Dysfunction of CD8+ T cells in people living with HIV-1 (PLWH) receiving anti-retroviral therapy (ART) has restricted the efficacy of dendritic cell (DC)-based immunotherapies against HIV-1. Heterogeneous immune exhaustion and metabolic states of CD8+ T cells might differentially associate with dysfunction. However, specific parameters associated to functional restoration of CD8+ T cells after DC treatment have not been investigated.We studied association of restoration of functional HIV-1-specific CD8+ T cell responses after stimulation with Gag-adjuvant-primed DC with ART duration, exhaustion, metabolic and memory cell subsets profiles.HIV-1-specific CD8+ T cell responses from a larger proportion of PLWH on long-term ART (more than 10 years; LT-ARTp) improved polyfunctionality and capacity to eliminate autologous p24+ infected CD4+ T cells in vitro. In contrast, functional improvement of CD8+ T cells from PLWH on short-term ART (less than a decade; ST-ARTp) after DC treatment was limited. This was associated with lower frequencies of central memory CD8+ T cells, increased co-expression of PD1 and TIGIT and reduced mitochondrial respiration and glycolysis induction upon TCR activation. In contrast, CD8+ T cells from LT-ARTp showed increased frequencies of TIM3+ PD1- cells and preserved induction of glycolysis. Treatment of dysfunctional CD8+ T cells from ST-ARTp with combined anti-PD1 and anti-TIGIT antibodies plus a glycolysis promoting drug restored their ability to eliminate infected CD4+ T cells.Together, our study identifies specific immunometabolic parameters for different PLWH subgroups potentially useful for future personalized DC-based HIV-1 vaccines.NIH (R21AI140930), MINECO/FEDER RETOS (RTI2018-097485-A-I00) and CIBERINF grants.
Summary The main obstacle to HIV eradication is the establishment of a long‐term persistent HIV reservoir. Although several therapeutic approaches have been developed to reduce and eventually eliminate the HIV reservoir, only a few have achieved promising results. A better knowledge of the mechanisms involved in the establishment and maintenance of HIV reservoir is of utmost relevance for the design of new therapeutic strategies aimed at purging it with the ultimate goal of achieving HIV eradication or alternatively a functional cure. In this regard, it is also important to take a close look into the cellular HIV reservoirs other than resting memory CD4 T‐cells with key roles in reservoir maintenance that have been recently described. Unraveling the special characteristics of these HIV cellular compartments could aid us in designing new therapeutic strategies to deplete the latent HIV reservoir.
The development of physiological models that reproduce SARS-CoV-2 infection in primary human cells will be instrumental to identify host-pathogen interactions and potential therapeutics. Here, using cell suspensions directly from primary human lung tissues (HLT), we have developed a rapid platform for the identification of viral targets and the expression of viral entry factors, as well as for the screening of viral entry inhibitors and anti-inflammatory compounds. The direct use of HLT cells, without long-term cell culture and in vitro differentiation approaches, preserves main immune and structural cell populations, including the most susceptible cell targets for SARS-CoV-2; alveolar type II (AT-II) cells, while maintaining the expression of proteins involved in viral infection, such as ACE2, TMPRSS2, CD147 and AXL. Further, antiviral testing of 39 drug candidates reveals a highly reproducible method, suitable for different SARS-CoV-2 variants, and provides the identification of new compounds missed by conventional systems, such as VeroE6. Using this method, we also show that interferons do not modulate ACE2 expression, and that stimulation of local inflammatory responses can be modulated by different compounds with antiviral activity. Overall, we present a relevant and rapid method for the study of SARS-CoV-2.
