ABSTRACT
The milder clinical manifestations of Omicron infection relative to pre-Omicron SARS-CoV-2 raises the possibility that extensive evolution results in reduced pathogenicity. To test this hypothesis, we quantified induction of cell fusion and cell death in SARS-CoV-2 evolved from ancestral virus during long-term infection. Both cell fusion and death were reduced in Omicron BA.1 infection relative to ancestral virus. Evolved virus was isolated at different times during a 6-month infection in an immunosuppressed individual with advanced HIV disease. The virus isolated 16 days post-reported symptom onset induced fusogenicity and cell death at levels similar to BA.1. However, fusogenicity was increased in virus isolated at 6 months post-symptoms to levels intermediate between BA.1 and ancestral SARS-CoV-2. Similarly, infected cell death showed a graded increase from earlier to later isolates. These results may indicate that, at least by the cellular measures used here, evolution in long-term infection does not necessarily attenuate the virus.
ABSTRACT
The SARS-CoV-2 Omicron (B.1.1.529) variant first emerged as the BA.1 sub-lineage, with extensive escape from neutralizing immunity elicited by previous infection with other variants, vaccines, or combinations of both1,2. Two new sub-lineages, BA.4 and BA.5, are now emerging in South Africa with changes relative to BA.1, including L452R and F486V mutations in the spike receptor binding domain. We isolated live BA.4 and BA.5 viruses and tested them against neutralizing immunity elicited to BA.1 infection in participants who were Omicron/BA.1 infected but unvaccinated (n=24) and participants vaccinated with Pfizer BNT162b2 or Johnson and Johnson Ad26.CoV.2S with breakthrough Omicron/BA.1 infection (n=15). In unvaccinated individuals, FRNT50, the inverse of the dilution for 50% neutralization, declined from 275 for BA.1 to 36 for BA.4 and 37 for BA.5, a 7.6 and 7.5-fold drop, respectively. In vaccinated BA.1 breakthroughs, FRNT50 declined from 507 for BA.1 to 158 for BA.4 (3.2-fold) and 198 for BA.5 (2.6-fold). Absolute BA.4 and BA.5 neutralization levels were about 5-fold higher in this group versus unvaccinated BA.1 infected participants. The observed escape of BA.4 and BA.5 from BA.1 elicited immunity is more moderate than of BA.1 against previous immunity1,3. However, the low absolute neutralization levels for BA.4 and BA.5, particularly in the unvaccinated group, are unlikely to protect well against symptomatic infection4.This may indicate that, based on neutralization escape, BA.4 and BA.5 have potential to result in a new infection wave.
ABSTRACT
Omicron (B.1.1.529) shows extensive escape from vaccine immunity, although vaccination reduces severe disease and death1. Boosting with vaccines incorporating variant spike sequences could possibly broaden immunity2. One approach to choose the variant may be to measure immunity elicited by vaccination combined with variant infection. Here we investigated Omicron neutralization in people infected with the Beta (B.1.351) variant and subsequently vaccinated with Pfizer BNT162b2. We observed that Beta infection alone elicited poor Omicron cross-neutralization, similar to what we previously found3 with BNT162b2 vaccination alone or in combination with ancestral or Delta virus infection. In contrast, Beta infection combined with BNT162b2 vaccination elicited neutralization with substantially lower Omicron escape.
ABSTRACT
The COVID-19 pandemic spread very fast around the world. A few days after the first detected case in South Africa, an infection started a large hospital outbreak in Durban, KwaZulu-Natal. Phylogenetic analysis of SARS-CoV-2 genomes can be used to trace the path of transmission within a hospital. It can also identify the source of the outbreak and provide lessons to improve infection prevention and control strategies. In this manuscript, we outline the obstacles we encountered in order to genotype SARS-CoV-2 in real-time during an urgent outbreak investigation. In this process, we encountered problems with the length of the original genotyping protocol, reagent stockout and sample degradation and storage. However, we managed to set up three different library preparation methods for sequencing in Illumina. We also managed to decrease the hands on library preparation time from twelve to three hours, which allowed us to complete the outbreak investigation in just a few weeks. We also fine-tuned a simple bioinformatics workflow for the assembly of high-quality genomes in real-time. In order to allow other laboratories to learn from our experience, we released all of the library preparation and bioinformatics protocols publicly and distributed them to other laboratories of the South African Network for Genomics Surveillance (SANGS) consortium.
