23 research outputs found

    Blood CXCR3(+) CD4 T Cells Are Enriched in Inducible Replication Competent HIV in Aviremic Antiretroviral Therapy-Treated Individuals

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    We recently demonstrated that lymph nodes (LNs) PD-1+/T follicular helper (Tfh) cells from antiretroviral therapy (ART)-treated HIV-infected individuals were enriched in cells containing replication competent virus. However, the distribution of cells containing inducible replication competent virus has been only partially elucidated in blood memory CD4 T-cell populations including the Tfh cell counterpart circulating in blood (cTfh). In this context, we have investigated the distribution of (1) total HIV-infected cells and (2) cells containing replication competent and infectious virus within various blood and LN memory CD4 T-cell populations of conventional antiretroviral therapy (cART)-treated HIV-infected individuals. In the present study, we show that blood CXCR3-expressing memory CD4 T cells are enriched in cells containing inducible replication competent virus and contributed the most to the total pool of cells containing replication competent and infectious virus in blood. Interestingly, subsequent proviral sequence analysis did not indicate virus compartmentalization between blood and LN CD4 T-cell populations, suggesting dynamic interchanges between the two compartments. We then investi-gated whether the composition of blood HIV reservoir may reflect the polarization of LN CD4 T cells at the time of reservoir seeding and showed that LN PD-1+ CD4 T cells of viremic untreated HIV-infected individuals expressed significantly higher levels of CXCR3 as compared to CCR4 and/or CCR6, suggesting that blood CXCR3-expressing CD4 T cells may originate from LN PD-1+ CD4 T cells. Taken together, these results indicate that blood CXCR3-expressing CD4 T cells represent the major blood compartment con-taining inducible replication competent virus in treated aviremic HIV-infected individuals

    CD160-Associated CD8 T-Cell Functional Impairment Is Independent of PD-1 Expression.

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    Expression of co-inhibitory molecules is generally associated with T-cell dysfunction in chronic viral infections such as HIV or HCV. However, their relative contribution in the T-cell impairment remains unclear. In the present study, we have evaluated the impact of the expression of co-inhibitory molecules such as 2B4, PD-1 and CD160 on the functions of CD8 T-cells specific to influenza, EBV and CMV. We show that CD8 T-cell populations expressing CD160, but not PD-1, had reduced proliferation capacity and perforin expression, thus indicating that the functional impairment in CD160+ CD8 T cells may be independent of PD-1 expression. The blockade of CD160/CD160-ligand interaction restored CD8 T-cell proliferation capacity, and the extent of restoration directly correlated with the ex vivo proportion of CD160+ CD8 T cells suggesting that CD160 negatively regulates TCR-mediated signaling. Furthermore, CD160 expression was not up-regulated upon T-cell activation or proliferation as compared to PD-1. Taken together, these results provide evidence that CD160-associated CD8 T-cell functional impairment is independent of PD-1 expression

    Host Molecule Incorporation into HIV Virions, Potential Influences in HIV Pathogenesis

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    During the last phase of HIV viral production, nascent HIV virions acquire a fraction of the cellular lipid membrane to create the external lipid envelope, a process by which cellular proteins present on the surface of the infected cell can be incorporated along with Env trimers. Interestingly, several studies indicated that these incorporated host molecules could conserve their biological activity and consequently contribute to HIV pathogenesis either by enhancing the infectivity of HIV virions, their tissue tropism or by affecting immune cell functions. The following review will describe the main approaches used to characterize membrane bound host molecule incorporation into HIV virions, the proposed mechanisms involved, and the role of a non-exhaustive list of incorporated molecules

    Inducible HIV-1 Reservoir Quantification: Clinical Relevance, Applications and Advancements of TILDA

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    The presence of a stable HIV-1 reservoir persisting over time despite effective antiretroviral suppression therapy precludes a cure for HIV-1. Characterizing and quantifying this residual reservoir is considered an essential prerequisite to develop and validate curative strategies. However, a sensitive, reproducible, cost-effective, and easily executable test is still needed. The quantitative viral outgrowth assay is considered the gold standard approach to quantify the reservoir in HIV-1-infected patients on suppressive ART, but it has several limitations. An alternative method to quantify the viral reservoir following the reactivation of latent HIV-1 provirus detects multiply-spliced tat/rev RNA (msRNA) molecules by real-time PCR [tat/rev induced limiting dilution assay (TILDA)]. This article provides a perspective overview of the clinical relevance, various applications, recent advancements of TILDA, and how the assay has contributed to our understanding of the HIV-1 reservoir

