Evaluation of 3D cell culture systems for host-pathogen interaction studies

Traditional cell culture models have limitations in extrapolating functional mechanisms that underlie strategies of microbial virulence. Indeed during the infection the pathogens adapt to different tissue-specific environmental factors. The development of in vitro models resembling human tissue physiology might allow the replacement of inaccurate or aberrant animal models. Three-dimensional (3D) cell culture systems are more reliable and more predictive models that can be used for the meaningful dissection of host–pathogen interactions. The lung and gut mucosae often represent the first site of exposure to pathogens and provide a physical barrier against their entry. Within this context, the tracheobronchial and small intestine tract were modelled by tissue engineering approach. The main work was focused on the development and the extensive characterization of a human organotypic airway model, based on a mechanically supported co-culture of normal primary cells. The regained morphological features, the retrieved environmental factors and the presence of specific epithelial subsets resembled the native tissue organization. In addition, the respiratory model enabled the modular insertion of interesting cell types, such as innate immune cells or multipotent stromal cells, showing a functional ability to release pertinent cytokines differentially. Furthermore this model responded imitating known events occurring during the infection by Non-typeable H. influenzae. Epithelial organoid models, mimicking the small intestine tract, were used for a different explorative analysis of tissue-toxicity. Further experiments led to detection of a cell population targeted by C. difficile Toxin A and suggested a role in the impairment of the epithelial homeostasis by the bacterial virulence machinery. The described cell-centered strategy can afford critical insights in the evaluation of the host defence and pathogenic mechanisms. The application of these two models may provide an informing step that more coherently defines relevant molecular interactions happening during the infection.

Apple latent infection caused by Neofabraea alba: host-pathogen interaction and disease management

Apple latent infection caused by Neofabraea alba: host-pathogen interaction and disease management Bull’s eye rot (BER) caused by Neofabraea alba is one of the most frequent and damaging latent infection occurring in stored pome fruits worldwide. Fruit infection occurs in the orchard, but disease symptoms appear only 3 months after harvest, during refrigerated storage. In Italy BER is particularly serious for late harvest apple cultivar as ‘Pink Lady™’. The purposes of this thesis were: i) Evaluate the influence of ‘Pink Lady™’ apple primary metabolites in N. alba quiescence ii) Evaluate the influence of pH in five different apple cultivars on BER susceptibility iii) To find out not chemical method to control N. alba infection iv) Identify some fungal volatile compounds in order to use them as N. alba infections markers. Results regarding the role of primary metabolites showed that chlorogenic, quinic and malic acid inhibit N. alba development. The study based on the evaluation of cultivar susceptibility, showed that Granny Smith was the most resistant apple cultivar among the varieties analyzed. Moreover, Granny Smith showed the lowest pH value from harvest until the end of storage, supporting the thesis that ambient pH could be involved in the interaction between N. alba and apple. In order to find out new technologies able to improve lenticel rot management, the application of a non-destructive device for the determination of chlorophyll content was applied. Results showed that fruit with higher chlorophyll content are less susceptible to BER, and molecular analyses comforted this result. Fruits with higher chlorophyll content showed up-regulation of PGIP and HCT, genes involved in plant defence. Through the application of PTR-MS and SPME GC-MS, 25 volatile organic compounds emitted by N. alba were identified. Among them, 16 molecules were identified as potential biomarkers.

Role of bioactive compounds in the gastrointestinal host-pathogen interaction of poultry and swine

The better understanding of mechanisms at the basis of host-pathogen interaction can represent a valid tool to increase productivity and contain economic losses in animal production through the maintenance of intestinal homeostasis. With this project, three preliminary in vitro studies were conducted with the aim of investigating how bioactive compounds could influence mechanisms of host-pathogen interaction in poultry and swine. Different panels of nature identical compounds, medium chain fatty acids, and plant extracts were employed against strains of Salmonella Typhimurium, Brachyspira hyodysenteriae, and Salmonella Enteritidis, respectively. When bacterial field strains were tested, the comparison between natural compounds and antibiotics was examined, with the aim of evaluating the role of the substances in the antibiotic-resistance context. Results demonstrate that bioactive compounds have positive effects on the host, the pathogen, or both in different experimental conditions. Additionally, when compared to antibiotics, bioactive compounds have proven to be valid alternatives to address the phenomenon of antibiotic resistance.

