Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2013 May 14;8(5):e64219.
doi: 10.1371/journal.pone.0064219. Print 2013.

A single HIV-1 cluster and a skewed immune homeostasis drive the early spread of HIV among resting CD4+ cell subsets within one month post-infection

Charline Bacchus  1 , Antoine Cheret, Véronique Avettand-Fenoël, Georges Nembot, Adeline Mélard, Catherine Blanc, Caroline Lascoux-Combe, Laurence Slama, Thierry Allegre, Clotilde Allavena, Yazdan Yazdanpanah, Claudine Duvivier, Christine Katlama, Cécile Goujard, Bao Chau Phung Seksik, Anne Leplatois, Jean-Michel Molina, Laurence Meyer, Brigitte Autran, Christine Rouzioux; OPTIPRIM ANRS 147 study group
Collaborators, Affiliations

A single HIV-1 cluster and a skewed immune homeostasis drive the early spread of HIV among resting CD4+ cell subsets within one month post-infection

Charline Bacchus et al. PLoS One. .

Abstract

Optimizing therapeutic strategies for an HIV cure requires better understanding the characteristics of early HIV-1 spread among resting CD4+ cells within the first month of primary HIV-1 infection (PHI). We studied the immune distribution, diversity, and inducibility of total HIV-DNA among the following cell subsets: monocytes, peripheral blood activated and resting CD4 T cells, long-lived (naive [TN] and central-memory [TCM]) and short-lived (transitional-memory [TTM] and effector-memory cells [TEM]) resting CD4+T cells from 12 acutely-infected individuals recruited at a median 36 days from infection. Cells were sorted for total HIV-DNA quantification, phylogenetic analysis and inducibility, all studied in relation to activation status and cell signaling. One month post-infection, a single CCR5-restricted viral cluster was massively distributed in all resting CD4+ subsets from 88% subjects, while one subject showed a slight diversity. High levels of total HIV-DNA were measured among TN (median 3.4 log copies/million cells), although 10-fold less (p = 0.0005) than in equally infected TCM (4.5), TTM (4.7) and TEM (4.6) cells. CD3-CD4+ monocytes harbored a low viral burden (median 2.3 log copies/million cells), unlike equally infected resting and activated CD4+ T cells (4.5 log copies/million cells). The skewed repartition of resting CD4 subsets influenced their contribution to the pool of resting infected CD4+T cells, two thirds of which consisted of short-lived TTM and TEM subsets, whereas long-lived TN and TCM subsets contributed the balance. Each resting CD4 subset produced HIV in vitro after stimulation with anti-CD3/anti-CD28+IL-2 with kinetics and magnitude varying according to subset differentiation, while IL-7 preferentially induced virus production from long-lived resting TN cells. In conclusion, within a month of infection, a clonal HIV-1 cluster is massively distributed among resting CD4 T-cell subsets with a flexible inducibility, suggesting that subset activation and skewed immune homeostasis determine the conditions of viral dissemination and early establishment of the HIV reservoir.

PubMed Disclaimer

Conflict of interest statement

Competing Interests: The OPTIPRIM Agence Nationale de Recherche sur le Sida 147 study had received funding from Merck Sharp & Dohme, Jansen, ViiV Healthcare and Gilead. These companies contributed to the OPTIPRIM sub-studies. This commercial source of funding did not alter the authors’ scientific guidance and production of results, nor the authors’ adherence to all the PLOS ONE policies on sharing data and materials.

