Staff

Alessandra M. Mezzelani

Primo Ricercatore
E-Mail

alessandramaria.mezzelani@cnr.it

PHONE

+390226422606

LOCATION

Segrate

ROOM (floor/number)

6/04

My research focuses on multi-omics approaches to elucidate gene–environment interactions in complex disorders, with particular emphasis on autism and the microbiota–gut–brain axis. I am the CNR PI of the European GEMMA (genome, environment, microbiome, and metabolome in autism) project. I also participate in AIRC-funded research on transcriptional alterations in tumour and immune cells in EGFR-mutant lung cancer, as well as in the Cariplo–Telethon project investigating the role of TTI2 in autosomal recessive intellectual developmental disorder. I collaborate with the Policlinico of Milan on single-cell transcriptomic studies of metabolic dysfunction-associated steatotic liver disease. I have devised an original “comparative genomics and gene network analysis” approach to identify novel genes associated with human traits and disorders, including social behaviour and longevity. I am also actively involved in CNR initiatives promoting communication, inclusion, and accessibility in research and public engagement. I coordinate the Translational Bioinformatics Laboratory, which integrates experimental and computational approaches by generating omics data and validating bioinformatic analyses, models, and predictive tools. The laboratory includes the Single Cell Analysis (SCA) platform (10x Genomics).

Nucleic acids isolation from different and complex matrices (e.g. cells, tissues, blood, fecis, saliva) and library preparation for high-throughput sequencing.

Comparative genomics and gene network analysis to infer novel genes associated with specific human traits

Transcriptomic analysis of cancer cells, stem cells, organoids, human and murine tissues in disease models

Sample and library preparation for high-throughput sequencing (bulk, single-cell, small and non-coding RNAs)

Study of the microbiome in the onset of complex diseases

Study of the microbiota-host-exposome interactions to elucidate how microbial dynamics and metabolite profiles influence host physiology and disease mechanisms