Characterization of DNA sequence properties through network and statistical approaches

In this thesis we will see that the DNA sequence is constantly shaped by the interactions with its environment at multiple levels, showing footprints of DNA methylation, of its 3D organization and, in the case of bacteria, of the interaction with the host organisms. In the first chapter, we will see that analyzing the distribution of distances between consecutive dinucleotides of the same type along the sequence, we can detect epigenetic and structural footprints. In particular, we will see that CG distance distribution allows to distinguish among organisms of different biological complexity, depending on how much CG sites are involved in DNA methylation. Moreover, we will see that CG and TA can be described by the same fitting function, suggesting a relationship between the two. We will also provide an interpretation of the observed trend, simulating a positioning process guided by the presence and absence of memory. In the end, we will focus on TA distance distribution, characterizing deviations from the trend predicted by the best fitting function, and identifying specific patterns that might be related to peculiar mechanical properties of the DNA and also to epigenetic and structural processes. In the second chapter, we will see how we can map the 3D structure of the DNA onto its sequence. In particular, we devised a network-based algorithm that produces a genome assembly starting from its 3D configuration, using as inputs Hi-C contact maps. Specifically, we will see how we can identify the different chromosomes and reconstruct their sequences by exploiting the spectral properties of the Laplacian operator of a network. In the third chapter, we will see a novel method for source clustering and source attribution, based on a network approach, that allows to identify host-bacteria interaction starting from the detection of Single-Nucleotide Polymorphisms along the sequence of bacterial genomes.

Cell Host-Microbe Interactions: Turning Pathogen Mechanisms Into Cell's Advantages

Host-Pathogen Interaction is a very vast field of biological sciences, indeed every year many un- known pathogens are uncovered leading to an exponential growth of this field. The present work lyes between its boundaries, touching different aspects of host-pathogen interaction: We have evaluate the permissiveness of Mesenchimal Stem cell (FM-MSC from now on) to all known human affecting herpesvirus. Our study demonstrate that FM-MSC are full permissive to HSV1, HSV2, HCMV and VZV. On the other hand HHV6, HHV7, EBV and HHV8 are susceptible, but failed to activate a lytic infection program. FM-MSC are pluripotent stem cell and have been studied intensely in last decade. FM-MSC are employed in some clinical applications. For this reason it is important to known the degree of susceptibility to transmittable pathogens. Our atten- tion has then moved to bacterial pathogens: we have performed a proteome-wide in silico analy- sis of Chlamydiaceae family, searching for putative Nuclear localization Signal (NLS). Chlamy- diaceae are a family of obligate intracellular parasites. It’s reasonably to think that its members could delivered to nucleus effector proteins via NLS sequences: if that were the case the identifi- cation of NLS carrying proteins could open the way to therapeutic approaches. Our results strengthen this hypothesis: we have identified 72 protein bearing NLS, and verified their func- tionality with in vivo assays. Finally we have conceived a molecular scissor, creating a fusion protein between HIV-1 IN protein and FokI catalytic domain (a deoxyexonuclease domain). Our aim is to obtain chimeric enzyme (trojIN) which selectively identify IN naturally occurring target (HIV LTR sites) and cleaves subsequently LTR carrying DNA (for example integrated HIV1 DNA). Our preliminary results are promising since we have identified trojIN mutated version capable to selectively recognize LTR carrying DNA in an in vitro experiments.

