We report here a novel primary T-cell model of HIV-1 latency. Our model has several advantages over existing models
[7],
[20],
[21]. Its speed and reproducibility facilitate the screening of unknown compounds and unique combinations and concentrations of known activators. The novel mCherry-luciferase dual reporter virus allow us to assess the number of cells responding to a specific inducer (mCherry) and the magnitude of the response within the entire population (luciferase). The single-step negative purification step for CD4 T cells from peripheral blood minimizes the manipulations of cells. We estimate that 200–1000 reactivation conditions can be screened with cells from a single unit of blood. The high signal-to-noise ratio with the luciferase reporter viruses suggests that non-optimized inducers with low reactivation activity can be readily detected. Thus, this assay could be valuable in the search for novel inducers or combinations of inducers.
Cells respond in many ways when HIV-1 proteins are expressed at high levels, causing differences in internal and external signaling properties. Our kinetic studies revealed viral proteins can be detected in latently infected cells within 2 h after induction. The full-length, replication-competent virus in this system also closely mimics latent HIV-1 infection in vivo and could be useful for monitoring potential changes in cellular responses associated with reactivating latent proviruses and expressing viral proteins. Of note, Nef+ and Nef− viruses responded to activators with similar kinetics, suggesting that Nef may not be important after viral reactivation. Effectiveness of “purging” of the latent reservoir can also be monitored in this system since cells are infected with a cytopathic and replication-competent virus. Finally, the release and accumulation of viral particles after reactivation can be quantified, thus providing useful information on the efficacy of various stimuli.
Using this model, post-integration HIV latency can be rapidly and reproducibly established. Our findings indicate that HIV integration levels correlate well with the levels of HIV expression observed after cellular stimulation
[24]. However, even with the most potent inducers, HIV reactivation levels reflect only a fraction of the total integrated HIV DNA detected. This finding suggests a variegated response within the entire population of latently infected cells with each cell likely containing a single integrated provirus. However, we cannot completely exclude the possibility that some cells contain more than one provirus, although the frequency of such an event is likely to be very low. Overall, we believe these results are comparable to results in patient samples where approximately 99% of the proviral DNA cannot be detected by limiting dilution co-culture growth assays
[1] or where only a fraction of J-Lat CD4 T cells each containing a single provirus respond to inducers
[12]. This model may also be useful for further characterizing the subset of latently infected cells that fail to respond to classic reactivation signals to discern the underlying mechanism(s).
Numerous model systems and data generated with patient-derived cells suggest that NF-κB is important in reactivating HIV-1 from latency
[18],
[38],
[39],
[40],
[43],
[48],
[49]. However, another highly robust primary CD4 T-cell model of HIV-1 latency did not agree
[15]. Although our findings suggest that CD4 memory T-cell subsets achieve different levels of activation with various inducers, NF-κB appears to be involved. Interestingly, latently infected transitional memory CD4 T cells preferentially responded to prostratin, a strong inducer of NF-κB but not NFAT
[48]. Model systems that more closely resemble a central memory CD4 T-cell phenotype might be less dependent on NF-κB for viral reactivation
[15]. Nevertheless, our findings indicate that all inducers reactivate HIV in each of these memory subsets, although the magnitude of reactivation appears greater in transitional memory CD4 T cells. We believe this primary model system will prove useful for continuing to dissect the curious differences between the two memory cell populations.
The precise mechanism by which the latent reservoir is established and maintained
in vivo is an area of ongoing debate. More studies are needed to determine the relative contributions of different cellular latent reservoirs to ongoing viremia during therapy and viral rebound after cessation of therapy
[50],
[51],
[52]. A heterogeneous latent reservoir could complicate development of effective eradication strategies aimed at purging the latent reservoir. One of the latently infected cell types identified, transitional memory CD4 T-cells, are latently infected
in vivo and may be maintained by homeostatic proliferation despite prolonged antitretroviral therapy
[23]. If these latently infected cells could be specifically targeted
in vivo it is possible that other latent reservoirs might naturally decay over time
[22]. Our results demonstrate that these transitional memory CD4 T cells may be easily targeted by T-cell activators, including prostratin. Although additional studies focusing on dissecting the different reactivation properties of these discrete latently infected cell populations are urgently needed, the model system presented here provides the flexibility to begin identifying optimal reactivation strategies.
One strategy to purge the latent reservoir involves cytokines or small molecules to attack different molecular pathways that maintain latency. Several studies suggested that combinations of NF-κB inducers (e.g., prostratin or PMA) and HDAC inhibitors (valproic acid or trichostatin A) might act synergistically
[44],
[45],
[46]. We observed modest synergy with some combinations of activators. However, in agreement with previous reports, this synergy was often transient and lacked consistency between different donors
[45],
[46]. Our results in this primary CD4 T-cell model suggest that prostratin alone may be nearly as potent as this agent in combination with HDAC inhibitors. Donor-dependent differences in the synergistic activation observed with combinations of prostratin and SAHA, if confirmed in patients, would dampen enthusiasm for this approach. The chromatin environment might have a more significant role in establishing latency in proliferating cell lines than in quiescent primary CD4 T cells. Additionally, the activation and binding of strong transcription factors to the HIV LTR could interrupt RNA Pol II transcriptional interference from upstream promoters, a process that is known to help maintain HIV latency
[53],
[54],
[55]. Our findings certainly raise the possibility that non-toxic single agents might prove capable of mounting a strong attack on the latent reservoir.
One very important unanswered question in the field is which of the primary CD4 T-cell models most closely recapitulates the biology of HIV latency occurring in vivo. While our model has several attractive features including the ability to rapidly establish latency in specific memory CD4 T-cell subsets and to test the effects of inducers on these cellular reservoirs, it will be important to test this model side-by-side with others. Only by carefully comparing results from the different models to results obtained with cells isolated from HIV-infected patients on HAART will it be possible to identify the best in vitro models for in vivo HIV latency.
As new translational approaches for eliminating the latent reservoir emerge, a flexible, high-throughput, and highly reproducible model of latent HIV-1 infection becomes increasingly important. The versatility of this primary cell model could make it useful for studies ranging from high-throughput compound screening to molecular characterization of the mechanisms of HIV-1 latency to studies of reservoirs within different memory CD4 T-cell subsets. We hope that this model will help overcome a major barrier in the HIV latency field allowing the rapid acquisition of data previously considered unobtainable.