Despite measures to contain the spread of SARS-CoV-2 infection, the pandemic is persisting, with a devastating impact on healthcare systems and the world economy (Verma et al., 2021). The research community rapidly mobilized and developed vaccines and therapeutics at unprecedented speed (Polack et al., 2020; Ball, 2021). COVID-19 vaccines have prevented serious illness and death and have in some cases interrupted chains of transmission at community level (Kampf, 2021). However, the COVID-19 pandemic remains a major concern in Africa due to dismal vaccine coverage (WHO, 2021a) and the emergence of variants of concern that may be more transmissible, cause more severe illness, or have the potential to evade immunity from prior infection or vaccination (Shinde et al., 2021).

The interaction of HIV-1 infection, common in sub-Saharan Africa (H. The Lancet, 2020), with COVID-19 remains understudied. Initial small studies reported that people living with HIV (PLWH) had similar or better COVID-19 outcomes (Calza et al., 2020; Lee et al., 2021). Larger epidemiological studies have demonstrated increased hospitalization and higher rates of COVID-19-related deaths among PLWH compared with HIV-negative individuals (Davies, 2020a; Geretti et al., 2020; Bhaskaran et al., 2021; Vizcarra et al., 2020). Other studies have linked HIV-mediated CD4⁺ T cell depletion to suboptimal T cell and humoral immune responses to SARS-CoV-2 (Riou, 2021). A recent study showed prolonged shedding of high titer SARS-CoV-2 and emergence of multiple mutations in an individual with advanced HIV and antiretroviral treatment (ART) failure (Karim et al., 2021b).

Although B cells have repeatedly been shown to play a pivotal role in immune protection against SARS-CoV-2 infection and antibody responses and are typically used to evaluate immune responses to currently licensed COVID-19 vaccines (Sahin et al., 2020; Khoury et al., 2021), mounting evidence suggest that T cell responses are equally important. For instance, strong SARS-CoV-2-specific T cell responses are associated with milder disease (Riou, 2021; Sette and Crotty, 2021; Liao et al., 2020; Schub et al., 2020; Rydyznski Moderbacher et al., 2020). Moreover, T cell responses can confer protection even in the absence of humoral responses, given that patients with inherited B cell deficiencies or hematological malignancies are able to fully recover from SARS-CoV-2 infection (Bange et al., 2021). In some instances, COVID-19 disease severity has been attributed to poor SARS-CoV-2-specific CD4⁺ T cell polyfunctionality potential, reduced proliferation capacity, and enhanced HLA-DR expression (Riou, 2021). Importantly, a recent study identified nonsynonymous mutations in known MHC-1-restricted CD8⁺ T cell epitopes following deep sequencing of SARS-CoV-2 viral isolates from patients, demonstrating the capacity of SARS-CoV-2 to escape from CTL recognition (Agerer et al., 2021). Regarding vaccine-induced T cell responses, it was recently shown that mRNA vaccines can stimulate Th1 and Th2 CD4⁺ T cell responses that correlate with post-boost CD8⁺ T cell responses and neutralizing antibodies (Painter et al., 2021). The cited examples, herein, highlight the need to gain more insight into T cell-mediated protection against COVID-19 (Altmann and Boyton, 2020).

This study used a cohort of PLWH and HIV-seronegative individuals diagnosed with COVID-19 during the first wave dominated by the wild-type (wt) D614G virus (Tegally et al., 2021c), and the second wave dominated by the Beta variant. Peripheral blood mononuclear cells (PBMCs) were used to determine the impact of HIV infection on SARS-CoV-2-specific T cell responses and to assess T cell cross-recognition. Our data showed impaired SARS-CoV-2-specific T cell responses in individuals with unsuppressed HIV infection and highlighted poor cellular cross-recognition between variants, which was more pronounced than those with unsuppressed HIV. The muted responses in unsuppressed HIV infection may be attributable to low absolute CD4 count and immune activation. Importantly, we identified mutations in the Beta variant that could potentially reduce T cell recognition. Taken together, these data highlight the need to ensure uninterrupted access to ART for PLWH during the COVID-19 pandemic.

Study participants were drawn from a longitudinal observational cohort study that enrolled and tracked patients with a positive COVID-19 qPCR test presenting at three hospitals in the greater Durban area. Study participants were recruited into this study based on HIV status and sample availability. They include 25 participants recruited during the first wave (wt) of the pandemic in KwaZulu-Natal from June to December 2020 (Karim et al., 2021a). Twenty-three second wave (Beta variant) participants were recruited from January to June 2021. All study participants were unvaccinated because the COVID-19 vaccine was not readily available in South Africa at the time. Study participants were stratified into three groups, namely HIV-seronegative (HIV-neg), people living with HIV (PLWH) with viral load below 50 copies/ml, here termed (suppressed), and PLWH with detectable viral load of ≥1000 copies/ml (viremic). Study participants included HIV-seronegative (HIV-neg) (n=17). PLWHs (n=31) were subdivided into suppressed (n=17) and viremic (n=14). The male-to-female ratio and age distribution were comparable between PLWH and HIV-seronegative groups (Table 1). The median CD4 count for PLWH (suppressed 661 and viremic 301) (p=0.0002, Table 1). Study participants had predominantly mild COVID-19 disease that did not require supplemental oxygen or ventilation (Table 1).

Unsuppressed HIV infection is associated with altered SARS-CoV-2-specific CD4⁺ and CD8⁺ T cell responses

Immunity to SARS-CoV-2 typically induces robust T cell responses, but the impact of HIV infection on these responses has not been fully elucidated (Bange et al., 2021; Riou et al., 2021; Grifoni et al., 2020). Thus, we sought to determine the impact of HIV infection on SARS-CoV-2-specific CD4⁺ and CD8⁺ T cell responses. PBMCs were stimulated with PepTivater 15 mer megapools purchased from Miltenyi Biotec. The pools contained predicted CD4 and CD8 epitopes spanning the entire Spike coding sequence (aa5-1273). Intracellular cytokine staining of peptide-stimulated PBMCs was followed by flowcytometric analyses described in the Materials and methods section. The samples used for these analyses were collected between 2 and 4 weeks after COVID-19 PCR positive diagnosis. The time points were selected based on longitudinal T cell analysis that showed SARS-CoV-2-specific T cell responses peaked between 14 and 30 days after PCR positive diagnosis (data not shown), consistent with other studies (Keeton et al., 2021; Keeton et al., 2022). Representative flow plots for each group and aggregate data show viremic PLWH had significantly lower frequencies of SARS-CoV-2-specific IFN-γ/TNF-α-producing CD4⁺ T cells compared to suppressed PLWH (p=0.002) and HIV-seronegative individuals (p=0.0006) (Figure 1B). There was no significant difference in SARS-CoV-2-specific IFN-γ/TNF-α-producing CD8⁺ T cells among the groups (Figure 1B), and no significant differences in SARS-CoV-2-specific CD4⁺ or CD8⁺ T cell frequencies were observed between the suppressed PLWH and HIV-seronegative individuals (Figure 1B).

Figure 1

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Simultaneous production of cytokines, commonly referred to as polyfunctionality, which is regarded as a measure of the quality of the T cell response, has been shown to correlate with viral control (Betts et al., 2006). Thus, we evaluated the quality of the CD4⁺ and CD8⁺ T cell responses among the groups by enumerating cells producing three (IFN-γ, TNF-α, and IL-2) cytokines in various combinations. Consistent with dual IFN-γ, TNF-α cytokine secretion data (Figure 1B), the patterns of cytokine production of HIV-seronegative was mostly similar to HIV suppressed individuals (pie charts, Figure 1C and D). Analysis of single cytokine production revealed that HIV-seronegative individuals and suppressed PLWH predominantly produced IFN-γ responses (green sectors of the pie chart, Figure 1C and D), whereas viremic PLWH predominantly produced TNF-α responses for both CD4⁺ and CD8⁺ T cells (magenta sectors of the pie chart, Figure 1C and D). Cells co-producing all three cytokines were very rare regardless of HIV status (red sectors of the pie chart, Figure 1C and D). Nonetheless, HIV-seronegative had greater frequencies of dual cytokine secreting cells compared to viremic PLWH (p=0.0330 for CD4, Figure 1C; p=0.0330 for CD8, Figure 1D). Taken together, the data show that uncontrolled HIV infection lowers the magnitude and alters the quality of SARS-CoV-2 T cell responses. Importantly, complete plasma HIV suppression preserves the capacity to mount high magnitude, dual-functional SARS-CoV-2-specific T cell responses.

