HIV skews the SARS-CoV-2 B cell response toward an extrafollicular maturation pathway

BackgroundHIV infection dysregulates the B cell compartment, affecting memory B cell formation and the antibody response to infection and vaccination. Understanding the B cell response to SARS-CoV-2 in people living with HIV (PLWH) may explain the increased morbidity, reduced vaccine efficacy, reduced clearance, and intra-host evolution of SARS-CoV-2 observed in some HIV-1 coinfections. MethodsWe compared B cell responses to COVID-19 in PLWH and HIV negative (HIV-ve) patients in a cohort recruited in Durban, South Africa, during the first pandemic wave in July 2020 using detailed flow cytometry phenotyping of longitudinal samples with markers of B cell maturation, homing and regulatory features. ResultsThis revealed a coordinated B cell response to COVID-19 that differed significantly between HIV-ve and PLWH. Memory B cells in PLWH displayed evidence of reduced germinal center (GC) activity, homing capacity and class-switching responses, with increased PD-L1 expression, and decreased Tfh frequency. This was mirrored by increased extrafollicular (EF) activity, with dynamic changes in activated double negative (DN2) and activated naive B cells, which correlated with anti-RBD-titres in these individuals. An elevated SARS-CoV-2 specific EF response in PLWH was confirmed using viral spike and RBD bait proteins. ConclusionsDespite similar disease severity, these trends were highest in participants with uncontrolled HIV, implicating HIV in driving these changes. EF B cell responses are rapid but give rise to lower affinity antibodies, less durable long-term memory, and reduced capacity to adapt to new variants. Further work is needed to determine the long-term effects of HIV on SARS-CoV-2 immunity, particularly as new variants emerge. FundingThis work was supported by a grant from the Wellcome Trust to the Africa Health Research Institute (Wellcome Trust Strategic Core Award [grant number 201433/Z/16/Z]). Additional funding was received from the South African Department of Science and Innovation through the National Research Foundation (South African Research Chairs Initiative, [grant number 64809]), and the Victor Daitz Foundation.

Unsuppressed HIV infection impairs T cell responses to SARS-CoV-2 infection and abrogates T cell cross-recognition

HIV infection has been identified as one of the major risk factors for severe COVID-19 disease, but the mechanisms underpinning this susceptability are still unclear. Here, we assessed the impact of HIV infection on the quality and epitope specificity of SARS-CoV-2 T cell responses in the first wave and second wave of the COVID-19 epidemic in South Africa. Flow cytometry was used to measure T cell responses following PBMC stimulation with SARS-CoV-2 peptide pools. Culture expansion was used to determine T cell immunodominance hierarchies and to assess potential SARS-CoV-2 escape from T cell recognition. HIV-seronegative individuals had significantly greater CD4+ and CD8+ T cell responses against the Spike protein compared to the viremic PLWH. Absolute CD4 count correlated positively with SARS-CoV-2 specific CD4+ and CD8+ T cell responses (CD4 r= 0.5, p=0.03; CD8 r=0.5, p=0.001), whereas T cell activation was negatively correlated with CD4+ T cell responses (CD4 r= -0.7, p=0.04). There was diminished T cell cross-recognition between the two waves, which was more pronounced in individuals with unsuppressed HIV infection. Importantly, we identify four mutations in the Beta variant that resulted in abrogation of T cell recognition. Together, we show that unsuppressed HIV infection markedly impairs T cell responses to SARS-Cov-2 infection and diminishes T cell cross-recognition. These findings may partly explain the increased susceptibility of PLWH to severe COVID-19 and also highlights their vulnerability to emerging SARS-CoV-2 variants of concern. One sentence summaryUnsuppressed HIV infection is associated with muted SARS-CoV-2 T cell responses and poorer recognition of the Beta variant.

A year of genomic surveillance reveals how the SARS-CoV-2 pandemic unfolded in Africa

The progression of the SARS-CoV-2 pandemic in Africa has so far been heterogeneous and the full impact is not yet well understood. Here, we describe the genomic epidemiology using a dataset of 8746 genomes from 33 African countries and two overseas territories. We show that the epidemics in most countries were initiated by importations, predominantly from Europe, which diminished following the early introduction of international travel restrictions. As the pandemic progressed, ongoing transmission in many countries and increasing mobility led to the emergence and spread within the continent of many variants of concern and interest, such as B.1.351, B.1.525, A.23.1 and C.1.1. Although distorted by low sampling numbers and blind-spots, the findings highlight that Africa must not be left behind in the global pandemic response, otherwise it could become a breeding ground for new variants.

