key: cord-0714240-jz65invd authors: FARAHI BILOOEI, S.; Jovicevic, D.; Iranzadeh, A.; Mpofu, C.; Muscat, I.; Thomas, A.; Steiner, H.; Meany, T. title: Rapid genome surveillance of SARS-CoV-2 and study of risk factors using shipping container laboratories and portable DNA sequencing technology date: 2022-02-26 journal: nan DOI: 10.1101/2022.02.25.22271277 sha: d94ed4cbfbba509abe7bb62f6b2467b75150e192 doc_id: 714240 cord_uid: jz65invd In this paper we report on genome sequencing of 154 SARS-CoV-2 samples between June and July 2021 (Summer outbreak) in the Bailiwick of Jersey, a UK channel island. We have analysed extensive data collected on 598,155 RT-qPCR tests that identified 8,950 positive cases as part of public health surveillance from September 2020 to August 2021. Our study implemented an amplicon-based sequencing approach using the Oxford Nanopore Technology (ONT) portable device. This revealed the emergence of twelve AY sublineages and were clustered into the Delta sub-clades 21I and 21J. This was integrated alongside an existing RT-qPCR diagnostic laboratory to provide a sample-to-sequence turnaround time of approximately 30 hours with significant scope for optimisation. Owing to the geographic remoteness of the island from large scale sequencing infrastructure, this presents an opportunity to provide policy makers with near real-time sequencing findings. Our analysis suggests that age and sex remained a substantial risk factor for mortality. We observe viral loads are higher in advanced ages and unvaccinated individuals. The median age of SARS-CoV-2 positive individuals was higher during winter than the summer outbreak, and the contact tracing program showed that younger individuals stayed positive for longer. pandemic. In September 2020, an OpenCell COVID-19 rapid testing laboratory was deployed inside a shipping container designed to diagnose the virus effectively. The laboratory carried out a reverse transcription-polymerase chain reaction (RT-qPCR) diagnostic workflow assay, which formed part of the Government of Jersey testing programme 25 . Patient registration, swabbing, and diagnostic testing of COVID-19 (CONTAIN Jersey) had an average turnaround of 12 hours, and genome sequencing of SARS-CoV-2 took 18 hours by the MinION platform. The Oxford Nanopore MinION is a field-deployable, portable device capable of generating real-time, long-read sequences, facilitating the fastidious sequencing of viral genomes 26, 27 . The MinION generates high read coverage, cost-effective, and rapid sequencing. The cost of sequencing using the ONT device (MK1C) is presented in Supplementary Fig S1. This study performed sequencing of 154 SARS-CoV-2 positive samples to identify amino acid change(s) and the variants circulating in the community. We aimed to identify risk factors associated with an increased risk of mortality. The Government of Jersey (GoJ) performed primary data collection as public health surveillance from September 2020 to August 2021. The testing programme involved screening all incoming passengers at the ports of entry (air or boat) and any domiciled residents within the community requesting a SARS-CoV-2 test (via contact tracing or symptomatic reasons). All passengers aged 11 and over were asked to complete a safer travel registration form upon arrival, including relevant information such as COVID-19 vaccination record, symptoms (if any) and previous travel history. All passengers and everyone tested through the community were asked to identify all symptoms before testing. If the infected subjects presented no symptoms, these cases were classed as asymptomatic. In addition, qualitative sequencing data was received from GoJ with sequencing performed by Micropathology laboratory Ltd, where an independent secondary swab of positive individuals was sequenced. The data received from these genome sequences was in the form of notes providing several mutations and the variant of the samples. Basecalling was performed on fast5 raw sequence data generated with MinION MK1C using Guppy v.4.2.2 (ONT) with the high-accuracy base-call setting (model dna_r9. 