T cell responses against the major SARS-CoV-2 structural proteins

Having observed differences in magnitude and quality of SARS-CoV-2 spike-specific T responses, we next measured responses directed against major structural proteins, the nucleocapsid (N), the membrane (M), and Spike (S), again using PepTivater peptide pools from Miltenyi biotec. Our data show all three major SARS-CoV-2 proteins are targeted by SARS-CoV-2-specific CD4⁺ and CD8⁺ T cells (Figure 2A and B), with a preponderance for greater S-specific CD8⁺ T cell responses relative to M (Figure 2A). These data suggest that most SARS-CoV-2 structural proteins can be targeted by T cells, consistent with previous reports (Tarke et al., 2021).

Figure 2

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Uncontrolled HIV infection abrogates SARS-CoV-2 T cell cross-recognition between wild-type D614G and Beta variant

To evaluate the impact of uncontrolled HIV infection on cross-reactive T cell responses between wt and the Beta variant, we compared the breadth of responses and the ability to cross-recognize SARS-CoV-2 Beta variant peptides among the three study groups. These studies were conducted using two sets of 15 mer overlapping peptides (OLPs). Set 1 was comprised of 16 wt peptides, spanning the receptor-binding domain (RBD) and non-RBD regions of spike (S) that are known hotspots for mutations (Tegally et al., 2021c). Set 2 consisted of corresponding peptides that included all the major mutations that define the Beta variant lineage (Wibmer et al., 2021). A detailed description of the peptides is contained in Supplementary file 1.

We first sought to determine cross-reactivity of SARS-CoV-2-specific CD4⁺ and CD8⁺ T cells induced following infection with the wt (D614G, wave 1) and Beta variant (wave 2), between each other. We found that wave 1 donors had significantly lower CD8⁺ (p=0.0312) and CD4⁺ T cell responses (p=0.0078) to Beta variant relative to corresponding wt responses (Figure 3A). Wave 2 donors had no significant differences in T cells responses to Beta and wt (Figure 3B). Using a 12-day cultured stimulation assay, we were able to massively expand the magnitude of SARS-CoV-2-specific CD4⁺ and CD8⁺ T cells (Figure 3C) and (Figure 3—figure supplement 1), and this allowed us to hone in on single peptide responses (Table 1). Representative data for a wave 1 donor shows three CD8⁺ and two CD4⁺ wt responses (red circles), that did not cross-recognize corresponding Beta variants (blue bars) (Figure 3D). Contrariwise, a representative wave 2 donor had one CD8⁺ and one CD4⁺T cell response to the Beta variant that did not cross-react to the wt version of the peptide (Figure 3E). Intra-donor comparison revealed significantly more CD8⁺ (p=0.0156) and CD4⁺ T cell responses (p=0.0312) to wt peptides compared to the corresponding Beta variant peptides in wave 1 donors (Figure 3F). Conversely, unlike the ex vivo data (Figure 3B), wave 2 donors had significantly more CD8⁺ T cell responses to Beta variant peptides relative to wt peptides (p=0.0312), and a trend toward increased CD4⁺ T cells against Beta peptides (p=0.0625), highlighting the increased sensitivity of expanded cells (Figure 3G). Taken together, these data show poor cross-recognition of wt and Beta variant epitopes.

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We then assessed the impact of HIV infection on cross-recognition of wt and Beta variant epitopes. Representative data for an HIV-seronegative individual from the first wave had six wt and five Beta variant CD8⁺ T cell responses, one was cross-recognized (circled) (Figure 4A). The same individual had five wt and five Beta variant CD4⁺ T responses, one was cross-recognized (Figure 4B). Similarly, a representative suppressed wave 1 donor had five wt and two Beta variant CD8⁺ T cell responses, one of which was cross-recognized (Figure 4C). This same donor had six wt and zero Beta variant CD4⁺ T cell responses (Figure 4D). A representative viremic individual had four weak wt CD8⁺ T cell responses and three borderline CD4 responses, none of which were cross-recognized (Figure 4E and F). Summary data showed viremic PLWH had significantly narrow breadth of SARS-CoV-2-specific CD8⁺ (p=0.039) and CD4⁺ T cell responses (p=0.033) compared to suppressed PLWH and HIV-seronegative individuals (Figure 4G and H). Collectively, these data show that SARS-CoV-2-specific T cell responses in viremic PLWH have limited breadth and subsequently poor cross-recognition potential.

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Identification of mutations in the Beta variant that are associated with reduced cross-recognition

Having shown poor T cell cross-recognition of SARS-CoV-2 epitopes between wt and Beta variant, we next sought to identify mutations that might be responsible for the loss of recognition. We combined all the T cell data for the 12 (4 HIV-negatives, 4 HIV-suppressed, and 4 HIV-viremics) donors used for cultured epitope screening studies. All the samples were culturally expanded using wt peptides from the first wave. This analysis identified four Beta variant peptides (listed in Supplementary file 1) that had significant reduction in CD8⁺ T cell recognition relative to wt peptides (Figure 5A). Three of these peptides were also poorly recognized by CD4⁺ T cells (Figure 5B). The amino acid sequences for wt and corresponding mutations include the E484K mutation, a key Beta variant spike residual change also associated with loss antibody binding (Wibmer et al., 2021). Taken together, these data identified mutations in the Beta variant that may abrogate T cell recognition, suggesting that they may be potential T cell escape mutations and warrant further investigation.

Figure 5

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Immunodominance hierarchy of SARS-CoV-2 CD8⁺ and CD4⁺ T cell responses targeting the spike protein

Virus-specific CD8⁺ and CD4⁺ T cells typically target viral epitopes in a distinct hierarchical order (Streeck et al., 2009; Laher et al., 2017). Identifying SARS-CoV-2 epitopes that are most frequently targeted by T cells is important for the design of vaccines that can induce protective T cell responses. To determine the immunodominance hierarchy of SAR-CoV-2 specific T cell responses targeting the spike protein, OLPs were ranked based on magnitude and frequency of recognition. This analysis revealed the most immunodominant wt peptides targeted by CD8⁺ T cell responses (Figure 6A). The Beta variant resulted in dramatic shift in the immunodominance hierarchy whereby, three of five most dominant wt CD8⁺ T cell responses (Figure 6A), their Beta variant versions were subdominant (downward arrows) (Figure 6B). Contrariwise, three subdominant wt responses were among the most dominant Beta variant responses (upward arrows) (Figure 6B). A similar trend was observed for CD4⁺ T cell responses (Figure 6C and D). These data demonstrated a shift in the immunodominant hierarchy between wt and Beta variant responses, which partly explains poor T cell cross-recognition between successive SARS-CoV-2 variants.

Figure 6

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The impact of HIV markers of diseases progression on SARS-CoV-2-specific T cell responses

To gain more insight into why viremic PLWH responded poorly to SARS-CoV-2 infection, we investigated if T cell activation defined here as co-expression of CD38 and HLA-DR, absolute CD4 count and plasma viral load, impacted immune responses (Du et al., 2009). The proportion of activated (CD38/HLA-DR) CD4⁺ T cells was higher in viremic PLWH compared to suppressed (p=0.02) and HIV-seronegative individuals (p=0.002; Figure 7A). Moreover, proportion of activated (CD38/HLA-DR) CD4⁺ T cells among viremic PLWH negatively correlated with absolute CD4 counts (r=–0.7, p=0.04; Figure 7B), and positively correlated with HIV plasma viral loads (r=0.9, p=0.0004; Figure 7C). Similarly, proportion of activated (CD38/HLA-DR) CD8⁺ T cells were significantly higher in viremic PLWH relative to suppressed PLWH (p=0.04) and HIV-seronegative individuals (p=0.0008; Figure 7D). The negative relationship between proportion of activated (CD38/HLA-DR) CD8⁺ T cells and CD4 counts did not reach statistical significance (Figure 7E), but proportion of activated (CD38/HLA-DR) CD8⁺ T cells were positively correlated with HIV plasma viral loads among viremic PLWH (r=0.8, p=0.0006; Figure 7F).

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Taken together, these data suggest that hyper immune activation driven by uncontrolled HIV infection impacts CD4⁺ and CD8⁺ T cell responses.

Finally, we interrogated the relationship between SARS-CoV-2-specific responses and disease severity, stratified into asymptomatic, mild, and severe diseases requiring oxygen supplementation, as previously defined (Karim et al., 2021a). We found no significant differences between the magnitude of CD4⁺ or CD8⁺ T cell responses and disease severity among the groups (Figure 7—figure supplement 1A,B). We next, examined sex differences and found no difference in CD4⁺ and CD8⁺T cell responses to SARS-CoV-2 infection (Figure 7—figure supplement 1C,D). Age is a risk factor for severe COVID-19 (WHO, 2021a); thus, we examined the relationship between age and T cell responses. There was a negative relationship between age and magnitude of CD8⁺ T cell responses (CD8 r=−0.6, p=0.002) (Figure 7—figure supplement 1E), and a similar trend for CD4⁺ T cell responses (CD4 r=−0.3, P=0.15) (Figure 7—figure supplement 1F). These data show that younger people had greater responses compared to older people, whereas disease severity and sex did not have discernible effect on SARS-CoV-2 T cell responses.

