36 research outputs found
Increased T cell trafficking as adjunct therapy for HIV-1
<div><p>Although antiretroviral drug therapy suppresses human immunodeficiency virus-type 1 (HIV-1) to undetectable levels in the blood of treated individuals, reservoirs of replication competent HIV-1 endure. Upon cessation of antiretroviral therapy, the reservoir usually allows outgrowth of virus and approaches to targeting the reservoir have had limited success. Ongoing cycles of viral replication in regions with low drug penetration contribute to this persistence. Here, we use a mathematical model to illustrate a new approach to eliminating the part of the reservoir attributable to persistent replication in drug sanctuaries. Reducing the residency time of CD4 T cells in drug sanctuaries renders ongoing replication unsustainable in those sanctuaries. We hypothesize that, in combination with antiretroviral drugs, a strategy to orchestrate CD4 T cell trafficking could contribute to a functional cure for HIV-1 infection.</p></div
The impact of trafficking on ongoing replication can be understood by focusing on the dynamics concerning the drug sanctuaries.
<p>The effective reproductive number can be understood by focusing on just the dynamics concerning infected cell numbers in the drug sanctuaries (Y<sub>0</sub>) when the drug sanctuaries hold only a small fraction of the body’s CD4 T cells. Under this assumption the net traffic of infected cells out of the drug sanctuaries is approximately κτ<sub>0</sub>Y<sub>0</sub> day<sup>-1</sup> (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006028#pcbi.1006028.s001" target="_blank">S1 Text</a> for details). The dynamics of infected cells in the drug sanctuaries will therefore be governed by a single influx rate (new infections at rate day<sup>-1</sup>) and two efflux rates (cell clearance at rate δ<sub>0</sub> Y<sub>0</sub> day<sup>-1</sup> and cell egress at rate κτ<sub>0</sub>Y<sub>0</sub> day<sup>-1</sup>).</p
A mathematical model of ongoing replication in drug sanctuaries.
<p>The model tracks the number of susceptible and infected cells in each of two spatial compartments, which can differ in size and in the effectiveness of antiretroviral therapy. Within each spatial compartment, infected cells can only transmit infection to other cells within the same spatial compartment, but a fraction of transmission is blocked by antiretroviral drugs. The model includes trafficking of cells between the two compartments, the rate of which can be changed using a trafficking therapy. The model also includes cell turnover.</p
The predicted impact of ‘trafficking therapy’ on ongoing replication in a lymph node.
<p>In the absence of therapy that promotes cell trafficking (top left), trafficking of CD4 T cells in and out of the drug sanctuaries is slow enough to allow ongoing cycles of replication. The sanctuaries include small regions within lymph nodes (purple region). The effectiveness of antiretroviral therapy is assumed to be high in other regions, referred to as the main compartment, including elsewhere in lymph nodes (pale region) and in the blood. In the main compartment, continuous cycles of replication are unsustainable. When trafficking therapy increases the trafficking rate above the critical threshold (bottom right), CD4 T cells move more rapidly through the lymphatic system, including between the drug sanctuaries and the main compartment. The egress of infected CD4 T cells from the drug sanctuaries lowers their density in this spatial compartment. As a result, fewer virus particles are produced in the drug sanctuaries. If trafficking is fast enough, the lower density of virus particles and infected cells in the drug sanctuaries combine to ensure that ongoing cycles of infection, either through cell-to-cell infection or free virus, is not sustainable.</p
Addition of trafficking therapy can halt ongoing replication in drug sanctuaries.
