Morphogenesis of follicular epithelium in Drosophila melanogaster: function of von Hippel-Lindau tumour suppressor gene

During my PhD I have been involved in several projects regarding the morphogenesis of the follicular epithelium, such as the analysis of the pathways that correlate follicular epithelium patterning and eggshell genes expression. Moreover, I used the follicular epithelium as a model system to analyze the function of the Drosophila homolog of the human von Hippel-Lindau (d-VHL) during oogenesis, in order to gain insight into the role of h-VHL for the pathogenesis of VHL disease. h-VHL is implicated in a variety of processes and there is now a greater appreciation of HIF-independent h-VHL functions that are relevant to tumour development, including maintenance and organization of the primary cilium, maintenance of the differentiated phenotype in renal cells and regulation of epithelial-mesenchymal transition. However, the function of h-VHL gene during development has not been fully understood. It was previously shown that d-VHL down-regulates the motility of tubular epithelial cells (tracheal cells) during embryogenesis. Epithelial morphogenesis is important for organogenesis and pivotal for carcinogenesis, but mechanisms that control it are poorly understood. The Drosophila follicular epithelium is a genetically tractable model to understand these mechanisms in vivo. Therefore, to examine whether d-VHL has a role in epithelial morphogenesis and maintenance, I performed genetic and molecular analyses by using in vivo and in vitro approaches. From my analysis, I determined that d-VHL binds to and stabilizes microtubules. Loss of d-VHL depolymerizes the microtubule network during oogenesis, leading to a possible deregulation in the subcellular trafficking transport of polarity markers from Golgi apparatus to the different domains in which follicle cells are divided. The analysis carried out has allowed to establish a significant role of d-VHL in the maintenance of the follicular epithelium integrity.

Clostridium difficile toxins facilitate bacterial colonization by modulating the fence and gate function of colonic epithelium

The contribution of Clostridium difficile toxin A and B (TcdA and TcdB) to cellular intoxication has been extensively studied, but their impact on bacterial colonization remains unclear. By setting-up two- and three-dimensional in vitro models of polarized gut epithelium, we investigated how C. difficile infection is affected by host cell polarity and whether TcdA and TcdB contribute to such events. Indeed, we observed that C. difficile adhesion and penetration of the epithelial barrier is substantially enhanced in poorly polarized or EGTA-treated cells, indicating that bacteria bind preferentially to the basolateral cell surface. In this context, we demonstrated that sub-lethal concentrations of C. difficile TcdA are able to alter cell polarity by causing redistribution of plasma membrane components between distinct surface domains. Taken together, the data suggest that toxin-mediated modulation of host cell organization may account for the capacity of this opportunistic pathogen to gain access to basolateral receptors leading to a successful colonization of the colonic mucosa.

Role of CARM1 (PRMT4) in high grade serous ovarian cancer metabolism and function of PRMT5 in ARID1A- deficient endometrial cancer invasion

The arginine methyltransferase CARM1 (PRMT4) is amplified and overexpressed in ~20% of high-grade serous ovarian cancer (HGSOC) and correlates with a poor survival. Therapeutic approaches based on CARM1 expression remain to be an unmet need. Here we show that fatty acid metabolism represents a metabolic vulnerability for HGSOC in a CARM1 expression status dependent manner. CARM1 promotes the de novo synthesis of fatty acids and monounsaturated fatty acids (MUFAs). The disruption of MUFAs synthesis by inhibition of SCD1 results in excessive accumulation of cytotoxic saturated fatty acids and it is synthetic lethal with CARM1 expression. Collectively, our data show that the pharmacological inhibition of MUFAs synthesis via SCD1 inhibition represents a therapeutic strategy for CARM1-high HGSOC. Another arginine methyltransferase, PRMT5, has been identified by our CRISPR screening analysis as a promising candidate for invasive ARID1A-deficient endometrial cancer. Endometrial Cancer frequently harbor somatic inactivating mutation of ARID1A that can promote an invasive phenotype. Our in vitro approach validated the CRISPR screening showing that both PRTM5 knock down and its pharmaceutical inhibition specifically hamper the invasion of ARID1A inactivated cells. Mechanistically, PRMT5 directly regulates the epithelia to mesenchymal transition pathway genes interacting with the SWI/SNF complexes. Moreover, in vivo experiments showed that PRMT5 inhibition contrasted the myometrium invasion highlighting PRMT5 inhibition as promising therapeutic strategy for ARID1A- inactivated aggressive endometrial cancer.

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.