Decoding Agc1 deficiency: bioinformatics approaches to unveil the functional implications of Slc25a12 on the transcriptome and epigenome

In the brain, mutations in SLC25A12 gene encoding AGC1 cause an ultra-rare genetic disease reported as a developmental and epileptic encephalopathy associated with global cerebral hypomyelination. Symptoms of the disease include diffused hypomyelination, arrested psychomotor development, severe hypotonia, seizures and are common to other neurological and developmental disorders. Amongst the biological components believed to be most affected by AGC1 deficiency are oligodendrocytes, glial cells responsible for myelination. Recent studies (Poeta et al, 2022) have also shown how altered levels of transcription factors and epigenetic modifications greatly affect proliferation and differentiation in oligodendrocyte precursor cells (OPCs). In this study we explore the transcriptomic landscape of Agc1 in two different system models: OPCs silenced for Agc1 and iPSCs from human patients differentiated to neural progenitors. Analyses range from differential expression analysis, alternative splicing, master regulator analysis. ATAC-seq results on OPCs were integrated with results from RNA-Seq to assess the activity of a TF based on the accessibility data from its putative targets, which allows to integrate RNA-Seq data to infer their role as either activators or repressors. All the findings for this model were also integrated with early data from iPSCs RNA-seq results, looking for possible commonalities between the two different system models, among which we find a downregulation in genes encoding for SREBP, a transcription factor regulating fatty acids biosynthesis, a key process for myelination which could explain the hypomyelinated state of patients. We also find that in both systems cells tend to form more neurites, likely losing their ability to differentiate, considering their progenitor state. We also report several alterations in the chromatin state of cells lacking Agc1, which confirms the hypothesis for which Agc1 is not a disease restricted only to metabolic alterations in the cells, but there is a profound shift of the regulatory state of these cells.

