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SARS-CoV-2 variants of concern (VOC) have arisen independently at multiple locations 1 , 2 and may reduce the efficacy of current vaccines that target the spike glycoprotein of SARS-CoV-2 3 . Here, using a live-virus neutralization assay, we compared the neutralization of a non-VOC variant with the 501Y.V2 VOC (also known as B.1.351) using plasma collected from adults who were hospitalized with COVID-19 during the two waves of infection in South Africa, the second wave of which was dominated by infections with the 501Y.V2 variant. Sequencing demonstrated that infections of plasma donors from the first wave were with viruses that did not contain the mutations associated with 501Y.V2, except for one infection that contained the E484K substitution in the receptor-binding domain. The 501Y.V2 virus variant was effectively neutralized by plasma from individuals who were infected during the second wave. The first-wave virus variant was effectively neutralized by plasma from first-wave infections. However, the 501Y.V2 variant was poorly cross-neutralized by plasma from individuals with first-wave infections; the efficacy was reduced by 15.1-fold relative to neutralization of 501Y.V2 by plasma from individuals infected in the second wave. By contrast, cross-neutralization of first-wave virus variants using plasma from individuals with second-wave infections was more effective, showing only a 2.3-fold decrease relative to neutralization of first-wave virus variants by plasma from individuals infected in the first wave. Although we tested only one plasma sample from an individual infected with a SARS-CoV-2 variant with only the E484K substitution, this plasma sample potently neutralized both variants. The observed effective neutralization of first-wave virus by plasma from individuals infected with 501Y.V2 provides preliminary evidence that vaccines based on VOC sequences could retain activity against other circulating SARS-CoV-2 lineages. Cross-neutralization assays of early variants and the 501Y.V2 variant of SARS-CoV-2 show that plasma from individuals infected with 501Y.V2 effectively neutralizes all variants, indicating that a vaccine that targets 501Y.V2 may also be effective against other SARS-CoV-2 variants.

A hallmark of pulmonary tuberculosis is the formation of macrophage-rich granulomas. These may restrict Mycobacterium tuberculosis (Mtb) growth, or progress to central necrosis and cavitation, facilitating pathogen growth. To determine factors leading to Mtb proliferation and host cell death, we used live cell imaging to track Mtb infection outcomes in individual primary human macrophages. Internalization of Mtb aggregates caused macrophage death, and phagocytosis of large aggregates was more cytotoxic than multiple small aggregates containing similar numbers of bacilli. Macrophage death did not result in clearance of Mtb. Rather, it led to accelerated intracellular Mtb growth regardless of prior activation or macrophage type. In contrast, bacillary replication was controlled in live phagocytes. Mtb grew as a clump in dead cells, and macrophages which internalized dead infected cells were very likely to die themselves, leading to a cell death cascade. This demonstrates how pathogen virulence can be achieved through numbers and aggregation states. Every year, around two million people worldwide die from tuberculosis, a disease caused by the bacterium Mycobacterium tuberculosis (Mtb). The bacteria generally infect the lungs. In response, the immune system forms structures called granulomas that attempt to control and isolate the infecting pathogens. Granulomas consist of immune cells known as macrophages, which engulf the M. tuberculosis bacteria and isolate them in a cellular compartment where the bacteria either cannot grow or are killed. However, if a large number of macrophages in a granuloma die, the granuloma’s core liquefies and the structure is coughed up into the airways, from where M. tuberculosis bacteria are transmitted to other people. But how do the bacteria manage to cause the extensive death of the cells that are supposed to control the infection? By imaging M. tuberculosis in human macrophages using time-lapse microscopy, Mahamed et al. reveal that the bacteria break down macrophage control by serially killing macrophages. M. tuberculosis cells first clump together and ‘gang up’ on a macrophage, which engulfs the clump and dies because the bacteria overwhelm it. This does not kill the bacteria, and they rapidly grow inside the dead macrophage. The dead cell is then cleaned up by another macrophage. However, the increasing number of bacteria inside the dead macrophage means that the new macrophage is even more likely to die than the first one. Hence, the bacteria use dead macrophages as fuel to grow on and as bait to attract the next immune cell. Overall, Mahamed et al. show that once a clump of M. tuberculosis initiates death of a single macrophage, it may lead to serial killing of other macrophages and a loss of control over the infection. An important next step will be to understand how the initial clump of bacteria is allowed to form.

