Analyzing the dependence structure of microarray data: a copula–based approach

The main aim of this Ph.D. dissertation is the study of clustering dependent data by means of copula functions with particular emphasis on microarray data. Copula functions are a popular multivariate modeling tool in each field where the multivariate dependence is of great interest and their use in clustering has not been still investigated. The first part of this work contains the review of the literature of clustering methods, copula functions and microarray experiments. The attention focuses on the K–means (Hartigan, 1975; Hartigan and Wong, 1979), the hierarchical (Everitt, 1974) and the model–based (Fraley and Raftery, 1998, 1999, 2000, 2007) clustering techniques because their performance is compared. Then, the probabilistic interpretation of the Sklar’s theorem (Sklar’s, 1959), the estimation methods for copulas like the Inference for Margins (Joe and Xu, 1996) and the Archimedean and Elliptical copula families are presented. In the end, applications of clustering methods and copulas to the genetic and microarray experiments are highlighted. The second part contains the original contribution proposed. A simulation study is performed in order to evaluate the performance of the K–means and the hierarchical bottom–up clustering methods in identifying clusters according to the dependence structure of the data generating process. Different simulations are performed by varying different conditions (e.g., the kind of margins (distinct, overlapping and nested) and the value of the dependence parameter ) and the results are evaluated by means of different measures of performance. In light of the simulation results and of the limits of the two investigated clustering methods, a new clustering algorithm based on copula functions (‘CoClust’ in brief) is proposed. The basic idea, the iterative procedure of the CoClust and the description of the written R functions with their output are given. The CoClust algorithm is tested on simulated data (by varying the number of clusters, the copula models, the dependence parameter value and the degree of overlap of margins) and is compared with the performance of model–based clustering by using different measures of performance, like the percentage of well–identified number of clusters and the not rejection percentage of H0 on . It is shown that the CoClust algorithm allows to overcome all observed limits of the other investigated clustering techniques and is able to identify clusters according to the dependence structure of the data independently of the degree of overlap of margins and the strength of the dependence. The CoClust uses a criterion based on the maximized log–likelihood function of the copula and can virtually account for any possible dependence relationship between observations. Many peculiar characteristics are shown for the CoClust, e.g. its capability of identifying the true number of clusters and the fact that it does not require a starting classification. Finally, the CoClust algorithm is applied to the real microarray data of Hedenfalk et al. (2001) both to the gene expressions observed in three different cancer samples and to the columns (tumor samples) of the whole data matrix.