Angiogenesis and angioregression gene expression analyses in swine corpus luteum

The corpus luteum (CL) lifespan is characterized by a rapid growth, differentiation and controlled regression of the luteal tissue, accompanied by an intense angiogenesis and angioregression. Indeed, the CL is one of the most highly vascularised tissue in the body with a proliferation rate of the endothelial cells 4- to 20-fold more intense than in some of the most malignant human tumours. This angiogenic process should be rigorously controlled to allow the repeated opportunities of fertilization. After a first period of rapid growth, the tissue becomes stably organized and prepares itself to switch to the phenotype required for its next apoptotic regression. In pregnant swine, the lifespan of the CLs must be extended to support embryonic and foetal development and vascularisation is necessary for the maintenance of luteal function. Among the molecules involved in the angiogenesis, Vascular Endothelial Growth Factor (VEGF) is the main regulator, promoting endothelial cells proliferation, differentiation and survival as well as vascular permeability and vessel lumen formation. During vascular invasion and apoptosis process, the remodelling of the extracellular matrix is essential for the correct evolution of the CL, particularly by the action of specific class of proteolytic enzymes known as matrix metalloproteinases (MMPs). Another important factor that plays a role in the processes of angiogenesis and angioregression during the CL formation and luteolysis is the isopeptide Endothelin-1 (ET-1), which is well-known to be a potent vasoconstrictor and mitogen for endothelial cells. The goal of the present thesis was to study the role and regulation of vascularisation in an adult vascular bed. For this purpose, using a precisely controlled in vivo model of swine CL development and regression, we determined the levels of expression of the members of VEGF system (VEGF total and specific isoforms; VEGF receptor-1, VEGFR-1; VEGF receptor-2, VEGFR-2) and ET- 1 system (ET-1; endothelin converting enzyme-1, ECE-1; endothelin receptor type A, ET-A) as well as the activity of the Ca++/Mg++-dependent endonucleases and gelatinases (MMP-2 and MMP-9). Three experiments were conducted to reach such objectives in CLs isolated from ovaries of cyclic, pregnant or fasted gilts. In the Experiment I, we evaluated the influence of acute fasting on VEGF production and VEGF, VEGFR-2, ET-1, ECE-1 and ET-A mRNA expressions in CLs collected on day 6 after ovulation (midluteal phase). The results indicated a down-regulation of VEGF, VEGFR-2, ET-1 and ECE-1 mRNA expression, although no change was observed for VEGF protein. Furthermore, we observed that fasting stimulated steroidogenesis by luteal cells. On the basis of the main effects of VEGF (stimulation of vessel growth and endothelial permeability) and ET-1 (stimulation of endothelial cell proliferation and vasoconstriction, as well as VEGF stimulation), we concluded that feed restriction possibly inhibited luteal vessel development. This could be, at least in part, compensated by a decrease of vasal tone due to a diminution of ET-1, thus ensuring an adequate blood flow and the production of steroids by the luteal cells. In the Experiment II, we investigated the relationship between VEGF, gelatinases and Ca++/Mg++-dependent endonucleases activities with the functional CL stage throughout the oestrous cycle and at pregnancy. The results demonstrated differential patterns of expression of those molecules in correspondence to the different phases of the oestrous cycle. Immediately after ovulation, VEGF mRNA/protein levels and MMP-9 activity are maximal. On days 5–14 after ovulation, VEGF expression and MMP-2 and -9 activities are at basal levels, while Ca++/Mg++-dependent endonuclease levels increased significantly in relation to day 1. Only at luteolysis (day 17), Ca++/Mg++-dependent endonuclease and MMP-2 spontaneous activity increased significantly. At pregnancy, high levels of MMP-9 and VEGF were observed. These results suggested that during the very early luteal phase, high MMPs activities coupled with high VEGF levels drive the tissue to an angiogenic phenotype, allowing CL growth under LH (Luteinising Hormone) stimulus, while during the late luteal phase, low VEGF and elevate MMPs levels may play a role in the apoptotic tissue and extracellular matrix remodelling during structural luteolysis. In the Experiment III, we described the expression patterns of all distinct VEGF isoforms throughout the oestrous cycle. Furthermore, the mRNA expression and protein levels of both VEGF receptors were also evaluated. Four novel VEGF isoforms (VEGF144, VEGF147, VEGF182, and VEGF164b) were found for the first time in swine and the seven identified isoforms presented four different patterns of expression. All isoforms showed their highest mRNA levels in newly formed CLs (day 1), followed by a decrease during mid-late luteal phase (days 10–17), except for VEGF182, VEGF188 and VEGF144 that showed a differential regulation during late luteal phase (day 14) or at luteolysis (day 17). VEGF protein levels paralleled the most expressed and secreted VEGF120 and VEGF164 isoforms. The VEGF receptors mRNAs showed a different pattern of expression in relation to their ligands, increasing between day 1 and 3 and gradually decreasing during the mid-late luteal phase. The differential regulation of some VEGF isoforms principally during the late luteal phase and luteolysis suggested a specific role of VEGF during tissue remodelling process that occurs either for CL maintenance in case of pregnancy or for noncapillary vessel development essential for tissue removal during structural luteolysis. In summary, our findings allow us to determine relationships among factors involved in the angiogenesis and angioregression mechanisms that take place during the formation and regression of the CL. Thus, CL provides a very interesting model for studying such factors in different fields of the basic research.