Figures

Figure 1
Figure 1. Total HIV-DNA measurement in peripheral blood cell subsets.
Total HIV-DNA was quantified in various cell populations from twelve acutely HIV-infected subjects. Results are expressed as the log10 HIV-DNA copies per million cells, and medians are shown. Each symbol represents a subject, and values below the threshold of detection were calculated for each assay according to the number of cells available. Of note, infection levels below the threshold of detection were found in 5/10 monocyte samples and 2/12 activated CD4 T lymphocyte samples (grey symbols). Only significant p values are shown. Abbreviations: CD4 T Ly, CD4+ T lymphocyte; ACT+ CD4 T Ly, activated CD4+ T lymphocyte; ACT- CD4 T Ly, resting CD4+ T lymphocyte; TN, naive CD4 T cell subset; TCM, central-memory CD4 T cell subset; TTM, transitional-memory CD4 T cell subset; TEM, effector-memory CD4 T cell subset.
Figure 2
Figure 2. HIV-1 diversity in blood and rectal cell subsets.
Each HIV-1 clone was compared to the sequence of reference FR-HXB2, figured on top of each maximum-likelihood tree as root. The numbers near the nodes indicate the percentage of bootstrap replicates (1,000). The ENV gene was cloned from plasma HIV-RNA (red circle), and from HIV-DNA in resting CD4 cells (green down-triangle), activated CD4 cells (open diamond), resting TN cells (green diamond), resting TCM cells (green square), resting TTM cells (green circle), resting TEM cells (green up-triangle), total rectal cells (black square) and isolated-CD4+ rectal cells (open square). Subject identification codes are indicated on top of each tree. All clusters identified with the maximum-likelihood approach were confirmed with a neighbor-joining analysis.
Figure 3
Figure 3. CD4 T cell subsets repartition and contribution to the pool of infected cells.
A: Monocytes, activated and resting CD4 T-cell (CD4 T Ly) contributions to the pool of infected PBMCs were calculated with the infection level and frequency of each subset. Only significant p values are shown. B: The repartition of resting CD4 T-cell subsets was assessed in twelve acutely HIV-infected individuals (grey) and in ten uninfected individuals (white). The analyzed resting CD4+ subsets are: naive (TN, CD45RA+CCR7+CD27+), central-memory (TCM, CD45RA-CCR7+CD27+), transitional-memory (TTM, CD45RA−CCR7−CD27+) and effector-memory cells (TEM, CD45RA−CCR7−CD27−). Results are expressed as the percentage of resting CD4 T cells. C: Resting CD4 T-cell subset contributions to the pool of infected resting CD4 T cells were calculated with the infection level and frequency of each subset.
Figure 4
Figure 4. Inducibility of HIV in resting CD4 T cell subsets.
A: Cell capacity to induce HIV replication from resting CD4 T cells was evaluated in nine subjects by stimulating sorted CD4 T-cell subsets with anti-CD3/anti-CD28 co-stimulation plus IL-2. HIV-RNA was quantified in supernatants of resting TN, TCM, TTM and TEM cells during a 13-day long culture at D3, D6, D8, D10 and D13. Results are expressed as the log10 of the ratio between the number of HIV-RNA copies quantified on a given day of culture and the level of total HIV-DNA in the subset measured at D0 of culture. Each symbol represents a subject. B and C: Resting CD4 T cell subsets were stimulated by a CD3/CD28 co-stimulation plus IL-2+/− IL-7, with IL-7 alone or without stimulation. In order to evaluate the effect of IL-7 on HIV production, results are expressed as the log10 of the ratio between the normalized HIV production in the IL-7-containing stimulation and in the IL-7-free stimulation (B, IL-7/unstimulated ratio; C, CD3/CD28 co-stimulation plus IL-2 plus IL-7/CD3/CD28 co-stimulation plus IL-2 ratio).
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Blankson JN, Persaud D, Siliciano RF (2002) The challenge of viral reservoirs in HIV-1 infection. Annu Rev Med 53: 557–593. - PubMed
    1. Eriksson S, Graf EH, Dahl V, Strain MC, Yukl SA, et al. (2013) Comparative Analysis of Measures of Viral Reservoirs in HIV-1 Eradication Studies. PLoS Pathogens 9(2): e1003174 doi:10.1371/journal.ppat.1003174. - DOI - PMC - PubMed
    1. Goujard C, Bonarek M, Meyer L, Bonnet F, Chaix ML, et al. (2006) CD4 cell count and HIV DNA level are independent predictors of disease progression after primary HIV type 1 infection in untreated patients. Clin Infect Dis 42: 709–715. - PubMed
    1. Cohen MS, Shaw GM, McMichael AJ, Haynes BF Acute HIV-1 Infection. N Engl J Med 364: 1943–1954. - PMC - PubMed
    1. Keele BF, Giorgi EE, Salazar-Gonzalez JF, Decker JM, Pham KT, et al. (2008) Identification and characterization of transmitted and early founder virus envelopes in primary HIV-1 infection. Proc Natl Acad Sci U S A 105: 7552–7557. - PMC - PubMed

Publication types

Grants and funding

This research was funded by the National French Agency on AIDS Research (Agence Nationale de Recherche sur le Sida, http://www.anrs.fr/), and supported by Merck Sharp & Dohme, Jansen, ViiV Healthcare and Gilead. C. Bacchus received a predoctoral fellowship from Pierre and Marie Curie University. The funders and supporters had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.