Characterization of the Caspr2 and NLGN2 ligands: a proteomic and biochemical approach

Autism Spectrum Disorder (ASD) is a range of early-onset conditions classified as neurodevelopmental disorders, characterized by deficits in social interactions and communication, as well as by restricted interest and repetitive behaviors. Among the proteins associated with this spectrum of disease there are Caspr2, α-NRXN1, NLGN1-4. Caspr2 is involved in the clustering of K+ channels at the juxtaparanodes, where it is proposed to bind TAG-1. Recent works reported a synaptic localization of Caspr2, but little is know on its role in this compartment. NRXNs and their ligand NLGNs, instead, have a well-defined role in the formation and maintenance of synapses. Among the neuroligins, NLGN2 binds NRXNs with the lowest affinity, suggesting that it could have other not yet characterized ligands. The aim of this work was to better characterize the binding of Caspr2 to TAG-1 and to identify new potential binding partner for Caspr2 and NLGN2. Unexpectedly, using Isothermal Titration Calorimetry and co-immunoprecipitation experiments the direct association of the first two proteins could not be verified and the results indicate that the first evidences reporting it were biased by false-positive artifacts. These findings, together with the uncharacterized synaptic localization of Caspr2, made the identification of new potential binding partners for this protein necessary. To find new proteins that associate with Caspr2 and NLGN2, affinity chromatography in tandem with mass spectrometry experiments were performed. Interestingly, about 25 new potential partners were found for these two proteins and NLGN1, that was originally included as a control: 5 of those, namely SFRP1, CLU, APOE, CNTN1 and TNR, were selected for further investigations. Only the association of CLU to NLGN2 was confirmed. In the future, screenings of the remaining candidates have to be carried out and the functional role for the proposed NLGN2-CLU complex has to be studied.

Motor control system in Parkinson’s disease: a modeling approach

Parkinson’s disease is a neurodegenerative disorder due to the death of the dopaminergic neurons of the substantia nigra of the basal ganglia. The process that leads to these neural alterations is still unknown. Parkinson’s disease affects most of all the motor sphere, with a wide array of impairment such as bradykinesia, akinesia, tremor, postural instability and singular phenomena such as freezing of gait. Moreover, in the last few years the fact that the degeneration in the basal ganglia circuitry induces not only motor but also cognitive alterations, not necessarily implicating dementia, and that dopamine loss induces also further implications due to dopamine-driven synaptic plasticity got more attention. At the present moment, no neuroprotective treatment is available, and even if dopamine-replacement therapies as well as electrical deep brain stimulation are able to improve the life conditions of the patients, they often present side effects on the long term, and cannot recover the neural loss, which instead continues to advance. In the present thesis both motor and cognitive aspects of Parkinson’s disease and basal ganglia circuitry were investigated, at first focusing on Parkinson’s disease sensory and balance issues by means of a new instrumented method based on inertial sensor to provide further information about postural control and postural strategies used to attain balance, then applying this newly developed approach to assess balance control in mild and severe patients, both ON and OFF levodopa replacement. Given the inability of levodopa to recover balance issues and the new physiological findings than underline the importance in Parkinson’s disease of non-dopaminergic neurotransmitters, it was therefore developed an original computational model focusing on acetylcholine, the most promising neurotransmitter according to physiology, and its role in synaptic plasticity. The rationale of this thesis is that a multidisciplinary approach could gain insight into Parkinson’s disease features still unresolved.