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Molecular parasitology Laboratory

Parassitologia molecolare

Referents: Prof. Davide Sassera, Dr. Michele Castelli

Co-workers: Umberto Postiglione (research fellow), Gherard Batisti Biffignandi (PhD student), Tiago Nardi (PhD student), Greta Bellinzona (PhD student), Beatrice Bisaglia (PhD student), Emanuela Clementi (technician)

The research activities of the Molecular Parasitology group are focused on the study of interactions between organisms of different species, of a mutualistic, commensalistic or parasitic character. We intend to characterize these systems from a functional and evolutionary point of view, as well as to provide interpretative bases useful for prevention and treatment of infections of medical/veterinary relevance. These studies use an integrated approach, including experimental and analytical techniques such as genomics, transcriptomics, machine learning, molecular biology, optical and electron microscopy. 

The main lines of research, divided into two main thematic areas, are listed below.


Integrated evolutionary analyzes on symbiotic bacteria

- evolutionary origin, dynamics and molecular-cellular mechanisms involved in the symbiosis of the Midichloria bacterium with Ixodidae ticks and in particular for their localization within the mitochondria

- origin and evolutionary differentiation of intracellular associations between bacteria and eukaryotes, with particular reference to the order of Rickettsiales (Alphaproteobacteria)

- origin and evolution of nutritional mutualistic symbiosis between bacteria and arthropods, such as ticks and bedbugs


"Omics" analysis on pathogens and parasites

- Development and use of innovative methods for monitoring vector arthropods, such as molecular screening techniques, environmental DNA, metagenomics, metatrascriptomics and ecological and multi-omics modeling

-genomic epidemiology of prokaryotic pathogenic organisms/parasites (e.g. Klebsiella, Staphylococcus, Listeria) and eukaryotes (e.g. Candida, Cryptosporidium), aimed at outbreak reconstruction and evolutionary analysis of virulence and resistance

- development of predictive models and bioinformatics pipelines for bacterial genomics, in particular for the prediction of determinants of antibiotic resistance, reconstruction of epidemic events and genomic plasticity in the acquisition of resistance and virulence factors