ABSTRACT
BackgroundThe emergence of a novel coronavirus, SARS-CoV-2, in December 2019, progressed to become a world pandemic in a few months and reached South Africa at the beginning of March. To investigate introduction and understand the early transmission dynamics of the virus, we formed the South African Network for Genomics Surveillance of COVID (SANGS_COVID), a network of ten government and university laboratories. Here, we present the first results of this effort, which is a molecular epidemiological study of the first twenty-one SARS-CoV-2 whole genomes sampled in the first port of entry, KwaZulu-Natal (KZN), during the first month of the epidemic. By combining this with calculations of the effective reproduction number (R), we aim to shed light on the patterns of infections that define the epidemic in South Africa. MethodsR was calculated using positive cases and deaths from reports provided by the four major provinces. Molecular epidemiology investigation involved sequencing viral genomes from patients in KZN using ARCTIC protocols and assembling whole genomes using meticulous alignment methods. Phylogenetic analysis was performed using maximum likelihood (ML) and Bayesian trees, lineage classification and molecular clock calculations. FindingsThe epidemic in South Africa has been very heterogeneous. Two of the largest provinces, Gauteng, home of the two large metropolis Johannesburg and Pretoria, and KwaZulu-Natal, home of the third largest city in the country Durban, had a slow growth rate on the number of detected cases. Whereas, Western Cape, home of Cape Town, and the Eastern Cape provinces the epidemic is spreading fast. Our estimates of transmission potential for South Africa suggest a decreasing transmission potential towards R=1 since the first cases and deaths have been reported. However, between 06 May and 18 May 2020, we estimate that R was on average 1.39 (1.04-2.15, 95% CI). We also demonstrate that early transmission in KZN, and most probably in all main regions of SA, was associated with multiple international introductions and dominated by lineages B1 and B. The study also provides evidence for locally acquired infections in a hospital in Durban within the first month of the epidemic, which inflated early mortality in KZN. InterpretationThis first report of SANGS_COVID consortium focuses on understanding the epidemic heterogeneity and introduction of SARS-CoV-2 strains in the first month of the epidemic in South Africa. The early introduction of SARS-CoV-2 in KZN included caused a localized outbreak in a hospital, provides potential explanations for the initially high death rates in the province. The current high rate of transmission of COVID-19 in the Western Cape and Eastern Cape highlights the crucial need to strength local genomic surveillance in South Africa. FundingUKZN Flagship Program entitled: Afrocentric Precision Approach to Control Health Epidemic, by a research Flagship grant from the South African Medical Research Council (MRC-RFA-UFSP-01- 2013/UKZN HIVEPI, by the the Technology Innovation Agency and the the Department of Science and Innovation and by National Human Genome Re- search Institute of the National Institutes of Health under Award Number U24HG006941. H3ABioNet is an initiative of the Human Health and Heredity in Africa Consortium (H3Africa). Research in context Evidence before this studyWe searched PubMed, BioRxiv and MedRxiv for reports on epidemiology and phylogenetic analysis using whole genome sequencing (WGS) of SARS-CoV-2. We used the following keywords: SARS-CoV-2, COVID-19, 2019-nCoV or novel coronavirus and transmission genomics, epidemiology, phylogenetic or reproduction number. Our search identified an important lack of molecular epidemiology studies in the southern hemisphere, with only a few reports from Latin America and one in Africa. In other early transmission reports on SARS-CoV-2 infections in Africa, authors focused on transmission dynamics, but molecular and phylogenetic methods were missing. Added value of this studyWith a growing sampling bias in the study of transmission genomics of the SARS-CoV-2 pandemic, it is important for us to report high-quality whole genome sequencing (WGS) of local SARS-CoV-2 samples and in-depth phylogenetic analyses of the first month of infection in South-Africa. In our molecular epidemiological investigation, we identify the early transmission routes of the infection in the KZN and report thirteen distinct introductions from many locations and a cluster of localized transmission linked to a healthcare setting that caused most of the initial deaths in South Africa. Furthermore, we formed a national consortium in South Africa, funded by the Department of Science and Innovation and the South African Medical Research Council, to capacitate ten local laboratories to produce and analyse SARS-CoV-2 data in near real time. Implications of all the available evidenceThe COVID-19 pandemic is progressing around the world and in Africa. Early transmission genomics and dynamics of SARS-CoV-2 throw light on the early stages of the epidemic in a given region. This facilitates the investigation of localized outbreaks and serves to inform public health responses in South Africa.
