Studio molecolare dei meccanismi dell'autoincompatibilità gametofitica in pero europeo (Pyrus communis)

Self-incompatibility (SI) systems have evolved in many flowering plants to prevent self-fertilization and thus promote outbreeding. Pear and apple, as many of the species belonging to the Rosaceae, exhibit RNase-mediated gametophytic self-incompatibility, a widespread system carried also by the Solanaceae and Plantaginaceae. Pear orchards must for this reason contain at least two different cultivars that pollenize each other; to guarantee an efficient cross-pollination, they should have overlapping flowering periods and must be genetically compatible. This compatibility is determined by the S-locus, containing at least two genes encoding for a female (pistil) and a male (pollen) determinant. The female determinant in the Rosaceae, Solanaceae and Plantaginaceae system is a stylar glycoprotein with ribonuclease activity (S-RNase), that acts as a specific cytotoxin in incompatible pollen tubes degrading cellular RNAs. Since its identification, the S-RNase gene has been intensively studied and the sequences of a large number of alleles are available in online databases. On the contrary, the male determinant has been only recently identified as a pollen-expressed protein containing a F-box motif, called S-Locus F-box (abbreviated SLF or SFB). Since F-box proteins are best known for their participation to the SCF (Skp1 - Cullin - F-box) E3 ubiquitine ligase enzymatic complex, that is involved in protein degradation through the 26S proteasome pathway, the male determinant is supposed to act mediating the ubiquitination of the S-RNases, targeting them for the degradation in compatible pollen tubes. Attempts to clone SLF/SFB genes in the Pyrinae produced no results until very recently; in apple, the use of genomic libraries allowed the detection of two F-box genes linked to each S haplotype, called SFBB (S-locus F-Box Brothers). In Japanese pear, three SFBB genes linked to each haplotype were cloned from pollen cDNA. The SFBB genes exhibit S haplotype-specific sequence divergence and pollen-specific expression; their multiplicity is a feature whose interpretation is unclear: it has been hypothesized that all of them participate in the S-specific interaction with the RNase, but it is also possible that only one of them is involved in this function. Moreover, even if the S locus male and female determinants are the only responsible for the specificity of the pollen-pistil recognition, many other factors are supposed to play a role in GSI; these are not linked to the S locus and act in a S-haplotype independent manner. They can have a function in regulating the expression of S determinants (group 1 factors), modulating their activity (group 2) or acting downstream, in the accomplishment of the reaction of acceptance or rejection of the pollen tube (group 3). This study was aimed to the elucidation of the molecular mechanism of GSI in European pear (Pyrus communis) as well as in the other Pyrinae; it was divided in two parts, the first focusing on the characterization of male determinants, and the second on factors external to the S locus. The research of S locus F-box genes was primarily aimed to the identification of such genes in European pear, for which sequence data are still not available; moreover, it allowed also to investigate about the S locus structure in the Pyrinae. The analysis was carried out on a pool of varieties of the three species Pyrus communis (European pear), Pyrus pyrifolia (Japanese pear), and Malus × domestica (apple); varieties carrying S haplotypes whose RNases are highly similar were chosen, in order to check whether or not the same level of similarity is maintained also between the male determinants. A total of 82 sequences was obtained, 47 of which represent the first S-locus F-box genes sequenced from European pear. The sequence data strongly support the hypothesis that the S locus structure is conserved among the three species, and presumably among all the Pyrinae; at least five genes have homologs in the analysed S haplotypes, but the number of F-box genes surrounding the S-RNase could be even greater. The high level of sequence divergence and the similarity between alleles linked to highly conserved RNases, suggest a shared ancestral polymorphism also for the F-box genes. The F-box genes identified in European pear were mapped on a segregating population of 91 individuals from the cross 'Abbé Fétel' × 'Max Red Bartlett'. All the genes were placed on the linkage group 17, where the S locus has been placed both in pear and apple maps, and resulted strongly associated to the S-RNase gene. The linkage with the RNase was perfect for some of the F-box genes, while for others very rare single recombination events were identified. The second part of this study was focused on the research of other genes involved in the SI response in pear; it was aimed on one side to the identification of genes differentially expressed in compatible and incompatible crosses, and on the other to the cloning and characterization of the transglutaminase (TGase) gene, whose role may be crucial in pollen rejection. For the identification of differentially expressed genes, controlled pollinations were carried out in four combinations (self pollination, incompatible, half-compatible and fully compatible cross-pollination); expression profiles were compared through cDNA-AFLP. 28 fragments displaying an expression pattern related to compatibility or incompatibility were identified, cloned and sequenced; the sequence analysis allowed to assign a putative annotation to a part of them. The identified genes are involved in very different cellular processes or in defense mechanisms, suggesting a very complex change in gene expression following the pollen/pistil recognition. The pool of genes identified with this technique offers a good basis for further study toward a better understanding of how the SI response is carried out. Among the factors involved in SI response, moreover, an important role may be played by transglutaminase (TGase), an enzyme involved both in post-translational protein modification and in protein cross-linking. The TGase activity detected in pear styles was significantly higher when pollinated in incompatible combinations than in compatible ones, suggesting a role of this enzyme in the abnormal cytoskeletal reorganization observed during pollen rejection reaction. The aim of this part of the work was thus to identify and clone the pear TGase gene; the PCR amplification of fragments of this gene was achieved using primers realized on the alignment between the Arabidopsis TGase gene sequence and several apple EST fragments; the full-length coding sequence of the pear TGase gene was then cloned from cDNA, and provided a precious tool for further study of the in vitro and in vivo action of this enzyme.