The extent to which Omicron infection 1 – 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. A study quantifying the neutralization of severe acute respiratory syndrome coronavirus 2 variants in individuals infected with Omicron/BA.1 shows that vaccinated individuals previously infected with Omicron have enhanced protection against reinfection with current variants, \\including Omicron/BA.2, while Omicron/BA.1 infected unvaccinated individuals have limited protection.

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.

Cell-to-cell spread of HIV, a directed mode of viral transmission, has been observed to be more rapid than cell-free infection. However, a mechanism for earlier onset of viral gene expression in cell-to-cell spread was previously uncharacterized. Here we used time-lapse microscopy combined with automated image analysis to quantify the timing of the onset of HIV gene expression in a fluorescent reporter cell line, as well as single cell staining for infection over time in primary cells. We compared cell-to-cell spread of HIV to cell-free infection, and limited both types of transmission to a two-hour window to minimize differences due to virus transit time to the cell. The mean time to detectable onset of viral gene expression in cell-to-cell spread was accelerated by 19% in the reporter cell line and by 35% in peripheral blood mononuclear cells relative to cell-free HIV infection. Neither factors secreted by infected cells, nor contact with infected cells in the absence of transmission, detectably changed onset. We recapitulated the earlier onset by infecting with multiple cell-free viruses per cell. Surprisingly, the acceleration in onset of viral gene expression was not explained by cooperativity between infecting virions. Instead, more rapid onset was consistent with a model where the fastest expressing virus out of the infecting virus pool sets the time for infection independently of the other co-infecting viruses.

HIV 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. We 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. This 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 centre (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 naïve 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. Despite 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. This 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.

Current TB treatment regimens are pathogen-directed and can be severely compromised by the development of drug resistance. Metformin has been proposed as an adjunctive therapy for TB, however relatively little is known about how metformin modulates the cellular interaction between Mtb and macrophages. We aimed to characterize how metformin modulates Mtb growth within macrophages. We utilized live cell tracking through time-lapse microscopy to better understand the biological effect of metformin in response to Mtb infection. Furthermore, the potent first-line anti-TB drug, isoniazid, was used as a comparator and as a companion drug. Metformin caused a 14.2-fold decrease in Mtb growth compared to the untreated control. Metformin combined with isoniazid controlled Mtb growth is slightly better than isoniazid alone. Metformin demonstrated the ability to regulate the cytokine and chemokine response over a 72 hour period, better than isoniazid only. We provide novel evidence that metformin controls mycobacterial growth by increasing host cell viability, and a direct and independent pro-inflammatory response to Mtb. Understanding the impact of metformin on Mtb growth within macrophages will advance our current knowledge on metformin as an adjunctive therapy, providing a new host-directed approach to TB treatment.

HIV has been reported to be cytotoxic in vitro and in lymph node infection models. Using a computational approach, we found that partial inhibition of transmissions of multiple virions per cell could lead to increased numbers of live infected cells. If the number of viral DNA copies remains above one after inhibition, then eliminating the surplus viral copies reduces cell death. Using a cell line, we observed increased numbers of live infected cells when infection was partially inhibited with the antiretroviral efavirenz or neutralizing antibody. We then used efavirenz at concentrations reported in lymph nodes to inhibit lymph node infection by partially resistant HIV mutants. We observed more live infected lymph node cells, but with fewer HIV DNA copies per cell, relative to no drug. Hence, counterintuitively, limited attenuation of HIV transmission per cell may increase live infected cell numbers in environments where the force of infection is high. The HIVvirus infects cells of the immune system. Once inside, it hijacks the cellular molecular machineries to make more copies of itself, which are then transmitted to new host cells. HIV eventually kills most cells it infects, either in the steps leading to the infection of the cell, or after the cell is already producing virus. HIV can spread between cells in two ways, known as cell-free or cell-to-cell. In the first, individual viruses are released from infected cells and move randomly through the body in the hope of finding new cells to infect. In the second, infected cells interact directly with uninfected cells. The second method is often much more successful at infecting new cells since they are exposed to multiple virus particles. HIV infections can be controlled by using combinations of antiretroviral drugs, such as efavirenz, to prevent the virus from making more of itself. With a high enough dose, the drugs can in theory completely stop HIV infections, unless the virus becomes resistant to treatment. However, some patients continue to use these drugs even after the virus they are infected with develops resistance. It is not clear what effect taking ineffective, or partially effective, drugs has on how HIV progresses. Using efavirenz, Jackson, Hunter et al. partially limited the spread of HIV between human cells grown in the laboratory. The experiments mirrored the situation where a partially resistant HIV strain spreads through the body. The results show that the success of cell-free infection is reduced as drug dose increases. Yet paradoxically, in cell-to-cell infection, the presence of drug caused more cells to become infected. This can be explained by the fact that, in cell-to-cell spread, each cell is exposed to multiple copies of the virus. The drug dose reduced the number of viral copies per cell without stopping the virus from infecting completely. The reduced number of viral copies per cell made it more likely that infected cells would survive the infection long enough to produce virus particles themselves. Viruses that can kill cells, such as HIV, must balance the need to make more of themselves against the speed that they kill their host cell to maximize the number of infected cells. If transmission between cells is too effective and too many virus particles are delivered to the new cell, the virus may not manage to infect new hosts before killing the old ones. These findings highlight this delicate balance. They also indicate a potential issue in using drugs to treat partially resistant virus strains. Without care, these treatments could increase the number of infected cells in the body, potentially worsening the effects of living with HIV.