The greater burden of HIV in sub-Saharan Africa makes investigating the impact of HIV infection on COVID-19 immunity and disease outcomes critical for bringing the epidemic under control in the region. Recent studies have documented strong cellular responses following SARS-CoV-2 infection and vaccination, but the effects of HIV on SARS-CoV-2-specific T cell responses are not well characterized. Here, we investigated the antigen-specific CD4⁺ and CD8⁺ T cell responses in a cohort of SARS-CoV-2- infected individuals with and without HIV infection. Our results show that unsuppressed HIV infection is associated with reduced cellular responses to SARS-CoV-2 infection. We also show that low absolute CD4 count and hyper immune activation are associated with diminution of SARS-CoV-2-specific T cell responses. Importantly, we identify spike mutations in the Beta variant that abrogate recognition by memory T cells raised against wt epitopes. Similarly, immune responses targeting Beta variant epitopes poorly cross-recognize corresponding wt epitopes. These data reveal the potential for emerging SARS-CoV-2 variants to escape T cell recognition. Importantly, our data highlight the potential for unsuppressed HIV infection to attenuate vaccine-induced T cell immunity.

HIV-induced immune dysregulation is well documented (Klatt et al., 2013). Unsuppressed HIV infection is associated with profound dysfunction of virus-specific T cell immunity partly caused by immune activation (Klatt et al., 2013; Ndhlovu et al., 2015). Recent studies have reported strong association between unsuppressed HIV infection and poor COVID disease outcomes, for instance, a large cross-section study found a link between severe HIV disease and poor COVID-19 outcomes including COVID-19-associated death (Chanda et al., 2020). This study showed that individuals with unsuppressed HIV infection mount weak responses to SARS-CoV-2 infection and poorly recognize SARS-CoV-2 Beta variant mutations. We also examined several mechanisms by which unsuppressed HIV can impact SARS-CoV-2-specific T cell responses and found that HIV-induced immune defects such as low CD4⁺ T cell counts, higher HIV plasma viral loads, and elevated immune activation were invariably associated with diminished SARS-CoV-2 responses. These findings are consistent with several recent reports, such as a case of one HIV-positive patient with low CD4 count that had prolonged CIVID-19 disease (Wang et al., 2020). The ability of unsuppressed HIV to cause severe immune activation was also recently documented by others (d’Ettorre et al., 2020; Sharov, 2021). Taken together, these data suggest that HIV-induced immune dysregulation negatively impacts the potential to mount robust T cell responses to SARS-CoV-2 infection.

Furthermore, although ART-mediated HIV suppression rarely results in complete immune reconstitution (Henrich et al., 2017), sustained complete plasma HIV suppression was associated with robust SARS-CoV-2 responses that were mostly similar in magnitude and quality to responses mounted by HIV-seronegative individuals. Given reduced levels of CD38 and HLA-DR dual positive cells and near normal absolute CD4 counts in suppressed individuals, it is reasonable to speculate that reduced immune activation and superior CD4⁺ T helper function were partly responsible for improved immune responses in suppressed individuals.

The emergence of several SARS-CoV-2 variants with mutations in the viral Spike (S) protein such as mutations in the RBD, N-terminal domain (NTD), and furin cleavage site region (Tarke, 2021) continue to fuel the epidemic. These mutations have been shown to directly affect ACE2 receptor binding affinity, infectivity, viral load, and transmissibility (Tarke, 2021; Greaney et al., 2021; Starr et al., 2021). The variants of concern identified since the start of the COVID-19 pandemic include the Alpha (Davies, 2020b), Beta (Tegally et al., 2021b), Gamma (Voloch et al., 2020), and Delta (Mallapaty, 2021), and now the Omicron variant. Most of these have been shown to attenuate neutralization but the impact of these mutations on T cell responses has not been extensively explored (Riou et al., 2022). However, a recent report demonstrating the potential for SARS-CoV-2 to evade cytolytic T lymphocyte (CTL) surveillance, highlight the need for more investigations regarding the potential CTL-driven immune pressure to shape emerging variants (Agerer et al., 2021). To this end, our study provides new evidence that SARS-CoV-2 has the potential to evade T cell recognition. Moreover, our data suggest that spike mutations in the Beta variant that were associated with antibody escape may also escape T cell recognition.

Southern Africa has had at least four epidemic waves of COVID-19. The first was a mixture of SARS-CoV-2 lineages (with D614G), the second wave was driven by the Beta variant (Tegally et al., 2021a), and the third by the Delta variant (Callaway, 2021). The fourth wave dominated by the highly mutated Omicron variant (WHO, 2021b; Viana et al., 2021). Intriguingly, there was some evidence that PLWH in South Africa had increased disease severity in the second wave compared to the first wave (Karim et al., 2021a). The precise mechanisms responsible for increased severity are not fully understood, but low CD4⁺ T cell counts and high neutrophil-to-lymphocyte ratio (NLR) showed strong association with disease severity (Karim et al., 2021a). Our data suggest that diminished T cell responses to the Beta variant even in previously exposed individuals may have contributed to severe disease in the second wave.

Here, we report poor cross-recognition of the Beta variant by individuals infected with wt and vice versa, which was exacerbated by unsuppressed HIV infection. However, others have reported better cross-recognition between variants and vaccines. Possible explanation for the apparent discrepancy include, (1) unlike other studies that compared responses to the entire spike protein using peptide pools to stimulate cells (Keeton et al., 2022; Gao et al., 2022), our cross-recognition studies focused on head-to-head comparisons of single wt peptides with corresponding variants peptides containing a lineage defining mutation (Keeton et al., 2022). We may have picked up fewer cross-reactive responses because we used dual section of IFN-γ and TNF-α as a readout for antigen-specific responses, which is more stringent than single cytokine producing cells. (3) We used cultured expansions prior to ICS assays which amplifies the response several folds above background and therefore more specific. In fact, our ex vivo cross-recognition data are comparable to other studies which also showed diminution of responses across variants (Keeton et al., 2022). Future studies should apply our cultured expansion and the dual cytokine secretion readout to assess cross-recognition among other variants and different vaccine regimens.

Although, we repeatedly showed robust in vitro T cell expansion following ex vivo peptide stimulation but limited expansion against mutant versions of the peptides, there is need to identify optimal peptides that were targeted by CD8⁺ and CD4⁺ T cells in the context of restricting MHC class I and II alleles. SARS-CoV-2 responses are generally very broad (Grifoni et al., 2020); thus, it is not clear from these studies how the loss of T cell cross-recognition in Spike affects the overall protective immunity. Furthermore, investigating if the observed poor T cell cross-recognition between wave 1 and wave 2 is generalizable to the Delta and the Omicron variants is clearly warranted. Importantly, our data raise the question of whether CTL selection pressure plays a significant role in shaping emerging variants. This concept should be investigated using larger longitudinal studies with longer durations of follow-up.

Previous work in this cohort examined the relationship T cell and B cell responses and found a positive association between CD8⁺ T cells frequency and several CD19 B cell subsets, which was attenuated in PLWH (Karim et al., 2021a), suggesting that both arms of the immune system are impacted by HIV/SARS-CoV-2 coinfection. However, the current study did not examine this relationship at antigen-specific level due to sample limitations. Future work is required to understand the relationship between T cell and humoral immunity and the impact of unsuppressed HIV infection on long-term protection.

In conclusion, we show that uncontrolled HIV infection is associated with low magnitude, reduced polyfunctionality, and diminished cross-recognition of SARS-CoV-2-specific CD4⁺ and CD8⁺ T cell responses. Importantly, fully suppressed PLWH had comparable SARS-CoV-2-specific T cell responses with HIV-seronegative individuals. These findings may partly explain high propensity for severe COVID-19 among PLWH and also highlight their vulnerability to emerging SARS-CoV-2 variants of concern, especially those with uncontrolled HIV infection. Hence, there is need to ensure uninterrupted access to ART for PLWH during the COVID-19 pandemic.

All source data files for the figures are now publicly available on our institutional website (Africa Health Research Institute database). The data can be accessed using this link: https://doi.org/10.23664/AHRI.SARS.CoV.2.