Investigating the role of single point mutations in the human proteome: a computational study

In the post genomic era with the massive production of biological data the understanding of factors affecting protein stability is one of the most important and challenging tasks for highlighting the role of mutations in relation to human maladies. The problem is at the basis of what is referred to as molecular medicine with the underlying idea that pathologies can be detailed at a molecular level. To this purpose scientific efforts focus on characterising mutations that hamper protein functions and by these affect biological processes at the basis of cell physiology. New techniques have been developed with the aim of detailing single nucleotide polymorphisms (SNPs) at large in all the human chromosomes and by this information in specific databases are exponentially increasing. Eventually mutations that can be found at the DNA level, when occurring in transcribed regions may then lead to mutated proteins and this can be a serious medical problem, largely affecting the phenotype. Bioinformatics tools are urgently needed to cope with the flood of genomic data stored in database and in order to analyse the role of SNPs at the protein level. In principle several experimental and theoretical observations are suggesting that protein stability in the solvent-protein space is responsible of the correct protein functioning. Then mutations that are found disease related during DNA analysis are often assumed to perturb protein stability as well. However so far no extensive analysis at the proteome level has investigated whether this is the case. Also computationally methods have been developed to infer whether a mutation is disease related and independently whether it affects protein stability. Therefore whether the perturbation of protein stability is related to what it is routinely referred to as a disease is still a big question mark. In this work we have tried for the first time to explore the relation among mutations at the protein level and their relevance to diseases with a large-scale computational study of the data from different databases. To this aim in the first part of the thesis for each mutation type we have derived two probabilistic indices (for 141 out of 150 possible SNPs): the perturbing index (Pp), which indicates the probability that a given mutation effects protein stability considering all the “in vitro” thermodynamic data available and the disease index (Pd), which indicates the probability of a mutation to be disease related, given all the mutations that have been clinically associated so far. We find with a robust statistics that the two indexes correlate with the exception of all the mutations that are somatic cancer related. By this each mutation of the 150 can be coded by two values that allow a direct comparison with data base information. Furthermore we also implement computational methods that starting from the protein structure is suited to predict the effect of a mutation on protein stability and find that overpasses a set of other predictors performing the same task. The predictor is based on support vector machines and takes as input protein tertiary structures. We show that the predicted data well correlate with the data from the databases. All our efforts therefore add to the SNP annotation process and more importantly found the relationship among protein stability perturbation and the human variome leading to the diseasome.

On-line adaptive visual tracking

Visual tracking is the problem of estimating some variables related to a target given a video sequence depicting the target. Visual tracking is key to the automation of many tasks, such as visual surveillance, robot or vehicle autonomous navigation, automatic video indexing in multimedia databases. Despite many years of research, long term tracking in real world scenarios for generic targets is still unaccomplished. The main contribution of this thesis is the definition of effective algorithms that can foster a general solution to visual tracking by letting the tracker adapt to mutating working conditions. In particular, we propose to adapt two crucial components of visual trackers: the transition model and the appearance model. The less general but widespread case of tracking from a static camera is also considered and a novel change detection algorithm robust to sudden illumination changes is proposed. Based on this, a principled adaptive framework to model the interaction between Bayesian change detection and recursive Bayesian trackers is introduced. Finally, the problem of automatic tracker initialization is considered. In particular, a novel solution for categorization of 3D data is presented. The novel category recognition algorithm is based on a novel 3D descriptors that is shown to achieve state of the art performances in several applications of surface matching.