Computational analyses on the structure-function relation in ion channels

Ion channels are protein molecules, embedded in the lipid bilayer of the cell membranes. They act as powerful sensing elements switching chemicalphysical stimuli into ion-fluxes. At a glance, ion channels are water-filled pores, which can open and close in response to different stimuli (gating), and one once open select the permeating ion species (selectivity). They play a crucial role in several physiological functions, like nerve transmission, muscular contraction, and secretion. Besides, ion channels can be used in technological applications for different purpose (sensing of organic molecules, DNA sequencing). As a result, there is remarkable interest in understanding the molecular determinants of the channel functioning. Nowadays, both the functional and the structural characteristics of ion channels can be experimentally solved. The purpose of this thesis was to investigate the structure-function relation in ion channels, by computational techniques. Most of the analyses focused on the mechanisms of ion conduction, and the numerical methodologies to compute the channel conductance. The standard techniques for atomistic simulation of complex molecular systems (Molecular Dynamics) cannot be routinely used to calculate ion fluxes in membrane channels, because of the high computational resources needed. The main step forward of the PhD research activity was the development of a computational algorithm for the calculation of ion fluxes in protein channels. The algorithm - based on the electrodiffusion theory - is computational inexpensive, and was used for an extensive analysis on the molecular determinants of the channel conductance. The first record of ion-fluxes through a single protein channel dates back to 1976, and since then measuring the single channel conductance has become a standard experimental procedure. Chapter 1 introduces ion channels, and the experimental techniques used to measure the channel currents. The abundance of functional data (channel currents) does not match with an equal abundance of structural data. The bacterial potassium channel KcsA was the first selective ion channels to be experimentally solved (1998), and after KcsA the structures of four different potassium channels were revealed. These experimental data inspired a new era in ion channel modeling. Once the atomic structures of channels are known, it is possible to define mathematical models based on physical descriptions of the molecular systems. These physically based models can provide an atomic description of ion channel functioning, and predict the effect of structural changes. Chapter 2 introduces the computation methods used throughout the thesis to model ion channels functioning at the atomic level. In Chapter 3 and Chapter 4 the ion conduction through potassium channels is analyzed, by an approach based on the Poisson-Nernst-Planck electrodiffusion theory. In the electrodiffusion theory ion conduction is modeled by the drift-diffusion equations, thus describing the ion distributions by continuum functions. The numerical solver of the Poisson- Nernst-Planck equations was tested in the KcsA potassium channel (Chapter 3), and then used to analyze how the atomic structure of the intracellular vestibule of potassium channels affects the conductance (Chapter 4). As a major result, a correlation between the channel conductance and the potassium concentration in the intracellular vestibule emerged. The atomic structure of the channel modulates the potassium concentration in the vestibule, thus its conductance. This mechanism explains the phenotype of the BK potassium channels, a sub-family of potassium channels with high single channel conductance. The functional role of the intracellular vestibule is also the subject of Chapter 5, where the affinity of the potassium channels hEag1 (involved in tumour-cell proliferation) and hErg (important in the cardiac cycle) for several pharmaceutical drugs was compared. Both experimental measurements and molecular modeling were used in order to identify differences in the blocking mechanism of the two channels, which could be exploited in the synthesis of selective blockers. The experimental data pointed out the different role of residue mutations in the blockage of hEag1 and hErg, and the molecular modeling provided a possible explanation based on different binding sites in the intracellular vestibule. Modeling ion channels at the molecular levels relates the functioning of a channel to its atomic structure (Chapters 3-5), and can also be useful to predict the structure of ion channels (Chapter 6-7). In Chapter 6 the structure of the KcsA potassium channel depleted from potassium ions is analyzed by molecular dynamics simulations. Recently, a surprisingly high osmotic permeability of the KcsA channel was experimentally measured. All the available crystallographic structure of KcsA refers to a channel occupied by potassium ions. To conduct water molecules potassium ions must be expelled from KcsA. The structure of the potassium-depleted KcsA channel and the mechanism of water permeation are still unknown, and have been investigated by numerical simulations. Molecular dynamics of KcsA identified a possible atomic structure of the potassium-depleted KcsA channel, and a mechanism for water permeation. The depletion from potassium ions is an extreme situation for potassium channels, unlikely in physiological conditions. However, the simulation of such an extreme condition could help to identify the structural conformations, so the functional states, accessible to potassium ion channels. The last chapter of the thesis deals with the atomic structure of the !- Hemolysin channel. !-Hemolysin is the major determinant of the Staphylococcus Aureus toxicity, and is also the prototype channel for a possible usage in technological applications. The atomic structure of !- Hemolysin was revealed by X-Ray crystallography, but several experimental evidences suggest the presence of an alternative atomic structure. This alternative structure was predicted, combining experimental measurements of single channel currents and numerical simulations. This thesis is organized in two parts, in the first part an overview on ion channels and on the numerical methods adopted throughout the thesis is provided, while the second part describes the research projects tackled in the course of the PhD programme. The aim of the research activity was to relate the functional characteristics of ion channels to their atomic structure. In presenting the different research projects, the role of numerical simulations to analyze the structure-function relation in ion channels is highlighted.