1. 1. Nkosi K
   2. Charasa C
   3. Papadopoulos AO
   4. Nguni TZ
   5. Karim F
   6. Moosa MYS
   7. Gazy I
   8. Jambo K
   9. Hanekom W
   10. Sigal A
   11. Ndhlovu ZM

   (2022) AHRI Data Repository

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

   https://doi.org/10.23664/AHRI.SARS.CoV.2

1. 1. Agerer B
   2. Koblischke M
   3. Gudipati V
   4. Montaño-Gutierrez LF
   5. Smyth M
   6. Popa A
   7. Genger JW
   8. Endler L
   9. Florian DM
   10. Mühlgrabner V
   11. Graninger M
   12. Aberle SW
   13. Husa AM
   14. Shaw LE
   15. Lercher A
   16. Gattinger P
   17. Torralba-Gombau R
   18. Trapin D
   19. Penz T
   20. Barreca D
   21. Fae I
   22. Wenda S
   23. Traugott M
   24. Walder G
   25. Pickl WF
   26. Thiel V
   27. Allerberger F
   28. Stockinger H
   29. Puchhammer-Stöckl E
   30. Weninger W
   31. Fischer G
   32. Hoepler W
   33. Pawelka E
   34. Zoufaly A
   35. Valenta R
   36. Bock C
   37. Paster W
   38. Geyeregger R
   39. Farlik M
   40. Halbritter F
   41. Huppa JB
   42. Aberle JH
   43. Bergthaler A

   (2021) SARS-CoV-2 mutations in MHC-I-restricted epitopes evade CD8⁺ T cell responses

   Science Immunology 6:eabg6461.

   https://doi.org/10.1126/sciimmunol.abg6461

   • PubMed
   • Google Scholar
2. 1. Altmann DM
   2. Boyton RJ

   (2020) SARS-CoV-2 T cell immunity: Specificity, function, durability, and role in protection

   Science Immunology 5:eabd6160.

   https://doi.org/10.1126/sciimmunol.abd6160

   • PubMed
   • Google Scholar
3. 1. Ball P

   (2021) The lightning-fast quest for COVID vaccines - and what it means for other diseases

   Nature 589:16–18.

   https://doi.org/10.1038/d41586-020-03626-1

   • PubMed
   • Google Scholar
4. 1. Bange EM
   2. Han NA
   3. Wileyto P
   4. Kim JY
   5. Gouma S
   6. Robinson J
   7. Greenplate AR
   8. Hwee MA
   9. Porterfield F
   10. Owoyemi O
   11. Naik K
   12. Zheng C
   13. Galantino M
   14. Weisman AR
   15. Ittner CAG
   16. Kugler EM
   17. Baxter AE
   18. Oniyide O
   19. Agyekum RS
   20. Dunn TG
   21. Jones TK
   22. Giannini HM
   23. Weirick ME
   24. McAllister CM
   25. Babady NE
   26. Kumar A
   27. Widman AJ
   28. DeWolf S
   29. Boutemine SR
   30. Roberts C
   31. Budzik KR
   32. Tollett S
   33. Wright C
   34. Perloff T
   35. Sun L
   36. Mathew D
   37. Giles JR
   38. Oldridge DA
   39. Wu JE
   40. Alanio C
   41. Adamski S
   42. Garfall AL
   43. Vella LA
   44. Kerr SJ
   45. Cohen JV
   46. Oyer RA
   47. Massa R
   48. Maillard IP
   49. Maxwell KN
   50. Reilly JP
   51. Maslak PG
   52. Vonderheide RH
   53. Wolchok JD
   54. Hensley SE
   55. Wherry EJ
   56. Meyer NJ
   57. DeMichele AM
   58. Vardhana SA
   59. Mamtani R
   60. Huang AC

   (2021) CD8⁺ T cells contribute to survival in patients with COVID-19 and hematologic cancer

   Nature Medicine 27:1280–1289.

   https://doi.org/10.1038/s41591-021-01386-7

   • PubMed
   • Google Scholar
5. 1. Betts MR
   2. Nason MC
   3. West SM
   4. De Rosa SC
   5. Migueles SA
   6. Abraham J
   7. Lederman MM
   8. Benito JM
   9. Goepfert PA
   10. Connors M
   11. Roederer M
   12. Koup RA

   (2006) HIV nonprogressors preferentially maintain highly functional HIV-specific CD8+ T cells

   Blood 107:4781–4789.

   https://doi.org/10.1182/blood-2005-12-4818

   • PubMed
   • Google Scholar
6. 1. Bhaskaran K
   2. Rentsch CT
   3. MacKenna B
   4. Schultze A
   5. Mehrkar A
   6. Bates CJ
   7. Eggo RM
   8. Morton CE
   9. Bacon SCJ
   10. Inglesby P
   11. Douglas IJ
   12. Walker AJ
   13. McDonald HI
   14. Cockburn J
   15. Williamson EJ
   16. Evans D
   17. Forbes HJ
   18. Curtis HJ
   19. Hulme WJ
   20. Parry J
   21. Hester F
   22. Harper S
   23. Evans SJW
   24. Smeeth L
   25. Goldacre B

   (2021) HIV infection and COVID-19 death: a population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform

   The Lancet. HIV 8:e24–e32.

   https://doi.org/10.1016/S2352-3018(20)30305-2

   • PubMed
   • Google Scholar
7. 1. Callaway E

   (2021) Delta coronavirus variant: scientists brace for impact

   Nature 595:17–18.

   https://doi.org/10.1038/d41586-021-01696-3

   • PubMed
   • Google Scholar
8. 1. Calza L
   2. Bon I
   3. Borderi M
   4. Colangeli V
   5. Viale P

   (2020) No Significant Effect of COVID-19 on immunological and virological parameters in pImmunological and Virological Parameters in Patients With HIV-1 Infection

   Journal of Acquired Immune Deficiency Syndromes 85:e6–e8.

   https://doi.org/10.1097/QAI.0000000000002427

   • PubMed
   • Google Scholar
9. 1. Chanda D
   2. Minchella PA
   3. Kampamba D
   4. Itoh M
   5. Hines JZ
   6. Fwoloshi S
   7. Boyd MA
   8. Hamusonde K
   9. Chirwa L
   10. Nikoi K
   11. Chirwa R
   12. Siwingwa M
   13. Sivile S
   14. Zyambo KD
   15. Mweemba A
   16. Mbewe N
   17. Mutengo KH
   18. Malama K
   19. Agolory S
   20. Mulenga LB

   (2020) Covid-19 severity and covid-19–associated deaths among hospitalized patients with hiv infection — zambia, march–december 2020

   MMWR. Morbidity and Mortality Weekly Report 70:807–810.

   https://doi.org/10.15585/mmwr.mm7022a2

   • PubMed
   • Google Scholar
10. Preprint

    1. Davies MA

    (2020a) HIV and Risk of COVID-19 Death: A Population Cohort Study from the Western Cape Province, South Africa

    medRxiv.

    https://doi.org/10.1101/2020.07.02.20145185

    • Google Scholar
11. Preprint

    1. Davies NG

    (2020b) Estimated Transmissibility and Severity of Novel SARS-CoV-2 Variant of Concern 202012/01 in England

    medRxiv.

    https://doi.org/10.1101/2020.12.24.20248822

    • Google Scholar
12. 1. Du J
    2. Wei L
    3. Li G
    4. Hua M
    5. Sun Y
    6. Wang D
    7. Han K
    8. Yan Y
    9. Song C
    10. Song R
    11. Zhang H
    12. Han J
    13. Liu J
    14. Kong Y

    (2009) Persistent high percentage of HLA-DR+CD38high CD8+ T Cells associated with immune disorder and disease severity of COVID-19

    Frontiers in Immunology 12:735125.

    https://doi.org/10.3389/fimmu.2021.735125

    • PubMed
    • Google Scholar
13. 1. d’Ettorre G
    2. Recchia G
    3. Ridolfi M
    4. Siccardi G
    5. Pinacchio C
    6. Innocenti GP
    7. Santinelli L
    8. Frasca F
    9. Bitossi C
    10. Ceccarelli G
    11. Borrazzo C
    12. Antonelli G
    13. Scagnolari C
    14. Mastroianni CM

    (2020) Analysis of type I IFN response and T cell activation in severe COVID-19/HIV-1 coinfection

    Medicine 99:e21803.

    https://doi.org/10.1097/MD.0000000000021803

    • PubMed
    • Google Scholar
14. 1. Gao Y
    2. Cai C
    3. Grifoni A
    4. Müller TR
    5. Niessl J
    6. Olofsson A
    7. Humbert M
    8. Hansson L
    9. Österborg A
    10. Bergman P
    11. Chen P
    12. Olsson A
    13. Sandberg JK
    14. Weiskopf D
    15. Price DA
    16. Ljunggren H-G
    17. Karlsson AC
    18. Sette A
    19. Aleman S
    20. Buggert M

    (2022) Ancestral SARS-CoV-2-specific T cells cross-recognize the Omicron variant

    Nature Medicine 28:472–476.