New approaches to open problems in gene expression microarray data

In the past decade, the advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to enormous progress in the life science. Among the most important innovations is the microarray tecnology. It allows to quantify the expression for thousands of genes simultaneously by measurin the hybridization from a tissue of interest to probes on a small glass or plastic slide. The characteristics of these data include a fair amount of random noise, a predictor dimension in the thousand, and a sample noise in the dozens. One of the most exciting areas to which microarray technology has been applied is the challenge of deciphering complex disease such as cancer. In these studies, samples are taken from two or more groups of individuals with heterogeneous phenotypes, pathologies, or clinical outcomes. these samples are hybridized to microarrays in an effort to find a small number of genes which are strongly correlated with the group of individuals. Eventhough today methods to analyse the data are welle developed and close to reach a standard organization (through the effort of preposed International project like Microarray Gene Expression Data -MGED- Society [1]) it is not unfrequant to stumble in a clinician's question that do not have a compelling statistical method that could permit to answer it.The contribution of this dissertation in deciphering disease regards the development of new approaches aiming at handle open problems posed by clinicians in handle specific experimental designs. In Chapter 1 starting from a biological necessary introduction, we revise the microarray tecnologies and all the important steps that involve an experiment from the production of the array, to the quality controls ending with preprocessing steps that will be used into the data analysis in the rest of the dissertation. While in Chapter 2 a critical review of standard analysis methods are provided stressing most of problems that In Chapter 3 is introduced a method to adress the issue of unbalanced design of miacroarray experiments. In microarray experiments, experimental design is a crucial starting-point for obtaining reasonable results. In a two-class problem, an equal or similar number of samples it should be collected between the two classes. However in some cases, e.g. rare pathologies, the approach to be taken is less evident. We propose to address this issue by applying a modified version of SAM [2]. MultiSAM consists in a reiterated application of a SAM analysis, comparing the less populated class (LPC) with 1,000 random samplings of the same size from the more populated class (MPC) A list of the differentially expressed genes is generated for each SAM application. After 1,000 reiterations, each single probe given a "score" ranging from 0 to 1,000 based on its recurrence in the 1,000 lists as differentially expressed. The performance of MultiSAM was compared to the performance of SAM and LIMMA [3] over two simulated data sets via beta and exponential distribution. The results of all three algorithms over low- noise data sets seems acceptable However, on a real unbalanced two-channel data set reagardin Chronic Lymphocitic Leukemia, LIMMA finds no significant probe, SAM finds 23 significantly changed probes but cannot separate the two classes, while MultiSAM finds 122 probes with score >300 and separates the data into two clusters by hierarchical clustering. We also report extra-assay validation in terms of differentially expressed genes Although standard algorithms perform well over low-noise simulated data sets, multi-SAM seems to be the only one able to reveal subtle differences in gene expression profiles on real unbalanced data. In Chapter 4 a method to adress similarities evaluation in a three-class prblem by means of Relevance Vector Machine [4] is described. In fact, looking at microarray data in a prognostic and diagnostic clinical framework, not only differences could have a crucial role. In some cases similarities can give useful and, sometimes even more, important information. The goal, given three classes, could be to establish, with a certain level of confidence, if the third one is similar to the first or the second one. In this work we show that Relevance Vector Machine (RVM) [2] could be a possible solutions to the limitation of standard supervised classification. In fact, RVM offers many