4 resultados para Eukaryotic Cells

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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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

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Sperm cells need hexoses as a substrate for their function, for both the maintenance of membrane homeostasis and the movement of the tail. These cells have a peculiar metabolism that has not yet been fully understood, but it is clear that they obtain energy from hexoses through glycolisis and/or oxidative phosphorylation. Spermatozoa are in contact with different external environments, beginning from the testicular and epididymal fluid, passing to the seminal plasma and finally to the female genital tract fluids; in addition, with the spread of reproductive biotechnologies, sperm cells are diluted and stored in various media, containing different energetic substrates. To utilize these energetic sources, sperm cells, as other eukaryotic cells, have a well-constructed protein system, that is mainly represented by the GLUT family proteins. These transporters have a membrane-spanning α-helix structure and work as an enzymatic pump that permit a fast gradient dependent passage of sugar molecules through the lipidic bilayer of sperm membrane. Many GLUTs have been studied in man, bull and rat spermatozoa; the presence of some GLUTs has been also demonstrated in boar and dog spermatozoa. The aims of the present study were - to determine the presence of GLUTs 1, 2, 3, 4 and 5 in boar, horse, dog and donkey spermatozoa and to describe their localization; - to study eventual changes in GLUTs location after capacitation and acrosome reaction in boar, stallion and dog spermatozoa; - to determine possible changes in GLUTs localization after capacitation induced by insulin and IGF stimulation in boar spermatozoa; - to evaluate changes in GLUTs localization after flow-cytometric sex sorting in boar sperm cells. GLUTs 1, 2, 3 and 5 presence and localization have been demonstrated in boar, stallion, dog and donkey spermatozoa by western blotting and immunofluorescence analysis; a relocation in GLUTs after capacitation has been observed only in dog sperm cells, while no changes have been observed in the other species examined. As for boar, the stimulation of the capacitation with insulin and IGF didn’t cause any change in GLUTs localization, as well as for the flow cytometric sorting procedure. In conclusion, this study confirms the presence of GLUTs 1, 2 ,3 and 5 in boar, dog, stallion and donkey spermatozoa, while GLUT 4 seems to be absent, as a confirmation of other studies. Only in dog sperm cells capacitating conditions induce a change in GLUTs distribution, even if the physiological role of these changes should be deepened.

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This work shows for the first time that native CSTB polymerizes on addition of Cu2+ and DnaK (Hsp70). Cysteines are involved in the polymerization process and in particular at least one cysteine is necessary. We propose that Cu2+ interacts with the thiol group of cysteine and oxidize it. The oxidized cysteine modifies the CSTB structure allowing interaction with DnaK/Hsp70 to occur. Thus, Cu2+ binding to CSTB exposes a site for DnaK and such interaction allows the polymerization of CSTB. The polymers generated from native CSTB monomers, are DTT sensitive and they may represent physiological polymers. Denatured CSTB does not require Cu2+ and polymerizes simply on addition of DnaK. The polymers generated from denatured CSTB do not respond to DTT. They have characteristics similar to those of the CSTB toxic aggregates described in vivo in eukaryotic cells following CSTB over-expression. Interaction between CSTB and Hsp70 is shown by IP experiments. The interaction occurs with WT CSTB and not with the cys mutant. This suggests that disulphur bonds are involved. Methal-cathalyzed oxidation of proteins involves reduction of the metal ion(s) bound to the protein itself and oxidation of neighboring ammino acid residues resulting in structural modification and de-stabilization of the molecule. In this work we propose that the cysteine thyol residue of CSTB in the presence of Cu2+ is oxidized, and cathalyzes the formation of disulphide bonds with Hsp70, that, once bound to CSTB, mediates its polymerization. In vivo this molecular mechanism of CSTB polymerization could be regulated by redox environment through the cysteine residue. This may imply that CSTB physiological polymers have a specific cellular function, different from that of the protease inhibitor known for the CSTB monomer. This hypothesis is interesting in relation to Progressive Myoclonus Epilepsy of type 1 (EPM1). This pathology is usually caused by mutations in the CSTB gene. CSTB is a ubiquitous protein, but EPM1 patients have problems only in the central nervous system. Maybe physiological CSTB polymers have a specific function altered in people affected by EPM1.

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Synthetic biology is a young field of applicative research aiming to design and build up artificial biological devices, useful for human applications. How synthetic biology emerged in past years and how the development of the Registry of Standard Biological Parts aimed to introduce one practical starting solution to apply the basics of engineering to molecular biology is presented in chapter 1 in the thesis The same chapter recalls how biological parts can make up a genetic program, the molecular cloning tecnique useful for this purpose, and an overview of the mathematical modeling adopted to describe gene circuit behavior. Although the design of gene circuits has become feasible the increasing complexity of gene networks asks for a rational approach to design gene circuits. A bottom-up approach was proposed, suggesting that the behavior of a complicated system can be predicted from the features of its parts. The option to use modular parts in large-scale networks will be facilitated by a detailed and shared characterization of their functional properties. Such a prediction, requires well-characterized mathematical models of the parts and of how they behave when assembled together. In chapter 2, the feasibility of the bottom-up approach in the design of a synthetic program in Escherichia coli bacterial cells is described. The rational design of gene networks is however far from being established. The synthetic biology approach can used the mathematical formalism to identify biological information not assessable with experimental measurements. In this context, chapter 3 describes the design of a synthetic sensor for identifying molecules of interest inside eukaryotic cells. The Registry of Standard parts collects standard and modular biological parts. To spread the use of BioBricks the iGEM competition was started. The ICM Laboratory, where Francesca Ceroni completed her Ph.D, partecipated with teams of students and Chapter 4 summarizes the projects developed.