Reconstruction and analysis of the NF-kB pathway interactome: a systems biology approach

Background. One of the phenomena observed in human aging is the progressive increase of a systemic inflammatory state, a condition referred to as “inflammaging”, negatively correlated with longevity. A prominent mediator of inflammation is the transcription factor NF-kB, that acts as key transcriptional regulator of many genes coding for pro-inflammatory cytokines. Many different signaling pathways activated by very diverse stimuli converge on NF-kB, resulting in a regulatory network characterized by high complexity. NF-kB signaling has been proposed to be responsible of inflammaging. Scope of this analysis is to provide a wider, systemic picture of such intricate signaling and interaction network: the NF-kB pathway interactome. Methods. The study has been carried out following a workflow for gathering information from literature as well as from several pathway and protein interactions databases, and for integrating and analyzing existing data and the relative reconstructed representations by using the available computational tools. Strong manual intervention has been necessarily used to integrate data from multiple sources into mathematically analyzable networks. The reconstruction of the NF-kB interactome pursued with this approach provides a starting point for a general view of the architecture and for a deeper analysis and understanding of this complex regulatory system. Results. A “core” and a “wider” NF-kB pathway interactome, consisting of 140 and 3146 proteins respectively, were reconstructed and analyzed through a mathematical, graph-theoretical approach. Among other interesting features, the topological characterization of the interactomes shows that a relevant number of interacting proteins are in turn products of genes that are controlled and regulated in their expression exactly by NF-kB transcription factors. These “feedback loops”, not always well-known, deserve deeper investigation since they may have a role in tuning the response and the output consequent to NF-kB pathway initiation, in regulating the intensity of the response, or its homeostasis and balance in order to make the functioning of such critical system more robust and reliable. This integrated view allows to shed light on the functional structure and on some of the crucial nodes of thet NF-kB transcription factors interactome. Conclusion. Framing structure and dynamics of the NF-kB interactome into a wider, systemic picture would be a significant step toward a better understanding of how NF-kB globally regulates diverse gene programs and phenotypes. This study represents a step towards a more complete and integrated view of the NF-kB signaling system.

Analysis of the immunological and functional features of the Neisserial Heparin Binding Antigen (NHBA)

Neisserial Heparin Binding Antigen (NHBA) is a surface-exposed lipoprotein ubiquitously expressed by genetically diverse Neisseria meningitidis strains and is an antigen of the multicomponent protein-based 4CMenB vaccine, able to induce bactericidal antibodies in humans and to bind heparin-like molecules. The aim of this study is to characterize the immunological and functional properties of NHBA. To evaluate immunogenicity and the contribution of aminoacid sequence variability to vaccine coverage, we constructed recombinant isogenic strains that are susceptible to bactericidal killing only by anti-NHBA antibodies and engineered them to express equal levels of selected NHBA peptides. In these recombinant strains, we observed different titres associated with the different peptide variants. These recombinant strains were then further engineered to express NHBA chimeric proteins to investigate the regions important for immunogenicity. In natural strains, anti-NHBA antibodies were found to be cross-protective against strains expressing different peptides. To investigate the functional properties of this antigen, the recombinant purified NHBA protein was tested in in vitro binding studies and was found to be able to bind epithelial cells. The binding was abolished when cells were treated specifically with heparinase III, suggesting that the interaction with the cells is mediated by heparan sulfate proteoglycans (HSPG). Mutation of the Arg-rich tract of NHBA abrogated the binding, confirming the importance of this region in mediating the binding to heparin-like molecules. In a panel of N. meningitidis strains, the deletion of nhba resulted in a reduction of adhesion with respect to each isogenic wild type strain. Furthermore, the adhesion of the wild-type strain was prevented by using anti-NHBA polyclonal sera, demonstrating the specificity of the interaction. These results suggest that NHBA could be a novel meningococcal adhesin contributing to host-cell interaction. Moreover, we analysed NHBA NalP-mediated cleavage in different NHBA peptides and showed that not all NHBA peptides are cleaved.

