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Comparative Study
. 2013;9(12):e1003834.
doi: 10.1371/journal.ppat.1003834. Epub 2013 Dec 26.

An in-depth comparison of latent HIV-1 reactivation in multiple cell model systems and resting CD4+ T cells from aviremic patients

Celsa A Spina  1 , Jenny Anderson  2 , Nancie M Archin  3 , Alberto Bosque  4 , Jonathan Chan  5 , Marylinda Famiglietti  4 , Warner C Greene  6 , Angela Kashuba  7 , Sharon R Lewin  8 , David M Margolis  9 , Matthew Mau  4 , Debbie Ruelas  5 , Suha Saleh  2 , Kotaro Shirakawa  5 , Robert F Siliciano  10 , Akul Singhania  11 , Paula C Soto  1 , Valeri H Terry  11 , Eric Verdin  6 , Christopher Woelk  12 , Stacey Wooden  13 , Sifei Xing  10 , Vicente Planelles  4
Affiliations
Comparative Study

An in-depth comparison of latent HIV-1 reactivation in multiple cell model systems and resting CD4+ T cells from aviremic patients

Celsa A Spina et al. PLoS Pathog. 2013.

Abstract

The possibility of HIV-1 eradication has been limited by the existence of latently infected cellular reservoirs. Studies to examine control of HIV latency and potential reactivation have been hindered by the small numbers of latently infected cells found in vivo. Major conceptual leaps have been facilitated by the use of latently infected T cell lines and primary cells. However, notable differences exist among cell model systems. Furthermore, screening efforts in specific cell models have identified drug candidates for "anti-latency" therapy, which often fail to reactivate HIV uniformly across different models. Therefore, the activity of a given drug candidate, demonstrated in a particular cellular model, cannot reliably predict its activity in other cell model systems or in infected patient cells, tested ex vivo. This situation represents a critical knowledge gap that adversely affects our ability to identify promising treatment compounds and hinders the advancement of drug testing into relevant animal models and clinical trials. To begin to understand the biological characteristics that are inherent to each HIV-1 latency model, we compared the response properties of five primary T cell models, four J-Lat cell models and those obtained with a viral outgrowth assay using patient-derived infected cells. A panel of thirteen stimuli that are known to reactivate HIV by defined mechanisms of action was selected and tested in parallel in all models. Our results indicate that no single in vitro cell model alone is able to capture accurately the ex vivo response characteristics of latently infected T cells from patients. Most cell models demonstrated that sensitivity to HIV reactivation was skewed toward or against specific drug classes. Protein kinase C agonists and PHA reactivated latent HIV uniformly across models, although drugs in most other classes did not.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Graphic summary of the ability of each compound to activate HIV within each cell model: (A) primary CD4 T cell models and patient cell outgrowth assay (QVOA), and (B) J-Lat T cell line clones.
Each compound and concentration tested is listed on the X-axis. In the primary CD4 cell models, each compound was tested using cells from 2, 3 or 4 different donors and in duplicate or triplicate with cells from each donor (See Methods Section for details). For the QVOA, results from the limiting dilution cultures from 3 patients were pooled to calculate one common IUPM (infectious units per million cells) value which was then normalized to that obtained with PHA. With the J-Lat clones, experiments were performed in triplicate. Asterisks represent “not done”.
Figure 2
Figure 2. Heatmap visualization of the ability of each compound to activate HIV within each model when excluding (A) and including (B) data from the QVOA model.
A reduced set of compounds was analyzed in (B) since not every compound was run at every concentration in the QVOA. The clustergram at the left of each heatmap reflects the relationships between compounds based on their ability to activate HIV across compounds. Since cells in all models responded to PHA with high strength, ranking was normalized within each model to the response to PHA at 10 µg/mL and, therefore, all models display in the heatmap the same relative responsiveness to this treatment. The clustergram at the top of each heatmap reflects the relationship between each model based on their response to compounds. Clustergrams were created by calculating Euclidean distances and then clustering distances using the average linkage method. The numbers at the nodes of clusters are AU p-values where 95% represents a p-value cut-off of 0.05 and only values 95% or greater are depicted. Red cells in the heatmaps reflect HIV activation whereas blue or blank cells indicate that the compound did not effectively activate HIV.
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