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.

Assessing poverty with survey data. Uni-dimensional, multidimensional and resilience poverty analysis in Kenya

Traditionally Poverty has been measured by a unique indicator, income, assuming this was the most relevant dimension of poverty. Sen’s approach has dramatically changed this idea shedding light over the existence of many more dimensions and over the multifaceted nature of poverty; poverty cannot be represented by a unique indicator that only can evaluate a specific aspect of poverty. This thesis tracks an ideal path along with the evolution of the poverty analysis. Starting from the unidimensional analysis based on income and consumptions, this research enter the world of multidimensional analysis. After reviewing the principal approaches, the Foster and Alkire method is critically analyzed and implemented over data from Kenya. A step further is moved in the third part of the thesis, introducing a new approach to multidimensional poverty assessment: the resilience analysis.

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.

Master Equation: Biological Applications and Thermodynamic Description

It is well known that many realistic mathematical models of biological systems, such as cell growth, cellular development and differentiation, gene expression, gene regulatory networks, enzyme cascades, synaptic plasticity, aging and population growth need to include stochasticity. These systems are not isolated, but rather subject to intrinsic and extrinsic fluctuations, which leads to a quasi equilibrium state (homeostasis). The natural framework is provided by Markov processes and the Master equation (ME) describes the temporal evolution of the probability of each state, specified by the number of units of each species. The ME is a relevant tool for modeling realistic biological systems and allow also to explore the behavior of open systems. These systems may exhibit not only the classical thermodynamic equilibrium states but also the nonequilibrium steady states (NESS). This thesis deals with biological problems that can be treat with the Master equation and also with its thermodynamic consequences. It is organized into six chapters with four new scientific works, which are grouped in two parts: (1) Biological applications of the Master equation: deals with the stochastic properties of a toggle switch, involving a protein compound and a miRNA cluster, known to control the eukaryotic cell cycle and possibly involved in oncogenesis and with the propose of a one parameter family of master equations for the evolution of a population having the logistic equation as mean field limit. (2) Nonequilibrium thermodynamics in terms of the Master equation: where we study the dynamical role of chemical fluxes that characterize the NESS of a chemical network and we propose a one parameter parametrization of BCM learning, that was originally proposed to describe plasticity processes, to study the differences between systems in DB and NESS.

Development of new tools and devices for CMB and foreground data analysis and future experiments

The discovery of the Cosmic Microwave Background (CMB) radiation in 1965 is one of the fundamental milestones supporting the Big Bang theory. The CMB is one of the most important source of information in cosmology. The excellent accuracy of the recent CMB data of WMAP and Planck satellites confirmed the validity of the standard cosmological model and set a new challenge for the data analysis processes and their interpretation. In this thesis we deal with several aspects and useful tools of the data analysis. We focus on their optimization in order to have a complete exploitation of the Planck data and contribute to the final published results. The issues investigated are: the change of coordinates of CMB maps using the HEALPix package, the problem of the aliasing effect in the generation of low resolution maps, the comparison of the Angular Power Spectrum (APS) extraction performances of the optimal QML method, implemented in the code called BolPol, and the pseudo-Cl method, implemented in Cromaster. The QML method has been then applied to the Planck data at large angular scales to extract the CMB APS. The same method has been applied also to analyze the TT parity and the Low Variance anomalies in the Planck maps, showing a consistent deviation from the standard cosmological model, the possible origins for this results have been discussed. The Cromaster code instead has been applied to the 408 MHz and 1.42 GHz surveys focusing on the analysis of the APS of selected regions of the synchrotron emission. The new generation of CMB experiments will be dedicated to polarization measurements, for which are necessary high accuracy devices for separating the polarizations. Here a new technology, called Photonic Crystals, is exploited to develop a new polarization splitter device and its performances are compared to the devices used nowadays.

Earthquake forecasting and seismic hazard analysis: some insights on the testing phase and the modeling

This thesis is divided in three chapters. In the first chapter we analyse the results of the world forecasting experiment run by the Collaboratory for the Study of Earthquake Predictability (CSEP). We take the opportunity of this experiment to contribute to the definition of a more robust and reliable statistical procedure to evaluate earthquake forecasting models. We first present the models and the target earthquakes to be forecast. Then we explain the consistency and comparison tests that are used in CSEP experiments to evaluate the performance of the models. Introducing a methodology to create ensemble forecasting models, we show that models, when properly combined, are almost always better performing that any single model. In the second chapter we discuss in depth one of the basic features of PSHA: the declustering of the seismicity rates. We first introduce the Cornell-McGuire method for PSHA and we present the different motivations that stand behind the need of declustering seismic catalogs. Using a theorem of the modern probability (Le Cam's theorem) we show that the declustering is not necessary to obtain a Poissonian behaviour of the exceedances that is usually considered fundamental to transform exceedance rates in exceedance probabilities in the PSHA framework. We present a method to correct PSHA for declustering, building a more realistic PSHA. In the last chapter we explore the methods that are commonly used to take into account the epistemic uncertainty in PSHA. The most widely used method is the logic tree that stands at the basis of the most advanced seismic hazard maps. We illustrate the probabilistic structure of the logic tree, and then we show that this structure is not adequate to describe the epistemic uncertainty. We then propose a new probabilistic framework based on the ensemble modelling that properly accounts for epistemic uncertainties in PSHA.

Genus Bifidobacterium: taxonomy studies and gene expression analysis on folate pathway

Folates (vitamin B9) are essential water soluble vitamins, whose deficiency in humans may contribute to the onset of several diseases, such as anaemia, cancer, cardiovascular diseases, neurological problems as well as defects in embryonic development. Human and other mammals are unable to synthesize ex novo folate obtaining it from exogenous sources, via intestinal absorption. Recently the gut microbiota has been identified as an important source of folates and the selection and use of folate producing microorganisms represents an innovative strategy to increase human folate levels. The aim of this thesis was to gain a fundamental understanding of folate metabolism in Bifidobacterium adolescentis. The work was subdivided in three main phases, also aimed to solve different problems encountered working with Bifidobacterium strains. First, a new identification method (based on PCR-RFLP of hsp60 gene) was specifically developed to identify Bifidobacterium strains. Secondly, Bifidobacterium adolescentis biodiversity was explored in order to recognize representing strains of this species to be screened for their folate production ability. Results showed that this species is characterized by a wide variability and support the idea that a possible new taxonomic re-organization would be required. Finally B. adolescentis folate metabolism was studied using a double approach. A quantitative analysis of folate content was complemented by the examination of expression levels of genes involved in folate related pathways. For the normalization process, required to increase the robustness of the qRT-PCR analysis, an appropriate set of reference genes was tested using two different algorithms. Results demonstrate that B.adolescentis strains may represent an endogenous source of natural folate and they could be used to fortify fermented dairy products. This bio-fortification strategy presents many advantages for the consumer, providing native folate forms more bio-available, and not implicated in the discussed controversy concerning the safety of high intake of synthetic folic acid.