Understanding the role of microglial extracellular vesicles (EVs) in neuroinflammation spreading: an in vitro study

Neuroinflammation is a crucial pathogenic mechanism that commonly underlies most neurodegenerative diseases. Microglia, the immune cells of the brain, play a critical role that changes depending on the stage of neuropathology: at early phases of brain diseases microglia display the neuroprotective phenotype which is switched to the classically activated pro-inflammatory subtype at later stages, contributing to neurodegeneration. The microglial phenotypic shift is characterized by a change in the release of bioactive molecules both soluble and through extracellular vesicles. Our in vitro studies aim to understand whether different types of activation could determine change in vesicles content, in particular miRNAs, and whether this could influence the activation state of control microglial cells. Microglial polarization has been induced in two different in vitro models: N9, microglial murine cell line, have been treated by using LPS towards a proinflammatory/neurotoxic phenotype or ATP towards antinflammatory/neuroprotective status; HMC3, human microglial cell line, have been activated using IFN-+ATP. We demonstrated that conditioned media/exosomes obtained from donor microglia were able to promote a pro-inflammatory phenotype in control cells, leading us to prove the existence of a neuroinflammation spreading process mediated by extracellular vesicles of microglia with a crucial role of miRNAs. Increased expression of miRNA-34a observed in N9 model underlines a possible contribution in the diffusion of proinflammatory activation of microglia. Thus, we tried to downregulate miR-34a expression using cleaving sequences of anti-mir-34a DNAzyme delivered by DNA nanostructures aimed to confirm the involvement of miR-34a in microglia polarization towards the neurotoxic phenotype. In conclusion, this thesis work reveal a new inflammation spreading mechanism that involves release of vesicles containing specific cargos by donor polarized microglia, particularly miRNAs, able to influence the phenotypic shift in unpolarized microglia: this process deserves to be deeply investigated as potential therapeutic target to counteract neurodegenerative diseases.

Uncovering the encoding and transmission of behaviourally relevant information in neural activity

Most cognitive functions require the encoding and routing of information across distributed networks of brain regions. Information propagation is typically attributed to physical connections existing between brain regions, and contributes to the formation of spatially correlated activity patterns, known as functional connectivity. While structural connectivity provides the anatomical foundation for neural interactions, the exact manner in which it shapes functional connectivity is complex and not yet fully understood. Additionally, traditional measures of directed functional connectivity only capture the overall correlation between neural activity, and provide no insight on the content of transmitted information, limiting their ability in understanding neural computations underlying the distributed processing of behaviorally-relevant variables. In this work, we first study the relationship between structural and functional connectivity in simulated recurrent spiking neural networks with spike timing dependent plasticity. We use established measures of time-lagged correlation and overall information propagation to infer the temporal evolution of synaptic weights, showing that measures of dynamic functional connectivity can be used to reliably reconstruct the evolution of structural properties of the network. Then, we extend current methods of directed causal communication between brain areas, by deriving an information-theoretic measure of Feature-specific Information Transfer (FIT) quantifying the amount, content and direction of information flow. We test FIT on simulated data, showing its key properties and advantages over traditional measures of overall propagated information. We show applications of FIT to several neural datasets obtained with different recording methods (magneto and electro-encephalography, spiking activity, local field potentials) during various cognitive functions, ranging from sensory perception to decision making and motor learning. Overall, these analyses demonstrate the ability of FIT to advance the investigation of communication between brain regions, uncovering the previously unaddressed content of directed information flow.