advantages compared, for example, with his well-known precursor (Support Vector Machine - SVM [3]). Among these advantages, the estimate of posterior probability of class membership represents a key feature to address the similarity issue. This is a highly important, but often overlooked, option of any practical pattern recognition system. We focused on Tumor-Grade-three-class problem, so we have 67 samples of grade I (G1), 54 samples of grade 3 (G3) and 100 samples of grade 2 (G2). The goal is to find a model able to separate G1 from G3, then evaluate the third class G2 as test-set to obtain the probability for samples of G2 to be member of class G1 or class G3. The analysis showed that breast cancer samples of grade II have a molecular profile more similar to breast cancer samples of grade I. Looking at the literature this result have been guessed, but no measure of significance was gived before.

Identification of Drosophila heart-specific Cis-Regulatory Modules under Hox control

Cardiac morphogenesis is a complex process governed by evolutionarily conserved transcription factors and signaling molecules. The Drosophila cardiac tube is linear, made of 52 pairs of cardiomyocytes (CMs), which express specific transcription factor genes that have human homologues implicated in Congenital Heart Diseases (CHDs) (NKX2-5, GATA4 and TBX5). The Drosophila cardiac tube is linear and composed of a rostral portion named aorta and a caudal one called heart, distinguished by morphological and functional differences controlled by Hox genes, key regulators of axial patterning. Overexpression and inactivation of the Hox gene abdominal-A (abd-A), which is expressed exclusively in the heart, revealed that abd-A controls heart identity. The aim of our work is to isolate the heart-specific cisregulatory sequences of abd-A direct target genes, the realizator genes granting heart identity. In each segment of the heart, four pairs of cardiomyocytes (CMs) express tinman (tin), homologous to NKX2-5, and acquire strong contractile and automatic rhythmic activities. By tyramide amplified FISH, we found that seven genes, encoding ion channels, pumps or transporters, are specifically expressed in the Tin-CMs of the heart. We initially used online available tools to identify their heart-specific cisregutatory modules by looking for Conserved Non-coding Sequences containing clusters of binding sites for various cardiac transcription factors, including Hox proteins. Based on these data we generated several reporter gene constructs and transgenic embryos, but none of them showed reporter gene expression in the heart. In order to identify additional abd-A target genes, we performed microarray experiments comparing the transcriptomes of aorta versus heart and identified 144 genes overexpressed in the heart. In order to find the heart-specific cis-regulatory regions of these target genes we developed a new bioinformatic approach where prediction is based on pattern matching and ordered statistics. We first retrieved Conserved Noncoding Sequences from the alignment between the D.melanogaster and D.pseudobscura genomes. We scored for combinations of conserved occurrences of ABD-A, ABD-B, TIN, PNR, dMEF2, MADS box, T-box and E-box sites and we ranked these results based on two independent strategies. On one hand we ranked the putative cis-regulatory sequences according to best scored ABD-A biding sites, on the other hand we scored according to conservation of binding sites. We integrated and ranked again the two lists obtained independently to produce a final rank. We generated nGFP reporter construct flies for in vivo validation. We identified three 1kblong heart-specific enhancers. By in vivo and in vitro experiments we are determining whether they are direct abd-A targets, demonstrating the role of a Hox gene in the realization of heart identity. The identified abd-A direct target genes may be targets also of the NKX2-5, GATA4 and/or TBX5 homologues tin, pannier and Doc genes, respectively. The identification of sequences coregulated by a Hox protein and the homologues of transcription factors causing CHDs, will provide a mean to test whether these factors function as Hox cofactors granting cardiac specificity to Hox proteins, increasing our knowledge on the molecular mechanisms underlying CHDs. Finally, it may be investigated whether these Hox targets are involved in CHDs.

