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There is increasing evidence that microbial interactions can happen within microbial communities resulting in an increase of the pathogen resistance to antimicrobial therapies. However, the mechanisms of these interactions remain elusive at the present day. Previously, it has been shown that in a polymicrobial community, β-lactam resistant bacteria can protect other non-resistant bacteria from the action of β-lactam drugs without any gene transfer between the resistant and non-resistant bacteria. This phenomenon was named as “sheltering effect” and occurs when the resistant bacteria releases proteins that give protection to the non-resistant bacteria living in the same environment.\ud Klebsiella pneumoniae is one of the world's most dangerous multidrug resistant pathogens. Infections from this bacterium are seriously threatening the public health due to their great ability to quickly become resistant to every antibiotic available today. Even more importantly, K. pneumoniae is found in the blood of patients with polymicrobial infections. This doctoral project focused on the investigation of the sheltering effect in this pathogen. Studies carried out here were designed to elucidate the causes of the variability of this phenomenon observed among different clinical isolates of K. pneumoniae. Furthermore, the role of the Sec-dependent pathway and of the outer membrane vesicles (OMVs) in the sheltering effect was investigated. The present study also examined how the sheltering effect changes in response to different concentrations of β-lactam in the medium. Lastly the presence of sheltering effect in presence of drugs different from the β-lactams was also investigated,\ud The results obtained by these tests also allowed the development of methods for the direct quantification of the sheltering effect based on the features observed on an agar plate. The causes of the variability in the sheltering effect detected on plate were investigated by carrying out Random Amplified Polymorphic DNA (RAPD), Polymerase Chain Reaction (PCR) and Whole Genome Sequencing (WGS) on the genome of the isolates to find a relationship between their genetic features and their potential of sheltering effect. Minimum Inhibitory Concentration (MIC) tests were also performed in the attempt to find a relationship between their resistance profiles and their sheltering effect potential.\ud The results obtained suggest that the sheltering effect is a widespread and variable phenomenon in K. pneumoniae. The protective effect is likely due to the extracellular release of OMV-associated β-lactamases after Sec-mediated translocation of these enzymes from the cytosol to the periplasm. The results also suggest that the sheltering effect diminishes in response to increasing concentrations of β-lactam in the medium. Furthermore, the sheltering effect was not observed in presence of drugs different from the β-lactams. Lastly, no relationship was found between the sheltering effect potential of the isolates and their genetic and resistance features analysed in this project. Therefore more studies will be necessary to elucidate the causes of this variability.

Background: L-type calcium channels (LTCCs) play important roles in regulating cardiomyocyte physiology, which is governed by appropriate LTCC trafficking to and density at the cell surface. Factors influencing the expression, half-life, subcellular trafficking, and gating of LTCCs are therefore critically involved in conditions of cardiac physiology and disease. Methods: Yeast 2-hybrid screenings, biochemical and molecular evaluations, protein interaction assays, fluorescence microscopy, structural molecular modeling, and functional studies were used to investigate the molecular mechanisms through which the LTCC Ca v β2 chaperone regulates channel density at the plasma membrane. Results: On the basis of our previous results, we found a direct linear correlation between the total amount of the LTCC pore-forming Ca v α1.2 and the Akt-dependent phosphorylation status of Ca v β2 both in a mouse model of diabetic cardiac disease and in 6 diabetic and 7 nondiabetic cardiomyopathy patients with aortic stenosis undergoing aortic valve replacement. Mechanistically, we demonstrate that a conformational change in Ca v β2 triggered by Akt phosphorylation increases LTCC density at the cardiac plasma membrane, and thus the inward calcium current, through a complex pathway involving reduction of Ca v α1.2 retrograde trafficking and protein degradation through the prevention of dynamin-mediated LTCC endocytosis; promotion of Ca v α1.2 anterograde trafficking by blocking Kir/Gem-dependent sequestration of Ca v β2, thus facilitating the chaperoning of Ca v α1.2; and promotion of Ca v α1.2 transcription by the prevention of Kir/Gem-mediated shuttling of Ca v β2 to the nucleus, where it limits the transcription of Ca v α1.2 through recruitment of the heterochromatin protein 1γ epigenetic repressor to the Cacna1c promoter. On the basis of this mechanism, we developed a novel mimetic peptide that, through targeting of Ca v β2, corrects LTCC life-cycle alterations, facilitating the proper function of cardiac cells. Delivery of mimetic peptide into a mouse model of diabetic cardiac disease associated with LTCC abnormalities restored impaired calcium balance and recovered cardiac function. Conclusions: We have uncovered novel mechanisms modulating LTCC trafficking and life cycle and provide proof of concept for the use of Ca v β2 mimetic peptide as a novel therapeutic tool for the improvement of cardiac conditions correlated with alterations in LTCC levels and function.