4 .1_450bps_hac). The obtained data were demultiplexed using guppy_barcoder (v4.2.2) with barcodes separating into individual folders in fastq reads. Nanopore fastq files were assembled and aligned to the Wuhan-Hu-1 reference genome (NC_045512.2) using the Coronavirus Typing Tool on Genome Detective 1.136 https://www.genomedetective.com, a web-based software application. Genomes were submitted to the Nextclade web page https://clades.nextstrain.org, and those that did not pass the standard quality control parameters were filtered out. Frameshift mutations and misplaced stop codons were polished manually by aligning genomes to the reference using MAFFT 30 and visualising the alignment files by Aliview 31 . Viral lineages were classified using the Pangolin (v3.1.16) 32 software tool http://pangolin.cog-uk.io. Previous work by Walker et al. (2020) presented an automated, UKAS accredited (Testing Laboratory No. 22071) COVID-19 diagnostic laboratory housed within a shipping container 25 . The nanopore sequencing was conducted in an adjacent laboratory also fitted in a shipping container. The sequencing laboratory requires a linear physical layout matching the workflow. The space of the container is divided into three different sections. Station A: contains two cabinets to avoid contamination. The RNA extracted from positive samples of SARS-CoV-2 are reverse transcribed. The cDNA mastermix should be added to the PCR plate in cabinet A and Viral RNA from samples must be added to the plate in cabinet B. The multiplex PCR Q5 HOTstart DNA Polymerase mastermix is added to the plate in cabinet A, and cDNA in cabinet B. Then, the end prep master mix is prepared and added to the plate in cabinet A. Amplified amplicon pools are then added to the plate in cabinet A. The barcoded amplicons are quantified using the Quantus Fluorometer using the Qubit™ 1X dsDNA HS Assay Kit. The AMII adapter ligation reaction is prepared and then purified by AMPureXP. Station B: the SARS-CoV-2 prepared library is loaded into the MinION for 6 hours. Station C: The PCR is placed in this station, and the plate containing the pool is placed in the thermal cycler for cDNA synthesis and then to run multiplexed PCR. The schematic illustration of the sequencing workflow is shown in (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 26, 2022. ; Figure 1 . Schematic illustration of sequencing unit. The unit contains three stations. The library preparation is carried out in station A, which then is loaded into the sequencing device in station B. The PCR is in station C. In order to identify the SARS-CoV Interestingly S: A222V and S: S943T mutations were present in 25% and 9% of sequences, All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. and nsp4:A446V (ORF1a: A3209V) that were present at frequencies of 25% and 24%, respectively. In addition to studying the whole genome sequences of 154 samples, we also analysed qualitative data on the mutation profile of 426 cases, which were sequenced in a separate, off-island laboratory (Micropathology Laboratories LTD). The third-party data observed several mutations and identified two variants between June to August 2021. The majority of sequences belonged to the Delta variant (B1.617.2) except for two isolated samples that belonged to the All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The S: T95I mutant was detected during the summer months, however shortly after the surge of cases, S: A222V was also detected but only for a short period. S: T95I mutant was present during summer, however S: A222V was detected only a short period during the surge in S: T95I cases (Fig. 2c) . The surge in S: A222V mutants peaked and dropped rapidly afterwards. Of the 426 cases sequenced, S: G142D and S: R158G mutations were identified as present, except for 2 cases. S: G142D mutation was only present in 2.6% of the cases sequenced in the OpenCell laboratory. The median Ct value of sequences containing S: T95I is 0.5 Ct lower than sequences containing S: A222V. Table 1 . Additional spike mutations were detected in sequences of the Delta genomes. The data presented in this report covered September 2020 to August 2021, which can be distinguished into two main SARS-CoV-2 outbreaks: the winter outbreak during December 2020 to January 2021 and the summer outbreak during July and August 2021. A total of 598,155 samples were tested for SARS-CoV-2 infection through on-island surveillance screening (community track, trace program, and workforce screening), hospital healthcare, and inbound travel. During both outbreaks, Jersey implemented movement restrictions on residents and All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 26, 2022. ; https://doi.org/10.1101/2022.02.25.22271277 doi: medRxiv preprint mandatory quarantine for inbound arriving passengers. The travel restrictions were lifted in April 2021 after the winter outbreak, and a traffic light region classification was applied for all incoming arrivals. Nonetheless, during the summer months, the number of confirmed positive cases rapidly peaked again. The implementation and lifting of government control measures, dates of major travel and community health