    Inducible HIV-1 Reservoir Quantification

    Get PDF
    The presence of a stable HIV-1 reservoir persisting over time despite effective antiretroviral suppression therapy precludes a cure for HIV-1. Characterizing and quantifying this residual reservoir is considered an essential prerequisite to develop and validate curative strategies. However, a sensitive, reproducible, cost-effective, and easily executable test is still needed. The quantitative viral outgrowth assay is considered the gold standard approach to quantify the reservoir in HIV-1-infected patients on suppressive ART, but it has several limitations. An alternative method to quantify the viral reservoir following the reactivation of latent HIV-1 provirus detects multiply-spliced tat/rev RNA (msRNA) molecules by real-time PCR [tat/rev induced limiting dilution assay (TILDA)]. This article provides a perspective overview of the clinical relevance, various applications, recent advancements of TILDA, and how the assay has contributed to our understanding of the HIV-1 reservoir.</p

    Inducible HIV-1 Reservoir Quantification

    Get PDF
    The presence of a stable HIV-1 reservoir persisting over time despite effective antiretroviral suppression therapy precludes a cure for HIV-1. Characterizing and quantifying this residual reservoir is considered an essential prerequisite to develop and validate curative strategies. However, a sensitive, reproducible, cost-effective, and easily executable test is still needed. The quantitative viral outgrowth assay is considered the gold standard approach to quantify the reservoir in HIV-1-infected patients on suppressive ART, but it has several limitations. An alternative method to quantify the viral reservoir following the reactivation of latent HIV-1 provirus detects multiply-spliced tat/rev RNA (msRNA) molecules by real-time PCR [tat/rev induced limiting dilution assay (TILDA)]. This article provides a perspective overview of the clinical relevance, various applications, recent advancements of TILDA, and how the assay has contributed to our understanding

    +CD4 T Cells Are Enriched in Inducible Replication Competent HIV in Aviremic Antiretroviral Therapy-Treated Individuals

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    +CD4 T cells. Taken together, these results indicate that blood CXCR3-expressing CD4 T cells represent the major blood compartment containing inducible replication competent virus in treated aviremic HIV-infected individual

    EBV and CMV-specific CD8 T cells express significantly more CD160 than Flu-specific CD8 T cells.

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    <p>Flow cytometric profiles of Flu, EBV and CMV-specific CD8 T cells expressing PD-1, CD160 and 2B4 <i>ex vivo</i>. The expression profiles of CD8 T cells were performed in 22 individuals using polychromatic flow cytometry. <b>(A)</b> 2B4, CD160 and PD-1 expression profiles of Flu, EBV and CMV-specific CD8 T cells detected by multimer staining (red) as compared to total CD8 T cells (black/grey) of three representative individuals (#KEL12 FLU HLA-A*02 GILGFVFTL, #652 EBV HLA-B*08 RAKFKQLL and #KEL12 CMV HLA-B*07 TPRVTGGGAM, respectively). <b>(B)</b> Frequencies of Flu, EBV and CMV-specific CD8 T cells expressing 2B4, CD160, PD-1. Red bars correspond to mean ± SEM. Statistical significance (<i>P</i> values) in panel <b>B</b> were obtained using One-way ANOVA (Kruskal-Wallis test) followed by a unpaired Student's t-test. <b>(C)</b> Expression profiles of 2B4, CD160, PD-1 of CMV, EBV and Flu-specific CD8 T cells. All the possible combinations of 2B4, CD160 and PD-1 expression are shown on the x axis and frequencies of 2B4, CD160 and PD-1 expression on CD8 and T-cell populations are shown on the y axis. Combinations of expression are grouped and color-coded on the basis of the number of molecules expressed. The pie chart summarizes the data, and each slice corresponds to the fraction of T cells expressing a given combination of molecules within the CD8 T-cell populations. Bars correspond to the fractions of distinct T-cell populations within the total T cells. Stars indicate statistical significance (*:<i>P</i><0.025; **:<i>P</i><0,005; ***:<i>P</i><0.0001) and were calculated using the SPICE software.</p

    CD160, but not PD-1 and/or 2B4 expression inversely correlates with CD8 T-cell proliferative capacity.

