche Cobas, Hologic Panther, Corman RdRp, Roche Flow, ABI QuantStudio 5, Seegene Nimbus, Qiagen Rotorgene, Abbott M2000, Thermo TaqPath, Xpert). We developed a Python tool, RonaLDO, to perform this validation (available under the GNU GPL3 open-source licence from https://github.com/quadram-institute-bioscience/ronaldo). Positives detected by diagnostic platforms were generally supported by sequencing data; platforms that used RT-qPCR were the best predictors of whether the sample would subsequently sequence successfully. To maximise success of sample sequencing for phylogenetic analysis, samples with Ct <31 should be chosen. For diagnostic tests that do not provide a quantifiable Ct value, adding a quantification step is recommended. The ARTIC SARS-CoV-2 sequencing protocol is highly sensitive, capable of detecting SARS-CoV-2 in samples with Cts in the high 30s. However, to routinely obtain whole genome coverage, samples with Ct <31 are recommended. Comparing different virus detection methods close to their LoD was challenging and significant discordance was observed.
ABSTRACT
ObjectivesThe SARS-CoV-2 Alpha variant was associated with increased transmission relative to other variants present at the time of its emergence and several studies have shown an association between Alpha variant infection and increased hospitalisation and 28-day mortality. However, none have addressed the impact on maximum severity of illness in the general population classified by the level of respiratory support required, or death. We aimed to do this. MethodsIn this retrospective multi-centre clinical cohort sub-study of the COG-UK consortium, 1475 samples from Scottish hospitalised and community cases collected between 1st November 2020 and 30th January 2021 were sequenced. We matched sequence data to clinical outcomes as the variant became dominant in Scotland and modelled the association between Alpha variant infection and severe disease using a 4-point scale of maximum severity by 28 days: 1. no respiratory support, 2. supplemental oxygen, 3. ventilation and 4. death. ResultsOur cumulative generalised linear mixed model analyses found evidence (cumulative odds ratio: 1.40, 95% CI: 1.02, 1.93) of a positive association between increased clinical severity and lineage (Alpha variant versus non-Alpha variant). ConclusionsThe Alpha variant was associated with more severe clinical disease in the Scottish population than co-circulating lineages.
ABSTRACT
SARS-CoV-2, the causative agent of COVID-19, emerged in Wuhan, China in December 2019 and spread rapidly throughout the world. Understanding the introductions of this new coronavirus in different settings may assist control efforts and the establishment of frameworks to support rapid response in future infectious disease outbreaks. We investigated the first four weeks of emergence of the SARS-CoV-2 virus in Scotland after the first case reported on the 1st March 2020. We obtained full genome sequences from 452 individuals with a laboratory-confirmed diagnosis of COVID-19, representing 20% of all cases until 1st April 2020 (n=2310). This permitted a genomic epidemiology approach to study the introductions and spread of the SARS-2 virus in Scotland. From combined phylogenetic and epidemiological analysis, we estimated at least 113 introductions of SARS-CoV-2 into Scotland during this period. Clusters containing multiple sequences suggestive of onward transmission occurred in 48/86 (56%). 42/86 (51%) clusters had no known international travel history indicating undetected introductions. The majority of viral sequences were most closely related to those circulating in other European countries, including Italy, Austria and Spain. Travel-associated introductions of SARS-CoV-2 into Scotland predated travel restrictions in the UK and other European countries. The first local transmission occurred three days after the first case. A shift from travel-associated to sustained community transmission was apparent after only 11 days. Undetected introductions occurred prior to the first known case of COVID-19. Earlier travel restrictions and quarantine measures might have resulted in fewer introductions into Scotland, thereby reducing the number of cases and the subsequent burden on health services. The high number of introductions and transmission rates were likely to have impacted on national contact tracing efforts. Our results also demonstrate that local real-time genomic epidemiology can be used to monitor transmission clusters and facilitate control efforts to restrict the spread of COVID-19. FundingMRC (MC UU 1201412), UKRI/Wellcome (COG-UK), Wellcome Trust Collaborator Award (206298/Z/17/Z - ARTIC Network; TCW Wellcome Trust Award 204802/Z/16/Z Research in contextO_ST_ABSEvidence before this studyC_ST_ABSCoronavirus disease-2019 (COVID-19) was first diagnosed in Scotland on the 1st of March 2020 following the emergence of the causative severe acute respiratory system coronavirus 2 (SARS-CoV-2) virus in China in December 2019. During the first month of the outbreak in Scotland, 2310 positive cases of COVID-19 were detected, associated with 1832 hospital admissions, 207 intensive care admissions and 126 deaths. The number of introductions into Scotland and the source of those introductions was not known prior to this study. Added value of this studyUsing a combined phylogenetic and epidemiological approach following real-time next generation sequencing of 452 SARS-CoV-2 samples, it was estimated that the virus was introduced to Scotland on at least 113 occasions, mostly from other European countries, including Italy, Austria and Spain. Localised outbreaks occurred in the community across multiple Scottish health boards, within healthcare facilities and an international conference and community transmission was established rapidly, before local and international lockdown measures were introduced.