Variation in peach fruit susceptibility to Monilinia laxa and gene expression

Brown rot caused by Monilinia laxa and Monilinia fructigena is considered one of the most important diseases affecting Prunus species. Although some losses can result from the rotten fruits in the orchard, most of the damage is caused to fruits during the post-harvest phase. Several studies reported that brown rot incidence during fruit development highly varies; it was found that at a period corresponding to the the pit hardening stage, fruit susceptibility drastically decreases, to be quickly restored afterwards. However the molecular basis of this phenomenon is still not well understood. Furthermore, no difference in the rot incidence was found between wound and un-wound fruits, suggesting that resistance associated more to a specifc biochemical response of the fruit, rather than to a higher mechanical resistance. So far, the interaction Monilinia-peach was analyzed through chemical approaches. In this study, a bio-molecular approach was undertaken in order to reveal alteration in gene expression associated to the variation of susceptibility. In this thesis three different methods for gene expression analysis were used to analyze the alterations in gene expression occurring in peach fruits during the pit hardening stage, in a period encompassing the temporary change in Monilinia susceptibility: real time PCR, microarray and cDNA AFLP techniques. In 2005, peach fruits (cv.K2) were weekly harvested during a 19-week long-period, starting from the fourth week after full bloom, until full maturity. At each sampling time, three replicates of 5 fruits each were dipped in the M.laxa conidial suspension or in distilled water, as negative control. The fruits were maintained at room temperature for 3 hours; afterwards, they were peeled with a scalpel; the peel was immediately frozen in liquid nitrogen and transferred to -80 °C until use. The degree of susceptibility of peach fruit to the pathogen was determined on 3 replicates of 20 fruits each, as percentage of infected fruits, after one week at 20 °C. Real time PCR analysis was performed to study the variation in expression of those genes encoding for the enzymes of the phenylpropanoid pathway (phenylalanine ammonia lyase (PAL), chalcone synthase (CHS), cinnamate 4-hydroxylase (C4H), leucoanthocyanidine reductase (LAR), hydroxycinnamoyl CoA quinate hydroxycinnamoyl transferase (HQT) and of the jasmonate pathway, such as lipoxygenase (LOX), both involved in the production of important defense compounds. Alteration in gene expression was monitored on fruit samples of a period encompassing the pit hardening stage and the corresponding temporary resistance to M.laxa infections, weekly, from the 6thto the 12th week after full bloom (AFB) inoculated with M. laxa or mock-inoculated. The data suggest a critical change in the expression level of the phenylpropanoid pathway from the 7th to the 8th week AFB; such change could be directly physiologically associated to the peach growth and it could indirectly determine the decrease of susceptibility of peach fruit to Monilinia rot during the subsequent weeks. To investigate on the transcriptome variation underneath the temporary loss of susceptibility of peach fruits to Monilinia rot, the microarray and the cDNA AFLP techniques were used. The samples harvested on the 8th week AFB (named S, for susceptible ones) and on the 12th week AFB (named R, for resistant ones) were compared, both inoculated or mock-inoculated. The microarray experiments were carried out at the University of Padua (Dept. of Environmental Agronomy and Crop Science), using the μPEACH1.0 microarray together with the suited protocols. The analysis showed that 30 genes (corresponding to the 0.6% of the total sequences (4806) contained in the μPeach1.0 microarray) were found up-regulated and 31 ( 0.6%) down regulated in RH vs. SH fruits. On the other hand, 20 genes (0.4%) were shown to be up-regulated and 13 (0.3%) down-regulated in the RI vs. SI fruit. No genes were found differentially expressed in the mock-inoculated resistant fruits (RH) vs. the inoculated resistant ones (RI). Among the up-regulated genes an ATP sulfurylase, an heat shock protein 70, the major allergen Pru P1, an harpin inducing protein and S-adenosylmethionine decarboxylase were found, conversely among the down-regulated ones, cinnamyl alcohol dehydrogenase, an histidine- containing phosphotransfer protein and the ferritin were found. The microarray experimental results and the data indirectly derived, were tested by Real Time PCR analysis. cDNA AFLP analysis was also performed on the same samples. 339 transcript derived fragments considered significant for Monilinia resistance, were selected, sequenced and classified. Genes potentially involved in cell rescue and defence were well represented (8%); several genes (12.1%) involved in the protein folding, post-transductional modification and genes (9.2%) involved in cellular transport were also found. A further 10.3% of genes were classified as involved in the metabolism of aminoacid, carbohydrate and fatty acid. On the other hand, genes involved in the protein synthesis (5.7%) and in signal transduction and communication (5.7%) were found. Among the most interesting genes found differentially expressed between susceptible and resistant fruits, genes encoding for pathogenesis related (PR) proteins were found. To investigate on the association of Monilinia resistance and PR biological function, the major allergen Pru P1 (GenBank accession AM493970) and its isoform (here named Pru P2), were expressed in heterologous system and in vitro assayed for their anti-microbial activity. The ribonuclease activity of the recombinant Pru P1 and Pru P2 proteins was assayed against peach total RNA. As the other PR10 proteins, they showed a ribonucleolytic activity, that could be important to contrast pathogen penetration. Moreover Pru P1 and Pru P2 recombinant proteins were checked for direct antimicrobial activity. No inhibitory effect of Pru P1 or Pru P2 was detected against the selected fungi.

