The effect of the HPV-16 minor capsid protein L2 on the HPV-16 viral transcription regulator E2

The nucleus contains a variety of morphologically distinct substructures called nuclear bodies, which include the promyelocytic leukemia oncogenic domains (PODs) also known as PML-NDIO. PODs are macromolecular multiprotein complexes that are present in all cultured cell lines as well as in vivo. The major component of PODs is the PML protein, which was originally identified as the fusion partner of retinoic acid receptor alpha (RARa) in the chromosomal translocation t(15;17) in patients with acute promyelocytic leukaemia (APL) (Kakizuka et al, 1991; Lavau et al, 1991; Goddard et al, 1992). The minor capsid proteins L2 of BPV-1, HPV-11 and HPV-33 have been shown to localise to PODs in the absence of other viral components (Day et al., 1998) and coexpression of BPV-1 12 with BPV-1 E2TA recruits E2 to PODs (Lambert et al, 2000). The presence of L2 in PODs also appears to be associated with the recruitment of the major capsid protein LI, the association of PODs with E2 is dependent on L2 but is independent of LI. The effect of HPV-16 L2 on the functions of HPV-16 E2 and the implications of this interaction to the virus life cycle are discussed. This study showed that HPV-16 L2 has a selective effect on the functions of HPV16 E2. L2 was able to down regulate the transcription transactivation function of E2 in HaCaT, U20S and C33a cells. No effect of L2 on E2 mediated DNA replication was observed. L2 was also able to reduce the level of E2 expression in HaCaT and U20S cells but not in C33a cells. The effect of L2 on E2 expression in HaCaT cells was further investigated by examining E2 mRNA levels and protein half-life. No difference in E2 mRNA or protein half-life was detected in the presence of L2. A series of L2 amino and carboxyl terminal deletion mutants were constructed as GST fusion proteins and GST binding assays were performed which showed that the amino terminus ofL2, even just the first 50 amino acids, was capable of binding with E2. GFP fusion forms of each L2 deletion mutant were also constructed and cellular localisation detected by immunofluorescence. GFP-L2 and all C terminal deletion mutants localised and were retained in the nucleus while the N-terminal deletion mutants localised to both the nucleus and the cytoplasm. Investigation of the effect of L2 deletion mutants on the transcription transactivation function of E2 showed that mutants expressing 1-200 and 150-473 amino acids of L2 do not down regulate function in HaCaT and C33a cells. In HaCaT cells, mutants expressing amino acids 1-50 and 1-100 also did not inhibit E2 function indicating that binding to E2 did not correlate with down regulation of transcription transactivation. Furthermore, only full-length L2 was able to reduce the level of E2 expression

Progressive CD4+ central–memory T cell decline results in CD4+ effector–memory insufficiency and overt disease in chronic SIV infection

Primary simian immunodeficiency virus (SIV) infections of rhesus macaques result in the dramatic depletion of CD4+ CCR5+ effector–memory T (TEM) cells from extra-lymphoid effector sites, but in most infections, an increased rate of CD4+ memory T cell proliferation appears to prevent collapse of effector site CD4+ TEM cell populations and acute-phase AIDS. Eventually, persistent SIV replication results in chronic-phase AIDS, but the responsible mechanisms remain controversial. Here, we demonstrate that in the chronic phase of progressive SIV infection, effector site CD4+ TEM cell populations manifest a slow, continuous decline, and that the degree of this depletion remains a highly significant correlate of late-onset AIDS. We further show that due to persistent immune activation, effector site CD4+ TEM cells are predominantly short-lived, and that their homeostasis is strikingly dependent on the production of new CD4+ TEM cells from central–memory T (TCM) cell precursors. The instability of effector site CD4+ TEM cell populations over time was not explained by increasing destruction of these cells, but rather was attributable to progressive reduction in their production, secondary to decreasing numbers of CCR5− CD4+ TCM cells. These data suggest that although CD4+ TEM cell depletion is a proximate mechanism of immunodeficiency, the tempo of this depletion and the timing of disease onset are largely determined by destruction, failing production, and gradual decline of CD4+ TCM cells

Profound CD4+/CCR5+ T cell expansion is induced by CD8+ lymphocyte depletion but does not account for accelerated SIV pathogenesis

