MECP2 GENE MUTATIONS IN RETT SYNDROME: PROTEOMIC APPROACH INVESTIGATION ON MOLECULAR MECHANISMS INVOLVED IN OXIDATIVE STRESS

Rett Syndrome (RTT; OMIM 312750) is a neurodevelopmental disorder mainly caused by mutations present in the X-linked methyl-CpG-binding 2 (MECP2) gene. Clinical manifestations of this syndrome are complex and with distinct severity’s degree; for instance, patients can have autistic-like behavior, loss of acquired speech with impaired motor skills and cardiac problems. Moreover, the correlation between specific MECP2 mutations and clinical phenotypes are not clear yet. Interesting, different genotypes can cause patient’s phenotype differently. Omics approaches, and among them proteomics, can play a fundamental role in exploring molecular mechanisms and shed light in the correlation genotype - phenotype from a molecular point of view. The aim of this work of thesis was the investigation on oxidative stress (OS) response pathways in RTT linked to specific MECP2 mutations with the use of proteomics and bioinformatic approaches. Primary fibroblasts were collected from RTT patients having R133C and R255X mutations and from healthy donors (HC). Thus, once it was performed a clustering of primary dermal fibroblasts based on their MECP2 gene mutations, different experiments were performed to investigate difference in OS, such as ROS and 4- HNE assay. Data showed distinct behavior of RTT fibroblasts in comparison to HC, but no significant differences were observed between the two diverse RTT fibroblasts bearing different mutations. The mutations R133C and R255X are reported to exhibited distinct clinical severity score, for this reason, a shotgun proteomics analysis, in particular a label free quantification (LFQ) mass spectrometry (MS) based, was applied in order to investigate the proteome profiles of RTT and HC fibroblasts. The bioinformatics elaboration allowed to obtain information on altered molecular pathways from a qualitative and quantitative point of view. Therefore, it was possible to evidence a preliminary correlation between RTT genotype and phenotype, focusing on those proteins involved in OS molecular mechanisms. Proteomics data were confirmed by molecular biology assays. In conclusion, proteomics, bioinformatics, and molecular biology assays were employed, enabling to study uncover phenotypic consequences linked to distinct MECP2 gene mutations. These findings confirm the high heterogeneity among RTT patients and contribute to a better understanding of this syndrome.