interventions are shown in (Fig. 3a) . A relatively high incidence of COVID-19 cases was mainly observed in younger age groups. The distribution of cases based on gender illustrated that more males than females received positive SARS-CoV-2 results (50.9% vs 49.1%) from August 2020 to August 2021. The infection rate in females was slightly higher (4.3%) than males during the winter outbreak. However, this was slightly changed during the summer outbreak by increasing males (2.9%) diagnosed with COVID-19 (Fig. 3b) . Epidemiological factors investigated for COVID-19 mortality were sex and age. In Jersey, 77 deaths were registered during the pandemic, with 55 confirmed deaths resulting from SARS-CoV-2. An age-dependent mortality rate had been demonstrated, with no death recorded among those younger than 39. The risk of mortality increases incrementally, affecting the 40-49 years old age group (1.3%), among those aged 50-59 years (5.5%), at age 60-69 years (5.2%), age 70-79 (22.1%), and with the highest mortality rate in those age ≥80 years (66.3%) (Fig. 3c) . The median age of deceased patients related to SARS-CoV-2 was 78 years. Additionally, the mortality rate was 21% higher in males than females. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (Fig. 3a) . Most individuals hospitalised were residents of care homes (Fig. 3b) . During the winter outbreak, 200 hospitalisations were recorded due to SARS-CoV-2 infection, of which 33 had fatal outcomes; All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. this was reduced to 50 hospitalisations and 8 deaths during the summer outbreak (Fig. 3b) . The number of positive cases from inbound travel also increased during the summer holiday compared to winter. The health care workers who tested positive during the winter outbreak counted 157 (20.9%) of total positive cases and later reduced to 135 (6%) during the summer outbreak. Symptomatic cases accounted for 32.6% of positive cases from January to July 2021. The mean age of SARS-CoV-2 symptomatic cases was 33 years old (interquartile range (IQR), . The 995 (45.4%) of total positive cases were individuals with symptoms during the summer outbreak, compared to 143 (19%) in the winter outbreak (Fig. 3c) . The self-reported symptoms by 117 individuals who tested positive were analysed to assess the prevalence. The most frequent symptoms experienced at the time of the test were headache (55%), sore throat (19%), runny/stuffy nose (17%), fatigue (14%), and persistent cough (14%). All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The positive cases shifted considerably towards older age groups during the winter outbreak. However, during July 2021, the confirmed cases among the elderly continuously decreased All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (Fig. 3d) . To determine the effect of age on the viral load, 822 Ct values from positive samples for both target genes arranged by different classes of age (>10, 10-19, 20-29, 30-39, 40-49, 50-59, 60-69, 70-79, and ≥80), were analysed and were found to be statistically significant (S gene p= 0.02, E gene p=0.01). Mean Ct value was also noticeably lower by 0.6 Ct for E gene and 1 Ct for S gene in the age group ≥80 (Table. 2). The mean Ct of the 70-79 age group was 1.9 and 1.8 Ct lower than the mean of all the E and S genes, respectively. The mean Ct of age group 60-69 was higher by 1.7 for the S gene and 2.9 for the E gene compared to mean Cts of all specimens, suggesting a lower viral load in the samples of this age category. Almost half of the positive cases (49.1%) were observed in the younger age group (10) (11) (12) (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) (27) (28) (29) . A higher viral load was observed among individuals over 70 years of age. The lowest Ct value was 13 for seven samples and the highest 43 ( Supplementary Fig S4) . The vaccination status of these individuals is unknown. By March 2021, the Jersey Government announced that 100% of all ≥80s had been fully vaccinated against SARS-CoV-2. At the start of July 2021 (summer outbreak), the same body reported that 51% of the population had both doses of a SARS-CoV-2 vaccine administered. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. individuals, as expected from the age-prioritisation vaccine roll-out in the UK. The individuals aged ≥40 had a higher viral load among infected unvaccinated groups than vaccinated, except age groups 50-59, which showed a higher viral load among vaccinated (Table. 3 A contact tracing strategy was carried out to identify people in direct contact with individuals who tested positive during June and July 2021. 