Dear Editor, The mechanistic pathways leading to immune dysregulation and complications driven by uncontrolled severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection remain major challenges.1, 2 Hence, a detailed analysis of the proteome, metabolome and lipidome profile of coronavirus disease 2019 (COVID-19) patients showing different severity grades might shed light on the disease pathophysiology and unveil new predictive biomarkers to promptly ascertain patient's outcomes. Our COVID-19 study cohort included 273 SARS-CoV-2 infected individuals recruited during the first wave (March–April 2020) in three different hospitals and grouped by the disease severity following the medical inclusion criteria3 in mild, severe or critical (Figure 1A), from whom demographic, preexisting clinical conditions and COVID-19 treatments are summarized in Table S1. The greatest significant differences were observed between mild and critically ill patients. These findings indicated that older individuals with comorbidities such as hypertension, obesity, diabetes and cardiovascular disorders, mostly presenting dyspnea (Figure 1B), may be at higher risk of suffering from severe respiratory distress with subsequent oxygen and drug requirements and, eventually, died. Similarly, the serum biochemical composition analysis revealed a well-differentiated blood pattern previously defined for critically ill patients (Figure S1). In light of the promising results already provided by omic technologies in the search for predictive biomarkers of COVID-19 severity,4, 5 we conducted a nontargeted multi-omic, including proteomic, metabolomic and lipidomic analyses, in the serum from patients of the COVID-19 study cohort. The proteomics analysis identified 65 proteins with a significant increase or decrease in abundance according to the disease severity (Figure 2A), which resulted to be highly interconnected (Figure 2B). Hence, the complement and coagulation cascades were markedly the most significantly enriched pathways related to COVID-19 severity (Figure 2C). Other protein-coding genes such as carboxypeptidases, protease inhibitors, acute phase proteins, extracellular matrix stabilizers and antimicrobial enzymes, were also significantly up-regulated in severely and critically ill patients. These results showed the essential contribution of these proteins in the coagulopathy phenomenon and hyperinflammatory state that subsequently enhances SARS-CoV-2 endocytosis and infectivity and promotes secondary bacterial infections, previously described as aggravators of severe and critical COVID-19 cases.6 Proteins with reduced abundance in critically ill patients with COVID-19 were mostly associated with lipid transport (apolipoproteins), which dysfunction seems to increase SARS-CoV-2 infectivity in patients with COVID-19.7 For the first time, fetuin-A (AHSG) and inter-α-trypsin inhibitor 3 (ITIH3) were determined as the most accurate biomarkers (random forest) of the critical clinical progression of COVID-19 (Figure 2D). The metabolomic and lipidomic analyses revealed 34 metabolites and 28 lipids that were significantly increased or decreased in relation to severity (Figure 3A). Interestingly, many of the altered metabolites were amino acids and sugars involved in central carbon metabolism. In line with previous reports,8, 9 critically ill patients showed a significant increase in glucose and glutamic acid (GA) levels but a reduction in glutamine, citrate and uric acid levels, suggesting mitochondrial dysfunction, an enhanced glutaminolysis and a shift from anaerobic to aerobic glycolysis (Warburg effect). Accordingly, D-glutamine and D-glutamate metabolism were the most significantly enriched pathways (Figure 3B, left panel), and were significantly related to seizures disorders, anoxia, heart failure, diabetes, obesity and inflammatory diseases (Figure 3B, right panel). Lipid levels that increased with severity were mainly triglycerides (TGs) and diacylglycerols, and those that decreased were predominantly sphingomyelins (SMs), cholesteryl esters (ChoEs) and lysophosphatidylcholines. Lipoproteins rich in TGs may trigger dysfunction in innate immunity and impair the defence mechanism against COVID-1910 and a reduced abundance of SMs and ChoEs may interfere in signal transduction and in key immune and cellular processes. Among them, GA and ChoE (18:0) resulted in the most powerful (random forest) predictive biomarkers for COVID-19 evolution (Figure 3C), confirmed by the prognosis accuracy determined by the receiver operating characteristic (ROC) analysis (Figure S2A–C, respectively). The highest accuracy was attained when combining both compounds in the distinction of mild from critical illnesses (Figure 2SD). To provide insights into the biological pathways related to the pathophysiology of the disease, we study the linkage and co-regulation between the distinct classes of biomolecules by integrating the most significant demographical and clinical data (Table S1 and Figure S1) and the top omic molecules determined above (Figure S3A,B) in Spearman correlation matrix analyses (Figure 4A1–3). Despite all three groups showing a similar association pattern for most of the variables analyzed, patients with mild illness (Figure 4A1) significantly differed from those of the severe and critical groups (Figure 4A2,3, respectively). In brief, significant correlations were obtained across the omic data, which were more intense between lipidomics than within the protein-encoding genes, and nearly negligible through metabolomics. The predictive power of the selected omics biomolecules as biomarkers for the severe disease was subsequently demonstrated by the high accuracy, sensitivity and specificity obtained by combining the four molecules in the ROC analysis (Figure 4B) to effectively distinguish critical COVID-19 patients from patients with mild disease (area under the curve [AUC] = 0.994). To precisely predict whether a patient will progress from severe to a life-threatening