Motivation: In recent years, structural genomics and ab initio molecular modeling activities are leading to the availability of a large number of structural models of proteins whose biochemical function is not known. The aim of this study was the development of a novel software tool that, given a protein’s structural model, predicts the presence and identity of active sites and/or ligand binding sites. Results: The algorithm implemented by ligand binding site recognition application (LIBRA) is based on a graph theory approach to find the largest subset of similar residues between an input protein and a collection of known functional sites. The algorithm makes use of two predefined databases for active sites and ligand binding sites, respectively, derived from the Catalytic Site Atlas and the Protein Data Bank. Tests indicate that LIBRA is able to identify the correct binding/active site in 90% of the cases analyzed, 90% of which feature the identified site as ranking first. As far as ligand binding site recognition is concerned, LIBRA outperforms other structure-based ligand binding sites detection tools with which it has been compared. Availability and implementation: The application, developed in Java SE 7 with a Swing GUI embedding a JMol applet, can be run on any OS equipped with a suitable Java Virtual Machine (JVM), and is available at the following URL: http://www.computationalbiology.it/software/LIBRAv1.zip. Contact: polticel@uniroma3.it Supplementary information: Supplementary data are available at Bioinformatics online.

Motivation: Structural genomics initiatives are increasingly leading to the determination of the 3D structure of target proteins whose catalytic function is not known. The aim of this work was that of developing a novel versatile tool for searching structural similarity, which allows to predict the catalytic function, if any, of these proteins. Results: The algorithm implemented by the tool is based on local structural comparison to find the largest subset of similar residues between an input protein and known functional sites. The method uses a geometric hashing approach where information related to residue pairs from the input structures is stored in a hash table and then is quickly retrieved during the comparison step. Tests on proteins belonging to different functional classes, done using the Catalytic Site Atlas entries as targets, indicate that the algorithm is able to identify the correct functional class of the input protein in the vast majority of the cases. Availability and implementation: The application was developed in Java SE 6, with a Java Swing Graphic User Interface (GUI). The system can be run locally on any operating system (OS) equipped with a suitable Java Virtual Machine, and is available at the following URL: http://www.computationalbiology.it/software/ASSISTv1.zip. Contact: polticel@uniroma3.it Supplementary information: Supplementary data are available at Bioinformatics online.

""Human serum albumin (HSA) accounts for most of the functions of plasma. Among. others, HSA serves as a carrier and a solubilizer for many endogenous and. exogenous ligands, including fatty acids (FAs) as well as peptides and proteins. such as the GA module of the bacterial poly(A)-binding (PAB) protein. Although. the biological function(s) of the GA module of the bacterial PAB protein is. unknown, the acquisition of the GA module adds selective advantages to the. bacterium in terms of growth rate and increase in virulence, probably by. providing the bacteria with FAs and, possibly, other nutrients transported by. HSA. Here, we hypothesize that the GA module may undergo a structural transition . from the all-α form to the 4β+α form typical of the GB domains upon binding of a . FA molecule, as part of the mechanism which allows the bacterial PAB protein to. extract FAs from HSA.""