Marek's disease virus prolongs survival of primary chicken B-cells by inducing a senescence-like phenotype.

Marek's disease virus (MDV) is an alphaherpesvirus that causes immunosuppression and deadly lymphoma in chickens. Lymphoid organs play a central role in MDV infection in animals. B-cells in the bursa of Fabricius facilitate high levels of MDV replication and contribute to dissemination at early stages of infection. Several studies investigated host responses in bursal tissue of MDV-infected chickens; however, the cellular responses specifically in bursal B-cells has never been investigated. We took advantage of our recently established in vitro infection system to decipher the cellular responses of bursal B-cells to infection with a very virulent MDV strain. Here, we demonstrate that MDV infection extends the survival of bursal B-cells in culture. Microarray analyses revealed that most cytokine/cytokine-receptor-, cell cycle- and apoptosis-associated genes are significantly down-regulated in these cells. Further functional assays validated these strong effects of MDV infections on cell cycle progression and thus, B-cell proliferation. In addition, we confirmed that MDV infections protect B-cells from apoptosis and trigger an accumulation of the autophagy marker Lc3-II. Taken together, our data indicate that MDV-infected bursal B-cells show hallmarks of a senescence-like phenotype, leading to a prolonged B-cell survival. This study provides an in-depth analysis of bursal B-cell responses to MDV infection and important insights into how the virus extends the survival of these cells.

In vitro model for lytic replication, latency, and transformation of an oncogenic alphaherpesvirus.

Marek's disease virus (MDV) is an alphaherpesvirus that causes deadly T-cell lymphomas in chickens and serves as a natural small animal model for virus-induced tumor formation. In vivo, MDV lytically replicates in B cells that transfer the virus to T cells in which the virus establishes latency. MDV also malignantly transforms CD4+ T cells with a T(reg) signature, ultimately resulting in deadly lymphomas. No in vitro infection system for primary target cells of MDV has been available due to the short-lived nature of these cells in culture. Recently, we characterized cytokines and monoclonal antibodies that promote survival of cultured chicken B and T cells. We used these survival stimuli to establish a culture system that allows efficient infection of B and T cells with MDV. We were able to productively infect with MDV B cells isolated from spleen, bursa or blood cultured in the presence of soluble CD40L. Virus was readily transferred from infected B to T cells stimulated with an anti-TCRαVß1 antibody, thus recapitulating the in vivo situation in the culture dish. Infected T cells could then be maintained in culture for at least 90 d in the absence of TCR stimulation, which allowed the establishment of MDV-transformed lymphoblastoid cell lines (LCL). The immortalized cells had a signature comparable to MDV-transformed CD4+ α/ß T cells present in tumors. In summary, we have developed a novel in vitro system that precisely reflects the life cycle of an oncogenic herpesivrus in vivo and will allow us to investigate the interaction between virus and target cells in an easily accessible system.

Estimation of dynamic metabolic activity in micro-tissue cultures from sensor recordings with an FEM model.

We estimated the dynamic cell metabolic activity and the distribution of the pH value and oxygen concentration in tissue samples cultured in vitro by using real-time sensor records and a numerical simulation of the underlying reaction-diffusion processes. As an experimental tissue model, we used chicken spleen slices. A finite element method model representing the biochemical processes and including the relevant sensor data was set up. By fitting the calculated results to the measured data, we derived the spatiotemporal values of the pH value, the oxygen concentration and the absolute metabolic activity (extracellular acidification and oxygen uptake rate) of the samples. Notably, the location of the samples in relation to the sensors has a great influence on the detectable metabolic rates. The long-term vitality of the tissue samples strongly depends on their size. We further discuss the benefits and limitations of the model.