From "wet biology" to statistical analysis of structural features with bioinformatics tools

Many new Escherichia coli outer membrane proteins have recently been identified by proteomics techniques. However, poorly expressed proteins and proteins expressed only under certain conditions may escape detection when wild-type cells are grown under standard conditions. Here, we have taken a complementary approach where candidate outer membrane proteins have been identified by bioinformatics prediction, cloned and overexpressed, and finally localized by cell fractionation experiments. Out of eight predicted outer membrane proteins, we have confirmed the outer membrane localization for five—YftM, YaiO, YfaZ, CsgF, and YliI—and also provide preliminary data indicating that a sixth—YfaL—may be an outer membrane autotransporter.

Design and implementation of bioinformatics tools for large scale genome annotation

The continuous increase of genome sequencing projects produced a huge amount of data in the last 10 years: currently more than 600 prokaryotic and 80 eukaryotic genomes are fully sequenced and publically available. However the sole sequencing process of a genome is able to determine just raw nucleotide sequences. This is only the first step of the genome annotation process that will deal with the issue of assigning biological information to each sequence. The annotation process is done at each different level of the biological information processing mechanism, from DNA to protein, and cannot be accomplished only by in vitro analysis procedures resulting extremely expensive and time consuming when applied at a this large scale level. Thus, in silico methods need to be used to accomplish the task. The aim of this work was the implementation of predictive computational methods to allow a fast, reliable, and automated annotation of genomes and proteins starting from aminoacidic sequences. The first part of the work was focused on the implementation of a new machine learning based method for the prediction of the subcellular localization of soluble eukaryotic proteins. The method is called BaCelLo, and was developed in 2006. The main peculiarity of the method is to be independent from biases present in the training dataset, which causes the over‐prediction of the most represented examples in all the other available predictors developed so far. This important result was achieved by a modification, made by myself, to the standard Support Vector Machine (SVM) algorithm with the creation of the so called Balanced SVM. BaCelLo is able to predict the most important subcellular localizations in eukaryotic cells and three, kingdom‐specific, predictors were implemented. In two extensive comparisons, carried out in 2006 and 2008, BaCelLo reported to outperform all the currently available state‐of‐the‐art methods for this prediction task. BaCelLo was subsequently used to completely annotate 5 eukaryotic genomes, by integrating it in a pipeline of predictors developed at the Bologna Biocomputing group by Dr. Pier Luigi Martelli and Dr. Piero Fariselli. An online database, called eSLDB, was developed by integrating, for each aminoacidic sequence extracted from the genome, the predicted subcellular localization merged with experimental and similarity‐based annotations. In the second part of the work a new, machine learning based, method was implemented for the prediction of GPI‐anchored proteins. Basically the method is able to efficiently predict from the raw aminoacidic sequence both the presence of the GPI‐anchor (by means of an SVM), and the position in the sequence of the post‐translational modification event, the so called ω‐site (by means of an Hidden Markov Model (HMM)). The method is called GPIPE and reported to greatly enhance the prediction performances of GPI‐anchored proteins over all the previously developed methods. GPIPE was able to predict up to 88% of the experimentally annotated GPI‐anchored proteins by maintaining a rate of false positive prediction as low as 0.1%. GPIPE was used to completely annotate 81 eukaryotic genomes, and more than 15000 putative GPI‐anchored proteins were predicted, 561 of which are found in H. sapiens. In average 1% of a proteome is predicted as GPI‐anchored. A statistical analysis was performed onto the composition of the regions surrounding the ω‐site that allowed the definition of specific aminoacidic abundances in the different considered regions. Furthermore the hypothesis that compositional biases are present among the four major eukaryotic kingdoms, proposed in literature, was tested and rejected. All the developed predictors and databases are freely available at: BaCelLo http://gpcr.biocomp.unibo.it/bacello eSLDB http://gpcr.biocomp.unibo.it/esldb GPIPE http://gpcr.biocomp.unibo.it/gpipe