Exploring host-pathogen interactions through protein microarray. Large-scale protein microarray analysis revealed novel human receptors for the staphylococcal immune evasion protein FLIPr and for the neisserial adhesin NadA

Adhesion, immune evasion and invasion are key determinants during bacterial pathogenesis. Pathogenic bacteria possess a wide variety of surface exposed and secreted proteins which allow them to adhere to tissues, escape the immune system and spread throughout the human body. Therefore, extensive contacts between the human and the bacterial extracellular proteomes take place at the host-pathogen interface at the protein level. Recent researches emphasized the importance of a global and deeper understanding of the molecular mechanisms which underlie bacterial immune evasion and pathogenesis. Through the use of a large-scale, unbiased, protein microarray-based approach and of wide libraries of human and bacterial purified proteins, novel host-pathogen interactions were identified. This approach was first applied to Staphylococcus aureus, cause of a wide variety of diseases ranging from skin infections to endocarditis and sepsis. The screening led to the identification of several novel interactions between the human and the S. aureus extracellular proteomes. The interaction between the S. aureus immune evasion protein FLIPr (formyl-peptide receptor like-1 inhibitory protein) and the human complement component C1q, key players of the offense-defense fighting, was characterized using label-free techniques and functional assays. The same approach was also applied to Neisseria meningitidis, major cause of bacterial meningitis and fulminant sepsis worldwide. The screening led to the identification of several potential human receptors for the neisserial adhesin A (NadA), an important adhesion protein and key determinant of meningococcal interactions with the human host at various stages. The interaction between NadA and human LOX-1 (low-density oxidized lipoprotein receptor) was confirmed using label-free technologies and cell binding experiments in vitro. Taken together, these two examples provided concrete insights into S. aureus and N. meningitidis pathogenesis, and identified protein microarray coupled with appropriate validation methodologies as a powerful large scale tool for host-pathogen interactions studies.