Bifidobacterium - Human Host Interaction: Role of Human Plasminogen

Bifidobacterium is an important genus of the human gastrointestinal microbiota, affecting several host physiological features. Despite the numerous Bifidobacterium related health-promoting activities, there is still a dearth of information about the molecular mechanisms at the basis of the interaction between this microorganism and the host. Bacterial surface associated proteins may play an important role in this interaction because of their ability to intervene with host molecules, as recently reported for the host protein plasminogen. Plasminogen is the zymogen of the trypsin-like serine protease plasmin, an enzyme with a broad substrate specificity. Aim of this thesis is to deepen the knowledge about the interaction between Bifidobacterium and the human plasminogen system and its role in the Bifidobacterium-host interaction process. As a bifidobacterial model, B. animalis subsp. lactis BI07 has been used because of its large usage in dairy and pharmaceutical preparations. We started from the molecular characterization of the interaction between plasminogen and one bifidobacterial plasminogen receptor, DnaK, a cell wall protein showing high affinity for plasminogen, and went on with the study of the impact of intestinal environmental factors, such as bile salts and inflammation, on the plasminogen-mediated Bifidobacterium-host interaction. According to our in vitro findings, by enhancing the activation of the bifidobacterial bound plasminogen to plasmin, the host inflammatory response results in the decrease of the bifidobacterial adhesion to the host enterocytes, favouring bacterial migration to the luminal compartment. Conversely, in the absence of inflammation, plasminogen acts as a molecular bridge between host enterocytes and bifidobacteria, enhancing Bifidobacterium adhesion. Furthermore, adaptation to physiological concentrations of bile salts enhances the capability of this microorganism to interact with the host plasminogen system. The host plasminogen system thus represents an important and flexible tool used by bifidobacteria in the cross-talk with the host.

Neural network modelling of the wave-structure interaction processes

This thesis presents a new Artificial Neural Network (ANN) able to predict at once the main parameters representative of the wave-structure interaction processes, i.e. the wave overtopping discharge, the wave transmission coefficient and the wave reflection coefficient. The new ANN has been specifically developed in order to provide managers and scientists with a tool that can be efficiently used for design purposes. The development of this ANN started with the preparation of a new extended and homogeneous database that collects all the available tests reporting at least one of the three parameters, for a total amount of 16’165 data. The variety of structure types and wave attack conditions in the database includes smooth, rock and armour unit slopes, berm breakwaters, vertical walls, low crested structures, oblique wave attacks. Some of the existing ANNs were compared and improved, leading to the selection of a final ANN, whose architecture was optimized through an in-depth sensitivity analysis to the training parameters of the ANN. Each of the selected 15 input parameters represents a physical aspect of the wave-structure interaction process, describing the wave attack (wave steepness and obliquity, breaking and shoaling factors), the structure geometry (submergence, straight or non-straight slope, with or without berm or toe, presence or not of a crown wall), or the structure type (smooth or covered by an armour layer, with permeable or impermeable core). The advanced ANN here proposed provides accurate predictions for all the three parameters, and demonstrates to overcome the limits imposed by the traditional formulae and approach adopted so far by some of the existing ANNs. The possibility to adopt just one model to obtain a handy and accurate evaluation of the overall performance of a coastal or harbor structure represents the most important and exportable result of the work.

