Three dimensional seismic imaging and earthquake locations in a complex, segmented fault region in Southern Apennines (Italy)

The southern Apennines of Italy have been experienced several destructive earthquakes both in historic and recent times. The present day seismicity, characterized by small-to-moderate magnitude earthquakes, was used like a probe to obatin a deeper knowledge of the fault structures where the largest earthquakes occurred in the past. With the aim to infer a three dimensional seismic image both the problem of data quality and the selection of a reliable and robust tomographic inversion strategy have been faced. The data quality has been obtained to develop optimized procedures for the measurements of P- and S-wave arrival times, through the use of polarization filtering and to the application of a refined re-picking technique based on cross-correlation of waveforms. A technique of iterative tomographic inversion, linearized, damped combined with a strategy of multiscale inversion type has been adopted. The retrieved P-wave velocity model indicates the presence of a strong velocity variation along a direction orthogonal to the Apenninic chain. This variation defines two domains which are characterized by a relatively low and high velocity values. From the comparison between the inferred P-wave velocity model with a portion of a structural section available in literature, the high velocity body was correlated with the Apulia carbonatic platforms whereas the low velocity bodies was associated to the basinal deposits. The deduced Vp/Vs ratio shows that the ratio is lower than 1.8 in the shallower part of the model, while for depths ranging between 5 km and 12 km the ratio increases up to 2.1 in correspondence to the area of higher seismicity. This confirms that areas characterized by higher values are more prone to generate earthquakes as a response to the presence of fluids and higher pore-pressures.

Computational methods for the analysis of protein structure and function

The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.

B-type cytochromes of the DOMON domain superfamily (Novel redox elements of plant plasma membrane)

The aim of the present study is understanding the properties of a new group of redox proteins having in common a DOMON-type domain with characteristics of cytochromes b. The superfamily of proteins containing a DOMON of this type includes a few protein families. With the aim of better characterizing this new protein family, the present work addresses both a CyDOM protein (a cytochrome b561) and a protein only comprised of DOMON(AIR12), both of plant origin. Apoplastic ascorbate can be regenerated from monodehydroascorbate by a trans-plasma membrane redox system which uses cytosolic ascorbate as a reductant and comprises a high potential cytochrome b. We identified the major plasma membrane (PM) ascorbate-reducible b-type cytochrome of bean (Phaseolus vulgaris) and soybean (Glycine max) hypocotyls as orthologs of Arabidopsis auxin-responsive gene air12. The protein, which is glycosylated and glycosylphosphatidylinositol-anchored to the external side of the PM in vivo, was expressed in Pichia pastoris in a recombinant form, lacking the glycosylphosphatidylinositol-modification signal, and purified from the culture medium. Recombinant AIR12 is a soluble protein predicted to fold into a β-sandwich domain and belonging to the DOMON superfamily. It is shown to be a b-type cytochrome with a symmetrical α-band at 561 nm, to be fully reduced by ascorbate and fully oxidized by monodehydroascorbate. Redox potentiometry suggests that AIR12 binds two high-potential hemes (Em,7 +135 and +236 mV). Phylogenetic analyses reveal that the auxin-responsive genes AIR12 constitute a new family of plasma membrane b-type cytochromes specific to flowering plants. Although AIR12 is one of the few redox proteins of the PM characterized to date, the role of AIR12 in trans-PM electron transfer would imply interaction with other partners which are still to be identified. Another part of the present project was aimed at understanding of a soybean protein comprised of a DOMON fused with a well-defined b561 cytochrome domain (CyDOM). Various bioinformatic approaches show this protein to be composed of an N-terminal DOMON followed by b561 domain. The latter contains five transmembrane helices featuring highly conserved histidines, which might bind haem groups. The CyDOM has been cloned and expressed in the yeast Pichia pastoris, and spectroscopic analyses have been accomplished on solubilized yeast membranes. CyDOM clearly reveal the properties of b-type cytochrome. The results highlight the fact that CyDOM is clearly able to lead an electron flux through the plasmamembrane. Voltage clamp experiments demonstrate that Xenopus laevis oocytes transformed with CyDOM of soybean exhibit negative electrical currents in presence of an external electron acceptor. Analogous investigations were carried out with SDR2, a CyDOM of Drosophila melanogaster which shows an electron transport capacity even higher than plant CyDOM. As quoted above, these data reinforce those obtained in plant CyDOM on the one hand, and on the other hand allow to attribute to SDR2-like proteins the properties assigned to CyDOM. Was expressed in Regenerated tobacco roots, transiently transformed with infected a with chimeral construct GFP: CyDOM (by A. rhizogenes infection) reveals a plasmamembrane localization of CyDOM both in epidermal cells of the elongation zone of roots and in root hairs. In conclusion. Although the data presented here await to be expanded and in part clarified, it is safe to say they open a new perspective about the role of this group of proteins. The biological relevance of the functional and physiological implications of DOMON redox domains seems noteworthy, and it can but increase with future advances in research. Beyond the very finding, however interesting in itself, of DOMON domains as extracellular cytochromes, the present study testifies to the fact that cytochrome proteins containing DOMON domains of the type of “CyDOM” can transfer electrons through membranes and may represent the most important redox component of the plasmamembrane as yet discovered.