Escape of SARS-CoV-2 501Y.V2 variants from neutralization by convalescent plasma

SARS-CoV-2 variants of concern (VOC) have arisen independently at multiple locations and may reduce efficacy of current vaccines targeted at the spike glycoprotein. We re-cently described the emergence of VOC in South Africa (501Y.V2 or PANGO lineage B.1.351) with mutations in the spike receptor-binding domain (RBD) and N-terminal domain (NTD). Here, using a live virus neutralization assay (LVNA), we compared neutralization of a first wave virus (B.1.1.117) versus the 501Y.V2 variant using plasma collected from adults hospitalized with COVID-19 from two South African infection waves, with the second wave dominated by 501Y.V2 infections. Sequencing demonstrated that infections in first wave plasma donors were with viruses harbouring none of the 501Y.V2-defining RBD or NTD mutations, except for one with E484K. 501Y.V2 virus was effectively neutralized by plasma from second wave infections and first wave virus was effectively neutralized by first wave plasma. In cross-neutralization, 501Y.V2 virus was poorly neutralized by first wave plasma, with an 8.4-fold drop in neutralization relative to first wave virus and a 15.1-fold drop relative to 501Y.V2 neutralization by second wave plasma. In contrast, second wave plasma neutralization of first wave virus was more effective, showing 4.1-fold decline relative to 501Y.V2 virus neutralization and 2.3-fold decline relative to first wave plasma neutralization. While we only tested one plasma elicited by E484K alone, this potently neutralized both variants. The observed effective neutralization of first wave virus by 501Y.V2 infection elicited plasma provides preliminary evidence that vaccines based on VOC sequences could retain activity against other circulating SARS-CoV-2 lineages.

HIV infection alters SARS-CoV-2 responsive immune parameters but not clinical outcomes in COVID-19 disease

There are conflicting reports on the effects of HIV on COVID-19. Here we analyzed disease severity and immune cell changes during and after SARS-CoV-2 infection in 236 participants from South Africa, of which 39% were people living with HIV (PLWH), during the first and second ({beta} dominated) infection waves. The second wave had more PLWH requiring supplemental oxygen relative to HIV negative participants. Higher disease severity was associated with low CD4 T cell counts and higher neutrophil to lymphocyte ratios (NLR). Yet, CD4 counts recovered and NLR stabilized after SARS-CoV-2 clearance in wave 2 infected PLWH, arguing for an interaction between SARS-CoV-2 and HIV infection leading to low CD4 and high NLR. The first infection wave, where severity in HIV negative and PLWH was similar, still showed some HIV modulation of SARS-CoV-2 immune responses. Therefore, HIV infection can synergize with the SARS-CoV-2 variant to change COVID-19 outcomes.

High Resolution analysis of Transmission Dynamics of Sars-Cov-2 in Two Major Hospital Outbreaks in South Africa Leveraging Intrahost Diversity

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes acute, highly transmissible respiratory infection in both humans and wide range of animal species. Its rapid spread globally and devasting effects have resulted into a major public health emergency prompting the need for methodological interventions to understand and control its spread. In particular, The ability to effectively retrace its transmission pathways in outbreaks remains a major challenge. This is further exacerbated by our limited understanding of its underlying evolutionary mechanism. Using NGS whole-genome data, we determined whether inter- and intra-host diversity coupled with bottleneck analysis can retrace the pathway of viral transmission in two epidemiologically well characterised nosocomial outbreaks in healthcare settings supported by phylogenetic analysis. Additionally, we assessed the mutational landscape, selection pressure and diversity of the identified variants. Our findings showed evidence of intrahost variant transmission and evolution of SARS-CoV-2 after infection These observations were consistent with the results from the bottleneck analysis suggesting that certain intrahost variants in this study could have been transmitted to recipients. In both outbreaks, we observed iSNVs and SNVs shared by putative source-recipients pairs. Majority of the observed iSNVs were positioned in the S and ORF1ab region. AG, CT and TC nucleotide changes were enriched across SARS-COV-2 genome. Moreover, SARS-COV-2 genome had limited diversity in some loci while being highly conserved in others. Overall, Our findings show that the synergistic effect of combining withinhost diversity and bottleneck estimations greatly enhances resolution of transmission events in Sars-Cov-2 outbreaks. They also provide insight into the genome diversity suggesting purifying selection may be involved in the transmission. Together these results will help in developing strategies to elucidate transmission events and curtail the spread of Sars-Cov-2

Major new lineages of SARS-CoV-2 emerge and spread in South Africa during lockdown.

In March 2020, the first cases of COVID-19 were reported in South Africa. The epidemic spread very fast despite an early and extreme lockdown and infected over 600,000 people, by far the highest number of infections in an African country. To rapidly understand the spread of SARS-CoV-2 in South Africa, we formed the Network for Genomics Surveillance in South Africa (NGS-SA). Here, we analyze 1,365 high quality whole genomes and identify 16 new lineages of SARS-CoV-2. Most of these unique lineages have mutations that are found hardly anywhere else in the world. We also show that three lineages spread widely in South Africa and contributed to [~]42% of all of the infections in the country. This included the first identified C lineage of SARS-CoV-2, C.1, which has 16 mutations as compared with the original Wuhan sequence. C.1 was the most geographically widespread lineage in South Africa, causing infections in multiple provinces and in all of the eleven districts in KwaZulu-Natal (KZN), the most sampled province. Interestingly, the first South-African specific lineage, B.1.106, which was identified in April 2020, became extinct after nosocomial outbreaks were controlled. Our findings show that genomic surveillance can be implemented on a large scale in Africa to identify and control the spread of SARS-CoV-2.

Whole Genome Sequencing of SARS-CoV-2: Adapting Illumina Protocols for Quick and Accurate Outbreak Investigation During a Pandemic

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.

Early transmission of SARS-CoV-2 in South Africa: An epidemiological and phylogenetic report

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.