Biological systems are composed of many interacting components - in ecological communities, populations of different species. Though the first models for interacting populations date to almost a century ago, the role of species interactions in regulating the response to perturbations, and in shaping community composition, is yet not well understood. Models for ecological communities have so far concentrated on small systems. Here I show that, on the other hand, large ecological communities display simple and consistent patterns that can be understood as the result of elementary stochastic processes. Using random matrix techniques, I study how the properties of the interaction networks influence the stability of ecological communities and the persistence of the populations. I conclude with a list of challenges that need to be overcome to have a more complete understanding of statical and dynamical properties of large ecosystems.

A general understanding of the complex phenomenon of protein evolution requires the accurate description of the constraints that define the subspace of proteins with mutations that do not appreciably reduce the fitness of the organism. Such constraints can have multiple origins, and here such constrained evolutionary trajectories are represented by a Markovian process throughout a set of protein-like structures artificially constructed to be topological inter- mediates between the structure of two natural occurring proteins. The number and type of intermediate steps defines how constrained the total evolutionary process is. The Caterpillar coarse-grained protein representation allows for both quantitative protein design and folding, making it the perfect tool for constructing the evolutionary trajectories. In fact, with computer simulations it is shown that, for a large set of real protein structures, the model produces designed sequences with similar physical properties to the corresponding natural occurring sequences. Ultimately, the Caterpillar model is unique in the…

Bringing the idea of integrating manmade oxidoreductases and allied proteins into cell and organelle to replace or augment component parts of metabolic and bioenergetic machinery, has some way to go to before benefit to mankind can be expected. Nevertheless, once realized, the impact on solar energy conversion into chemical fuels, on remediating hemorrhagic traumas, or on correcting respiratory dysfunction of genetic or aging origins will be considerable. We combine first-principles light- and oxidant/reductant substrate-driven electron transfer engineering common to natural oxidoreductase proteins with first-principles α-helical protein design to reproduce oxidoreductase and related functions in structurally transparent man-made proteins we call maquettes. Maquettes promote diverse natural functions including light-capture and multistep energy transfer and efficient charge-separation, diffusive inter-protein electron-transfer, and O2 ligation and transport. Maquettes prove to be biocompatible: bacterial expression is coupled with biogenesis and ligation of cofactors such as hemes B and C, bilins and indications of chlorophyll. Maquettes can be…

Protein-protein interactions are of fundamental importance in virtually all cellular processes. Our group has focused on the analysis and prediction of these interactions through the combined use of structural data and evolutionary information. In a study of over 1,000 couples of homologous interfaces, we uncovered astonishing plasticity in the way interface structure evolves. We also identified some rather invariant features which provide tracks for extracting meaningful information from multiple sequence alignments of binding partners. On these bases, we developed a protein docking method which improves the prediction of protein interfaces and was used in a number of protein docking cases related to the maintenance of genome stability. Understanding how interfaces co-evolve opens new perspectives for the design of novel protein binders which we shall also discussed.

In living related kidney transplant recipients, current strategies to improve graft outcome consider information at the HLA locus. Given that more than 50 % of fully HLA matched kidneys fail at 10 years post-transplant, we investigated whether information outside of the HLA locus can also impact long-term graft function (LTGF). We used a new method using DNA exome sequencing from kidney graft recipients (R) and their living donors (D) to determine R/D mismatches at the amino acid level over entire exomes. We estimated the number of amino acid mismatches in transmembrane proteins, more likely to be recognized as foreign by the recipient's immune system, and designated this tally as the allogenomics mismatch score (AMS). The AMS can be measured prior to transplantation for potential donor and recipient pairs and could be used in graft attribution algorithms. We examined the degree of relationship between the AMS and post-transplantation kidney allograft function using mixed…

Cancer cells are highly proliferative. Drugs that impair cell proliferation – antimitotic drugs – are indeed quite effective in treating cancer. Their mechanism of action is quite well understood. Several antimitotic drugs impair microtubule polymerization and thus do not allow cells to segregate their chromosomes. Cells arrested in their division cycle, however, will not remain arrested forever. Some will die and some will adapt resuming proliferation. The choice between these two fates is stochastic, with virtually identical cells going different paths. With a combination of mathematical models and live-cell imaging, we have analyzed the phenomenon of adaptation, and we have identified a possible source of variability that contributes to determine cell fate under constant drug treatment.

DNA damage and ensuing DNA damage response activation are key players in tumor suppression and ageing. I will discuss how DDR impacts on them and on the biology of stem cells. Finally, I will propose a novel and unprecedented role of non-coding RNAs in the modulation of the DNA damage response.