User interaction widgets for interactive theorem proving

Matita (that means pencil in Italian) is a new interactive theorem prover under development at the University of Bologna. When compared with state-of-the-art proof assistants, Matita presents both traditional and innovative aspects. The underlying calculus of the system, namely the Calculus of (Co)Inductive Constructions (CIC for short), is well-known and is used as the basis of another mainstream proof assistant—Coq—with which Matita is to some extent compatible. In the same spirit of several other systems, proof authoring is conducted by the user as a goal directed proof search, using a script for storing textual commands for the system. In the tradition of LCF, the proof language of Matita is procedural and relies on tactic and tacticals to proceed toward proof completion. The interaction paradigm offered to the user is based on the script management technique at the basis of the popularity of the Proof General generic interface for interactive theorem provers: while editing a script the user can move forth the execution point to deliver commands to the system, or back to retract (or “undo”) past commands. Matita has been developed from scratch in the past 8 years by several members of the Helm research group, this thesis author is one of such members. Matita is now a full-fledged proof assistant with a library of about 1.000 concepts. Several innovative solutions spun-off from this development effort. This thesis is about the design and implementation of some of those solutions, in particular those relevant for the topic of user interaction with theorem provers, and of which this thesis author was a major contributor. Joint work with other members of the research group is pointed out where needed. The main topics discussed in this thesis are briefly summarized below. Disambiguation. Most activities connected with interactive proving require the user to input mathematical formulae. Being mathematical notation ambiguous, parsing formulae typeset as mathematicians like to write down on paper is a challenging task; a challenge neglected by several theorem provers which usually prefer to fix an unambiguous input syntax. Exploiting features of the underlying calculus, Matita offers an efficient disambiguation engine which permit to type formulae in the familiar mathematical notation. Step-by-step tacticals. Tacticals are higher-order constructs used in proof scripts to combine tactics together. With tacticals scripts can be made shorter, readable, and more resilient to changes. Unfortunately they are de facto incompatible with state-of-the-art user interfaces based on script management. Such interfaces indeed do not permit to position the execution point inside complex tacticals, thus introducing a trade-off between the usefulness of structuring scripts and a tedious big step execution behavior during script replaying. In Matita we break this trade-off with tinycals: an alternative to a subset of LCF tacticals which can be evaluated in a more fine-grained manner. Extensible yet meaningful notation. Proof assistant users often face the need of creating new mathematical notation in order to ease the use of new concepts. The framework used in Matita for dealing with extensible notation both accounts for high quality bidimensional rendering of formulae (with the expressivity of MathMLPresentation) and provides meaningful notation, where presentational fragments are kept synchronized with semantic representation of terms. Using our approach interoperability with other systems can be achieved at the content level, and direct manipulation of formulae acting on their rendered forms is possible too. Publish/subscribe hints. Automation plays an important role in interactive proving as users like to delegate tedious proving sub-tasks to decision procedures or external reasoners. Exploiting the Web-friendliness of Matita we experimented with a broker and a network of web services (called tutors) which can try independently to complete open sub-goals of a proof, currently being authored in Matita. The user receives hints from the tutors on how to complete sub-goals and can interactively or automatically apply them to the current proof. Another innovative aspect of Matita, only marginally touched by this thesis, is the embedded content-based search engine Whelp which is exploited to various ends, from automatic theorem proving to avoiding duplicate work for the user. We also discuss the (potential) reusability in other systems of the widgets presented in this thesis and how we envisage the evolution of user interfaces for interactive theorem provers in the Web 2.0 era.

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.

Reverse genetic studies of Benyvirus - Polymyxa betae molecular interaction: Role of the RNA4-encoded protein in virus transmission

