Ugo Bastolla

Although a physicist by training, I have always been interested in Biology, and I am convinced that only a multidisciplinary approach allow understanding the complexity of life and that biology strongly benefits from mathematical formalism resting on statistical mechanics on one side and on evolution on the other side. In this context, proteins are particularly interesting as a bridge between the two disciplines.
After my diploma work in Physics in Rome with Prof. Luca Peliti on a model of neutral evolution, I did my PhD thesis with Prof. Giorgio Parisi (2021 Physics Nobel prize), studying random Boolean networks as a null model of genetic regulation. Subsequently, I worked in Germany with Prof. Peter Grassberger, contributing to develop methods for Monte Carlo simulations of model proteins, which stimulated me to investigate protein folding stability and its relationship with protein evolution, which is now my main research interest. I developed this line as an independent researcher in the groups of Prof. Walter Knapp in FU-Berlin, Prof. Michael Lässig at the Max-Planck-Institute, Prof. Alfonso Valencia in the Center for Astrobiology in Madrid and finally in the Bioinformatics Unit of the CBMSO directed by Prof. Angel R. Ortiz, which I came to direct after he sadly and prematurely passed away.
In this field, I developed simple mathematical models that estimate the folding stability of proteins both with respect to unfolding and with respect to incorrect folding (misfolding, rarely taken into account) and I applied them to study protein evolution. I focused on the mutual relationship between folding stability and evolutionary parameters (mutation bias, population size), detecting selection for biophysical properties, and developing stability-aware substitution models that improve phylogenetic inference. I also investigated the occurrence and evolution of disordered proteins in the Centrosome.
Another subject of my interest is protein dynamics. I developed an elastic network model in torsion angle space that allows characterizing protein function by identifying conformation changes favored by natural selection and computing dynamical couplings between pairs of residues. These two lines have now merged in the structure and stability constrained protein evolution model (SSCPE) for phylogenetic inference, the subject of the present proposal.
In collaboration with experimental groups, I studied chromatin structure, developing a method for classifying chromatin states and studying their relationship with the processes of genome transcription and replication.
My other main field of interest is theoretical ecology, in particular the search of the ecosystem properties that favor the maintenance of biodiversity in the face of environmental changes. I contributed to develop structural stability as the mathematical framework that allows addressing this question, characterizing under which circumstances mutualistic interactions enhance structural stability and biodiversity. This work directed my interest to study interactions in bacterial communities, where there are many instances of cooperative interactions, and I developed a method to identify them from metagenomic data.