Quantitative considerations to gather maximum information from viral growth efficiency studies: the example of polyomavirus type BK (BKV).

This short communication shows how the application of simple mathematical formulae allows researchers to extract maximum information from viral growth efficiency studies at virtually no additional costs (in terms of time or money), thus improving the comparability of results (growth rates, replicative capacities, efficacies of antivirals) between in vitro and in vivo growth efficiency studies. This could help in elucidating kinetic links between the molecular basis of virus function and clinical findings.

Polyomavirus BK with rearranged noncoding control region emerge in vivo in renal transplant patients and increase viral replication and cytopathology.

Immunosuppression is required for BK viremia and polyomavirus BK-associated nephropathy (PVAN) in kidney transplants (KTs), but the role of viral determinants is unclear. We examined BKV noncoding control regions (NCCR), which coordinate viral gene expression and replication. In 286 day-matched plasma and urine samples from 129 KT patients with BKV viremia, including 70 with PVAN, the majority of viruses contained archetypal (ww-) NCCRs. However, rearranged (rr-) NCCRs were more frequent in plasma than in urine samples (22 vs. 4%; P < 0.001), and were associated with 20-fold higher plasma BKV loads (2.0 x 10(4)/ml vs. 4.4 x 10(5)/ml; P < 0.001). Emergence of rr-NCCR in plasma correlated with duration and peak BKV load (R(2) = 0.64; P < 0.001). This was confirmed in a prospective cohort of 733 plasma samples from 227 patients. For 39 PVAN patients with available biopsies, rr-NCCRs were associated with more extensive viral replication and inflammation. Cloning of 10 rr-NCCRs revealed diverse duplications or deletions in different NCCR subregions, but all were sufficient to increase early gene expression, replication capacity, and cytopathology of recombinant BKV in vitro. Thus, rr-NCCR BKV emergence in plasma is linked to increased replication capacity and disease in KTs.

Cytomegalovirus and polyomavirus BK posttransplant.

Virus replication and progression to disease in transplant patients is determined by patient-, graft- and virus-specific factors. This complex interaction is modulated by the net state of immunosuppression and its impact on virus-specific cellular immunity. Due to the increasing potency of immunosuppressive regimens, graft rejections have decreased, but susceptibility to infections has increased. Therefore, cytomegalovirus (CMV) remains the most important viral pathogen posttransplant despite availability of effective antiviral drugs and validated strategies for prophylactic, preemptive and therapeutic intervention. CMV replication can affect almost every organ system, with frequent recurrences and increasing rates of antiviral resistance. Together with indirect long-term effects, CMV significantly reduces graft and patient survival after solid organ and hematopoietic stem cell transplantation. The human polyomavirus called BK virus (BKV), on the other hand, only recently surfaced as pathogen with organ tropism largely limited to the reno-urinary tract, manifesting as polyomavirus-associated nephropathy in kidney transplant and hemorrhagic cystitis in hematopoetic stem cell transplant patients. No licensed anti-polyoma viral drugs are available, and treatment relies mainly on improving immune functions to regain control over BKV replication. In this review, we discuss diagnostic and therapeutic aspects of CMV and BKV replication and disease posttransplantation.

Viral dynamics in transplant patients: implications for disease.

Viral infections cause substantial morbidity and mortality in transplant patients. Quantifying viral loads is widely appreciated as a direct means to diagnose and monitor the course of viral infections. Recent studies indicate that the kinetics of viral load changes rather than single viral load measurements better correlate with organ involvement. In this Review, we will summarise the current knowledge regarding the kinetics of viruses relevant to transplantation including cytomegalovirus, Epstein-Barr virus, the herpes viruses 6 and 7, hepatitis C virus, GB virus C, adenovirus, and the emerging human polyomavirus type BK. We discuss the implications of viral kinetics for organ pathology as well as for the evaluation of antiviral interventions in transplant patients.

HIV replication elicits little cytopathic effects in vivo: analysis of surrogate markers for virus production, cytotoxic T cell response and infected cell death.

Several potential mechanisms for viral destruction of HIV-infected cells have been described. The hypothesis was examined that if HIV were cytopathic, a positive relation between the in vivo virus production or CTL activity and infected cell death should be observed. In a regression analysis no significant relation was found between surrogate markers for in vivo virus production or the virus-specific CTL response and death rates of productively infected cells. In a subgroup of patients the hypothesis is rejected that HIV replication elicits a large (R(2) > 0.25) cytopathic effect (P < 0.05, N = 36). It is concluded that HIV replication elicits little cytopathic effect in productively infected cells and that CD4(+) T lymphocytes are eroded by other mechanisms.

