Metodi molecolari nello studio della variabilità genetica di Tuber borchii

Tuber borchii (Ascomycota, order Pezizales) is highly valued truffle sold in local markets in Italy. Despite its economic importance, knowledge on its distribution and population variation is scarce. The objective of this work was to investigate the evolutionary forces shaping the genetic structure of this fungus using coalescent and phylogenetic methods to reconstruct the evolutionary history of populations in Italy. To assess population structure, 61 specimens were collected from 11 different Provinces of Italy. Sampling was stratified across hosts and habitats to maximize coverage in native oak and pine stands and both mychorrizae and fruiting bodies were collected. Samples were identified considering anatomo-morphological characters. DNA was extracted and both multilocus (AFLP) and single-locus (18 loci from rDNA, nDNA, and mtDNA) approaches were used to look for polymorphisms. Screening AFLP profiles, both Jaccard and Dice coefficients of similarity were utilized to transform binary matrix into a distance matrix and then to desume Neighbour-Joining trees. Though these are only preliminary examinations, phylogenetic trees were totally concordant with those deriving from single locus analyses. Phylogenetic analyses of the nuclear loci were performed using maximum likelihood with PAUP and a combined phylogenetic inference, using Bayesian estimation with all nuclear gene regions, was carried out. To reconstruct the evolutionary history, we estimated recurrent migration, migration across the history of the sample, and estimated the mutation and approximate age of mutations in each tree using SNAP Workbench. The combined phylogenetic tree using Bayesian estimation suggests that there are two main haplotypes that are difficult to be differentiated on the basis of morphology, of ecological parameters and symbiontic tree. Between these two lineages, that occur in sympatry within T. borchii populations, there is no evidence of recurrent migration. However, migration over the history of the sample was asymmetrical suggesting that isolation was a result of interrupted gene flow followed by range expansion. Low levels of divergence between the haplotypes indicate that there are likely to be two cryptic species within the T. borchii population sampled. Our results suggest that isolation between populations of T. borchii could have led to reproductive isolation between two lineages. This isolation is likely due to sympatric speciation caused by a multiple colonization from different refugia or a recent isolation. In attempting to determinate whether these haplotypes represent separate species or a partition of the same species we applied Biological and Mechanistic species Concepts. Notwithstanding, further analyses are necessary to evaluate if selection favoured premating or post-mating isolation.

Computational investigations of ion conduction mechanisms using enhanced sampling methods

Proper ion channels’ functioning is a prerequisite for a normal cell and disorders involving ion channels, or channelopathies, underlie many human diseases. Long QT syndromes (LQTS) for example may arise from the malfunctioning of hERG channel, caused either by the binding of drugs or mutations in HERG gene. In the first part of this thesis I present a framework to investigate the mechanism of ion conduction through hERG channel. The free energy profile governing the elementary steps of ion translocation in the pore was computed by means of umbrella sampling simulations. Compared to previous studies, we detected a different dynamic behavior: according to our data hERG is more likely to mediate a conduction mechanism which has been referred to as “single-vacancy-like” by Roux and coworkers (2001), rather then a “knock-on” mechanism. The same protocol was applied to a model of hERG presenting the Gly628Ser mutation, found to be cause of congenital LQTS. The results provided interesting insights about the reason of the malfunctioning of the mutant channel. Since they have critical functions in viruses’ life cycle, viral ion channels, such as M2 proton channel, are considered attractive targets for antiviral therapy. A deep knowledge of the mechanisms that the virus employs to survive in the host cell is of primary importance in the identification of new antiviral strategies. In the second part of this thesis I shed light on the role that M2 plays in the control of electrical potential inside the virus, being the charge equilibration a condition required to allow proton influx. The ion conduction through M2 was simulated using metadynamics technique. Based on our results we suggest that a potential anion-mediated cation-proton exchange, as well as a direct anion-proton exchange could both contribute to explain the activity of the M2 channel.

A novel map-matching procedure for low-sampling GPS data with applications to traffic flow analysis

An extensive sample (2%) of private vehicles in Italy are equipped with a GPS device that periodically measures their position and dynamical state for insurance purposes. Having access to this type of data allows to develop theoretical and practical applications of great interest: the real-time reconstruction of traffic state in a certain region, the development of accurate models of vehicle dynamics, the study of the cognitive dynamics of drivers. In order for these applications to be possible, we first need to develop the ability to reconstruct the paths taken by vehicles on the road network from the raw GPS data. In fact, these data are affected by positioning errors and they are often very distanced from each other (~2 Km). For these reasons, the task of path identification is not straightforward. This thesis describes the approach we followed to reliably identify vehicle paths from this kind of low-sampling data. The problem of matching data with roads is solved with a bayesian approach of maximum likelihood. While the identification of the path taken between two consecutive GPS measures is performed with a specifically developed optimal routing algorithm, based on A* algorithm. The procedure was applied on an off-line urban data sample and proved to be robust and accurate. Future developments will extend the procedure to real-time execution and nation-wide coverage.

Local Earthquake Tomography by trans-dimensional Monte Carlo Sampling

In this study a new, fully non-linear, approach to Local Earthquake Tomography is presented. Local Earthquakes Tomography (LET) is a non-linear inversion problem that allows the joint determination of earthquakes parameters and velocity structure from arrival times of waves generated by local sources. Since the early developments of seismic tomography several inversion methods have been developed to solve this problem in a linearized way. In the framework of Monte Carlo sampling, we developed a new code based on the Reversible Jump Markov Chain Monte Carlo sampling method (Rj-McMc). It is a trans-dimensional approach in which the number of unknowns, and thus the model parameterization, is treated as one of the unknowns. I show that our new code allows overcoming major limitations of linearized tomography, opening a new perspective in seismic imaging. Synthetic tests demonstrate that our algorithm is able to produce a robust and reliable tomography without the need to make subjective a-priori assumptions about starting models and parameterization. Moreover it provides a more accurate estimate of uncertainties about the model parameters. Therefore, it is very suitable for investigating the velocity structure in regions that lack of accurate a-priori information. Synthetic tests also reveal that the lack of any regularization constraints allows extracting more information from the observed data and that the velocity structure can be detected also in regions where the density of rays is low and standard linearized codes fails. I also present high-resolution Vp and Vp/Vs models in two widespread investigated regions: the Parkfield segment of the San Andreas Fault (California, USA) and the area around the Alto Tiberina fault (Umbria-Marche, Italy). In both the cases, the models obtained with our code show a substantial improvement in the data fit, if compared with the models obtained from the same data set with the linearized inversion codes.