    https://doi.org/10.1038/s41591-022-01700-x

    • PubMed
    • Google Scholar
15. 1. Geretti AM
    2. Stockdale AJ
    3. Kelly SH
    4. Cevik M
    5. Collins S
    6. Waters L
    7. Villa G
    8. Docherty A
    9. Harrison EM
    10. Turtle L
    11. Openshaw P
    12. Baillie JK
    13. Sabin C
    14. Semple M
    15. Group CS

    (2020) Outcomes of COVID-19 related hospitalisation among people with HIV in the ISARIC WHO clinical characterisation protocol UK protocol: Prospective observational study

    SSRN Electronic Journal 1:3666248.

    https://doi.org/10.2139/ssrn.3666248

    • Google Scholar
16. 1. Greaney AJ
    2. Loes AN
    3. Crawford KHD
    4. Starr TN
    5. Malone KD
    6. Chu HY
    7. Bloom JD

    (2021) Comprehensive mapping of mutations in the SARS-CoV-2 receptor-binding domain that affect recognition by polyclonal human plasma antibodies

    Cell Host & Microbe 29:463–476.

    https://doi.org/10.1016/j.chom.2021.02.003

    • PubMed
    • Google Scholar
17. 1. Grifoni A
    2. Weiskopf D
    3. Ramirez SI
    4. Mateus J
    5. Dan JM
    6. Moderbacher CR
    7. Rawlings SA
    8. Sutherland A
    9. Premkumar L
    10. Jadi RS
    11. Marrama D
    12. de Silva AM
    13. Frazier A
    14. Carlin AF
    15. Greenbaum JA
    16. Peters B
    17. Krammer F
    18. Smith DM
    19. Crotty S
    20. Sette A

    (2020) Targets of t cell responses to sars-cov-2 coronavirus in humans with covid-19 disease and unexposed individuals

    Cell 181:1489–1501.

    https://doi.org/10.1016/j.cell.2020.05.015

    • PubMed
    • Google Scholar
18. 1. H. The Lancet

    (2020) When pandemics collide

    The Lancet. HIV 7:e301.

    https://doi.org/10.1016/S2352-3018(20)30113-2

    • PubMed
    • Google Scholar
19. 1. Henrich TJ
    2. Hatano H
    3. Bacon O
    4. Hogan LE
    5. Rutishauser R
    6. Hill A
    7. Kearney MF
    8. Anderson EM
    9. Buchbinder SP
    10. Cohen SE
    11. Abdel-Mohsen M
    12. Pohlmeyer CW
    13. Fromentin R
    14. Hoh R
    15. Liu AY
    16. McCune JM
    17. Spindler J
    18. Metcalf-Pate K
    19. Hobbs KS
    20. Thanh C
    21. Gibson EA
    22. Kuritzkes DR
    23. Siliciano RF
    24. Price RW
    25. Richman DD
    26. Chomont N
    27. Siliciano JD
    28. Mellors JW
    29. Yukl SA
    30. Blankson JN
    31. Liegler T
    32. Deeks SG

    (2017) HIV-1 persistence following extremely early initiation of antiretroviral therapy (ART) during acute HIV-1 infection: An observational study

    PLOS Medicine 14:e1002417.

    https://doi.org/10.1371/journal.pmed.1002417

    • PubMed
    • Google Scholar
20. 1. Kampf G

    (2021) The epidemiological relevance of the COVID-19-vaccinated population is increasing

    The Lancet Regional Health. Europe 11:100272.

    https://doi.org/10.1016/j.lanepe.2021.100272

    • PubMed
    • Google Scholar
21. 1. Karim F
    2. Gazy I
    3. Cele S
    4. Zungu Y
    5. Krause R
    6. Bernstein M
    7. Khan K
    8. Ganga Y
    9. Rodel H
    10. Mthabela N
    11. Mazibuko M
    12. Muema D
    13. Ramjit D
    14. Ndung’u T
    15. Hanekom W
    16. Gosnell B
    17. Lessells RJ
    18. Wong EB
    19. de Oliveira T
    20. Moosa MYS
    21. Lustig G
    22. Leslie A
    23. Kløverpris H
    24. Sigal A
    25. COMMIT-KZN Team

    (2021a) HIV status alters disease severity and immune cell responses in Beta variant SARS-CoV-2 infection wave

    eLife 10:e67397.

    https://doi.org/10.7554/eLife.67397

    • PubMed
    • Google Scholar
22. Preprint

    1. Karim F
    2. Moosa M
    3. Gosnell B
    4. Cele S
    5. Giandhari J
    6. Pillay S
    7. Tegally H
    8. Wilkinson E
    9. San J
    10. Msomi N
    11. Mlisana K
    12. Khan K
    13. Bernstein M
    14. Manickchund N
    15. Singh L
    16. Ramphal U
    17. Hanekom W
    18. Lessells R
    19. Sigal A
    20. de Oliveira T
    21. COMMIT-KZN Team

    (2021b) Persistent SARS-CoV-2 Infection and Intra-Host Evolution in Association with Advanced HIV Infection

    medRxiv.

    https://doi.org/10.1101/2021.06.03.21258228

    • Google Scholar
23. 1. Keeton R
    2. Richardson SI
    3. Moyo-Gwete T
    4. Hermanus T
    5. Tincho MB
    6. Benede N
    7. Manamela NP
    8. Baguma R
    9. Makhado Z
    10. Ngomti A
    11. Motlou T
    12. Mennen M
    13. Chinhoyi L
    14. Skelem S
    15. Maboreke H
    16. Doolabh D
    17. Iranzadeh A
    18. Otter AD
    19. Brooks T
    20. Noursadeghi M
    21. Moon JC
    22. Grifoni A
    23. Weiskopf D
    24. Sette A
    25. Blackburn J
    26. Hsiao N-Y
    27. Williamson C
    28. Riou C
    29. Goga A
    30. Garrett N
    31. Bekker L-G
    32. Gray G
    33. Ntusi NAB
    34. Moore PL
    35. Burgers WA

    (2021) Prior infection with SARS-CoV-2 boosts and broadens Ad26.COV2.S immunogenicity in a variant-dependent manner

    Cell Host & Microbe 29:1611–1619.

    https://doi.org/10.1016/j.chom.2021.10.003

    • PubMed
    • Google Scholar
24. 1. Keeton R
    2. Tincho MB
    3. Ngomti A
    4. Baguma R
    5. Benede N
    6. Suzuki A
    7. Khan K
    8. Cele S
    9. Bernstein M
    10. Karim F
    11. Madzorera SV
    12. Moyo-Gwete T
    13. Mennen M
    14. Skelem S
    15. Adriaanse M
    16. Mutithu D
    17. Aremu O
    18. Stek C
    19. du Bruyn E
    20. Van Der Mescht MA
    21. de Beer Z
    22. de Villiers TR
    23. Bodenstein A
    24. van den Berg G
    25. Mendes A
    26. Strydom A
    27. Venter M
    28. Giandhari J
    29. Naidoo Y
    30. Pillay S
    31. Tegally H
    32. Grifoni A
    33. Weiskopf D
    34. Sette A
    35. Wilkinson RJ
    36. de Oliveira T
    37. Bekker L-G
    38. Gray G
    39. Ueckermann V
    40. Rossouw T
    41. Boswell MT
    42. Bhiman JN
    43. Moore PL
    44. Sigal A
    45. Ntusi NAB
    46. Burgers WA
    47. Riou C

    (2022) T cell responses to SARS-CoV-2 spike cross-recognize Omicron

    Nature 603:488–492.

    https://doi.org/10.1038/s41586-022-04460-3

    • PubMed
    • Google Scholar
25. 1. Khoury DS
    2. Cromer D
    3. Reynaldi A
    4. Schlub TE
    5. Wheatley AK
    6. Juno JA
    7. Subbarao K
    8. Kent SJ
    9. Triccas JA
    10. Davenport MP

    (2021) Neutralizing antibody levels are highly predictive of immune protection from symptomatic SARS-CoV-2 infection

    Nature Medicine 27:1205–1211.

    https://doi.org/10.1038/s41591-021-01377-8

    • PubMed
    • Google Scholar
26. 1. Klatt NR
    2. Chomont N
    3. Douek DC
    4. Deeks SG

    (2013) Immune activation and HIV persistence: implications for curative approaches to HIV infection

    Immunological Reviews 254:326–342.

    https://doi.org/10.1111/imr.12065

    • PubMed
    • Google Scholar
27. 1. Laher F
    2. Ranasinghe S
    3. Porichis F
    4. Mewalal N
    5. Pretorius K
    6. Ismail N
    7. Buus S
    8. Stryhn A
    9. Carrington M
    10. Walker BD
    11. Ndung’u T
    12. Ndhlovu ZM

