Viral load in tissues during the early and chronic phase of non-pathogenic SIVagm infection

Antiinflammatory profiles during primary SIV infection in African green monkeys are associated with protection against AIDS

T cell activation levels in HIV infection are predictive of AIDS progression. We searched for the immunological correlates of protection against disease progression by studying the early stages of nonpathogenic SIV infection in African green monkeys (SIVagm). The African green monkeys (AGMs) displayed high peak viremias and a transient decline in levels of blood CD4(+) and CD8(+) T cells between days 5 and 17 after infection. A concomitant increase in levels of CD4(+)DR(+), CD8(+)DR(+), and CD8(+)CD28(-) cells was detected. After the third week, T cell activation returned to baseline levels, which suggested a protective downregulation of T cell activation. A very early (24 hours after infection) and strong induction of TGF-beta1 and FoxP3 expression was detected and correlated with increases in levels of CD4(+)CD25(+) and CD8(+)CD25(+) T cells. This was followed by a significant increase in levels of IL-10, whereas IFN-gamma gene upregulation was more transient, and levels of TNF-alpha and MIP-1alpha/beta transcripts did not increase in either blood or tissues. The profiles were significantly different during primary SIV infection in macaques (SIVmac); that is, there was a delayed increase in IL-10 levels accompanied by moderate and persistent increases in TGF-beta levels. Together, our data show that SIVagm infection is associated with an immediate antiinflammatory environment and suggest that TGF-beta may participate in the generation of Tregs, which may prevent an aberrant chronic T cell hyperactivation.

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.