Abstract One mechanism of variant formation may be evolution during long-term infection in immunosuppressed people. To understand the viral phenotypes evolved during such infection, we tested SARS-CoV-2 viruses evolved from an ancestral B.1 lineage infection lasting over 190 days post-diagnosis in an advanced HIV disease immunosuppressed individual. Sequence and phylogenetic analysis showed two evolving sub-lineages, with the second sub-lineage replacing the first sub-lineage in a seeming evolutionary sweep. Each sub-lineage independently evolved escape from neutralizing antibodies. The most evolved virus for the first sub-lineage (isolated day 34) and the second sub-lineage (isolated day 190) showed similar escape from ancestral SARS-CoV-2 and Delta-variant infection elicited neutralizing immunity despite having no spike mutations in common relative to the B.1 lineage. The day 190 isolate also evolved higher cell-cell fusion and faster viral replication and caused more cell death relative to virus isolated soon after diagnosis, though cell death was similar to day 34 first sub-lineage virus. These data show that SARS-CoV-2 strains in prolonged infection in a single individual can follow independent evolutionary trajectories which lead to neutralization escape and other changes in viral properties.

Background Severe Covid-19 leads to higher neutralizing antibody levels, a key correlate of protection. However, the host proteins associated with this response have not been fully characterized. We asked which proteins in the blood plasma associate with neutralization, anti-spike antibody levels, and disease severity in a South African cohort upon first SARS-CoV-2 exposure. Methods We used a longitudinal observational cohort design to collect blood at 6 days (acute infection) and 32 days (convalescence) post-diagnosis. We performed SomaScan proteomics on acute blood plasma and measured SARS-CoV-2 plasma neutralization capacity and anti-spike antibody levels in convalescent plasma. Disease severity was scored based on requirement for supplemental oxygen and was mild to moderate (no critically ill participants). Results We find differentially expressed proteins associating with neutralization, anti-spike antibody levels, and disease severity, with strong overlap between proteins associated with neutralization and spike binding, and moderate overlap between neutralization and disease severity. High neutralizers, regardless of requirement for supplemental oxygen, are found to have risk factors and markers for being more ill compared to low neutralizers. We can reasonably predict who becomes a high neutralizer based on individual proteins. The best predictor for neutralization is HSPA8, known to bind viral proteins and cross-present extracellular antigens. The strongest associated pathway is fatty acid metabolism, whose inhibition results in suppression of viral replication. Conclusions These results show that host proteins and pathways involved early in SARS-CoV-2 infection associate with neutralizing antibody levels elicited by the infection at convalescence. Plain Language Summary The immune response to SARS-CoV-2 infection leads to the production of antibodies that prevent the virus from infecting cells. This protects people from future infections with the same virus. People differ in their ability to make antibody responses after infection. The source of this variability, in terms of differences in expressed proteins, remains poorly understood. Here, we categorize South African study participants who were infected with SARS-CoV-2 for the first time into those with high and low antibody responses and link this with differences in specific proteins close to the time of infection. We find that proteins and pathways which play a role in SARS-CoV-2 infection also associate with stronger antibody responses. Khairallah et al., investigate the host proteins associated with a strong neutralizing antibody response to SARS-CoV-2. High neutralizing antibody responses to SARS-CoV-2 are associated with specific protein expression patterns, especially HSPA8 and pathways like fatty acid metabolism, which can predict immune strength and correlate with disease severity.