    (2017) HIV controllers exhibit enhanced frequencies of major histocompatibility complex class II Tetramer⁺ gag-specific CD4⁺ T cells in chronic clade C HIV-1 Infection

    Journal of Virology 91:e02477-16.

    https://doi.org/10.1128/JVI.02477-16

    • PubMed
    • Google Scholar
28. 1. Lee KW
    2. Yap SF
    3. Ngeow YF
    4. Lye MS

    (2021) COVID-19 in people living with HIV: A systematic review and meta-analysis

    International Journal of Environmental Research and Public Health 18:3554.

    https://doi.org/10.3390/ijerph18073554

    • PubMed
    • Google Scholar
29. 1. Liao M
    2. Liu Y
    3. Yuan J
    4. Wen Y
    5. Xu G
    6. Zhao J
    7. Cheng L
    8. Li J
    9. Wang X
    10. Wang F
    11. Liu L
    12. Amit I
    13. Zhang S
    14. Zhang Z

    (2020) Single-cell landscape of bronchoalveolar immune cells in patients with COVID-19

    Nature Medicine 26:842–844.

    https://doi.org/10.1038/s41591-020-0901-9

    • PubMed
    • Google Scholar
30. 1. Mallapaty S

    (2021) India’s massive COVID surge puzzles scientists

    Nature 592:667–668.

    https://doi.org/10.1038/d41586-021-01059-y

    • PubMed
    • Google Scholar
31. 1. Ndhlovu ZM
    2. Kamya P
    3. Mewalal N
    4. Kløverpris HN
    5. Nkosi T
    6. Pretorius K
    7. Laher F
    8. Ogunshola F
    9. Chopera D
    10. Shekhar K
    11. Ghebremichael M
    12. Ismail N
    13. Moodley A
    14. Malik A
    15. Leslie A
    16. Goulder PJR
    17. Buus S
    18. Chakraborty A
    19. Dong K
    20. Ndung’u T
    21. Walker BD

    (2015) Magnitude and kinetics of CD8+ T Cell activation during hyperacute HIV infection impact viral set point

    Immunity 43:591–604.

    https://doi.org/10.1016/j.immuni.2015.08.012

    • PubMed
    • Google Scholar
32. 1. Painter MM
    2. Mathew D
    3. Goel RR
    4. Apostolidis SA
    5. Pattekar A
    6. Kuthuru O
    7. Baxter AE
    8. Herati RS
    9. Oldridge DA
    10. Gouma S
    11. Hicks P
    12. Dysinger S
    13. Lundgreen KA
    14. Kuri-Cervantes L
    15. Adamski S
    16. Hicks A
    17. Korte S
    18. Giles JR
    19. Weirick ME
    20. McAllister CM
    21. Dougherty J
    22. Long S
    23. D’Andrea K
    24. Hamilton JT
    25. Betts MR
    26. Bates P
    27. Hensley SE
    28. Grifoni A
    29. Weiskopf D
    30. Sette A
    31. Greenplate AR
    32. Wherry EJ

    (2021) Rapid induction of antigen-specific CD4⁺ T cells is associated with coordinated humoral and cellular immunity to SARS-CoV-2 mRNA vaccination

    Immunity 54:2133–2142.

    https://doi.org/10.1016/j.immuni.2021.08.001

    • PubMed
    • Google Scholar
33. 1. Polack FP
    2. Thomas SJ
    3. Kitchin N
    4. Absalon J
    5. Gurtman A
    6. Lockhart S
    7. Perez JL
    8. Pérez Marc G
    9. Moreira ED
    10. Zerbini C
    11. Bailey R
    12. Swanson KA
    13. Roychoudhury S
    14. Koury K
    15. Li P
    16. Kalina WV
    17. Cooper D
    18. Frenck RW Jr
    19. Hammitt LL
    20. Türeci Ö
    21. Nell H
    22. Schaefer A
    23. Ünal S
    24. Tresnan DB
    25. Mather S
    26. Dormitzer PR
    27. Şahin U
    28. Jansen KU
    29. Gruber WC
    30. C4591001 Clinical Trial Group

    (2020) Safety and efficacy of the bnt162b2 mrna covid-19 vaccine

    The New England Journal of Medicine 383:2603–2615.

    https://doi.org/10.1056/NEJMoa2034577

    • PubMed
    • Google Scholar
34. Preprint

    1. Riou C

    (2021) Profile of SARS-CoV-2-Specific CD4 T cell response: relationship with disease severity and impact of HIV-1 and active mycobacterium tuberculosis co-infection

    medRxiv.

    https://doi.org/10.1101/2021.02.16.21251838

    • Google Scholar
35. 1. Riou C
    2. du Bruyn E
    3. Stek C
    4. Daroowala R
    5. Goliath RT
    6. Abrahams F
    7. Said-Hartley Q
    8. Allwood BW
    9. Hsiao N-Y
    10. Wilkinson KA
    11. Arlehamn CSL
    12. Sette A
    13. Wasserman S
    14. Wilkinson RJ
    15. HIATUS consortium

    (2021) Relationship of SARS-CoV-2-specific CD4 response to COVID-19 severity and impact of HIV-1 and tuberculosis coinfection

    The Journal of Clinical Investigation 131:149125.

    https://doi.org/10.1172/JCI149125

    • PubMed
    • Google Scholar
36. 1. Riou C
    2. Keeton R
    3. Moyo-Gwete T
    4. Hermanus T
    5. Kgagudi P
    6. Baguma R
    7. Valley-Omar Z
    8. Smith M
    9. Tegally H
    10. Doolabh D
    11. Iranzadeh A
    12. Tyers L
    13. Mutavhatsindi H
    14. Tincho MB
    15. Benede N
    16. Marais G
    17. Chinhoyi LR
    18. Mennen M
    19. Skelem S
    20. du Bruyn E
    21. Stek C
    22. de Oliveira T
    23. Williamson C
    24. Moore PL
    25. Wilkinson RJ
    26. Ntusi NAB
    27. Burgers WA
    28. South African cellular immunity network

    (2022) Escape from recognition of SARS-CoV-2 variant spike epitopes but overall preservation of T cell immunity

    Science Translational Medicine 14:eabj6824.

    https://doi.org/10.1126/scitranslmed.abj6824

    • PubMed
    • Google Scholar
37. 1. Rydyznski Moderbacher C
    2. Ramirez SI
    3. Dan JM
    4. Grifoni A
    5. Hastie KM
    6. Weiskopf D
    7. Belanger S
    8. Abbott RK
    9. Kim C
    10. Choi J
    11. Kato Y
    12. Crotty EG
    13. Kim C
    14. Rawlings SA
    15. Mateus J
    16. Tse LPV
    17. Frazier A
    18. Baric R
    19. Peters B
    20. Greenbaum J
    21. Ollmann Saphire E
    22. Smith DM
    23. Sette A
    24. Crotty S

    (2020) Antigen-specific adaptive immunity to sars-cov-2 in acute covid-19 and associations with age and disease severity

    Cell 183:996–1012.

    https://doi.org/10.1016/j.cell.2020.09.038

    • PubMed
    • Google Scholar
38. 1. Sahin U
    2. Muik A
    3. Derhovanessian E
    4. Vogler I
    5. Kranz LM
    6. Vormehr M
    7. Baum A
    8. Pascal K
    9. Quandt J
    10. Maurus D
    11. Brachtendorf S
    12. Lörks V
    13. Sikorski J
    14. Hilker R
    15. Becker D
    16. Eller A-K
    17. Grützner J
    18. Boesler C
    19. Rosenbaum C
    20. Kühnle M-C
    21. Luxemburger U
    22. Kemmer-Brück A
    23. Langer D
    24. Bexon M
    25. Bolte S
    26. Karikó K
    27. Palanche T
    28. Fischer B
    29. Schultz A
    30. Shi P-Y
    31. Fontes-Garfias C
    32. Perez JL
    33. Swanson KA
    34. Loschko J
    35. Scully IL
    36. Cutler M
    37. Kalina W
    38. Kyratsous CA
    39. Cooper D
    40. Dormitzer PR
    41. Jansen KU
    42. Türeci Ö

    (2020) COVID-19 vaccine BNT162b1 elicits human antibody and T_H1 T cell responses

    Nature 586:594–599.

    https://doi.org/10.1038/s41586-020-2814-7

    • PubMed
    • Google Scholar
39. 1. Schub D
    2. Klemis V
    3. Schneitler S
    4. Mihm J
    5. Lepper PM
    6. Wilkens H
    7. Bals R
    8. Eichler H
    9. Gärtner BC
    10. Becker SL
    11. Sester U
    12. Sester M
    13. Schmidt T

    (2020) High levels of SARS-CoV-2-specific T cells with restricted functionality in severe courses of COVID-19