Molecular analysis of special type breast carcinomas

The project was developed into three parts: the analysis of p63 isoform in breast tumours; the study of intra-tumour eterogeneicity in metaplastic breast carcinoma; the analysis of oncocytic breast carcinoma. p63 is a sequence-specific DNA-binding factor, homologue of the tumour suppressor and transcription factor p53. The human p63 gene is composed of 15 exons and transcription can occur from two distinct promoters: the transactivating isoforms (TAp63) are generated by a promoter upstream of exon 1, while the alternative promoter located in intron 3 leads to the expression of N-terminal truncated isoforms (ΔNp63). It has been demonstrated that anti-p63 antibodies decorate the majority of squamous cell carcinomas of different organs; moreover tumours with myoepithelial differentiation of the breast show nuclear p63 expression. Two new isoforms have been described with the same sequence as TAp63 and ΔNp63 but lacking exon 4: d4TAp63 and ΔNp73L, respectively. Purpose of the study was to investigate the molecular expression of N-terminal p63 isoforms in benign and malignant breast tissues. In the present study 40 specimens from normal breast, benign lesions, DIN/DCIS, and invasive carcinomas were analyzed by immunohistochemistry and RT-PCR (Reverse Transcriptase-PCR) in order to disclose the patterns of p63 expression. We have observed that the full-length isoforms can be detected in non neoplastic and neoplastic lesions, while the short isoforms are only present in the neoplastic cells of invasive carcinomas. Metaplastic carcinomas of the breast are a heterogeneous group of neoplasms which exhibit varied patterns of metaplasia and differentiation. The existence of such non-modal populations harbouring distinct genetic aberrations may explain the phenotypic diversity observed within a given tumour. Intra-tumour morphological heterogeneity is not uncommon in breast cancer and it can often be appreciated in metaplastic breast carcinomas. Aim of this study was to determine the existence of intra-tumour genetic heterogeneity in metaplastic breast cancers and whether areas with distinct morphological features in a given tumour might be underpinned by distinct patterns of genetic aberrations. 47 cases of metaplastic breast carcinomas were retrieved. Out of the 47 cases, 9 had areas that were of sufficient dimensions to be independently microdissected. Our results indicate that at least some breast cancers are composed of multiple non-modal populations of clonally related cells and provide direct evidence that at least some types of metaplastic breast cancers are composed of multiple non-modal clones harbouring distinct genetic aberrations. Oncocytic tumours represent a distinctive set of lesions with typical granular cytoplasmatic eosinophilia of the neoplastic cells. Only rare example of breast oncocytic carcinomas have been reported in literature and the incidence is probably underestimated. In this study we have analysed 33 cases of oncocytic invasive breast carcinoma of the breast, selected according to morphological and immunohistochemical criteria. These tumours were morphologically classified and studied by immunohistochemistry and aCGH. We have concluded that oncocytic breast carcinoma is a morphologic entity with distinctive ultrastructural and histological features; immunohistochemically is characterized by a luminal profile, it has a frequency of 19.8%, has not distinctive clinical features and, at molecular level, shows a specific constellation of genetic aberration.