Genotypic variation in Actinidia deliciosa fruit size and carbohydrate content

In a global and increasingly competitive fresh produce market, more attention is being given to fruit quality traits and consumer satisfaction. Kiwifruit occupies a niche position in the worldwide market, when compared to apples, oranges or bananas. It is a fruit with extraordinarily good nutritional traits, and its benefits to human health have been widely described. Until recently, international trade in kiwifruit was restricted to a single cultivar, but different types of kiwifruit are now becoming available in the market. Effective programmes of kiwifruit improvement start by considering the requirements of consumers, and recent surveys indicate that sweeter fruit with better flavour are generally preferred. There is a strong correlation between at-harvest dry matter and starch content, and soluble solid concentration and flavour when fruit are eating ripe. This suggests that carbon accumulation strongly influences the development of kiwifruit taste. The overall aim of the present study was to determine what factors affect carbon accumulation during Actinidia deliciosa berry development. One way of doing this is by comparing kiwifruit genotypes that differ greatly in their ability to accumulate dry matter in their fruit. Starch is the major component of dry matter content. It was hypothesized that genotypes were different in sink strength. Sink strength, by definition, is the effect of sink size and sink activity. Chapter 1 reviews fruit growth, kiwifruit growth and development and carbon metabolism. Chapter 2 describes the materials and methods used. Chapter 3, 4, 5 and 6 describes different types of experimental work. Chapter 7 contains the final discussions and the conclusions Three Actinidia deliciosa breeding populations were analysed in detail to confirm that observed differences in dry matter content were genetically determined. Fruit of the different genotypes differed in dry matter content mainly because of differences in starch concentrations and dry weight accumulation rates, irrespective of fruit size. More detailed experiments were therefore carried out on genotypes which varied most in fruit starch concentrations to determine why sink strengths were so different. The kiwifruit berry comprises three tissues which differ in dry matter content. It was initially hypothesised that observed differences in starch content could be due to a larger proportion of one or other of these tissues, for example, of the central core which is highest in dry matter content. The study results showed that this was not the case. Sink size, intended as cell number or cell size, was then investigated. The outer pericarp makes up about 60% of berry weight in ‘Hayward’ kiwifruit. The outer pericarp contains two types of parenchyma cells: large cells with low starch concentration, and small cells with high starch concentration. Large cell, small cell and total cell densities in the outer pericarp were shown to be not correlated with either dry matter content or fruit size but further investigation of volume proportion among cell types seemed justified. It was then shown that genotypes with fruit having higher dry matter contents also had a higher proportion of small cells. However, the higher proportion of small cell volume could only explain half of the observed differences in starch content. So, sink activity, intended as sucrose to starch metabolism, was investigated. In transiently starch storing sinks, such as tomato fruit and potato tubers, a pivotal role in carbon metabolism has been attributed to sucrose cleaving enzymes (mainly sucrose synthase and cell wall invertase) and to ADP-glucose pyrophosphorylase (the committed step in starch synthesis). Studies on tomato and potato genotypes differing in starch content or in final fruit soluble solid concentrations have demonstrated a strong link with either sucrose synthase or ADP-glucose pyrophosphorylase, at both enzyme activity and gene expression levels, depending on the case. Little is known about sucrose cleaving enzyme and ADP-glucose pyrophosphorylase isoforms. The HortResearch Actinidia EST database was then screened to identify sequences putatively encoding for sucrose synthase, invertase and ADP-glucose pyrophosphorylase isoforms and specific primers were designed. Sucrose synthase, invertase and ADP-glucose pyrophosphorylase isoform transcript levels were anlayzed throughout fruit development of a selection of four genotypes (two high dry matter and two low dry matter). High dry matter genotypes showed higher amounts of sucrose synthase transcripts (SUS1, SUS2 or both) and higher ADP-glucose pyrophosphorylase (AGPL4, large subunit 4) gene expression, mainly early in fruit development. SUS1- like gene expression has been linked with starch biosynthesis in several crop (tomato, potato and maize). An enhancement of its transcript level early in fruit development of high dry matter genotypes means that more activated glucose (UDP-glucose) is available for starch synthesis. This can be then correlated to the higher starch observed since soon after the onset of net starch accumulation. The higher expression level of AGPL4 observed in high dry matter genotypes suggests an involvement of this subunit in drive carbon flux into starch. Changes in both enzymes (SUSY and AGPse) are then responsible of higher starch concentrations. Low dry matter genotypes showed generally higher vacuolar invertase gene expression (and also enzyme activity), early in fruit development. This alternative cleavage strategy can possibly contribute to energy loss, in that invertases’ products are not adenylated, and further reactions and transport are needed to convert carbon into starch. Although these elements match well with observed differences in starch contents, other factors could be involved in carbon metabolism control. From the microarray experiment, in fact, several kinases and transcription factors have been found to be differentially expressed. Sink strength is known to be modified by application of regulators. In ‘Hayward’ kiwifruit, the synthetic cytokinin CPPU (N-(2-Chloro-4-Pyridyl)-N-Phenylurea) promotes a dramatic increase in fruit size, whereas dry matter content decreases. The behaviour of CPPU-treated ‘Hayward’ kiwifruit was similar to that of fruit from low dry matter genotypes: dry matter and starch concentrations were lower. However, the CPPU effect was strongly source limited, whereas in genotype variation it was not. Moreover, CPPU-treated fruit gene expression (at sucrose cleavage and AGPase levels) was similar to that in high dry matter genotypes. It was therefore concluded that CPPU promotes both sink size and sink activity, but at different “speeds” and this ends in the observed decrease in dry matter content and starch concentration. The lower “speed” in sink activity is probably due to a differential partitioning of activated glucose between starch storage and cell wall synthesis to sustain cell expansion. Starch is the main carbohydrate accumulated in growing Actinidia deliciosa fruit. Results obtained in the present study suggest that sucrose synthase and AGPase enzymes contribute to sucrose to starch conversion, and differences in their gene expression levels, mainly early in fruit development, strongly affect the rate at which starch is therefore accumulated. This results are interesting in that starch and Actinidia deliciosa fruit quality are tightly connected.