    JCI Insight 5:142167.

    https://doi.org/10.1172/jci.insight.142167

    • PubMed
    • Google Scholar
40. 1. Sette A
    2. Crotty S

    (2021) Adaptive immunity to SARS-CoV-2 and COVID-19

    Cell 184:861–880.

    https://doi.org/10.1016/j.cell.2021.01.007

    • PubMed
    • Google Scholar
41. 1. Sharov KS

    (2021) HIV/SARS-CoV-2 co-infection: T cell profile, cytokine dynamics and role of exhausted lymphocytes

    International Journal of Infectious Diseases 102:163–169.

    https://doi.org/10.1016/j.ijid.2020.10.049

    • PubMed
    • Google Scholar
42. 1. Shinde V
    2. Bhikha S
    3. Hoosain Z
    4. Archary M
    5. Bhorat Q
    6. Fairlie L
    7. Lalloo U
    8. Masilela MSL
    9. Moodley D
    10. Hanley S
    11. Fouche L
    12. Louw C
    13. Tameris M
    14. Singh N
    15. Goga A
    16. Dheda K
    17. Grobbelaar C
    18. Kruger G
    19. Carrim-Ganey N
    20. Baillie V
    21. de Oliveira T
    22. Lombard Koen A
    23. Lombaard JJ
    24. Mngqibisa R
    25. Bhorat AE
    26. Benadé G
    27. Lalloo N
    28. Pitsi A
    29. Vollgraaff P-L
    30. Luabeya A
    31. Esmail A
    32. Petrick FG
    33. Oommen-Jose A
    34. Foulkes S
    35. Ahmed K
    36. Thombrayil A
    37. Fries L
    38. Cloney-Clark S
    39. Zhu M
    40. Bennett C
    41. Albert G
    42. Faust E
    43. Plested JS
    44. Robertson A
    45. Neal S
    46. Cho I
    47. Glenn GM
    48. Dubovsky F
    49. Madhi SA
    50. 2019nCoV-501 Study Group

    (2021) Efficacy of nvx-cov2373 covid-19 vaccine against the b.1.351 variant

    The New England Journal of Medicine 384:1899–1909.

    https://doi.org/10.1056/NEJMoa2103055

    • PubMed
    • Google Scholar
43. 1. Starr TN
    2. Greaney AJ
    3. Addetia A
    4. Hannon WW
    5. Choudhary MC
    6. Dingens AS
    7. Li JZ
    8. Bloom JD

    (2021) Prospective mapping of viral mutations that escape antibodies used to treat COVID-19

    Science 371:850–854.

    https://doi.org/10.1126/science.abf9302

    • PubMed
    • Google Scholar
44. 1. Streeck H
    2. Jolin JS
    3. Qi Y
    4. Yassine-Diab B
    5. Johnson RC
    6. Kwon DS
    7. Addo MM
    8. Brumme C
    9. Routy J-P
    10. Little S
    11. Jessen HK
    12. Kelleher AD
    13. Hecht FM
    14. Sekaly R-P
    15. Rosenberg ES
    16. Walker BD
    17. Carrington M
    18. Altfeld M

    (2009) Human immunodeficiency virus type 1-Specific CD8 ⁺ T-Cell responses during primary infection are major determinants of the viral set point and loss of CD4 ⁺ T Cells

    Journal of Virology 83:7641–7648.

    https://doi.org/10.1128/JVI.00182-09

    • PubMed
    • Google Scholar
45. Preprint

    1. Tarke A

    (2021) Negligible Impact of SARS-CoV-2 Variants on CD4⁺ and CD8⁺ T Cell Reactivity in COVID-19 Exposed Donors and Vaccinees

    bioRxiv.

    https://doi.org/10.1101/2021.02.27.433180

    • Google Scholar
46. 1. Tarke A
    2. Sidney J
    3. Kidd CK
    4. Dan JM
    5. Ramirez SI
    6. Yu ED
    7. Mateus J
    8. da Silva Antunes R
    9. Moore E
    10. Rubiro P
    11. Methot N
    12. Phillips E
    13. Mallal S
    14. Frazier A
    15. Rawlings SA
    16. Greenbaum JA
    17. Peters B
    18. Smith DM
    19. Crotty S
    20. Weiskopf D
    21. Grifoni A
    22. Sette A

    (2021) Comprehensive analysis of T cell immunodominance and immunoprevalence of SARS-CoV-2 epitopes in COVID-19 cases

    Cell Reports. Medicine 2:100204.

    https://doi.org/10.1016/j.xcrm.2021.100204

    • PubMed
    • Google Scholar
47. 1. Tegally H
    2. Wilkinson E
    3. Giovanetti M
    4. Iranzadeh A
    5. Fonseca V
    6. Giandhari J
    7. Doolabh D
    8. Pillay S
    9. San EJ
    10. Msomi N
    11. Mlisana K
    12. von Gottberg A
    13. Walaza S
    14. Allam M
    15. Ismail A
    16. Mohale T
    17. Glass AJ
    18. Engelbrecht S
    19. Van Zyl G
    20. Preiser W
    21. Petruccione F
    22. Sigal A
    23. Hardie D
    24. Marais G
    25. Hsiao N
    26. Korsman S
    27. Davies MA
    28. Tyers L
    29. Mudau I
    30. York D
    31. Maslo C
    32. Goedhals D
    33. Abrahams S
    34. Laguda-Akingba O
    35. Alisoltani-Dehkordi A
    36. Godzik A
    37. Wibmer CK
    38. Sewell BT
    39. Lourenço J
    40. Alcantara LCJ
    41. Kosakovsky Pond SL
    42. Weaver S
    43. Martin D
    44. Lessells RJ
    45. Bhiman JN
    46. Williamson C
    47. de Oliveira T

    (2021a) Detection of a SARS-CoV-2 variant of concern in South Africa

    Nature 592:438–443.

    https://doi.org/10.1038/s41586-021-03402-9

    • PubMed
    • Google Scholar
48. Preprint

    1. Tegally H
    2. Wilkinson E
    3. Giovanetti M
    4. Iranzadeh A
    5. Fonseca V
    6. Giandhari J
    7. Doolabh D
    8. Pillay S
    9. San EJ
    10. Msomi N
    11. Mlisana K
    12. von Gottberg A
    13. Walaza S
    14. Allam M
    15. Ismail A
    16. Mohale T
    17. Glass AJ
    18. Engelbrecht S
    19. Van Zyl G
    20. Preiser W
    21. Petruccione F
    22. Sigal A
    23. Hardie D
    24. Marais G
    25. Hsiao M
    26. Korsman S
    27. Davies MA
    28. Tyers L
    29. Mudau I
    30. York D
    31. Maslo C
    32. Goedhals D
    33. Abrahams S
    34. Laguda-Akingba O
    35. Alisoltani-Dehkordi A
    36. Godzik A
    37. Wibmer CK
    38. Sewell BT
    39. Lourenço J
    40. Alcantara LCJ
    41. Pond SLK
    42. Weaver S
    43. Martin D
    44. Lessells RJ
    45. Bhiman JN
    46. Williamson C
    47. de Oliveira T

    (2021b) Emergence and Rapid Spread of a New Severe Acute Respiratory Syndrome-Related Coronavirus 2 (SARS-CoV-2) Lineage with Multiple Spike Mutations in South Africa

    medRxiv.

    https://doi.org/10.1101/2020.12.21.20248640

    • Google Scholar
49. 1. Tegally H
    2. Wilkinson E
    3. Lessells RJ
    4. Giandhari J
    5. Pillay S
    6. Msomi N
    7. Mlisana K
    8. Bhiman JN
    9. von Gottberg A
    10. Walaza S
    11. Fonseca V
    12. Allam M
    13. Ismail A
    14. Glass AJ
    15. Engelbrecht S
    16. Van Zyl G
    17. Preiser W
    18. Williamson C
    19. Petruccione F
    20. Sigal A
    21. Gazy I
    22. Hardie D
    23. Hsiao NY
    24. Martin D
    25. York D
    26. Goedhals D
    27. San EJ
    28. Giovanetti M
    29. Lourenço J
    30. Alcantara LCJ
    31. de Oliveira T

    (2021c) Sixteen novel lineages of SARS-CoV-2 in South Africa

    Nature Medicine 27:440–446.

    https://doi.org/10.1038/s41591-021-01255-3

    • PubMed
    • Google Scholar
50. 1. Verma P
    2. Dumka A
    3. Bhardwaj A
    4. Ashok A
    5. Kestwal MC
    6. Kumar P

    (2021) A statistical analysis of impact of covid19 on the global economy and stock index returns

    SN Computer Science 2:27.