InSAR deformation measurements of the earthquake cycle in transcurrent tectonic domains, analytical and analog modeling

I applied the SBAS-DInSAR method to the Mattinata Fault (MF) (Southern Italy) and to the Doruneh Fault System (DFS) (Central Iran). In the first case, I observed limited internal deformation and determined the right lateral kinematic pattern with a compressional pattern in the northern sector of the fault. Using the Okada model I inverted the observed velocities defining a right lateral strike slip solution for the MF. Even if it fits the data within the uncertainties, the modeled slip rate of 13-15 mm yr-1 seems too high with respect to the geological record. Concerning the Western termination of DFS, SAR data confirms the main left lateral transcurrent kinematics of this fault segment, but reveal a compressional component. My analytical model fits successfully the observed data and quantifies the slip in ~4 mm yr-1 and ~2.5 mm yr-1 of pure horizontal and vertical displacement respectively. The horizontal velocity is compatible with geological record. I applied classic SAR interferometry to the October–December 2008 Balochistan (Central Pakistan) seismic swarm; I discerned the different contributions of the three Mw > 5.7 earthquakes determining fault positions, lengths, widths, depths and slip distributions, constraining the other source parameters using different Global CMT solutions. A well constrained solution has been obtained for the 09/12/2008 aftershock, whereas I tested two possible fault solutions for the 28-29/10/08 mainshocks. It is not possible to favor one of the solutions without independent constraints derived from geological data. Finally I approached the study of the earthquake-cycle in transcurrent tectonic domains using analog modeling, with alimentary gelatins like crust analog material. I successfully joined the study of finite deformation with the earthquake cycle study and sudden dislocation. A lot of seismic cycles were reproduced in which a characteristic earthquake is recognizable in terms of displacement, coseismic velocity and recurrence time.

OPA1 isoforms and protein domains in the rescue of mitochondrial dysfunctions

Mutations in OPA1 gene have been identified in the majority of patients with Dominant Optic Atrophy (DOA), a blinding disease, and the syndromic form DOA-plus. OPA1 protein is a mitochondrial GTPase involved in various mitochondrial functions, present in humans in eight isoforms, resulting from alternative splicing and proteolytic processing. In this study we have investigated the specific role of each isoform through expression in OPA-/- MEFs, by evaluating their ability to improve the defective mitochondrial phenotypes. All isoforms were able to rescue the energetic efficiency, mitochondrial DNA (mtDNA) content and cristae integrity, but only the presence of both long and short forms could recover the mitochondrial morphology. In order to identify the OPA1 protein domains crucial for its functions, we selected and modified the isoform 1, shown to be one of the most efficient in preserving mitochondrial phenotype, to express three specific OPA1 variants, namely: one with a different N-terminus portion, one unable to generate short form owing to deletion of S1 cleavage site and one with a defective GTPase domain. We demonstrated that the simultaneous presence of the N- and C-terminus of OPA1 was essential for the mtDNA maintenance; a cleavable isoform generating s-forms was necessary to completely rescue the energetic competence and the presence of the C-terminus was sufficient to partially recover the cristae ultrastructure. Lastly, several pathogenic OPA1 mutations were inserted in MEF clones and the biochemical features investigated, to correlate the defective phenotypes with the clinical severity of patients. Our results clearly indicate that this cell model reflects very well the clinical characteristics of the patients, and therefore can be proposed as an useful tool to shed light on the pathomechanism underlying DOA.

Learning Methods and Algorithms for Semantic Text Classification across Multiple Domains

Information is nowadays a key resource: machine learning and data mining techniques have been developed to extract high-level information from great amounts of data. As most data comes in form of unstructured text in natural languages, research on text mining is currently very active and dealing with practical problems. Among these, text categorization deals with the automatic organization of large quantities of documents in priorly defined taxonomies of topic categories, possibly arranged in large hierarchies. In commonly proposed machine learning approaches, classifiers are automatically trained from pre-labeled documents: they can perform very accurate classification, but often require a consistent training set and notable computational effort. Methods for cross-domain text categorization have been proposed, allowing to leverage a set of labeled documents of one domain to classify those of another one. Most methods use advanced statistical techniques, usually involving tuning of parameters. A first contribution presented here is a method based on nearest centroid classification, where profiles of categories are generated from the known domain and then iteratively adapted to the unknown one. Despite being conceptually simple and having easily tuned parameters, this method achieves state-of-the-art accuracy in most benchmark datasets with fast running times. A second, deeper contribution involves the design of a domain-independent model to distinguish the degree and type of relatedness between arbitrary documents and topics, inferred from the different types of semantic relationships between respective representative words, identified by specific search algorithms. The application of this model is tested on both flat and hierarchical text categorization, where it potentially allows the efficient addition of new categories during classification. Results show that classification accuracy still requires improvements, but models generated from one domain are shown to be effectively able to be reused in a different one.