The use of wastewater for SARS-CoV-2 surveillance is a useful complementary tool to clinical surveillance. The aims of this study were to characterize SARS-CoV-2 from wastewater samples, and to identify variants of concern present in samples collected from wastewater treatment plants in South African urban metros from April 2021 to January 2022. A total of 325 samples were collected from 15 wastewater treatment plants. Nucleic acids were extracted from concentrated samples, and subjected to amplicon-based whole genome sequencing. To identify variants of concerns and lineages, we used the Freyja tool (https://github.com/andersen-lab/Freyja), which assigns each sample with the prevalence of each variant present. We also used signature mutation analysis to identify variants in each wastewater treatment site. A heatmap was generated to identify patterns of emerging mutations in the spike gene using Excel conditional formatting. Using the Freyja tool, the Beta variant was detected and became predominate from April to June 2021 followed by the Delta variant and lastly the Omicron variant. Our heatmap approach was able to identify a pattern during the changes of predominate variant in wastewater with the emergence of mutations and the loss of others. In conclusion, sequencing of SARS-CoV-2 from wastewater largely corresponded with sequencing from clinical specimens. Our heatmap has the potential to detect new variants prior to emergence in clinical samples and this may be particularly useful during times of low disease incidence between waves, when few numbers of positive clinical samples are collected and submitted for testing. A limitation of wastewater sequencing is that it is not possible to identify new variants, as variants are classified based on known mutations in clinical strains.
South Africas fourth COVID-19 wave was driven predominantly by three lineages (BA.1, BA.2 and BA.3) of the SARS-CoV-2 Omicron variant of concern. We have now identified two new lineages, BA.4 and BA.5. The spike proteins of BA.4 and BA.5 are identical, and comparable to BA.2 except for the addition of 69-70del, L452R, F486V and the wild type amino acid at Q493. The 69-70 deletion in spike allows these lineages to be identified by the proxy marker of S-gene target failure with the TaqPath COVID-19 qPCR assay. BA.4 and BA.5 have rapidly replaced BA.2, reaching more than 50% of sequenced cases in South Africa from the first week of April 2022 onwards. Using a multinomial logistic regression model, we estimate growth advantages for BA.4 and BA.5 of 0.08 (95% CI: 0.07 - 0.09) and 0.12 (95% CI: 0.09 - 0.15) per day respectively over BA.2 in South Africa.
Investment in Africa over the past year with regards to SARS-CoV-2 genotyping has led to a massive increase in the number of sequences, exceeding 100,000 genomes generated to track the pandemic on the continent. Our results show an increase in the number of African countries able to sequence within their own borders, coupled with a decrease in sequencing turnaround time. Findings from this genomic surveillance underscores the heterogeneous nature of the pandemic but we observe repeated dissemination of SARS-CoV-2 variants within the continent. Sustained investment for genomic surveillance in Africa is needed as the virus continues to evolve, particularly in the low vaccination landscape. These investments are very crucial for preparedness and response for future pathogen outbreaks. One-Sentence SummaryExpanding Africa SARS-CoV-2 sequencing capacity in a fast evolving pandemic.
Among the 30 non-synonymous nucleotide substitutions in the Omicron S-gene are 13 that have only rarely been seen in other SARS-CoV-2 sequences. These mutations cluster within three functionally important regions of the S-gene at sites that will likely impact (i) interactions between subunits of the Spike trimer and the predisposition of subunits to shift from down to up configurations, (ii) interactions of Spike with ACE2 receptors, and (iii) the priming of Spike for membrane fusion. We show here that, based on both the rarity of these 13 mutations in intrapatient sequencing reads and patterns of selection at the codon sites where the mutations occur in SARS-CoV-2 and related sarbecoviruses, prior to the emergence of Omicron the mutations would have been predicted to decrease the fitness of any genomes within which they occurred. We further propose that the mutations in each of the three clusters therefore cooperatively interact to both mitigate their individual fitness costs, and adaptively alter the function of Spike. Given the evident epidemic growth advantages of Omicron over all previously known SARS-CoV-2 lineages, it is crucial to determine both how such complex and highly adaptive mutation constellations were assembled within the Omicron S-gene, and why, despite unprecedented global genomic surveillance efforts, the early stages of this assembly process went completely undetected.
BackgroundThe SARS-CoV-2 Omicron variant of concern (VOC) almost completely replaced other variants in South Africa during November 2021, and was associated with a rapid increase in COVID-19 cases. We aimed to assess clinical severity of individuals infected with Omicron, using S Gene Target Failure (SGTF) on the Thermo Fisher Scientific TaqPath COVID-19 PCR test as a proxy. MethodsWe performed data linkages for (i) SARS-CoV-2 laboratory tests, (ii) COVID-19 case data, (iii) genome data, and (iv) the DATCOV national hospital surveillance system for the whole of South Africa. For cases identified using Thermo Fisher TaqPath COVID-19 PCR, infections were designated as SGTF or non-SGTF. Disease severity was assessed using multivariable logistic regression models comparing SGTF-infected individuals diagnosed between 1 October to 30 November to (i) non-SGTF in the same period, and (ii) Delta infections diagnosed between April and November 2021. ResultsFrom 1 October through 6 December 2021, 161,328 COVID-19 cases were reported nationally; 38,282 were tested using TaqPath PCR and 29,721 SGTF infections were identified. The proportion of SGTF infections increased from 3% in early October (week 39) to 98% in early December (week 48). On multivariable analysis, after controlling for factors associated with hospitalisation, individuals with SGTF infection had lower odds of being admitted to hospital compared to non-SGTF infections (adjusted odds ratio (aOR) 0.2, 95% confidence interval (CI) 0.1-0.3). Among hospitalised individuals, after controlling for factors associated with severe disease, the odds of severe disease did not differ between SGTF-infected individuals compared to non-SGTF individuals diagnosed during the same time period (aOR 0.7, 95% CI 0.3-1.4). Compared to earlier Delta infections, after controlling for factors associated with severe disease, SGTF-infected individuals had a lower odds of severe disease (aOR 0.3, 95% CI 0.2-0.5). ConclusionEarly analyses suggest a reduced risk of hospitalisation among SGTF-infected individuals when compared to non-SGTF infected individuals in the same time period. Once hospitalised, risk of severe disease was similar for SGTF- and non-SGTF infected individuals, while SGTF-infected individuals had a reduced risk of severe disease when compared to earlier Delta-infected individuals. Some of this reducton is likely a result of high population immunity.