Enabling computationally intensive bioinformatics applications on the Grid platform

Bioinformatics is a recent and emerging discipline which aims at studying biological problems through computational approaches. Most branches of bioinformatics such as Genomics, Proteomics and Molecular Dynamics are particularly computationally intensive, requiring huge amount of computational resources for running algorithms of everincreasing complexity over data of everincreasing size. In the search for computational power, the EGEE Grid platform, world's largest community of interconnected clusters load balanced as a whole, seems particularly promising and is considered the new hope for satisfying the everincreasing computational requirements of bioinformatics, as well as physics and other computational sciences. The EGEE platform, however, is rather new and not yet free of problems. In addition, specific requirements of bioinformatics need to be addressed in order to use this new platform effectively for bioinformatics tasks. In my three years' Ph.D. work I addressed numerous aspects of this Grid platform, with particular attention to those needed by the bioinformatics domain. I hence created three major frameworks, Vnas, GridDBManager and SETest, plus an additional smaller standalone solution, to enhance the support for bioinformatics applications in the Grid environment and to reduce the effort needed to create new applications, additionally addressing numerous existing Grid issues and performing a series of optimizations. The Vnas framework is an advanced system for the submission and monitoring of Grid jobs that provides an abstraction with reliability over the Grid platform. In addition, Vnas greatly simplifies the development of new Grid applications by providing a callback system to simplify the creation of arbitrarily complex multistage computational pipelines and provides an abstracted virtual sandbox which bypasses Grid limitations. Vnas also reduces the usage of Grid bandwidth and storage resources by transparently detecting equality of virtual sandbox files based on content, across different submissions, even when performed by different users. BGBlast, evolution of the earlier project GridBlast, now provides a Grid Database Manager (GridDBManager) component for managing and automatically updating biological flatfile databases in the Grid environment. GridDBManager sports very novel features such as an adaptive replication algorithm that constantly optimizes the number of replicas of the managed databases in the Grid environment, balancing between response times (performances) and storage costs according to a programmed cost formula. GridDBManager also provides a very optimized automated management for older versions of the databases based on reverse delta files, which reduces the storage costs required to keep such older versions available in the Grid environment by two orders of magnitude. The SETest framework provides a way to the user to test and regressiontest Python applications completely scattered with side effects (this is a common case with Grid computational pipelines), which could not easily be tested using the more standard methods of unit testing or test cases. The technique is based on a new concept of datasets containing invocations and results of filtered calls. The framework hence significantly accelerates the development of new applications and computational pipelines for the Grid environment, and the efforts required for maintenance. An analysis of the impact of these solutions will be provided in this thesis. This Ph.D. work originated various publications in journals and conference proceedings as reported in the Appendix. Also, I orally presented my work at numerous international conferences related to Grid and bioinformatics.

Neutronics analyses for fast spectrum nuclear systems and scenario studies for advanced nuclear fuel cycles