Produzione di virus sintetici per lo studio dei meccanismi di interazione coinvolti nell'induzione di resistenza

Beet soil-borne mosaic virus (BSBMV) and Beet necrotic yellow vein virus (BNYVV) are members of Benyvirus genus. BSBMV has been reported only in the United States while BNYVV has a worldwide distribution. Both viruses are vectored by Polymyxa betae, possess similar host ranges, particles number and morphology. Both viruses are not serologically related but have similar genomic organizations. Field isolates consist of four RNA species but some BNYVV isolates contain a fifth RNA. RNAs 1 and 2 are essential for infection and replication while RNAs 3 and 4 play important roles on plant and vector interactions, respectively. Nucleotide and amino acid analyses revealed BSBMV and BNYVV are different enough to be classified in two different species. Additionally in BNYVV/BSBMV mixed infections, a competition was previous described in sugar beet, where BNYVV infection reduces BSBMV accumulation in both susceptible and resistant cultivars. Considering all this observations we hypothesized that BNYVV and BSBMV crossed study, exploiting their similarities and divergences, can improve investigation of molecular interactions between sugar beets and Benyviruses. The main achievement of our research is the production of a cDNA biologically active clones collection of BNYVV and BSBMV RNAs, from which synthetic copies of both Benyviruses can be transcribed. Moreover, through recombination experiments we demonstrated, for the first time, the BNYVV RNA 1 and 2 capability to trans-replicate and encapsidate BSBMV RNA 3 and 4, either the BSBMV RNA 1 and 2 capability to replicate BNYVV RNA2 in planta. We also demonstrated that BSBMV RNA3 support long-distance movement of BNYVV RNA 1 and 2 in B. macrocarpa and that 85 foreign sequence as p29HA, GFP and RFP, are successfully expressed, in C. quinoa, by BSBMV RNA3 based replicon (RepIII) also produced by our research. These results confirm the close correlation among the two viruses. Interestingly, the symptoms induced by BSBMV RNA-3 on C. quinoa leaves are more similar to necrotic local lesions caused by BNYVV RNA-5 p26 than to strongly chlorotic local lesions or yellow spot induced by BNYVV RNA- 3 encoded p25. As previous reported BSBMV p29 share 23% of amino acid sequence identity with BNYVV p25 but identity increase to 43% when compared with sequence of BNYVV RNA-5 p26. Based on our results the essential sequence (Core region) for the longdistance movement of BSBMV and BNYVV in B. macrocarpa, is not only carried by RNA3s species but other regions, perhaps located on the RNA 1 and 2, could play a fundamental role in this matter. Finally a chimeric RNA, composed by the 5’ region of RNA4 and 3’ region of RNA3 of BSBMV, has been produced after 21 serial mechanically inoculation of wild type BSBMV on C. quinoa plants. Chimera seems unable to express any protein, but it is replicated and transcript in planta. It could represent an important tool to study the interactions between Benyvirus and plant host. In conclusion different tools, comprising a method to study synthetic viruses under natural conditions of inoculum through P. Betae, have been produced and new knowledge are been acquired that will allow to perform future investigation of the molecular interactions between sugar beets and Benyviruses.

Identification of surface protein complexes of Streptococcus pyogenes through protein microarray technology

A systematic characterization of the composition and structure of the bacterial cell-surface proteome and its complexes can provide an invaluable tool for its comprehensive understanding. The knowledge of protein complexes composition and structure could offer new, more effective targets for a more specific and consequently effective immune response against a complex instead of a single protein. Large-scale protein-protein interaction screens are the first step towards the identification of complexes and their attribution to specific pathways. Currently, several methods exist for identifying protein interactions and protein microarrays provide the most appealing alternative to existing techniques for a high throughput screening of protein-protein interactions in vitro under reasonably straightforward conditions. In this study approximately 100 proteins of Group A Streptococcus (GAS) predicted to be secreted or surface exposed by genomic and proteomic approaches were purified in a His-tagged form and used to generate protein microarrays on nitrocellulose-coated slides. To identify protein-protein interactions each purified protein was then labeled with biotin, hybridized to the microarray and interactions were detected with Cy3-labelled streptavidin. Only reciprocal interactions, i. e. binding of the same two interactors irrespective of which of the two partners is in solid-phase or in solution, were taken as bona fide protein-protein interactions. Using this approach, we have identified 20 interactors of one of the potent toxins secreted by GAS and known as superantigens. Several of these interactors belong to the molecular chaperone or protein folding catalyst families and presumably are involved in the secretion and folding of the superantigen. In addition, a very interesting interaction was found between the superantigen and the substrate binding subunit of a well characterized ABC transporter. This finding opens a new perspective on the current understanding of how superantigens are modified by the bacterial cell in order to become major players in causing disease.

Genomic characterization of the italian wolf (Canis lupus): the genes involved in black coat colour determination and application of microarray technique for snps detection.

This study provides a comprehensive genetic overview on the endangered Italian wolf population. In particular, it focuses on two research lines. On one hand, we focalised on melanism in wolf in order to isolate a mutation related with black coat colour in canids. With several reported black individuals (an exception at European level), the Italian wolf population constituted a challenging research field posing many unanswered questions. As found in North American wolf, we reported that melanism in the Italian population is caused by a different melanocortin pathway component, the K locus, in which a beta-defensin protein acts as an alternative ligand for the Mc1r. This research project was conducted in collaboration with Prof. Gregory Barsh, Department of Genetics and Paediatrics, Stanford University. On the other hand, we performed analysis on a high number of SNPs thanks to a customized Canine microarray useful to integrate or substitute the STR markers for genotyping individuals and detecting wolf-dog hybrids. Thanks to DNA microchip technology, we obtained an impressive amount of genetic data which provides a solid base for future functional genomic studies. This study was undertaken in collaboration with Prof. Robert K. Wayne, Department of Ecology and Evolutionary Biology, University of California, Los Angeles (UCLA).

