SARS-CoV-2 spike protein diversity at an intra-host level, among SARS-CoV-2 infected individuals in South Africa, 2020 to 2022.

Intra-host diversity studies are used to characterise the mutational heterogeneity of SARS-CoV-2 infections in order to understand the impact of virus-host adaptations. This study investigated the frequency and diversity of the spike (S) protein mutations within SARS-CoV-2 infected South African individuals. The study included SARS-CoV-2 respiratory samples, from individuals of all ages, received at the National Health Laboratory Service at Charlotte Maxeke Johannesburg Academic hospital, Gauteng, South Africa, from June 2020 to May 2022. Single nucleotide polymorphism (SNP) assays and whole genome sequencing were performed on a random selection of SARS-CoV-2 positive samples. The allele frequency (AF) was determined using TaqMan Genotyper software for SNP PCR analysis and galaxy.eu for analysis of FASTQ reads from sequencing. The SNP assays identified 5.3% (50/948) of Delta cases with heterogeneity at delY144 (4%; 2/50), E484Q (6%; 3/50), N501Y (2%; 1/50) and P681H (88%; 44/50), however only heterogeneity for E484Q and delY144 were confirmed by sequencing. From sequencing we identified 9% (210/2381) of cases with Beta, Delta, Omicron BA.1, BA.2.15, and BA.4 lineages that had heterogeneity in the S protein. Heterogeneity was primarily identified at positions 19 (1.4%) with T19IR (AF 0.2-0.7), 371 (92.3%) with S371FP (AF 0.1-1.0), and 484 (1.9%) with E484AK (0.2-0.7), E484AQ (AF 0.4-0.5) and E484KQ (AF 0.1-0.4). Mutations at heterozygous amino acid positions 19, 371 and 484 are known antibody escape mutations, however the impact of the combination of multiple substitutions identified at the same position is unknown. Therefore, we hypothesise that intra-host SARS-CoV-2 quasispecies with heterogeneity in the S protein facilitate competitive advantage of variants that can completely/partially evade host's natural and vaccine-induced immune responses.

Molecular Epidemiology of SARS-CoV-2 during Five COVID-19 Waves and the Significance of Low-Frequency Lineages.

SARS-CoV-2 lineages and variants of concern (VOC) have gained more efficient transmission and immune evasion properties with time. We describe the circulation of VOCs in South Africa and the potential role of low-frequency lineages on the emergence of future lineages. Whole genome sequencing was performed on SARS-CoV-2 samples from South Africa. Sequences were analysed with Nextstrain pangolin tools and Stanford University Coronavirus Antiviral & Resistance Database. In 2020, 24 lineages were detected, with B.1 (3%; 8/278), B.1.1 (16%; 45/278), B.1.1.348 (3%; 8/278), B.1.1.52 (5%; 13/278), C.1 (13%; 37/278) and C.2 (2%; 6/278) circulating during the first wave. Beta emerged late in 2020, dominating the second wave of infection. B.1 and B.1.1 continued to circulate at low frequencies in 2021 and B.1.1 re-emerged in 2022. Beta was outcompeted by Delta in 2021, which was thereafter outcompeted by Omicron sub-lineages during the 4th and 5th waves in 2022. Several significant mutations identified in VOCs were also detected in low-frequency lineages, including S68F (E protein); I82T (M protein); P13L, R203K and G204R/K (N protein); R126S (ORF3a); P323L (RdRp); and N501Y, E484K, D614G, H655Y and N679K (S protein). Low-frequency variants, together with VOCs circulating, may lead to convergence and the emergence of future lineages that may increase transmissibility, infectivity and escape vaccine-induced or natural host immunity.

Genomic epidemiology of SARS-CoV-2 during the first four waves in Mozambique

Mozambique reported the first case of coronavirus disease 2019 (COVID-19) in March 2020 and it has since spread to all provinces in the country. To investigate the introductions and spread of SARS-CoV-2 in Mozambique, 1 142 whole genome sequences sampled within Mozambique were phylogenetically analyzed against a globally representative set, reflecting the first 25 months of the epidemic. The epidemic in the country was marked by four waves of infection, the first associated with B.1 ancestral lineages, while the Beta, Delta, and Omicron Variants of Concern (VOCs) were responsible for most infections and deaths during the second, third, and fourth waves. Large-scale viral exchanges occurred during the latter three waves and were largely attributed to southern African origins. Not only did the country remain vulnerable to the introductions of new variants but these variants continued to evolve within the borders of the country. Due to the Mozambican health system already under constraint, and paucity of data in Mozambique, there is a need to continue to strengthen and support genomic surveillance in the country as VOCs and Variants of interests (VOIs) are often reported from the southern African region.

Molecular Epidemiology and Diversity of SARS-CoV-2 in Ethiopia, 2020-2022.

Ethiopia is the second most populous country in Africa and the sixth most affected by COVID-19 on the continent. Despite having experienced five infection waves, >499,000 cases, and ~7500 COVID-19-related deaths as of January 2023, there is still no detailed genomic epidemiological report on the introduction and spread of SARS-CoV-2 in Ethiopia. In this study, we reconstructed and elucidated the COVID-19 epidemic dynamics. Specifically, we investigated the introduction, local transmission, ongoing evolution, and spread of SARS-CoV-2 during the first four infection waves using 353 high-quality near-whole genomes sampled in Ethiopia. Our results show that whereas viral introductions seeded the first wave, subsequent waves were seeded by local transmission. The B.1.480 lineage emerged in the first wave and notably remained in circulation even after the emergence of the Alpha variant. The B.1.480 was outcompeted by the Delta variant. Notably, Ethiopia's lack of local sequencing capacity was further limited by sporadic, uneven, and insufficient sampling that limited the incorporation of genomic epidemiology in the epidemic public health response in Ethiopia. These results highlight Ethiopia's role in SARS-CoV-2 dissemination and the urgent need for balanced, near-real-time genomic sequencing.

