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Generation of AAV-based, arrayed genetic libraries for in vivo functional selection: an innovative approach to identify secreted factors and microRNAs against degenerative disorders (FunSel)
Date du début: 1 avr. 2010, Date de fin: 31 mars 2015 PROJET  TERMINÉ 

A foremost health problem stems from the burden of degenerative diseases, including heart failure, neurodegeneration, retinal degeneration and diabetes, essentially linked to the aging of the human population and the incapacity of post-mitotic tissues to undergo efficient repair. This is an ambitious, highly innovative project aimed at developing an in vivo selection procedure, based on gene transfer of two genetic libraries cloned into Adeno-Associated Virus (AAV)-based vectors, for the identification of novel secreted factors or microRNAs providing benefit against various degenerative diseases. Two arrayed libraries will be generated, one coding for ~1,300 cDNAs from the mouse secretome, the other for all known microRNAs (~800 genes). Pools of vectors from each library will be obtained with serotypes suitable for in vivo transduction of different organs. The vectors will be injected in a series of mouse models of degenerative disorders involving damage to cardiomyocytes,, neurodegeneration, retinal degeneration and loss of beta-cells in the pancreas. The degenerative conditions will drive the selection for secreted factors or miRNA putatively preventing cell apoptosis, enhancing residual cell function or, in the best possible scenario, promoting tissue regeneration. This in vivo selection approach, which is supported by very encouraging preliminary results, has never been attempted before and is rendered possible by the property of AAV vectors to be produced at high titers, infect tissues at high multiplicity, persist in the transduced cells for prolonged period of times and efficiently express their transgenes in vivo. In addition to its final goal of identifying novel biotherapeutics, the project entails the successful achievement of several intermediate objectives and is expected to extend both technology and knowledge beyond the state-of-the art.

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