disease, not only the four but all the top-omic selected biomarkers need to be integrated into the ROC analysis (AUC = 0.811; Figure 4C). Taking a step further, the inclusion of AHSG, ITIH, GA and ChoE (18:0) in a predictive biomarker panel for COVID-19 severity was validated in a randomly selected subset of patients. The regression modelling analysis confirmed the usefulness (classification accuracy >90%) of the biomarker panel in distinguishing mild to critical COVID-19 outcomes (Figure 4D). Once more, all these findings highlighted the complex interactions between certain biological processes and the most serious complications arising from SARS-CoV-2 infections and revealed their potential as predictive biomarkers of disease severity. Limitations are the small sample size to perform subgroup analyses and the lack of a non-infected SARS-CoV-2 group of subjects. However, this study was conducted in a representative symptomatic well-characterized Spanish cohort to determine predictive biomarkers of COVID-19 severity. In conclusion, the multi-omic analysis identified new specific molecules related to complement and coagulation cascades, platelet activation, cell adhesion, acute inflammation, energy production (Krebs cycle and Warburg effect), amino acid catabolism and lipid transport as fingerprints of the acute disease. A novel biomarker panel consisting of AHSG, ITIH3, GA and ChoE (18:0) was proposed for the accurate differentiation of mild from critical COVID-19 outcomes. This study would not have been possible without the generous collaboration of all the patients and their families and medical and nursing staff who have taken part in the project. We want to particularly acknowledge the collaboration of the Departments of Preventive Medicine and Epidemiology, Internal Medicine, Critical Care, Emergency, Occupational Health, Laboratory Medicine and Molecular Biology, and BioBank-IISPV (B.0000853 and B.0000854) integrated into the Spanish National Biobanks Platform (PT20/00197) and CERCA Programme (Generalitat de Catalunya) and IISPV for their collaboration. We also thank Pol Herrero, Maria Guirro and Antoni del Pino from the Proteomics and Metabolomics facilities of the Centre for Omic Sciences (COS) Joint Unit of the Universitat Rovira i Virgili-Eurecat for their contribution to mass spectrometry analyses. This work has been developed in the framework of the COVIDOMICS' project supported by Direcció General de Recerca i Innovació en Salut (DGRIS), Departament de Salut, Generalitat de Catalunya (PoC-6-17 and PoC1-5). The research has also been funded by the Programa de Suport als Grups de Recerca AGAUR (2017SGR948), the SPANISH AIDS Research Network [RD16/0025/0006, RD16/0025/0007 and RD16/0025/0020]-ISCIII-FEDER (Spain), the Centro de Investigación Biomédica en Red de Enfermedades Infecciosas-ISCIII [CB21/13/00020], Madrid, Spain and Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades Junta de Andalucía (research Project CV20-85418). Elena Yeregui was supported by the Instituto de Salud Carlos III (ISCIII) under grant agreement "FI20/00118″ through the programme "Contratos Predoctorales de Formación en Investigación en Salud". Laia Reverté was supported by the Instituto de Salud Carlos III (ISCIII) under grant agreement "CD20/00105″ through the programme "Contratos Sara Borrell". Francesc Vidal was supported by grants from the Programa de Intensificación de Investigadores (INT20/00031)-ISCIII and by "Premi a la Trajectòria Investigadora dels Hospitals de l'ICS 2018″. Anna Rull was supported by a grant from IISPV through the project "2019/IISPV/05″ (Boosting Young Talent), by GeSIDA through the "III Premio para Jóvenes Investigadores 2019″ and by the Instituto de Salud Carlos III (ISCIII) under grant agreement "CP19/00146″ through the Miguel Servet Program. Maria José Buzón was supported by the Miguel Servet Program (CP17/00179). Ezequiel Ruiz-Mateos was supported by the Spanish Research Council (CSIC). Alicia Gutiérrez-Valencia was supported by the Instituto de Salud Carlos III, cofinanced by the European Development Regional Fund ("A way to achieve Europe"), Subprograma Miguel Servet (grant CP19/00159). This project was also funded by a donation from the city Council of Perafort (to Teresa Auguet). The authors declare that they have no conflict of interest. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
The presence of neutralizing antibodies (NAbs) is a major correlate of protection for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Thus, different in vitro pseudoviruses-based assays have been described to detect NAbs against SARS-CoV-2. However, the determination of NAbs against SARS-CoV-2 in people living with HIV (PLWH) through HIV-based pseudoparticles could be influenced by cross-neutralization activity or treatment, impeding accurate titration of NAbs. Two assays were compared using replication-defective HIV or VSV-based particles pseudotyped with SARS-CoV-2 spike to measure NAbs in COVID-19-recovered and COVID-19-naïve PLWH. The assay based on HIV-pseudoparticles displayed neutralization activity in all COVID-19-recovered PLWH with a median neutralizing titer 50 (NT50) of 1417.0 (interquartile range [IQR]: 450.3-3284.0), but also in 67% of COVID-19-naïve PLWH (NT50: 631.5, IQR: 16.0-1535.0). Regarding VSV-pseudoparticles system, no neutralization was observed in COVID-19-naïve PLWH as expected, whereas in comparison with HIV-pseudoparticles assay lower neutralization titers were measured in 75% COVID-19-recovered PLWH (NT50: 100.5; IQR: 20.5-1353.0). Treatment with integrase inhibitors was associated with inaccurate increase in neutralization titers when HIV-based pseudoparticles were used. IgG purification and consequent elimination of drugs from samples avoided the interference with retroviral cycle and corrected the lack of specificity observed in HIV-pseudotyped assay. This study shows methodological alternatives based on pseudoviruses systems to determine specific SARS-CoV-2 neutralization titers in PLWH.