The present PhD thesis summarizes the three-years study about the neutronic investigation of a new concept nuclear reactor aiming at the optimization and the sustainable management of nuclear fuel in a possible European scenario. A new generation nuclear reactor for the nuclear reinassance is indeed desired by the actual industrialized world, both for the solution of the energetic question arising from the continuously growing energy demand together with the corresponding reduction of oil availability, and the environment question for a sustainable energy source free from Long Lived Radioisotopes and therefore geological repositories. Among the Generation IV candidate typologies, the Lead Fast Reactor concept has been pursued, being the one top rated in sustainability. The European Lead-cooled SYstem (ELSY) has been at first investigated. The neutronic analysis of the ELSY core has been performed via deterministic analysis by means of the ERANOS code, in order to retrieve a stable configuration for the overall design of the reactor. Further analyses have been carried out by means of the Monte Carlo general purpose transport code MCNP, in order to check the former one and to define an exact model of the system. An innovative system of absorbers has been conceptualized and designed for both the reactivity compensation and regulation of the core due to cycle swing, as well as for safety in order to guarantee the cold shutdown of the system in case of accident. Aiming at the sustainability of nuclear energy, the steady-state nuclear equilibrium has been investigated and generalized into the definition of the ``extended'' equilibrium state. According to this, the Adiabatic Reactor Theory has been developed, together with a New Paradigm for Nuclear Power: in order to design a reactor that does not exchange with the environment anything valuable (thus the term ``adiabatic''), in the sense of both Plutonium and Minor Actinides, it is required indeed to revert the logical design scheme of nuclear cores, starting from the definition of the equilibrium composition of the fuel and submitting to the latter the whole core design. The New Paradigm has been applied then to the core design of an Adiabatic Lead Fast Reactor complying with the ELSY overall system layout. A complete core characterization has been done in order to asses criticality and power flattening; a preliminary evaluation of the main safety parameters has been also done to verify the viability of the system. Burn up calculations have been then performed in order to investigate the operating cycle for the Adiabatic Lead Fast Reactor; the fuel performances have been therefore extracted and inserted in a more general analysis for an European scenario. The present nuclear reactors fleet has been modeled and its evolution simulated by means of the COSI code in order to investigate the materials fluxes to be managed in the European region. Different plausible scenarios have been identified to forecast the evolution of the European nuclear energy production, including the one involving the introduction of Adiabatic Lead Fast Reactors, and compared to better analyze the advantages introduced by the adoption of new concept reactors. At last, since both ELSY and the ALFR represent new concept systems based upon innovative solutions, the neutronic design of a demonstrator reactor has been carried out: such a system is intended to prove the viability of technology to be implemented in the First-of-a-Kind industrial power plant, with the aim at attesting the general strategy to use, to the largest extent. It was chosen then to base the DEMO design upon a compromise between demonstration of developed technology and testing of emerging technology in order to significantly subserve the purpose of reducing uncertainties about construction and licensing, both validating ELSY/ALFR main features and performances, and to qualify numerical codes and tools.

Experimental and numerical analyses about the efficiency of flow through devices for the sediment controll in urban runoff

As land is developed, the impervious surfaces that are created increase the amount of runoff during rainfall events, disrupting the natural hydrologic cycle, with an increment in volume of runoff and in pollutant loadings. Pollutants deposited or derived from an activity on the land surface will likely end up in stormwater runoff in some concentration, such as nutrients, sediment, heavy metals, hydrocarbons, gasoline additives, pathogens, deicers, herbicides and pesticides. Several of these pollutants are particulate-bound, so it appears clear that sediment removal can provide significant water-quality improvements and it appears to be important the knowledge of the ability of stromwater treatment devices to retain particulate matter. For this reason three different units which remove sediments have been tested through laboratory. In particular a roadside gully pot has been tested under steady hydraulic conditions, varying the characteristics of the influent solids (diameter, particle size distribution and specific gravity). The efficiency in terms of particles retained has been evaluated as a function of influent flow rate and particles characteristics; results have been compared to efficiency evaluated applying an overflow rate model. Furthermore the role of particles settling velocity in efficiency determination has been investigated. After the experimental runs on the gully pot, a standard full-scale model of an hydrodynamic separator (HS) has been tested under unsteady influent flow rate condition, and constant solid concentration at the input. The results presented in this study illustrate that particle separation efficiency of the unit is predominately influenced by operating flow rate, which strongly affects the particles and hydraulic residence time of the system. The efficiency data have been compared to results obtained from a modified overflow rate model; moreover the residence time distribution has been experimentally determined through tracer analyses for several steady flow rates. Finally three testing experiments have been performed for two different configurations of a full-scale model of a clarifier (linear and crenulated) under unsteady influent flow rate condition, and constant solid concentration at the input. The results illustrate that particle separation efficiency of the unit is predominately influenced by the configuration of the unit itself. Turbidity measures have been used to compare turbidity with the suspended sediments concentration, in order to find a correlation between these two values, which can allow to have a measure of the sediments concentration simply installing a turbidity probe.