Cache-aware development of high integrity real-time systems

Cost, performance and availability considerations are forcing even the most conservative high-integrity embedded real-time systems industry to migrate from simple hardware processors to ones equipped with caches and other acceleration features. This migration disrupts the practices and solutions that industry had developed and consolidated over the years to perform timing analysis. Industry that are confident with the efficiency/effectiveness of their verification and validation processes for old-generation processors, do not have sufficient insight on the effects of the migration to cache-equipped processors. Caches are perceived as an additional source of complexity, which has potential for shattering the guarantees of cost- and schedule-constrained qualification of their systems. The current industrial approach to timing analysis is ill-equipped to cope with the variability incurred by caches. Conversely, the application of advanced WCET analysis techniques on real-world industrial software, developed without analysability in mind, is hardly feasible. We propose a development approach aimed at minimising the cache jitters, as well as at enabling the application of advanced WCET analysis techniques to industrial systems. Our approach builds on:(i) identification of those software constructs that may impede or complicate timing analysis in industrial-scale systems; (ii) elaboration of practical means, under the model-driven engineering (MDE) paradigm, to enforce the automated generation of software that is analyzable by construction; (iii) implementation of a layout optimisation method to remove cache jitters stemming from the software layout in memory, with the intent of facilitating incremental software development, which is of high strategic interest to industry. The integration of those constituents in a structured approach to timing analysis achieves two interesting properties: the resulting software is analysable from the earliest releases onwards - as opposed to becoming so only when the system is final - and more easily amenable to advanced timing analysis by construction, regardless of the system scale and complexity.

Machine-learning methods for structure prediction of β-barrel membrane proteins

Different types of proteins exist with diverse functions that are essential for living organisms. An important class of proteins is represented by transmembrane proteins which are specifically designed to be inserted into biological membranes and devised to perform very important functions in the cell such as cell communication and active transport across the membrane. Transmembrane β-barrels (TMBBs) are a sub-class of membrane proteins largely under-represented in structure databases because of the extreme difficulty in experimental structure determination. For this reason, computational tools that are able to predict the structure of TMBBs are needed. In this thesis, two computational problems related to TMBBs were addressed: the detection of TMBBs in large datasets of proteins and the prediction of the topology of TMBB proteins. Firstly, a method for TMBB detection was presented based on a novel neural network framework for variable-length sequence classification. The proposed approach was validated on a non-redundant dataset of proteins. Furthermore, we carried-out genome-wide detection using the entire Escherichia coli proteome. In both experiments, the method significantly outperformed other existing state-of-the-art approaches, reaching very high PPV (92%) and MCC (0.82). Secondly, a method was also introduced for TMBB topology prediction. The proposed approach is based on grammatical modelling and probabilistic discriminative models for sequence data labeling. The method was evaluated using a newly generated dataset of 38 TMBB proteins obtained from high-resolution data in the PDB. Results have shown that the model is able to correctly predict topologies of 25 out of 38 protein chains in the dataset. When tested on previously released datasets, the performances of the proposed approach were measured as comparable or superior to the current state-of-the-art of TMBB topology prediction.

Fattori eziologici della Sindrome del Tunnel Carpale: una revisione sistematica con meta-analisi degli studi analitici

OBIETTIVO: sintetizzare le evidenze disponibili sulla relazione tra i fattori di rischio (personali e lavorativi) e l’insorgenza della Sindrome del Tunnel Carpale (STC). METODI: è stata condotta una revisione sistematica della letteratura su database elettronici considerando gli studi caso-controllo e di coorte. Abbiamo valutato la qualità del reporting degli studi con la checklist STROBE. Le stime studio-specifiche sono state espresse come OR (IC95%) e combinate con una meta-analisi condotta con un modello a effetti casuali. La presenza di eventuali bias di pubblicazione è stata valutata osservando l’asimmetria del funnel plot e con il test di Egger. RISULTATI: Sono stati selezionati 29 studi di cui 19 inseriti nella meta-analisi: 13 studi caso-controllo e 6 di coorte. La meta-analisi ha mostrato un aumento significativo di casi di STC tra i soggetti obesi sia negli studi caso-controllo [OR 2,4 (1,9-3,1); I(2)=70,7%] che in quelli di coorte [OR 2,0 (1,6-2,7); I(2)=0%]. L'eterogeneità totale era significativa (I(2)=59,6%). Risultati simili si sono ottenuti per i diabetici e soggetti affetti da malattie della tiroide. L’esposizione al fumo non era associata alla STC sia negli studi caso-controllo [OR 0,7 (0,4-1,1); I(2)=83,2%] che di coorte [OR 0,8 (0,6-1,2); I(2)=45,8%]. A causa delle molteplici modalità di valutazione non è stato possibile calcolare una stima combinata delle esposizioni professionali con tecniche meta-analitiche. Dalla revisione, è risultato che STC è associata con: esposizione a vibrazioni, movimenti ripetitivi e posture incongrue di mano-polso. CONCLUSIONI: I risultati della revisione sistematica confermano le evidenze dell'esistenza di un'associazione tra fattori di rischio personali e STC. Nonostante la diversa qualità dei dati sull'esposizione e le differenze degli effetti dei disegni di studio, i nostri risultati indicano elementi di prova sufficienti di un legame tra fattori di rischio professionali e STC. La misurazione dell'esposizione soprattutto per i fattori di rischio professionali, è un obiettivo necessario per studi futuri.