<p>These figures show model predictions of the impact of therapeutic interventions on infected cell numbers in the drug sanctuaries (red lines) and main compartment (black lines). In each figure, prior to time 0 (grey shaded area), the host is only taking antiretroviral therapy (ART). At this stage, the effectiveness of antiretroviral therapy is high in the main compartment of the body (z<sub>1</sub> = 0.97), but lower in the drug sanctuaries (z<sub>0</sub> = 0.6). Furthermore, the per cell rate that cells traffic between compartments (governed by parameter <i>τ</i><sub>0</sub> = 0.5 day<sup>-1</sup>) and the per cell rate that infected cells are cleared from the drug sanctuaries (δ<sub>0</sub> = 0.5 day<sup>-1</sup>) are slow enough to allow ongoing cycles of replication to persist in the drug sanctuaries. At time 0, additional therapy that either increases the cell trafficking rate (a and b), increases the cell clearance rate of infected cells from the drug sanctuaries (c), or both (d) is applied. In a), the trafficking rate is increased sufficiently (κ = 5) that ongoing viral replication is no longer sustainable. In b), the trafficking rate is increased to a level (κ = 3.5) just below the critical threshold and infected cell numbers decline to a new, lower equilibrium in the drug sanctuaries, but in the main compartment they increase. In c), the per cell clearance rate of infected cells in the drug sanctuaries is increased to the same level as in the main compartment (δ<sub>0</sub> = 1 day<sup>-1</sup>). Here, the assumption that the effective drug concentration is highly impaired in the drug sanctuaries results in infected cell numbers declining to a new equilibrium. In d) both the per cell trafficking rate and the per cell clearance rate are increased to levels (κ = 3.5 and δ<sub>0</sub> = 1 day<sup>-1</sup>) which independently would not stop ongoing replication (b and c), but, in combination, do so. All parameter values used in these calculations are provided in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006028#pcbi.1006028.s009" target="_blank">S1 Table</a>.</p
The threshold for ongoing replication is dependent upon several factors including the rate of CD4 T cell trafficking.
<p>The grey line plots the relationship between the per cell rate that CD4 T cells traffic out of drug sanctuaries (κτ<sub>0</sub> day<sup>-1</sup>) and the effectiveness of antiretroviral therapy in the drug sanctuaries (z<sub>0</sub>), under the assumption that the drug sanctuaries are also immune sanctuaries (δ<sub>0</sub> = 0.5 day<sup>-1</sup>,δ<sub>1</sub> = 1 day<sup>-1</sup>). Boosting immune control in the sanctuaries so that there are equal infected cell clearance rates in each compartment (δ<sub>0</sub> = δ<sub>1</sub> = 1 day<sup>-1</sup>) acts additively with boosting cell trafficking rates so that the threshold for sustainable replication is decreased (black line). This figure reveals that antiretroviral therapy, trafficking therapy and immune therapy could all work in synergy to halt ongoing replication in drug sanctuaries. Guided by clinical findings, these plots assume that antiretroviral therapy is very effective in the main compartment (z<sub>1</sub> = 0.97) and drug sanctuaries are very small in size compared to the main compartment.</p
Structure-function analysis of Vpus for counteraction of two tetherin activities.
<p>(<b>A</b>) As for <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003895#ppat-1003895-g004" target="_blank">Figure <b>4</b></a>, but functional profiles of each Vpu is shown according to its ability to counteract tetherin to promote virus release, and to suppress NF-κB activation by tetherin. Tetherin counteraction (virus release) is measured relative to NL4.3 Vpu (100%), whereas suppression of signalling is presented as % reduction of NF-κB activation relative to the negative control. Defective/sub-optimal Vpus are defined as 0–81% for tetherin counteraction, and 0–50% for signalling suppression. Cutoffs are indicated by dark red solid lines. Vpus were categorised according to whether they were defective for tetherin counteraction for virus release (n = 31), signalling suppression (n = 26), or both (n = 15), then compared to their closest functional relatives and to the Vpu population as a whole, to deduce the amino acid changes responsible for the defect. Each defective/sub-optimal Vpu is coloured according to the location of the inactivating mutation, as detailed in the key, and then highlighted in (B). (<b>B</b>) As for <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003895#ppat-1003895-g004" target="_blank"><b>Figure 4B</b></a>, but in contrast, here we have only indicated residues identified in these analyses involved in tetherin counteraction for virus release (dark grey squares above logo plot), tetherin counteraction for signalling suppression (dark grey circles above logo plot), or both, rather than also indicated residues previously identified in the literature.</p
Analysis of tetherin signalling suppression by 304 natural Vpu alleles.