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    <p><b>(A–B)</b> Representative flow cytometric profiles of 2B4, PD-1 and CD160 expression of CMV (#700 CMV HLA-A*02 NLVPMVATV) and Flu (#304 FLU HLA-A*02 GILGFVFTL) specific CD8 T cells detected by multimer staining (red) as compared to total CD8 T cells (black/grey). <b>(C–D)</b> Representative CMV (#700 CMV HLA-A*02 NLVPMVATV) and Flu (#MP FLU HLA-A*02 GILGFVFTL) specific CD8 T-cell proliferation capacity assessed by CFSE based assay. <b>(E)</b> Proliferation index (CFSElow CD8 T-cell frequency/Multimer-specific CD8 T-cell frequency) CMV, EBV and FLU-specific CD8 T cells. Red bars correspond to mean ± SEM. <b>(F)</b> Correlations between proliferation index (CFSElow CD8 T-cell frequency/Multimer-specific CD8 T-cell frequency; x axes) and the virus-specific CD8 T-cell subsets distribution (percentage of Multimer-specific CD8 T cells expressing the different combinations of 2B4, PD1 and CD160; y axes). Statistical significance (<i>P</i> values) in panel <b>E</b> were obtained using One-way ANOVA (Kruskal-Wallis test) followed by a Student's t-test. <i>P</i> values in <b>F</b> were obtained using Spearman's rank correlations.</p

    CD160 blockade significantly increases virus-specific CD8 T-cell proliferation.

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    <p><b>(A)</b> Representative example of EBV-specific CD8 T-cell proliferation (#675 EBV HLA-B*08 RAKFKQLL) in presence or in absence of anti-CD160 mAbs and/or anti-PDL-1/2 mAbs assessed by CFSE-based assay. <b>(B)</b> Percentage of CMV, EBV and Flu-specific CD8 T-cell proliferation in presence or not of anti-CD160 mAb (N = 21). <b>(C)</b> Percentage of CMV, EBV and Flu-specific CD8 T-cell proliferation in presence or not of anti-PDL-1/2 mAb (N = 21). <b>(D)</b> Fold increase in the frequency of CFSE low CD8 T cells in presence of anti-CD160 and/or anti-PDL-1/2 mAb as compared to untreated virus-specific CD8 T cells from virus-specific CD8 T-cell populations harboring both 2B4<sup>+</sup>CD160<sup>−</sup>PD-1<sup>+</sup> and 2B4<sup>+</sup>CD160<sup>+</sup>PD-1<sup>−</sup> CD8 T-cell populations (2B4<sup>+</sup>CD160<sup>−</sup>PD-1<sup>+</sup> and 2B4<sup>+</sup>CD160<sup>+</sup>PD-1<sup>−</sup> virus-specific CD8 T cells >10%) (N = 5) or <b>(E)</b> from virus-specific CD8 T-cell populations containing the highest proportion of 2B4<sup>+</sup>CD160<sup>+</sup>PD-1<sup>+</sup> CD8 T-cell population (2B4<sup>+</sup>CD160<sup>+</sup>PD-1<sup>+</sup> virus-specific CD8 T cells >30%) (N = 6). <b>(F)</b> Fold increase in the frequency of CFSE low CD8 T cells in presence of anti-PDL-1/2 mAb on virus-specific CD8 T cells dominated by 2B4<sup>−</sup>CD160<sup>−</sup>PD-1<sup>+</sup>, 2B4<sup>+</sup>CD160<sup>−</sup>PD-1<sup>+</sup> or 2B4<sup>+</sup>CD160<sup>+</sup>PD-1<sup>+</sup> CD8 T-cell populations. Red bars correspond to mean ± SEM. Statistical significance (<i>P</i> values) were obtained using One-way ANOVA (Kruskal-Wallis test) (panel <b>D–F</b>) followed by a paired Student's t-test (panels <b>B–C</b>), Wilcoxon Signed Rank test (<b>D–E</b>), or unpaired Student's t-test (panels <b>F</b>).</p
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