Rapid dynamics of polyomavirus type BK in renal transplant recipients.

BACKGROUND: Polyomavirus type BK-associated nephropathy (PVAN) is an emerging cause of early renal transplant failure. No specific antiviral treatment has been established. Current interventions rely on improving immune functions by reducing immunosuppression. In patients with PVAN, a high BK virus (BKV) load is detectable in plasma. However, the relationship between BKV replication and disease is not well understood. METHODS: In a retrospective analysis of BKV plasma load in renal transplant recipients undergoing allograft nephrectomy (n = 3) or changes in immunosuppressive regimen (n = 12), we calculated viral clearance rates and generation times and estimated the loss of BKV-infected renal cells. RESULTS: After nephrectomy, BKV clearance was fast (viral half-life [t(1/2)], 1-2 h) or moderately fast (t(1/2), 20-38 h), depending on the sampling density, but it was independent of continued immunosuppressive regimens. After changing immunosuppressive regimens, BKV was cleared with a t(1/2) of 6 h-17 days. Using the basic reproductive ratio, the efficacies of intervention ranged from 7% to 83% (mean, 28%; median, 22%). CONCLUSION: The results emphasize that high-level BKV replication is a major pathogenetic factor that may have implications for genome rearrangements, immune evasion, and antiviral resistance.

Contrasting B cell- and T cell-based protective vaccines.

A substantial research effort is devoted to the development of vaccines based on T cells. Such a vaccine would provide a means to protect against infection with HIV and stop the current pandemic. Here we investigate the possibility to develop a protective T cell-based vaccine. We do this by means of a mathematical model which describes the dynamics of a pathogen and the immune system in the early stages of infection. We compare an immune response that is near immediate--as is the case for a humoral response--with that of a response in which the effector cells have to be formed from precursor cells--as occurs in T cell responses. The latter applies to a T cell-based vaccine. A near immediate response is associated with a threshold number of effector cells above which an infection cannot take hold. For a T cell-based vaccine this threshold increases with the amount of antigen the immune system is exposed to. For small initial doses, as one would naturally expect to occur, this gives rise to impractically large thresholds. Thus, although a T cell vaccine might work against a high dose exposure, it might fail when exposed against to a low-dose exposure. This limits, we argue, the efficacy of T cell-based vaccines.

Spatial models of virus-immune dynamics.

To date, the majority of theoretical models describing the dynamics of infectious diseases in vivo are based on the assumption of well-mixed virus and cell populations. Because many infections take place in solid tissues, spatially structured models represent an important step forward in understanding what happens when the assumption of well-mixed populations is relaxed. Here, we explore models of virus and virus-immune dynamics where dispersal of virus and immune effector cells was constrained to occur locally. The stability properties of our spatial virus-immune dynamics models remained robust under almost all biologically plausible dispersal schemes, regardless of their complexity. The various spatial dynamics were compared to the basic non-spatial dynamics and important differences were identified: When space was assumed to be homogeneous, the dynamics generated by non-spatial and spatially structured models differed substantially at the peak of the infection. Thus, non-spatial models may lead to systematic errors in the estimates of parameters underlying acute infection dynamics. When space was assumed to be heterogeneous, spatial coupling not only changed the equilibrium properties of the uncoupled populations but also equalized the dynamics and thereby reduced the likelihood of dynamic elimination of the infection. In line with experimental and clinical observations, long-lasting oscillation periods were virtually absent. When source-sink dynamics were considered, the long-term outcome of the infection depended critically on the degree of spatial coupling. The infection collapsed when emigration from source sites became too large. Finally, we discuss the implications of spatially structured models on medical treatment of infectious diseases, and note that a huge gap exists in data accurately describing infection dynamics in solid tissues.

Glancing behind virus load variation in HIV-1 infection.

Although the steady-state virus load during HIV-1 infection is remarkably stable within a patient, it displays variation over several orders of magnitude between patients. Despite intensive research, the host and virus factors that are responsible for the observed variation remain poorly understood. Comparison of model predictions with clinical data suggests that most of the variation in steady-state virus load between patients reflects variation of the net rate at which activated CD4 cells are produced.