Project description:Usutu virus (USUV) is a neurotropic flavivirus closely related to West Nile virus (WNV). Its enzootic cycle mainly involves mosquitoes and birds. Human infection can occur with occasional, but sometimes severe, neurological complications. Since its emergence and spread in Europe over the last two decades, USUV has been linked to significant avian outbreaks, especially among Passeriformes, including European blackbirds (Turdus merula). Strikingly, no in vivo avian model exists so far to study this arbovirus. The domestic canary (Serinus canaria) is a passerine, which is considered as a highly susceptible model of infection by WNV. Here, we experimentally challenged domestic canaries with two different doses of USUV. All inoculated birds presented detectable amounts of viral RNA in the blood and RNA shedding via feathers and droppings during the early stages of the infection, as determined by RT-qPCR. Mortality occurred in both infected groups (1/5 and 2/5, respectively) and was not necessarily correlated to a pure neurological disease. Subsequent analyses of samples from dead birds showed histopathological changes and virus tropism mimicking those reported in naturally infected birds. A robust seroconversion followed the infection in almost all the surviving canaries. Altogether, these results demonstrate that domestic canaries constitute an interesting experimental model for the study of USUV pathogenesis and transmission.
Project description:Song production in songbirds is controlled by a network of nuclei distributed across several brain regions, which drives respiratory and vocal motor systems to generate sound. We built a model for birdsong production, whose variables are the average activities of different neural populations within these nuclei of the song system. We focus on the predictions of respiratory patterns of song, because these can be easily measured and therefore provide a validation for the model. We test the hypothesis that it is possible to construct a model in which (1) the activity of an expiratory related (ER) neural population fits the observed pressure patterns used by canaries during singing, and (2) a higher forebrain neural population, HVC, is sparsely active, simultaneously with significant motor instances of the pressure patterns. We show that in order to achieve these two requirements, the ER neural population needs to receive two inputs: a direct one, and its copy after being processed by other areas of the song system. The model is capable of reproducing the measured respiratory patterns and makes specific predictions on the timing of HVC activity during their production. These results suggest that vocal production is controlled by a circular network rather than by a simple top-down architecture.
Project description:Within the overall project, we performed a set of microarrays to validate RNAseq data. In this data set, we compare the expression data of song nuclei to the optical tectrum dissected from adult canaries housed at long day cycles to identify nuclei specific genes.