11,220 individuals were tested as part of the contact tracing strategy on days 0, 5, and 10. 911 (8.1%) tested positive in test 1 (day 0), 591 tested positive on the second test (day 5), and 185 individuals continued to test positive on test 3 (day 10). The viral load of direct contacts was assessed by age and date, displayed in Fig. 5 . The age of infected individuals was higher during the first test. The individuals who remained positive on the second and third tests were younger than the median age in the first test on day 0. The viral load had a positive, strong significant correlation with the age of the direct contact positive cases (r = 0.82, P < 0.04). All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. We studied rapid SARS-CoV-2 genome sequencing to assess amino acid changes in the virus and focused on the epidemiology in a well-controlled and monitored setting on the island of Jersey. The ONT device was used for sequencing, which offered a portable and cost-effective solution. The turnaround time of sequencing using the ONT devices is straightforward and fast. The library preparation takes about 12 hours and 6 hours to run the library on the device to receive the fast5 or fastq files. The rapid sequencing of SARS-CoV-2 enables fast identification of new variants in the local laboratories rather than days in overseas laboratories. This study aimed to investigate the mutation profile of positive individuals in Jersey during the summer outbreak. The genome sequencing carried out in the OpenCell laboratories showed the Delta variant sub-clade (21I and 21J) as the dominant variant circulated in the community during the summer outbreak. Two main sublineages were identified based on the signature mutations in the spike (S: A222V and S: T95I). The prevalence of S: A222V mutant declined rapidly and presented only briefly (12th June to 7th July 2021). S: A222V was first identified and expanded during early summer 2020 in Spain and was characteristic of the B.1.177 lineage 33 . S: T95I was found in more than half of the sequences during summer 2021. Interestingly, this mutation is also associated with the Omicron variant. The viral load of samples containing T95I are slightly higher than the samples containing A222V. The increased viral load of this sublineage is associated with the presence of NTD mutation S: G142D. S: G142D mutation was present in 2.6% of our sequenced samples; however, it was observed in all the Delta cases identified in the qualitative data. The variation in the G142D mutation in the Delta genome is caused by the dropout of a sequencing amplicon 34 . The reappearing of the mutations, including S: A222V and All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 26, 2022. ; https://doi.org/10.1101/2022.02.25.22271277 doi: medRxiv preprint S: T95I in new emerging variants, may be attributed to the genetic background of the population where the mutation originated. Furthermore, the impact of population genetic processes such as founder effects that alter genetic variations could be a significant factor in the presence of some mutations in several lineages. S: L452R (96.5%) and S: T478K (100%) were almost always present in all genome sequences of the sublineage I and II list of mutations, which is known to cause structural changes that increase spike stability and disrupt the RBD interaction with the ACE2 receptor, resulting in a more infectious and high-risk SARS-CoV-2 35 deaths has substantially dropped compared to winter, implying that population vaccination reduces the number of hospitalisations and mortality associated with SARS-CoV-2 [37] [38] [39] . The study of positive cases in Jersey illustrated that A slightly higher percentage of infected cases was observed in females during the winter outbreak with no statistical significance. However, the overall proportion of SARS-CoV-2 infected cases is higher in males than females, which may suggest the SARS-CoV-2 virus has sex-specific differences in infectivity. The slightly higher positive cases in females could partially be because they are more likely to follow the guidelines during the pandemic and, therefore, more likely to participate in regular screening tests 40 . The mortality rate was 1.5-fold higher in males, suggesting male sex is a risk factor associated with SARS-CoV-2 mortality. The gender gap observed may point to an underlying biological mechanism. Biological sex differences affect immune responses that lead to differential All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. Males have been recorded to have more significant expression of ACE2 receptors 43,44 , impacted by X chromosome and sex-related