Depletion of CD8+ lymphocytes during acute simian immunodeficiency virus (SIV) infection of rhesus macaques (RMs) results in irreversible prolongation of peak-level viral replication and rapid disease progression, consistent with a major role for CD8+ lymphocytes in determining postacute-phase viral replication set points. However, we report that CD8+ lymphocyte depletion is also associated with a dramatic induction of proliferation among CD4+ effector memory T (TEM) cells and, to a lesser extent, transitional memory T (TTrM) cells, raising the question of whether an increased availability of optimal (activated/proliferating), CD4+/CCR5+ SIV “target” cells contributes to this accelerated pathogenesis. In keeping with this, depletion of CD8+ lymphocytes in SIV− RMs led to a sustained increase in the number of potential CD4+ SIV targets, whereas such depletion in acute SIV infection led to increased target cell consumption. However, we found that the excess CD4+ TEM cell proliferation of CD8+ lymphocyte–depleted, acutely SIV-infected RMs was completely inhibited by interleukin (IL)-15 neutralization, and that this inhibition did not abrogate the rapidly progressive infection in these RMs. Moreover, although administration of IL-15 during acute infection induced robust CD4+ TEM and TTrM cell proliferation, it did not recapitulate the viral dynamics of CD8+ lymphocyte depletion. These data suggest that CD8+ lymphocyte function has a larger impact on the outcome of acute SIV infection than the number and/or activation status of target cells available for infection and viral production

Timing of initiation of anti-retroviral therapy predicts post-treatment control of SIV replication.

One approach to 'functional cure' of HIV infection is to induce durable control of HIV replication after the interruption of antiretroviral therapy (ART). However, the major factors that determine the viral 'setpoint' level after treatment interruption are not well understood. Here we combine data on ART interruption following SIV infection for 124 total animals from 10 independent studies across 3 institutional cohorts to understand the dynamics and predictors of post-treatment viral control. We find that the timing of treatment initiation is an important determinant of both the peak and early setpoint viral levels after treatment interruption. During the first 3 weeks of infection, every day of delay in treatment initiation is associated with a 0.22 log10 copies/ml decrease in post-rebound peak and setpoint viral levels. However, delay in initiation of ART beyond 3 weeks of infection is associated with higher post-rebound setpoint viral levels. For animals treated beyond 3 weeks post-infection, viral load at ART initiation was the primary predictor of post-rebound setpoint viral levels. Potential alternative predictors of post-rebound setpoint viral loads including cell-associated DNA or RNA, time from treatment interruption to rebound, and pre-interruption CD8+ T cell responses were also examined in the studies where these data were available. This analysis suggests that optimal timing of treatment initiation may be an important determinant of post-treatment control of HIV

Lymph nodes as barriers to T-cell rejuvenation in aging mice and nonhuman primates

In youth, thymic involution curtails production of new naive T cells, placing the onus of T-cell maintenance upon secondary lymphoid organs (SLO). This peripheral maintenance preserves the size of the T-cell pool for much of the lifespan, but wanes in the last third of life, leading to a dearth of naive T cells in blood and SLO, and contributing to suboptimal immune defense. Both keratinocyte growth factor (KGF) and sex steroid ablation (SSA) have been shown to transiently increase the size and cellularity of the old thymus. It is less clear whether this increase can improve protection of old animals from infectious challenge. Here, we directly measured the extent to which thymic rejuvenation benefits the peripheral T-cell compartment of old mice and nonhuman primates. Following treatment of old animals with either KGF or SSA, we observed robust rejuvenation of thymic size and cellularity, and, in a reporter mouse model, an increase in recent thymic emigrants (RTE) in the blood. However, few RTE were found in the spleen and even fewer in the lymph nodes, and SSA-treated mice showed no improvement in immune defense against West Nile virus. In parallel, we found increased disorganization and fibrosis in old LN of both mice and nonhuman primates. These results suggest that SLO defects with aging can negate the effects of successful thymic rejuvenation in immune defense.Bowman Professorship in Medical Science; National Institute of Allergy and Infectious Diseases [P01 AG052359, U01 AI82529]; NIH/NIAID; NIH/NIA [P01 052359]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

A short summary of the experimental studies used in the current analysis.

