An HIV-1 Replication Pathway Utilizing Reverse Transcription Products That Fail To Integrate

Self Cite

HIV-1 infection leads to the progressive depletion of the CD4 T cell compartment by various known and unknown mechanisms.In vivo, HIV-1 infects both activated and resting CD4 T cells, but in vitro, in the absence of any stimuli, resting CD4 T cells from peripheral blood are resistant to infection. This resistance is generally attributed to an intracellular environment that does not efficiently support processes such as reverse transcription (RT), resulting in abortive infection. Here, we show that in vitro HIV-1 infection of resting CD4 T cells induces substantial cell death, leading to abortive infection. In vivo, however, various microenvironmental stimuli in lymphoid and mucosal tissues provide support for HIV-1 replication. For example, common gamma-chain cytokines (CGCC), such as interleukin-7 (IL-7), render resting CD4 T cells permissible to HIV-1 infection without inducing T cell activation. Here, we find that CGCC primarily allow productive infection by preventing HIV-1 triggering of apoptosis, as evidenced by early release of cytochrome c and caspase 3/7 activation. Cell death is triggered both by products of reverse transcription and by virion-borne Vpr protein, and CGCC block both mechanisms. When HIV-1 RT efficiency was enhanced by SIVmac239 Vpx protein, cell death was still observed, indicating that the speed of reverse transcription and the efficiency of its completion contributed little to HIV-1-induced cell death in this system. These results show that a major restriction on HIV-1 infection in resting CD4 T cells resides in the capacity of these cells to survive the early steps of HIV-1 infection. IMPORTANCE A major consequence of HIV-1 infection is the destruction of CD4 T cells.Here, we show that delivery of virion-associated Vpr protein and the process of reverse transcription are each sufficient to trigger apoptosis of resting CD4 T cells isolated from peripheral blood. While these 2 mechanisms have been previously described in various cell types, we show for the first time their concerted effect in inducing resting CD4 T cell depletion. Importantly, we found that cytokines such as IL-7 and IL-4, which are particularly active in sites of HIV-1 replication, protect resting CD4 T cells from these cytopathic effects and, primarily through this protection, rather than through enhancement of specific replicative steps, they promote productive infection. This study provides important new insights for the understanding of the early steps of HIV-1 infection and T cell depletion. E arly human immunodeficiency virus type 1 (HIV-1) infection is characterized by rapid and substantial depletion of both activated and resting CD4 T cells (1). The acute phase of both human HIV-1 infection and simian immunodeficiency virus (SIV) infection of macaques is characterized by Ն90% of viral RNA ϩ cells displaying a resting phenotype (2). It is during this stage that the main HIV-1 reservoir and source of virus rebound in vivo is established in resting memory T cells. Latency can be directly established upon...

Section: A Major Consequence Of Hiv-1 Infection Is the Destruction Ofmentioning

confidence: 99%

HIV-1 Vpr- and Reverse Transcription-Induced Apoptosis in Resting Peripheral Blood CD4 T Cells and Protection by Common Gamma-Chain Cytokines

Trinité

Chan

Lee

et al. 2016

Self Cite

“…ϩ T cells (58)(59)(60)(61). To exclude the possibility that some forms of this unintegrated HIV-1 DNA become integrated upon T cell activation, resulting in productive infection and virus particle production, we next assessed the contribution of unintegrated HIV-1 LAI DNA to extracellular vRNA production from both T N and T CM cells by including the integrase inhibitor raltegravir (RAL) at the same time as anti-CD3/CD28 (Fig.…”

Section: Resting Cd4mentioning

confidence: 99%

Establishment and Reversal of HIV-1 Latency in Naive and Central Memory CD4⁺T CellsIn Vitro