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic in southern Africa has been characterised by three distinct waves. The first was associated with a mix of SARS-CoV-2 lineages, whilst the second and third waves were driven by the Beta and Delta variants respectively1-3. In November 2021, genomic surveillance teams in South Africa and Botswana detected a new SARS-CoV-2 variant associated with a rapid resurgence of infections in Gauteng Province, South Africa. Within three days of the first genome being uploaded, it was designated a variant of concern (Omicron) by the World Health Organization and, within three weeks, had been identified in 87 countries. The Omicron variant is exceptional for carrying over 30 mutations in the spike glycoprotein, predicted to influence antibody neutralization and spike function4. Here, we describe the genomic profile and early transmission dynamics of Omicron, highlighting the rapid spread in regions with high levels of population immunity.
The emergence of SARS-CoV-2 Omicron, first identified in Botswana and South Africa, may compromise vaccine effectiveness and the ability of antibodies triggered by previous infection to protect against re-infection (1). Here we investigated whether Omicron escapes antibody neutralization in South Africans, either previously SARS-CoV-2 infected or uninfected, who were vaccinated with Pfizer BNT162b2. We also investigated if Omicron requires the ACE2 receptor to infect cells. We isolated and sequence confirmed live Omicron virus from an infected person in South Africa and compared plasma neutralization of this virus relative to an ancestral SARS-CoV-2 strain with the D614G mutation, observing that Omicron still required ACE2 to infect. For neutralization, blood samples were taken soon after vaccination, so that vaccine elicited neutralization was close to peak. Neutralization capacity of the D614G virus was much higher in infected and vaccinated versus vaccinated only participants but both groups had 22-fold Omicron escape from vaccine elicited neutralization. Previously infected and vaccinated individuals had residual neutralization predicted to confer 73% protection from symptomatic Omicron infection, while those without previous infection were predicted to retain only about 35%. Both groups were predicted to have substantial protection from severe disease. These data support the notion that high neutralization capacity elicited by a combination of infection and vaccination, and possibly boosting, could maintain reasonable effectiveness against Omicron. A waning neutralization response is likely to decrease vaccine effectiveness below these estimates. However, since protection from severe disease requires lower neutralization levels and involves T cell immunity, such protection may be maintained.
Global genomic surveillance of SARS-CoV-2 has identified variants associated with increased transmissibility, neutralization resistance and disease severity. Here we report the emergence of the PANGO lineage C.1.2, detected at low prevalence in South Africa and eleven other countries. The emergence of C.1.2, associated with a high substitution rate, includes changes within the spike protein that have been associated with increased transmissibility or reduced neutralization sensitivity in SARS-CoV-2 VOC/VOIs. Like Beta and Delta, C.1.2 shows significantly reduced neutralization sensitivity to plasma from vaccinees and individuals infected with the ancestral D614G virus. In contrast, convalescent donors infected with either Beta or Delta showed high plasma neutralization against C.1.2. These functional data suggest that vaccine efficacy against C.1.2 will be equivalent to Beta and Delta, and that prior infection with either Beta or Delta will likely offer protection against C.1.2.
Mauritius, a small island in the Indian Ocean, has had a unique experience of the SARS-CoV-2 pandemic. In March 2020, Mauritius endured a small first wave and quickly implemented control measures which allowed elimination of local transmission of SARS-CoV-2. When borders to the island reopened, it was accompanied by mandatory quarantine and testing of incoming passengers to avoid reintroduction of the virus into the community. As variants of concern (VOCs) emerged elsewhere in the world, Mauritius began using genomic surveillance to keep track of quarantined cases of these variants. In March 2021, another local outbreak occurred, and sequencing was used to investigate this new wave of local infections. Here, we analyze 154 SARS-CoV-2 viral genomes from Mauritius, which represent 12% of all the infections seem in Mauritius, these were both from specimens of incoming passengers before March 2021 and those of cases during the second wave. Our findings indicate that despite the presence of known VOCs Beta (B.1.351) and Alpha (B.1.1.7) among quarantined passengers, the second wave of local SARS-CoV-2 infections in Mauritius was caused by a single introduction and dominant circulation of the B.1.1.318 virus. The B.1.1.318 variant is characterized by fourteen non-synonymous mutations in the S-gene, with five encoded amino acid substitutions (T95I, E484K, D614G, P681H, D796H) and one deletion (Y144del) in the Spike glycoprotein. This variant seems to be increasing in prevalence and it is now present in 34 countries. This study highlights that despite having stopped the introduction of more transmissible VOCs by travel quarantines, a single undetected introduction of a B.1.1.318 lineage virus was enough to initiate a large local outbreak in Mauritius and demonstrated the need for continuous genomic surveillance to fully inform public health decisions.