Impact of HIV-1 Vpu-mediated downregulation of CD48 on NK-cell-mediated antibody-dependent cellular cytotoxicity.

HIV-1 evades antibody-dependent cellular cytotoxicity (ADCC) responses not only by controlling Env conformation and quantity at the cell surface but also by altering NK cell activation via the downmodulation of several ligands of activating and co-activating NK cell receptors. The signaling lymphocyte activation molecule (SLAM) family of receptors, which includes NTB-A and 2B4, act as co-activating receptors to sustain NK cell activation and cytotoxic responses. These receptors cooperate with CD16 (FcγRIII) and other activating receptors to trigger NK cell effector functions. In that context, Vpu-mediated downregulation of NTB-A on HIV-1-infected CD4 T cells was shown to prevent NK cell degranulation via an homophilic interaction, thus contributing to ADCC evasion. However, less is known on the capacity of HIV-1 to evade 2B4-mediated NK cell activation and ADCC. Here, we show that HIV-1 downregulates the ligand of 2B4, CD48, from the surface of infected cells in a Vpu-dependent manner. This activity is conserved among Vpu proteins from the HIV-1/SIVcpz lineage and depends on conserved residues located in its transmembrane domain and dual phosphoserine motif. We show that NTB-A and 2B4 stimulate CD16-mediated NK cell degranulation and contribute to ADCC responses directed to HIV-1-infected cells to the same extent. Our results suggest that HIV-1 has evolved to downmodulate the ligands of both SLAM receptors to evade ADCC. IMPORTANCE Antibody-dependent cellular cytotoxicity (ADCC) can contribute to the elimination of HIV-1-infected cells and HIV-1 reservoirs. An in-depth understanding of the mechanisms used by HIV-1 to evade ADCC might help develop novel approaches to reduce the viral reservoirs. Members of the signaling lymphocyte activation molecule (SLAM) family of receptors, such as NTB-A and 2B4, play a key role in stimulating NK cell effector functions, including ADCC. Here, we show that Vpu downmodulates CD48, the ligand of 2B4, and this contributes to protect HIV-1-infected cells from ADCC. Our results highlight the importance of the virus to prevent the triggering of the SLAM receptors to evade ADCC.

HIV-1 Envelope Glycoprotein Cell Surface Localization Is Associated with Antibody-Induced Internalization.

To minimize immune responses against infected cells, HIV-1 has evolved different mechanisms to limit the surface expression of its envelope glycoproteins (Env). Recent observations suggest that the binding of certain broadly neutralizing antibodies (bNAbs) targeting the 'closed' conformation of Env induces its internalization. On the other hand, non-neutralizing antibodies (nNAbs) that preferentially target Env in its 'open' conformation, remain bound to Env on the cell surface for longer periods of time. In this study, we attempt to better understand the underlying mechanisms behind the differential rates of antibody-mediated Env internalization. We demonstrate that 'forcing' open Env using CD4 mimetics allows for nNAb binding and results in similar rates of Env internalization as those observed upon the bNAb binding. Moreover, we can identify distinct populations of Env that are differentially targeted by Abs that mediate faster rates of internalization, suggesting that the mechanism of antibody-induced Env internalization partially depends on the localization of Env on the cell surface.

Identification of SARS-CoV-2-specific immune alterations in acutely ill patients.

Dysregulated immune profiles have been described in symptomatic patients infected with SARS-CoV-2. Whether the reported immune alterations are specific to SARS-CoV-2 infection or also triggered by other acute illnesses remains unclear. We performed flow cytometry analysis on fresh peripheral blood from a consecutive cohort of (a) patients hospitalized with acute SARS-CoV-2 infection, (b) patients of comparable age and sex hospitalized for another acute disease (SARS-CoV-2 negative), and (c) healthy controls. Using both data-driven and hypothesis-driven analyses, we found several dysregulations in immune cell subsets (e.g., decreased proportion of T cells) that were similarly associated with acute SARS-CoV-2 infection and non-COVID-19-related acute illnesses. In contrast, we identified specific differences in myeloid and lymphocyte subsets that were associated with SARS-CoV-2 status (e.g., elevated proportion of ICAM-1+ mature/activated neutrophils, ALCAM+ monocytes, and CD38+CD8+ T cells). A subset of SARS-CoV-2-specific immune alterations correlated with disease severity, disease outcome at 30 days, and mortality. Our data provide an understanding of the immune dysregulation specifically associated with SARS-CoV-2 infection among acute care hospitalized patients. Our study lays the foundation for the development of specific biomarkers to stratify SARS-CoV-2-positive patients at risk of unfavorable outcomes and to uncover candidate molecules to investigate from a therapeutic perspective.

Integrated immunovirological profiling validates plasma SARS-CoV-2 RNA as an early predictor of COVID-19 mortality.

Despite advances in COVID-19 management, identifying patients evolving toward death remains challenging. To identify early predictors of mortality within 60 days of symptom onset (DSO), we performed immunovirological assessments on plasma from 279 individuals. On samples collected at DSO11 in a discovery cohort, high severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral RNA (vRNA), low receptor binding domain­specific immunoglobulin G and antibody-dependent cellular cytotoxicity, and elevated cytokines and tissue injury markers were strongly associated with mortality, including in patients on mechanical ventilation. A three-variable model of vRNA, with predefined adjustment by age and sex, robustly identified patients with fatal outcome (adjusted hazard ratio for log-transformed vRNA = 3.5). This model remained robust in independent validation and confirmation cohorts. Since plasma vRNA's predictive accuracy was maintained at earlier time points, its quantitation can help us understand disease heterogeneity and identify patients who may benefit from new therapies.