    https://doi.org/10.1007/s42979-020-00410-w

    • PubMed
    • Google Scholar
51. Preprint

    1. Viana R
    2. Moyo S
    3. Amoako DG
    4. Tegally H
    5. Scheepers C
    6. Althaus CL
    7. Anyaneji UJ
    8. Bester PA
    9. Boni MF
    10. Chand M
    11. Choga WT
    12. Colquhoun R
    13. Davids M
    14. Deforche K
    15. Doolabh D
    16. Engelbrecht S
    17. Everatt J
    18. Giandhari J
    19. Giovanetti M
    20. Hardie D
    21. Hill V
    22. Hsiao NY
    23. Iranzadeh A
    24. Ismail A
    25. Joseph C
    26. Joseph R
    27. Koopile L
    28. Pond SLK
    29. Kraemer MU
    30. Kuate-Lere L
    31. Laguda-Akingba O
    32. Lesetedi-Mafoko O
    33. Lessells RJ
    34. Lockman S
    35. Lucaci AG
    36. Maharaj A
    37. Mahlangu B
    38. Maponga T
    39. Mahlakwane K
    40. Makatini Z
    41. Marais G
    42. Maruapula D
    43. Masupu K
    44. Matshaba M
    45. Mayaphi S
    46. Mbhele N
    47. Mbulawa MB
    48. Mendes A
    49. Mlisana K
    50. Mnguni A
    51. Mohale T
    52. Moir M
    53. Moruisi K
    54. Mosepele M
    55. Motsatsi G
    56. Motswaledi MS
    57. Mphoyakgosi T
    58. Msomi N
    59. Mwangi PN
    60. Naidoo Y
    61. Ntuli N
    62. Nyaga M
    63. Olubayo L
    64. Pillay S
    65. Radibe B
    66. Ramphal Y
    67. Ramphal U
    68. San JE
    69. Scott L
    70. Shapiro R
    71. Singh L
    72. Smith-Lawrence P
    73. Stevens W
    74. Strydom A
    75. Subramoney K
    76. Tebeila N
    77. Tshiabuila D
    78. Tsui J
    79. van Wyk S
    80. Weaver S
    81. Wibmer CK
    82. Wilkinson E
    83. Wolter N
    84. Zarebski AE
    85. Zuze B
    86. Goedhals D
    87. Preiser W
    88. Treurnicht F
    89. Venter M
    90. Williamson C
    91. Pybus OG
    92. Bhiman J
    93. Glass A
    94. Martin DP
    95. Rambaut A
    96. Gaseitsiwe S
    97. von Gottberg A
    98. de Oliveira T

    (2021) Rapid Epidemic Expansion of the SARS-CoV-2 Omicron Variant in Southern Africa

    medRxiv.

    https://doi.org/10.1101/2021.12.19.21268028

    • Google Scholar
52. 1. Vizcarra P
    2. Pérez-Elías MJ
    3. Quereda C
    4. Moreno A
    5. Vivancos MJ
    6. Dronda F
    7. Casado JL
    8. COVID-19 ID Team

    (2020) Description of COVID-19 in HIV-infected individuals: a single-centre, prospective cohort

    The Lancet. HIV 7:e554–e564.

    https://doi.org/10.1016/S2352-3018(20)30164-8

    • PubMed
    • Google Scholar
53. Preprint

    1. Voloch CM
    2. Silva F R
    3. de Almeida LGP
    4. Cardoso CC
    5. Brustolini OJ
    6. Gerber AL
    7. Guimarães A
    8. Mariani D
    9. Costa R
    10. Ferreira OC
    11. Cavalcanti AC
    12. Frauches TS
    13. de Mello CMB
    14. Galliez RM
    15. Faffe DS
    16. Castiñeiras T
    17. Tanuri A
    18. de Vasconcelos ATR
    19. Covid19-UFRJ Workgroup
    20. LNCC-Workgroup

    (2020) Genomic Characterization of a Novel SARS-CoV-2 Lineage from Rio de Janeiro, Brazil

    bioRxiv.

    https://doi.org/10.1101/2020.12.23.20248598

    • Google Scholar
54. 1. Wang M
    2. Luo L
    3. Bu H
    4. Xia H

    (2020) One case of coronavirus disease 2019 (COVID-19) in a patient co-infected by HIV with a low CD4+ T-cell count

    International Journal of Infectious Diseases 96:148–150.

    https://doi.org/10.1016/j.ijid.2020.04.060

    • PubMed
    • Google Scholar
55. Report

    1. WHO

    (2021a)

    Update on Omicron. WHO DASH board

    WHO.

    • Google Scholar
56. Report

    1. WHO

    (2021b)

    Update on Omicron

    WHO DASH board.

    • Google Scholar
57. 1. Wibmer CK
    2. Ayres F
    3. Hermanus T
    4. Madzivhandila M
    5. Kgagudi P
    6. Oosthuysen B
    7. Lambson BE
    8. de Oliveira T
    9. Vermeulen M
    10. van der Berg K
    11. Rossouw T
    12. Boswell M
    13. Ueckermann V
    14. Meiring S
    15. von Gottberg A
    16. Cohen C
    17. Morris L
    18. Bhiman JN
    19. Moore PL

    (2021) SARS-CoV-2 501Y.V2 escapes neutralization by South African COVID-19 donor plasma

    Nature Medicine 27:622–625.

    https://doi.org/10.1038/s41591-021-01285-x

    • PubMed
    • Google Scholar

Author details

1. Thandeka Nkosi

   Africa Health Research Institute, Nelson R. Mandela School of Medicine, University of Kwa-Zulu Natal, Durban, South Africa

   Contribution

   Investigation, Writing - original draft, Writing – review and editing

   Contributed equally with

   Caroline Chasara

   Competing interests

   No competing interests declared

2. Caroline Chasara

   Africa Health Research Institute, Nelson R. Mandela School of Medicine, University of Kwa-Zulu Natal, Durban, South Africa

   Contribution

   Investigation, Writing - original draft

   Contributed equally with

   Thandeka Nkosi

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-6860-6111

3. Andrea O Papadopoulos

   Africa Health Research Institute, Nelson R. Mandela School of Medicine, University of Kwa-Zulu Natal, Durban, South Africa

   Contribution

   Resources, Formal analysis, Investigation, Writing - original draft, Project administration, Writing – review and editing

   For correspondence

   andrea.papadopoulos@ahri.org

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-5317-1418

4. Tiza L Nguni

   Africa Health Research Institute, Nelson R. Mandela School of Medicine, University of Kwa-Zulu Natal, Durban, South Africa

   Contribution

   Investigation, Methodology, Writing - original draft

   Competing interests

   No competing interests declared

5. Farina Karim

   Africa Health Research Institute, Nelson R. Mandela School of Medicine, University of Kwa-Zulu Natal, Durban, South Africa

   Contribution

   Data curation, Project administration

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9698-016X

6. Mahomed-Yunus S Moosa

   HIV Pathogenesis Program, School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa

   Contribution

   Resources, Investigation, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-6191-4023

7. Inbal Gazy

   KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa

   Contribution

   Data curation, Project administration

   Competing interests

   No competing interests declared

8. Kondwani Jambo

   1. Malawi-Liverpool-Wellcome Trust Clinical Research Programme, Blantyre, Malawi
   2. Liverpool School of Tropical Medicine, Liverpool, United Kingdom

   Contribution

   Formal analysis, Writing – review and editing

   Competing interests

   No competing interests declared

9. COMMIT-KZN-Team

   Africa Health Research Institute, Nelson R. Mandela School of Medicine, University of Kwa-Zulu Natal, Durban, South Africa

   Contribution

   Data curation, Investigation, Project administration

   Competing interests

   No competing interests declared

10. Willem Hanekom

    1. Africa Health Research Institute, Nelson R. Mandela School of Medicine, University of Kwa-Zulu Natal, Durban, South Africa
    2. Division of Infection and Immunity, University College London, London, United Kingdom

    Contribution

    Conceptualization, Funding acquisition, Writing – review and editing

    Competing interests

    No competing interests declared

11. Alex Sigal

    Africa Health Research Institute, Nelson R. Mandela School of Medicine, University of Kwa-Zulu Natal, Durban, South Africa

    Contribution

    Data curation, Project administration, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-8571-2004

12. Zaza M Ndhlovu

    1. Africa Health Research Institute, Nelson R. Mandela School of Medicine, University of Kwa-Zulu Natal, Durban, South Africa
    2. HIV Pathogenesis Program, School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
    3. Ragon Institute of MGH, MIT and Harvard, Cambridge, United States

    Contribution

    Conceptualization, Formal analysis, Validation, Investigation, Writing - original draft, Project administration, Writing – review and editing

    For correspondence

    zndhlovu@mgh.harvard.edu

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-2708-3315

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