Identification of SARS-CoV-2 Omicron variant using spike gene target failure and genotyping assays, Gauteng, South Africa, 2021.

The circulation of Omicron BA.1 led to the rapid increase in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases in South Africa in November 2021, which warranted the use of more rapid detection methods. We, therefore, assessed the ability to detect Omicron BA.1 using genotyping assays to identify specific mutations in SARS-CoV-2 positive samples, Gauteng province, South Africa. The TaqPath™ COVID-19 real-time polymerase chain reaction assay was performed on all samples selected to identify spike gene target failure (SGTF). SARS-CoV-2 genotyping assays were used for the detection of del69/70 and K417N mutation. Whole-genome sequencing was performed on a subset of genotyped samples to confirm these findings. Of the positive samples received, 11.0% (175/1589) were randomly selected to assess if SGTF and genotyping assays, that detect del69/70 and K417N mutations, could identify Omicron BA.1. We identified SGTF in 98.9% (173/175) of samples, of which 88.0% (154/175) had both the del69/70 and K417N mutation. The genotyped samples (45.7%; 80/175) that were sequenced confirmed Omicron BA.1 (97.5%; 78/80). Our data show that genotyping for the detection of the del69/70 and K417N coupled with SGTF is efficient to exclude Alpha and Beta variants and rapidly detect Omicron BA.1. However, we still require assays for the detection of unique mutations that will allow for the differentiation between other Omicron sublineages. Therefore, the use of genotyping assays to detect new dominant or emerging lineages of SARS-CoV-2 will be beneficial in limited-resource settings.

Omicron infection enhances Delta antibody immunity in vaccinated persons.

The extent to which Omicron infection1-9, with or without previous vaccination, elicits protection against the previously dominant Delta (B.1.617.2) variant is unclear. Here we measured the neutralization capacity against variants of severe acute respiratory syndrome coronavirus 2 in 39 individuals in South Africa infected with the Omicron sublineage BA.1 starting at a median of 6 (interquartile range 3-9) days post symptom onset and continuing until last follow-up sample available, a median of 23 (interquartile range 19-27) days post symptoms to allow BA.1-elicited neutralizing immunity time to develop. Fifteen participants were vaccinated with Pfizer's BNT162b2 or Johnson & Johnson's Ad26.CoV2.S and had BA.1 breakthrough infections, and 24 were unvaccinated. BA.1 neutralization increased from a geometric mean 50% focus reduction neutralization test titre of 42 at enrolment to 575 at the last follow-up time point (13.6-fold) in vaccinated participants and from 46 to 272 (6.0-fold) in unvaccinated participants. Delta virus neutralization also increased, from 192 to 1,091 (5.7-fold) in vaccinated participants and from 28 to 91 (3.0-fold) in unvaccinated participants. At the last time point, unvaccinated individuals infected with BA.1 had low absolute levels of neutralization for the non-BA.1 viruses and 2.2-fold lower BA.1 neutralization, 12.0-fold lower Delta neutralization, 9.6-fold lower Beta variant neutralization, 17.9-fold lower ancestral virus neutralization and 4.8-fold lower Omicron sublineage BA.2 neutralization relative to vaccinated individuals infected with BA.1. These results indicate that hybrid immunity formed by vaccination and Omicron BA.1 infection should be protective against Delta and other variants. By contrast, infection with Omicron BA.1 alone offers limited cross-protection despite moderate enhancement.

Comparison of SARS-CoV-2 sequencing using the ONT GridION and the Illumina MiSeq.

BACKGROUND: Over 4 million SARS-CoV-2 genomes have been sequenced globally in the past 2 years. This has been crucial in elucidating transmission chains within communities, the development of new diagnostic methods, vaccines, and antivirals. Although several sequencing technologies have been employed, Illumina and Oxford Nanopore remain the two most commonly used platforms. The sequence quality between these two platforms warrants a comparison of the genomes produced by the two technologies. Here, we compared the SARS-CoV-2 consensus genomes obtained from the Oxford Nanopore Technology GridION and the Illumina MiSeq for 28 sequencing runs. RESULTS: Our results show that the MiSeq had a significantly higher number of consensus genomes classified by Nextclade as good and mediocre compared to the GridION. The MiSeq also had a significantly higher genome coverage and mutation counts than the GridION. CONCLUSION: Due to the low genome coverage, high number of indels, and sensitivity to SARS-CoV-2 viral load noted with the GridION when compared to MiSeq, we can conclude that the MiSeq is more favourable for SARS-CoV-2 genomic surveillance, as successful genomic surveillance is dependent on high quality, near-whole consensus genomes.

Rapid Replacement of SARS-CoV-2 Variants by Delta and Subsequent Arrival of Omicron, Uganda, 2021.

Genomic surveillance in Uganda showed rapid replacement of severe acute respiratory syndrome coronavirus 2 over time by variants, dominated by Delta. However, detection of the more transmissible Omicron variant among travelers and increasing community transmission highlight the need for near-real-time genomic surveillance and adherence to infection control measures to prevent future pandemic waves.