BACKGROUND. Human immunodeficiency virus (HIV) elite controllers are able to control infection with HIV-1 spontaneously to undetectable levels in the absence of antiretroviral therapy, but the mechanisms leading to this phenotype are poorly understood. Although low frequencies of HIV-infected peripheral CD4(+) T cells have been reported in this group, it remains unclear to what extent these are due to viral attenuation, active immune containment, or intracellular host factors that restrict virus replication. METHODS. We assessed proviral DNA levels, autologous viral growth from and infectability of in vitro activated, CD8(+) T cell-depleted CD4(+) T cells from HIV elite controllers (mean viral load, <50 copies/mL), viremic controllers (mean viral load, <2000 copies/mL), chronic progressors, and individuals receiving highly active antiretroviral therapy. RESULTS. Although we successfully detected autologous virus production in ex vivo activated CD4(+) T cells from all chronic progressors and from most of the viremic controllers, we were able to measure robust autologous viral replication in only 2 of 14 elite controllers subjected to the same protocol. In vitro activated autologous CD4(+) T cells from elite controllers, however, supported infection with both X4 and R5 tropic HIV strains at comparable levels to those in CD4(+) T cells from HIV-uninfected subjects. Proviral DNA levels were the lowest in elite controllers, suggesting that extremely low frequencies of infected cells contribute to difficulty in isolation of virus. CONCLUSIONS. These data indicate that elite control is not due to inability of activated CD4(+) T cells to support HIV infection, but the relative contributions of host and viral factors that account for maintenance of low-level infection remain to be determined.
Latent HIV-1-infected cells generated early in the infection are responsible for viral persistence, and we hypothesized that addition of maraviroc to triple therapy in patients recently infected with HIV-1 could accelerate decay of the viral reservoir.Patients recently infected (<24 weeks) by chemokine receptor 5 (CCR5)-using HIV-1 were randomized to a raltegravir + tenofovir/emtricitabine regimen (control arm, n = 15) or the same regimen intensified with maraviroc (+MVC arm, n = 15). Plasma viral load, cell-associated HIV-1 DNA (total, integrated, and episomal), and activation/inflammation markers were measured longitudinally.Plasma viral load decayed in both groups, reaching similar residual levels at week 48. Total cell-associated HIV-1 DNA also decreased in both groups during the first month, although subsequently at a slightly faster rate in the +MVC arm. The transient increase in two long terminal repeat (2-LTR) circles observed in both groups early after initiation of treatment decreased earlier in MVC-treated individuals. Early (week 12) increase of CD4 T-cell counts was higher in the +MVC arm. Conversely, CD8 T-cell counts and CD4 T-cell activation decreased slower in the +MVC arm. Absolute CD4 T-cell and CD8 T-cell counts, immune activation, CD4/CD8 T-cell ratio, and soluble inflammation markers were similar in both arms at the end of the study.Addition of maraviroc in early integrase inhibitor-based treatment of HIV-1 infection results in faster reduction of 2-LTR newly infected cells and recovery of CD4 T-cell counts, and a modest reduction in total reservoir size after 48 weeks of treatment. Paradoxically, CCR5 blockade also induced a slower decrease in plasma viremia and immune activation.
HIV-1 establishes a lifelong infection in the human body, but host factors that influence viral persistence remain poorly understood. Cell-intrinsic characteristics of CD4 T cells, the main target cells for HIV-1, may affect the composition of the latent viral reservoir by altering the susceptibility to CD8 T-cell-mediated killing.We observed that susceptibilities of CD4 T cells to CD8 T-cell-mediated killing, as determined in direct ex vivo assays, were significantly higher in persons with natural control of HIV-1 (elite controllers) than in individuals effectively treated with antiretroviral therapy. These differences were most pronounced in naive and in terminally differentiated CD4 T cells and corresponded to a reduced viral reservoir size in elite controllers. Interestingly, the highest susceptibility to CD8 T-cell-mediated killing and lowest reservoirs of cell-associated HIV-1 DNA was consistently observed in elite controllers expressing the protective HLA class I allele B57.These data suggest that the functional responsiveness of host CD4 T cells to cytotoxic effects of HIV-1-specific CD8 T cells can contribute to shaping the structure and composition of the latently infected CD4 T-cell pool.
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