9 resultados para Origin of tetralophodont structure

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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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.

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My PhD project has been focused on the study of the pulsating variable stars in two ultra-faint dwarf spheroidal satellites of the Milky Way, namely, Leo IV and Hercules; and in two fields of the Large Magellanic Cloud (namely, the Gaia South Ecliptic Pole calibration field, and the 30 Doradus region) that were repeatedly observed in the KS band by the VISTA Magellanic Cloud (VMC, PI M.R. Cioni) survey of the Magellanic System.

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The Reverse Vaccinology (RV) approach allows using genomic information for the delineation of new protein-based vaccines starting from an in silico analysis. The first powerful example of the application of the RV approach is given by the development of a protein-based vaccine against serogroup B Meningococcus. A similar approach was also used to identify new Staphylococcus aureus vaccine candidates, including the ferric hydroxamate-binding lipoprotein FhuD2. S. aureus is a widespread human pathogen, which employs various different strategies for iron uptake, including: (i) siderophore-mediated iron acquisition using the endogenous siderophores staphyloferrin A and B, (ii) siderophore-mediated iron acquisition using xeno-siderophores (the pathway exploited by FhuD2) and (iii) heme-mediated iron acquisition. In this work the high resolution crystal structure of FhuD2 in the iron (III)-siderophore-bound form was determined. FhuD2 belongs to the Periplasmic Binding Protein family (PBP ) class III, and is principally formed by two globular domains, at the N- and C-termini of the protein, that make up a cleft where ferrichrome-iron (III) is bound. The N- and C-terminal domains, connected by a single long α-helix, present Rossmann-like folds, showing a β-stranded core and an α-helical periphery, which do not undergo extensive structural rearrangement when they interact with the ligand, typical of class III PBP members. The structure shows that ferrichrome-bound iron does not come directly into contact with the protein; rather, the metal ion is fully coordinated by six oxygen donors of the hydroxamate groups of three ornithine residues, which, with the three glycine residues, make up the peptide backbone of ferrichrome. Furthermore, it was found that iron-free ferrichrome is able to subtract iron from transferrin. This study shows for the first time the structure of FhuD2, which was found to bind to siderophores ,and that the protein plays an important role in S. aureus colonization and infection phases.

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From the late 1980s, the automation of sequencing techniques and the computer spread gave rise to a flourishing number of new molecular structures and sequences and to proliferation of new databases in which to store them. Here are presented three computational approaches able to analyse the massive amount of publicly avalilable data in order to answer to important biological questions. The first strategy studies the incorrect assignment of the first AUG codon in a messenger RNA (mRNA), due to the incomplete determination of its 5' end sequence. An extension of the mRNA 5' coding region was identified in 477 in human loci, out of all human known mRNAs analysed, using an automated expressed sequence tag (EST)-based approach. Proof-of-concept confirmation was obtained by in vitro cloning and sequencing for GNB2L1, QARS and TDP2 and the consequences for the functional studies are discussed. The second approach analyses the codon bias, the phenomenon in which distinct synonymous codons are used with different frequencies, and, following integration with a gene expression profile, estimates the total number of codons present across all the expressed mRNAs (named here "codonome value") in a given biological condition. Systematic analyses across different pathological and normal human tissues and multiple species shows a surprisingly tight correlation between the codon bias and the codonome bias. The third approach is useful to studies the expression of human autism spectrum disorder (ASD) implicated genes. ASD implicated genes sharing microRNA response elements (MREs) for the same microRNA are co-expressed in brain samples from healthy and ASD affected individuals. The different expression of a recently identified long non coding RNA which have four MREs for the same microRNA could disrupt the equilibrium in this network, but further analyses and experiments are needed.

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The aim of this thesis, included within the THESEUS project, is the development of a mathematical model 2DV two-phase, based on the existing code IH-2VOF developed by the University of Cantabria, able to represent together the overtopping phenomenon and the sediment transport. Several numerical simulations were carried out in order to analyze the flow characteristics on a dike crest. The results show that the seaward/landward slope does not affect the evolution of the flow depth and velocity over the dike crest whereas the most important parameter is the relative submergence. Wave heights decrease and flow velocities increase while waves travel over the crest. In particular, by increasing the submergence, the wave height decay and the increase of the velocity are less marked. Besides, an appropriate curve able to fit the variation of the wave height/velocity over the dike crest were found. Both for the wave height and for the wave velocity different fitting coefficients were determined on the basis of the submergence and of the significant wave height. An equation describing the trend of the dimensionless coefficient c_h for the wave height was derived. These conclusions could be taken into consideration for the design criteria and the upgrade of the structures. In the second part of the thesis, new equations for the representation of the sediment transport in the IH-2VOF model were introduced in order to represent beach erosion while waves run-up and overtop the sea banks during storms. The new model allows to calculate sediment fluxes in the water column together with the sediment concentration. Moreover it is possible to model the bed profile evolution. Different tests were performed under low-intensity regular waves with an homogeneous layer of sand on the bottom of a channel in order to analyze the erosion-deposition patterns and verify the model results.