Beet necrotic yellow vein virus (BNYVV), the leading infectious agent that affects sugar beet, is included within viruses transmitted through the soil from plasmodiophorid as Polymyxa betae. BNYVV is the causal agent of Rhizomania, which induces abnormal rootlet proliferation and is widespread in the sugar beet growing areas in Europe, Asia and America; for review see (Peltier et al., 2008). In this latter continent, Beet soil-borne mosaic virus (BSBMV) has been identified (Lee et al., 2001) and belongs to the benyvirus genus together with BNYVV, both vectored by P. betae. BSBMV is widely distributed only in the United States and it has not been reported yet in others countries. It was first identified in Texas as a sugar beet virus morphologically similar but serologically distinct to BNYVV. Subsequent sequence analysis of BSBMV RNAs evidenced similar genomic organization to that of BNYVV but sufficient molecular differences to distinct BSBMV and BNYVV in two different species (Rush et al., 2003). Benyviruses field isolates usually consist of four RNA species but some BNYVV isolates contain a fifth RNA. RNAs -1 contains a single long ORF encoding polypeptide that shares amino acid homology with known viral RNA-dependent RNA polymerases (RdRp) and helicases. RNAs -2 contains six ORFs: capsid protein (CP), one readthrough protein, triple gene block proteins (TGB) that are required for cell-to-cell virus movement and the sixth 14 kDa ORF is a post-translation gene silencing suppressor. RNAs -3 is involved on disease symptoms and is essential for virus systemic movement. BSBMV RNA-3 can be trans-replicated, trans-encapsidated by the BNYVV helper strain (RNA-1 and -2) (Ratti et al., 2009). BNYVV RNA-4 encoded one 31 kDa protein and is essential for vector interactions and virus transmission by P. betae (Rahim et al., 2007). BNYVV RNA-5 encoded 26 kDa protein that improve virus infections and accumulation in the hosts. We are interest on BSBMV effect on Rhizomania studies using powerful tools as full-length infectious cDNA clones. B-type full-length infectious cDNA clones are available (Quillet et al., 1989) as well as A/P-type RNA-3, -4 and -5 from BNYVV (unpublished). A-type BNYVV full-length clones are also available, but RNA-1 cDNA clone still need to be modified. During the PhD program, we start production of BSBMV full-length cDNA clones and we investigate molecular interactions between plant and Benyviruses exploiting biological, epidemiological and molecular similarities/divergences between BSBMV and BNYVV. During my PhD researchrs we obtained full length infectious cDNA clones of BSBMV RNA-1 and -2 and we demonstrate that they transcripts are replicated and packaged in planta and able to substitute BNYVV RNA-1 or RNA-2 in a chimeric viral progeny (BSBMV RNA-1 + BNYVV RNA-2 or BNYVV RNA-1 + BSBMV RNA-2). During BSBMV full-length cDNA clones production, unexpected 1,730 nts long form of BSBMV RNA-4 has been detected from sugar beet roots grown on BSBMV infected soil. Sequence analysis of the new BSBMV RNA-4 form revealed high identity (~100%) with published version of BSBMV RNA-4 sequence (NC_003508) between nucleotides 1-608 and 1,138-1,730, however the new form shows 528 additionally nucleotides between positions 608-1,138 (FJ424610). Two putative ORFs has been identified, the first one (nucleotides 383 to 1,234), encode a protein with predicted mass of 32 kDa (p32) and the second one (nucleotides 885 to 1,244) express an expected product of 13 kDa (p13). As for BSBMV RNA-3 (Ratti et al., 2009), full-length BSBMV RNA-4 cDNA clone permitted to obtain infectious transcripts that BNYVV viral machinery (Stras12) is able to replicate and to encapsidate in planta. Moreover, we demonstrated that BSBMV RNA-4 can substitute BNYVV RNA-4 for an efficient transmission through the vector P. betae in Beta vulgaris plants, demonstrating a very high correlation between BNYVV and BSBMV. At the same time, using BNYVV helper strain, we studied BSBMV RNA-4’s protein expression in planta. We associated a local necrotic lesions phenotype to the p32 protein expression onto mechanically inoculated C. quinoa. Flag or GFP-tagged sequences of p32 and p13 have been expressed in viral context, using Rep3 replicons, based on BNYVV RNA-3. Western blot analyses of local lesions contents, using FLAG-specific antibody, revealed a high molecular weight protein, which suggest either a strong interaction of BSBMV RNA4’s protein with host protein(s) or post translational modifications. GFP-fusion sequences permitted the subcellular localization of BSBMV RNA4’s proteins. Moreover we demonstrated the absence of self-activation domains on p32 by yeast two hybrid system approaches. We also confirmed that p32 protein is essential for virus transmission by P. betae using BNYVV helper strain and BNYVV RNA-3 and we investigated its role by the use of different deleted forms of p32 protein. Serial mechanical inoculation of wild-type BSBMV on C. quinoa plants were performed every 7 days. Deleted form of BSBMV RNA-4 (1298 bp) appeared after 14 passages and its sequence analysis shows deletion of 433 nucleotides between positions 611 and 1044 of RNA-4 new form. We demonstrated that this deleted form can’t support transmission by P. betae using BNYVV helper strain and BNYVV RNA-3, moreover we confirmed our hypothesis that BSBMV RNA-4 described by Lee et al. (2001) is a deleted form. Interesting after 21 passages we identifed one chimeric form of BSBMV RNA-4 and BSBMV RNA-3 (1146 bp). Two putative ORFs has been identified on its sequence, the first one (nucleotides 383 to 562), encode a protein with predicted mass of 7 kDa (p7), corresponding to the N-terminal of p32 protein encoded by BSBMV RNA-4; the second one (nucleotides 562 to 789) express an expected product of 9 kDa (p9) corresponding to the C-terminal of p29 encoded by BSBMV RNA-3. Results obtained by our research in this topic opened new research lines that our laboratories will develop in a closely future. In particular BSBMV p32 and its mutated forms will be used to identify factors, as host or vector protein(s), involved in the virus transmission through P. betae. The new results could allow selection or production of sugar beet plants able to prevent virus transmission then able to reduce viral inoculum in the soil.