Zerbato

Serrao

Lenzi

et al. 2016

The latent HIV-1 reservoir primarily resides in resting CD4؉ T cells which are a heterogeneous population composed of both naive (T N ) and memory cells. In HIV-1-infected individuals, viral DNA has been detected in both naive and memory CD4 ؉ T cell subsets although the frequency of HIV-1 DNA is typically higher in memory cells, particularly in the central memory (T CM ) cell subset. T N and T CM cells are distinct cell populations distinguished by many phenotypic and physiological differences. In this study, we used a primary cell model of HIV-1 latency that utilizes direct infection of highly purified T N and T CM cells to address differences in the establishment and reversal of HIV-1 latency. Consistent with what is seen in vivo, we found that HIV-1 infected T N cells less efficiently than T CM cells. However, when the infected T N cells were treated with latency-reversing agents, including anti-CD3/CD28 antibodies, phorbol myristate acetate/phytohemagglutinin, and prostratin, as much (if not more) extracellular virion-associated HIV-1 RNA was produced per infected T N cell as per infected T CM cell. There were no major differences in the genomic distribution of HIV-1 integration sites between T N and T CM cells that accounted for these observed differences. We observed decay of the latent HIV-1 cells in both T cell subsets after exposure to each of the latency-reversing agents. Collectively, these data highlight significant differences in the establishment and reversal of HIV-1 latency in T N and T CM CD4؉ T cells and suggest that each subset should be independently studied in preclinical and clinical studies. IMPORTANCE The latent HIV-1 reservoir is frequently described as residing within resting memory CD4؉ T cells. This is largely due to the consistent finding that memory CD4 ؉ T cells, specifically the central (T CM )

“…1. Control experiments utilizing cell counting and eFluor670 dye dilution (14) demonstrated that Jurkat cell proliferation over 2 days was unaffected by the variable cell densities employed here (not shown).…”

Section: Resultsmentioning

confidence: 99%

“…Cells were infected in the indicated total volume (1 ml or 2 ml) with a 3-fold serial dilution of an equal mixture of green fluorescent protein (GFP) and yellow fluorescent protein (YFP) reporter HIV-1 strains (NLENG1-ES-IRES and NLENY1-ES-IRES, respectively) pseudotyped with the HIV-1 NL4-3 envelope for single-round infection (12,13). The highest virus dose was 1.5 ϫ 10 8 virions, as assessed by real-time PCR for genomic RNA (14). Infections were either by spinoculation for 2 h at 1,200 ϫ g and 37°C (14) or by overnight incubation only, each in the presence of 10 g/ml DEAE-dextran (Sigma).…”

Section: Methodsmentioning

confidence: 99%

“…The highest virus dose was 1.5 ϫ 10 8 virions, as assessed by real-time PCR for genomic RNA (14). Infections were either by spinoculation for 2 h at 1,200 ϫ g and 37°C (14) or by overnight incubation only, each in the presence of 10 g/ml DEAE-dextran (Sigma). A 1 day postinfection, one half of the total volume of each well was replaced with fresh culture medium.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

On the Laws of Virus Spread through Cell Populations

Wodarz

Chan

Trinité

et al. 2014

Self Cite

The dynamics of viral infections have been investigated extensively, often with a combination of experimental and mathematical approaches. Mathematical descriptions of virus spread through cell populations are well established in the literature and have yielded important insights, yet the formulation of certain fundamental aspects of virus dynamics models remains uncertain and untested. Here, we investigate the process of infection and, in particular, the effect of varying the target cell population size on the number of productively infected cells generated. Using an in vitro single-round HIV-1 infection system, we find that the established modeling framework cannot accurately fit the data. If the model is fit to data with the lowest number of cells and is used to predict data generated with larger cell populations, the model significantly overestimates the number of productively infected cells generated. Interestingly, this deviation becomes stronger under experimental conditions that promote mixing of cells and viruses. The reason for the deviation is that the standard model makes certain oversimplifying assumptions about the fate of viruses that fail to find a cell in their immediate proximity. We derive from stochastic processes a different model that assumes simultaneous access of the virus to multiple target cells. In this scenario, if no cell is available to the virus at its location, it has a chance to interact with other cells, a process that can be promoted by mixing of the populations. This model can accurately fit the experimental data and suggests a new interpretation of mass action in virus dynamics models. IMPORTANCE Understanding the principles of virus growth through cell populations is of fundamental importance to virology. It helps us make informed decisions about intervention strategies aimed at preventing virus growth, such as drug treatment or vaccination approaches, e.g., in HIV infection, yet considerable uncertainty remains in this respect. An important variable in this context Studying the dynamics of virus replication has generated important insights into several human infections, including those caused by human immunodeficiency virus (HIV) as well as hepatitis B and C viruses (1-6). Mathematical modeling of viral dynamics has played a crucial role in this research, allowing the estimation of critical replication parameters in order to obtain a better understanding of viral evolution, the interactions between viruses and the immune system, and the response of viral infections to antiviral drug therapy. The accuracy with which virus dynamics are described and, more importantly, predicted depends on various simplifying assumptions underlying the model; these have been discussed, e.g., in reference 7. Here we investigate the fundamental structure of the infection term, that is, the overall rate at which target cells in a population become infected in the presence of the virus. We specifically discover how the number of target cells available to the virus influences the number of...