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.

Exercise associated factors affecting cardiovascular health and function: from myocyte signaling to genetic variations

The exact mechanisms of the exercise induced adaptations is not lucid, but recent studies have delineated two means of signaling by which the adaptations occur (1) substrate availability signaling (metabolic stress) (2) hormone-receptor signaling. We have decided to specifically investigate two metabolic signaling enzymes [AMP-activated kinase (AMPK) and Sirtuin 1(SIRT1)] and two hormones [Adiponectin and Adrenergic stimulation].Tis based on four papers with the following conclusions: (1)Increase in SIRT1 activity and expression in H9c2 cells treated with phenylephrine is an adaptive response to the hypertrophic stress, mediated by AMPK. (2)The lack of optimal nutritional conditions (energetic substrates) due to a prolonged activation of AMPK can contrast the establishment of hypertrophy, possibly also by means of the negative modulation of ODC activity. (3) Our findings offer a possibile hypothesis as to the fact the the G allele on site 45 could lead to the increasd risk of Type II diabetes through a decrease in lean body mass. (4) Our results suggest that there is an ADIPOQ gene effect in relation to bone parameters. Statistical analysis show that the presence of the T allele in position 45 favors an increase in lumbar spine bone mineral content (BMC) when compared to subjects with a G allele substitution, which can be do the the increase in lean body mass in this genotype group.

Pathogenic role of IL-33-mediated eosinophil infiltration and function in experimental inflammatory bowel disease

IL-33/ST2 axis is known to promote Th2 immune responses and has been linked to several autoimmune and inflammatory disorders, including inflammatory bowel disease (IBD), and recent evidences show that it can regulate eosinophils (EOS) infiltration and function. Based also on the well documented relationship between EOS and IBD, we assessed the role of IL-33-mediated eosinophilia and ileal inflammation in SAMP1/YitFc (SAMP) murine model of Th1/Th2 chronic enteritis, and we found that IL-33 is related to inflammation progression and EOS infiltration as well as IL-5 and eotaxins increase. Administering IL-33 to SAMP and AKR mice augmented eosinophilia, eotaxins mRNA expression and Th2 molecules production, whereas blockade of ST2 and/or typical EOS molecules, such as IL-5 and CCR3, resulted in a marked decrease of inflammation, EOS infiltration, IL-5 and eotaxins mRNA expression and Th2 cytokines production. Human data supported mice’s showing an increased colocalization of IL-33 and EOS in the colon mucosa of UC patients, as well as an augmented IL-5 and eotaxins mRNA expression, when compared to non-UC. Lastly we analyzed SAMP raised in germ free (GF) condition to see the microbiota effect on IL-33 expression and Th2 responses leading to chronic intestinal inflammation. We found a remarkable decrease in ileal IL-33 and Th2 cytokines mRNA expression as well as EOS infiltration in GF versus normal SAMP with comparable inflammatory scores. Moreover, EOS depletion in normal SAMP didn’t affect IL-33 mRNA expression. These data demonstrate a pathogenic role of IL-33-mediated eosinophilia in chronic intestinal inflammation, and that blockade of IL-33 and/or downstream EOS activation may represent a novel therapeutic modality to treat patients with IBD. Also they highlight the gut microbiota role in IL-33 production, and the following EOS infiltration in the intestinal mucosa, confirming that the microbiota is essential in mounting potent Th2 response leading to chronic ileitis in SAMP.

Evaluation of bone strength: microtomographic tecniques

This thesis is a part of a larger study about the characterization of mechanical and histomorphometrical properties of bone. The main objects of this study were the bone tissue properties and its resistance to mechanical loads. Moreover, the knowledge about the equipment selected to carry out the analyses, the micro-computed tomography (micro-CT), was improved. Particular attention was given to the reliability over time of the measuring instrument. In order to understand the main characteristics of bone mechanical properties a study of the skeletal, the bones of which it is composed and biological principles that drive their formation and remodelling, was necessary. This study has led to the definition of two macro-classes describing the main components responsible for the resistance to fracture of bone: quantity and quality of bone. The study of bone quantity is the current clinical standard measure for so-called bone densitometry, and research studies have amply demonstrated that the amount of tissue is correlated with its mechanical properties of elasticity and fracture. However, the models presented in the literature, including information on the mere quantity of tissue, have often been limited in describing the mechanical behaviour. Recent investigations have underlined that also the bone-structure and the tissue-mineralization play an important role in the mechanical characterization of bone tissue. For this reason in this thesis the class defined as bone quality was mainly studied, splitting it into two sub-classes of bone structure and tissue quality. A study on bone structure was designed to identify which structural parameters, among the several presented in the literature, could be integrated with the information about quantity, in order to better describe the mechanical properties of bone. In this way, it was also possible to analyse the iteration between structure and function. It has been known for long that bone tissue is capable of remodeling and changing its internal structure according to loads, but the dynamics of these changes are still being analysed. This part of the study was aimed to identify the parameters that could quantify the structural changes of bone tissue during the development of a given disease: osteoarthritis. A study on tissue quality would have to be divided into different classes, which would require a scale of analysis not suitable for the micro-CT. For this reason the study was focused only on the mineralization of the tissue, highlighting the difference between bone density and tissue density, working in a context where there is still an ongoing scientific debate.