Development, degeneration and neural network of the bodily self

The question addressed by this dissertation is how the human brain builds a coherent representation of the body, and how this representation is used to recognize its own body. Recent approaches by neuroimaging and TMS revealed hints for a distinct brain representation of human body, as compared with other stimulus categories. Neuropsychological studies demonstrated that body-parts and self body-parts recognition are separate processes sub-served by two different, even if possibly overlapping, networks within the brain. Bodily self-recognition is one aspect of our ability to distinguish between self and others and the self/other distinction is a crucial aspect of social behaviour. This is the reason why I have conducted a series of experiment on subjects with everyday difficulties in social and emotional behaviour, such as patients with autism spectrum disorders (ASD) and patients with Parkinson’s disease (PD). More specifically, I studied the implicit self body/face recognition (Chapter 6) and the influence of emotional body postures on bodily self-processing in TD children as well as in ASD children (Chapter 7). I found that the bodily self-recognition is present in TD and in ASD children and that emotional body postures modulate self and others’ body processing. Subsequently, I compared implicit and explicit bodily self-recognition in a neuro-degenerative pathology, such as in PD patients, and I found a selective deficit in implicit but not in explicit self-recognition (Chapter 8). This finding suggests that implicit and explicit bodily self-recognition are separate processes subtended by different mechanisms that can be selectively impaired. If the bodily self is crucial for self/other distinction, the space around the body (personal space) represents the space of interaction and communication with others. When, I studied this space in autism, I found that personal space regulation is impaired in ASD children (Chapter 9).

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.

Study of Rapid Alkalinization Factor (RALF)genes as plant susceptibility agents during plant-pathogen interaction in strawberry

Rapid Alkalinization Factor (RALF) are cysteins-rich peptides ubiquitous in plant kingdom. They play multiple roles as hormone signals and recently their involvement in host-pathogen crosstalk as negative regulator of immunity in Arabidopsis has also been recognized. In addition, RALF homologue peptides are secreted by different fungal pathogens as effectors during early stages of infections. The aim of this work was to characterize RALF genes as susceptibility factors during plant pathogen interaction in strawberry. For this, the genomic organization of the RALF gene families in the octoploid strawberry (Fragaria × ananassa) and the re-annotated genome of Fragaria vesca were described , identifying 13 member in F. vesca (FvRALF) and 50 members in F. x ananassa (FaRALF). The changes in expression of fruit FaRALF genes was investigated upon infection with C.acutatum and B. cinerea showing that, among RALF genes expressed in fruit, FaRALF3 was the only one upregulated by fungal infection in the ripe stage. A role of FaRALF3 as susceptibility gene was then assessed trough Agrobacterium-mediated transient FaRALF3 overexpression and silencing in fruits, revealing that FaRALF3 expression promotes fungal growth and hyphae penetration in host tissues. In silico analysis was used to identify distinct pathogen inducible elements upstream of the FaRALF3 gene. Agroinfiltration of strawberry fruit with deletion constructs of the FaRALF3 promoter identified a 5’ region required for FaRALF3 expression in fruit, but failed to identify a region responsible for fungal induced expression. Furthermore, FaRALF3 and strawberry receptor FERONIA (FaMRLK47) were heterologously expressed in E. coli in order to purify active proteins forms and study RALF-FERONIA interaction in strawberry. However, it was not possible to obtain pure and active proteins. Finally RNAi transgenic plants silenced for the FvRALF13 gene were genotypically and phenotypically characterized suggesting a role of FvRALF13 in flowering time regulation and reproductive organs development.