hormonal levels 45 . Moreover, social-cultural constructs and behavioural differences may also play fundamental roles in mediating the development of severe COVID-19 outcomes in males 46, 47 . In this study, the mortality rate in patients older than ≥80 years was 66.3% of total cases, indicating age is a strong predictor of mortality for SARS-CoV-2. Aged immune systems combined with other age-related complications, such as reduced reserve capacity of vital organs and comorbidities, all of which make older adults susceptible to a more severe disease course or death when responding to COVID-19 infection [48] [49] [50] [51] [52] . All population ages are prone to COVID-19 infection, with the average age of infection being 36 years in Jersey. This study examined associations between SARS-CoV-2 viral load and the age of confirmed COVID-19 cases across seven age groups. Higher viral loads were observed in adults aged ≥70, suggesting that viral RNA levels are higher in older age groups than for younger positive individuals. This observation is further supported by several other studies that found a higher viral load among the elderly groups 51, 53, 54 . The viral load was higher during Delta prevalence in the summer outbreak, which may partially explain this variant's rapid and intense transmission 21, 55, 56 . The contact trace investigations over 10 days showed that younger individuals stayed positive for longer. One reason could be that nearly all older adults were vaccinated during summer 2021, indicating that vaccination affects the faster viral decline. This study has several limitations. The samples selected for sequencing only contained Ct values below 30, as it is difficult to sequence very low viral load samples. The sex of individual positive cases was missing, and only total positive cases for each month were considered. The vaccine status of positive cases in the community was unknown and therefore was not considered in the Ct value study. Infected inbound passenger individuals with either 1 or 2 doses of vaccine were categorised in one group. We compared the median Ct value of the summer outbreak to winter; however, the community's variants during summer can not be confirmed. While the dominant variant present during winter in the UK is the Alpha variant, this can not be confirmed as no sequencing has been carried out on samples during that time. Future work is required to focus on a more longitudinal approach to study and compare the Delta variant viral load to other variants. Further studies are required to improve the limitations All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted February 26, 2022. ; https://doi.org/10.1101/2022.02.25.22271277 doi: medRxiv preprint of the ONT, such as detecting InDel, which remains a problem. The base-calling accuracy requires better performance and shorter turnaround time, which implies improved algorithms. In conclusion, we present data suggesting age and male sex are risk factors for mortality from COVID-19 infection. The infected older age (70+) individuals had a higher viral load. The positive summer cases were among younger individuals, with symptomatic cases escalating during the summer outbreak compared to winter. However, the number of care home cases, hospitalisations and deaths were substantially decreased during summer. 30% of the positive cases among travellers were vaccinated and showed a lower viral load across the spectrum of age. Finally, the younger infected individuals stayed positive for longer, and the age of SARS-CoV-2 infected individuals who tested positive was reduced from winter to summer. SFB conceived and designed the analysis and carried out the genome sequencing, quality control, and genome assembly. AI polished and checked the quality of genome sequences. AT categorised and classified Ct value data. SFB and DJ wrote the manuscript. TM and HS supervised the project from conducting the research to writing the manuscript. All authors critically corrected and revised the manuscript. 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(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity We thank G. Kerr, K. Osborne. A. Hoogkamer, J. Andron, B. Edwards, and V. Morel for their invaluable help in the transfer of the government of Jersey SARS-CoV-2 data, which was central to the achievement of this work, J. Perez, E. Bransden, and members of COVID-19 diagnostic laboratories of OpenCell for their help and excellent support throughout the sequencing work.We thank Stanhope Plc for facilitating and accommodating shipping container laboratories on their premises. See supplementary materials with figures S1-4.