The first column is the identifier as it appears in the text. The more detailed parameters of the studies are presented in the Table A in S1 Text.</p

Impact of protective MHC Mamu-A*01, B*08, and B*17 on the setpoint and peak viral load.

A. Fitting the model defined by Formula (2) to data from macaques with any protective MHC-1 alleles A*01, B*08, B*17 (purple points and curves) and macaques without these known protective alleles (blues points and curves). The curves are allowed to differ by only one parameter (the viral load at day 0 post infection–b0), with the rest of the parameters fitted simultaneously to both datasets. For the data on post-rebound setpoint viral levels, the model allowing different viral levels for animals with protective alleles fits better than the model with all parameters the same. The setpoint viral load is lower in macaques with protective alleles by 0.65 log10 copies/ml (F-test’s p-value = 0.0002, best-fit parameters are in Table F in S1 Text. The best-fit parameters for the model with single b0 are in Table B in S1 Text). B. For data on post-rebound peak viral levels, the best fit model is one in which there is no difference between groups with and without protective alleles (indicated as grey curve) (F-test p-value = 0.61. Best-fit parameters of the model with different b0 are presented in Table F in S1 Text. Best-fit parameters for the model with a single b0 are in Table B in S1 Text). This suggests that the post-rebound peak viral load is not affected by the presence of protective MHC-1 Mamu-A*01, B*08, and B*17 alleles.</p

Duration of post-rebound viral control to <10,000 copies/ml.

In order to compare the duration of post-rebound control, we compared the proportion of each cohort that maintained post-rebound viral loads below 10,000 copies per ml at different times after ATI. The first 30 days after detection of viral rebound are ignored to avoid the initial post-rebound peak of viral load in the analysis of the duration of viral control (shaded grey). A. The proportion of animals maintaining viral control over time post-rebound is higher in groups treated around the optimal time, however the difference is not significant when comparing three groups together (p-values for the log-rank test are shown in the figures). Coloured stars indicate groups where all animals had viral loads greater than 10,000 copies per ml at day 30 post detection. B. Animals that have a low peak of the virus during early rebound are more likely to maintain low viral control over time. C. Having a low viral growth rate during post-treatment rebound is also associated with longer-term control of post-rebound viral loads.</p

Determinants of post-treatment rebound setpoint viral load.

We analysed animals from the three cohorts to understand factors associated with the post-rebound setpoint viral level. Viral load at treatment (A) and peak viral load before treatment (B) where poorly predictive of post-rebound setpoint viral load when data from all treatment times was combined. However, when we divided the animals into those treated before day 20 and after day 20, clear patterns emerged. (C,D) For animals treated before day 20, the viral load at treatment (C) does not predict setpoint viral load at rebound. Instead, the day of treatment (D) is a significant predictor of the setpoint viral load. (E,F). In animals treated after 20 days post-infection, viral load at treatment is a good predictor of the rebound setpoint viral load (E), while the rebound peak viral load is only weakly associated with rebound setpoint (F).</p

Fig 5 -

Reservoir size, reactivation frequency, and early post-rebound viral setpoint: (A, B) Weak or no association of SIV DNA (A) and SIV RNA (B) with the set point viral load at rebound. Linear mixed effect modeling (considering each cohort as a random effect for the slope and intercept of the line) finds no relationship between SIV DNA and RNA with the setpoint viral load we used. Fixed effect slopes are -0.066 and -0.202, p-values for slopes are 0.56 and 0.117 for SIV DNA and SIV RNA respectively (see Table E in S1 Text for the best-fit parameters). The frequency of rebound was directly measured in a subset of animals infected with a barcoded virus (C). Higher frequency of rebound was significantly associated with lower post-rebound setpoint viral load (r = -0.58, p = 0.016). D, E, F To investigate the relationship between time-to-rebound and post-rebound setpoint viral loads, we divided the groups into two, separating those higher or lower than the median post-rebound setpoint viral levels. Time to detection of virus after treatment interruption in monkeys with setpoint viral load less than or equal to median setpoint viral load (blue line) and greater than median (red line) is not different in any of the groups (log-rank test).</p