A regional environmental accounting matrix and integrated environmental economic analyses to support regional planning

This research deals with the deepening and use of an environmental accounting matrix in Emilia-Romagna, RAMEA air emissions (regional NAMEA), carried out by the Regional Environment Agency (Arpa) in an European project. After a depiction of the international context regarding the widespread needing to integrate economic indicators and go beyond conventional reporting system, this study explains the structure, update and development of the tool. The overall aim is to outline the matrix for environmental assessments of regional plans, draw up sustainable reports and monitor effects of regional policies in a sustainable development perspective. The work focused on an application of a Shift-Share model, on the integration with eco-taxes, industrial waste production, energy consumptions, on applications of the extended RAMEA as a policy tool, following Eurostat guidelines. The common thread is the eco-efficiency (economic-environmental efficiency) index. The first part, in English, treats the methodology used to build a more complete tool; in the second part RAMEA has been applied on two regional case studies, in Italian, to support decision makers regarding Strategic Environmental Assessments’ processes (2001/42/EC). The aim is to support an evidence-based policy making by integrating sustainable development concerns at all levels. The first case study regards integrated environmental-economic analyses in support to the SEA of the Regional Waste management plan. For the industrial waste production an extended and updated RAMEA has been developed as a useful policy tool, to help in analysing and monitoring the state of environmental-economic performances. The second case study deals with the environmental report for the SEA of the Regional Program concerning productive activities. RAMEA has been applied aiming to an integrated environmental-economic analysis of the context, to investigate the performances of the regional production chains and to depict and monitor the area where the program should be carried out, from an integrated environmental-economic perspective.

Fish quality assessment through the application of chemico-physical, sensory and microbiological analyses

The quality of fish products is indispensably linked to the freshness of the raw material modulated by appropriate manipulation and storage conditions, specially the storage temperature after catch. The purpose of the research presented in this thesis, which was largely conducted in the context of a research project funded by Italian Ministry of Agricultural, Food and Forestry Policies (MIPAAF), concerned the evaluation of the freshness of farmed and wild fish species, in relation to different storage conditions, under ice (0°C) or at refrigeration temperature (4°C). Several specimens of different species, bogue (Boops boops), red mullet (Mullus barbatus), sea bream (Sparus aurata) and sea bass (Dicentrarchus labrax), during storage, under the different temperature conditions adopted, have been examined. The assessed control parameters were physical (texture, through the use of a dynamometer; visual quality using a computer vision system (CVS)), chemical (through footprint metabolomics 1H-NMR) and sensory (Quality Index Method (QIM). Microbiological determinations were also carried out on the species of hake (Merluccius merluccius). In general obtained results confirmed that the temperature of manipulation/conservation is a key factor in maintaining fish freshness. NMR spectroscopy showed to be able to quantify and evaluate the kinetics for unselected compounds during fish degradation, even a posteriori. This can be suitable for the development of new parameters related to quality and freshness. The development of physical methods, particularly the image analysis performed by computer vision system (CVS), for the evaluation of fish degradation, is very promising. Among CVS parameters, skin colour, presence and distribution of gill mucus, and eye shape modification evidenced a high sensibility for the estimation of fish quality loss, as a function of the adopted storage conditions. Particularly the eye concavity index detected on fish eye showed a high positive correlation with total QIM score.

Graph algorithms for bioinformatics

Biological data are inherently interconnected: protein sequences are connected to their annotations, the annotations are structured into ontologies, and so on. While protein-protein interactions are already represented by graphs, in this work I am presenting how a graph structure can be used to enrich the annotation of protein sequences thanks to algorithms that analyze the graph topology. We also describe a novel solution to restrict the data generation needed for building such a graph, thanks to constraints on the data and dynamic programming. The proposed algorithm ideally improves the generation time by a factor of 5. The graph representation is then exploited to build a comprehensive database, thanks to the rising technology of graph databases. While graph databases are widely used for other kind of data, from Twitter tweets to recommendation systems, their application to bioinformatics is new. A graph database is proposed, with a structure that can be easily expanded and queried.