<p>As for <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003895#ppat-1003895-g002" target="_blank">Figure 2</a>, representatives of all amino acid sequences obtained through SGA were tested in tetherin signalling suppression assays. The time point of each sample, in years post-seroconversion, is indicated beneath the graph with the patient identification and progression group. Results are shown as % reduction of maximum tetherin-mediated NF-κB activation. NL4.3, and the NL4.3 S52,56A Vpu mutant, defective for both CD4 downregulation and tetherin counteraction activity, are indicated by dashed lines (at 49 and 17%, respectively). Each symbol represents the average of a minimum of three independent experiments, weighted to represent the allele frequency of each variant, to give an overall proportional representation of function per time point. Means for overall Vpu function for each time point are shown as short horizontal lines. Significant differences between time points from each individual are indicated by asterisks. Briefly, the assays were performed as follows: 50 ng of tetherin or empty vector constructs were co-transfected with 50 ng of pCRVI-Vpu or empty vector, and 10 ng of an NF-κB-dependent firefly luciferase reporter construct and 5 ng of a control renilla luciferase construct. 24 hours later, cells were lysed and the luciferase activity determined. Results are displayed as % reduction of luciferase activation in the presence of Vpu relative to the mean maximum activity in the absence of Vpu.</p
Analysis of CD4 downregulation and tetherin antagonism of 304 natural Vpu alleles.
<p>Representatives of all amino acid sequences obtained through SGA were cloned and tested in standardised assays for the two major functions of Vpu: (<b>A</b>) cell surface CD4 downregulation and (<b>B</b>) tetherin counteraction. The time point of each sample, in years post-seroconversion, is indicated beneath the graph with the patient identification and progression group. The function of each Vpu is represented relative to the prototypical Vpu from NL4.3, as indicated by a dashed line at 100%, and the functions of all other Vpus are represented as a percentage thereof. The NL4.3 S52,56A Vpu mutant, defective for both CD4 downregulation and tetherin counteraction activity, is indicated by a dashed line (at 0% on the CD4 downregulation graph and 13% on the tetherin counteraction graph). Each symbol represents the average of a minimum of three independent experiments, weighted to represent the number of sequences obtained per sample with that particular amino acid sequence (allele frequency), to give an overall proportional representation of function per time point. Means for overall Vpu function for each time point are shown as short horizontal lines. Significant differences between time points from each individual are indicated by asterisks. Briefly, the assays were performed as follows: (<b>A</b>) HeLa-TZMbl cells were co-transfected with 100 ng of pCRVI-Vpu or empty vector (EV) plasmid and 100 ng of pCR3.1-eGFP. 24 hours later cell surface CD4 levels were analysed by flow cytometry. CD4 downregulation was determined by comparing median fluorescent intensities of CD4 in the presence and absence of Vpu, with the downregulation achieved by NL4.3 Vpu set at 100%. Note that the absolute value of CD4 reduction achieved by NL4.3 was 80%±6. (<b>B</b>) 293T cells were transfected with a fixed dose (50 ng) of pCR3.1-hu-tetherin in combination with 500 ng of NL4.3-del Vpu proviral plasmid and 25 ng of pCRVI-Vpu. 48 hours later the supernatants are removed from the cells and assayed on Hela-TZMbl cells for the quantity of infectious virus. The 100% line represents the amount of infectious virus released in the presence of NL4.3, to allow direct comparisons between the CD4 downregulation and tetherin counteraction assays. 25 ng of pCRVI-Vpu was used as this quantity produced the same amount of Vpu protein as that of the full-length NL4.3 molecular clone, as determined by Western blot analysis.</p
<i>In vivo</i> variation of HIV-1 clade B <i>vpu.</i>
<p>Unrooted maximum likelihood phylogeny of 851 <i>vpu</i> nucleotide sequences derived from 25 samples from 14 HIV-1-infected individuals. Individuals were classified according to time from seroconversion to progression to AIDS: 5 rapid progressors (RPs), 4 normal progressors (NPs) and 5 long-term non-progressors (LTNPs) with sequences from each individual coloured and labelled accordingly. Bootstrap supports (% confidence) are shown at the base of the branch for each individual. Branch lengths indicate the number of nucleotide substitutions per site.</p