Precision mapping of gene expression and proteins in the brain using gene editing and barcoded viral vectors

Sammanfattning: The human brain is a masterpiece of intricate design and impeccable functionality. It serves as the ultimate command center for our thoughts, sensations, and actions, which define our very existence. This organ operates flawlessly, with billions of neurons working in perfect harmony to process information, create memories, and regulate our emotions. The brain's neural network is composed of trillions of connections, consisting of interconnected cells that communicate through electrical impulses and chemical signals at remarkable speeds. These connections, also known as synapses, serve as the means of communication that allow for information to travel uninterrupted throughout the brain. This intricate network enables us to think, learn, reason, and react to our surroundings. However, neurological disorders have the potential to disrupt this delicate balance, leading to a range of manifestations. These can include gradual memory erosion in Alzheimer's disease to the slow progression of motor and cognitive impairment in Parkinson's disease. Each condition presents a unique puzzle for scientists and researchers to decipher. The intricate interactions of genes, proteins, and neural circuits create a complex landscape that holds the key to understanding these disorders' origins and potential treatments.In this thesis, we worked on understanding a new type of neuronal communication based on the retrotransposon protein of Arc. The investigation was conducted using a gene editing technique based on the CRISPR/Cas9 system, next-generation sequencing technologies, and refined immunohistochemistry protocol. Using a mouse animal model, our findings reinforced the hypothesis that Arc has the capacity for inter-neuronal transport, as previously proposed in vitro studies. An additional objective of the thesis has been the investigation of molecular changes occurring within the Substantia Nigra throughout the progression of Parkinson's disease. At the core of this disorder's pathophysiology lies the alpha-synuclein protein. With this objective in mind, we developed a single- cell methodology to effectively investigate modifications in gene expression provoked by an overload of alpha- synuclein in animal models of rodents. From this data set, the overarching goal is to train a machine learning able to predict the disease course and to establish possible therapeutic interventions.