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Italy has a preeminent rank in kiwifruit industry, being the first exporter and the second largest producer after China. However, in the last years kiwifruit yields and the total cultivated area considerably decreased, due to the pandemic spread of the bacterial canker caused by Pseudomonas syringae pv. actinidiae (Psa). Several climatic conditions and cultural practices affect the development of the bacterial canker. This research work focused on the impact of agricultural practices and microclimate conditions on the incidence and epidemiology of Psa in the orchard. Therefore, the effect of fertilization, irrigation, use of bio-regulators, rootstock, training system and pruning were examined. The effect of different tunnel systems was analyzed as well, to study the plant-pathogen interaction. Considering the importance of insects as vectors in other pathosystems, the role of Metcalfa pruinosa in the spread of the bacterial canker was investigated in controlled conditions. In addition, quality and storage properties of fruits from infected plants were assessed. The study of all these aspects of the agronomic practices is useful to define a strategy to limit the bacterial diffusion in the orchard. Overall, excess nitrogen fertilization, water stress, stagnant water supplies, pruning before summer and the high number of Metcalfa pruinosa increased the Psa incidence. In contrast, tunnel covers may be useful for the control of the disease, with special attention to the kind of material.

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Multiple Myeloma (MM) is a hematologic cancer with heterogeneous and complex genomic landscape, where Copy Number Alterations (CNAs) play a key role in the disease's pathogenesis and prognosis. It is of biological and clinical interest to study the temporal occurrence of early alterations, as they play a disease "driver" function by deregulating key tumor pathways. This study presents an innovative bioinformatic tools suite created for harmonizing and tracing the origin of CNAs throughout the evolutionary history of MM. To this aim, large cohorts of newly-diagnosed MM (NDMM, N=1582) and Smoldering-MM (SMM, N=282) were aggregated. The tools developed in this study enable the harmonization of CNAs as obtained from different genomic platforms in such a way that a high statistical power can be obtained. By doing so, the high numerosity of those cohorts was harnessed for the identification of novel genes characterized as "driver" (NFKB2, NOTCH2, MAX, EVI5 and MYC-ME2-enhancer), and the generation of an innovative timing model, implemented with a statistical method to introduce confidence intervals in the CNAs-calls. By applying this model on both NDMM and SMM cohorts, it was possible to identify specific CNAs (1q(CKS1B)amp, 13q(RB1)del, 11q(CCND1)amp and 14q(MAX)del) and categorize them as "early"/ "driver" events. A high level of precision was guaranteed by the narrow confidence intervals in the timing estimates. These CNAs were proposed as critical MM alterations, which play a foundational role in the evolutionary history of both SMM and NDMM. Finally, a multivariate survival model was able to identify the independent genomic alterations with the greatest effect on patients’ survival, including RB1-del, CKS1B-amp, MYC-amp, NOTCH2-amp and TRAF3-del/mut. In conclusion, the alterations that were identified as both "early-drivers” and correlated with patients’ survival were proposed as biomarkers that, if included in wider survival models, could provide a better disease stratification and an improved prognosis definition.

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Introgression of domestic cat genes into European wildcat (Felis silvestris silvestris) populations and reduction of wildcats’ range in Europe, leaded by habitat loss and fragmentation, are considered two of the main conservation problems for this endangered feline. This thesis addressed the questions related with the artificial hybridization and populations’ fragmentation, using a conservation genetics perspective. We combined the use of highly polymorphic loci, Bayesian statistical inferences and landscape analyses tools to investigate the origin of the geographic-genetic substructure of European wildcats (Felis silvestris silvestris) in Italy and Europe. The genetic variability of microsatellites evidenced that European wildcat populations currently distributed in Italy differentiated in, and expanded from two distinct glacial refuges during the Last Glacial Maximum. The genetic and geographic substructure detected between the eastern and western sides of the Apennine ridge, resulted by adaptation to specific ecological conditions of the Mediterranean habitats. European wildcat populations in Europe are strongly structured into 5 geographic-genetic macro clusters corresponding to: the Italian peninsular & Sicily; Balkans & north-eastern Italy; Germany eastern; central Europe; and Iberian Peninsula. Central European population might have differentiated in the extra-Mediterranean Würm ice age refuge areas (Northern Alps, Carpathians, and the Bulgarian mountain systems), while the divergence among and within the southern European populations might have resulted by the Pleistocene bio geographical framework of Europe, with three southern refugia localized in the Balkans, Italian Peninsula and Iberia Peninsula. We further combined the use of most informative autosomal SNPs with uniparental markers (mtDNA and Y-linked) for accurately detecting parental genotypes and levels of introgressive hybridization between European wild and domestic cats. A total of 11 hybrids were identified. The presence of domestic mitochondrial haplotypes shared with some wild individuals led us to hypnotize the possibility that ancient introgressive events might have occurred and that further investigation should be recommended.