Applications of High Speed Configurable Logic Devices in Modern Particle Physics Experiments

Several activities were conducted during my PhD activity. For the NEMO experiment a collaboration between the INFN/University groups of Catania and Bologna led to the development and production of a mixed signal acquisition board for the Nemo Km3 telescope. The research concerned the feasibility study for a different acquisition technique quite far from that adopted in the NEMO Phase 1 telescope. The DAQ board that we realized exploits the LIRA06 front-end chip for the analog acquisition of anodic an dynodic sources of a PMT (Photo-Multiplier Tube). The low-power analog acquisition allows to sample contemporaneously multiple channels of the PMT at different gain factors in order to increase the signal response linearity over a wider dynamic range. Also the auto triggering and self-event-classification features help to improve the acquisition performance and the knowledge on the neutrino event. A fully functional interface towards the first level data concentrator, the Floor Control Module, has been integrated as well on the board, and a specific firmware has been realized to comply with the present communication protocols. This stage of the project foresees the use of an FPGA, a high speed configurable device, to provide the board with a flexible digital logic control core. After the validation of the whole front-end architecture this feature would be probably integrated in a common mixed-signal ASIC (Application Specific Integrated Circuit). The volatile nature of the configuration memory of the FPGA implied the integration of a flash ISP (In System Programming) memory and a smart architecture for a safe remote reconfiguration of it. All the integrated features of the board have been tested. At the Catania laboratory the behavior of the LIRA chip has been investigated in the digital environment of the DAQ board and we succeeded in driving the acquisition with the FPGA. The PMT pulses generated with an arbitrary waveform generator were correctly triggered and acquired by the analog chip, and successively they were digitized by the on board ADC under the supervision of the FPGA. For the communication towards the data concentrator a test bench has been realized in Bologna where, thanks to a lending of the Roma University and INFN, a full readout chain equivalent to that present in the NEMO phase-1 was installed. These tests showed a good behavior of the digital electronic that was able to receive and to execute command imparted by the PC console and to answer back with a reply. The remotely configurable logic behaved well too and demonstrated, at least in principle, the validity of this technique. A new prototype board is now under development at the Catania laboratory as an evolution of the one described above. This board is going to be deployed within the NEMO Phase-2 tower in one of its floors dedicated to new front-end proposals. This board will integrate a new analog acquisition chip called SAS (Smart Auto-triggering Sampler) introducing thus a new analog front-end but inheriting most of the digital logic present in the current DAQ board discussed in this thesis. For what concern the activity on high-resolution vertex detectors, I worked within the SLIM5 collaboration for the characterization of a MAPS (Monolithic Active Pixel Sensor) device called APSEL-4D. The mentioned chip is a matrix of 4096 active pixel sensors with deep N-well implantations meant for charge collection and to shield the analog electronics from digital noise. The chip integrates the full-custom sensors matrix and the sparsifification/readout logic realized with standard-cells in STM CMOS technology 130 nm. For the chip characterization a test-beam has been set up on the 12 GeV PS (Proton Synchrotron) line facility at CERN of Geneva (CH). The collaboration prepared a silicon strip telescope and a DAQ system (hardware and software) for data acquisition and control of the telescope that allowed to store about 90 million events in 7 equivalent days of live-time of the beam. My activities concerned basically the realization of a firmware interface towards and from the MAPS chip in order to integrate it on the general DAQ system. Thereafter I worked on the DAQ software to implement on it a proper Slow Control interface of the APSEL4D. Several APSEL4D chips with different thinning have been tested during the test beam. Those with 100 and 300 um presented an overall efficiency of about 90% imparting a threshold of 450 electrons. The test-beam allowed to estimate also the resolution of the pixel sensor providing good results consistent with the pitch/sqrt(12) formula. The MAPS intrinsic resolution has been extracted from the width of the residual plot taking into account the multiple scattering effect.