Bosentan, an endothelin receptor antagonist, ameliorates collagen-induced arthritis: the role of TNF-alpha in the induction of endothelin system genes

Endothelins (ETs) are involved in several inflammatory events. The present study investigated the efficacy of bosentan, a dual ETA/ETB receptor antagonist, in collagen-induced arthritis (CIA) in mice. CIA was induced in DBA/1J mice. Arthritic mice were treated with bosentan (100 mg/kg) once a day, starting from the day when arthritis was clinically detectable. CIA progression was assessed by measurements of visual clinical score, paw swelling and hypernociception. Histological changes, neutrophil infiltration and pro-inflammatory cytokines were evaluated in the joints. Gene expression in the lymph nodes of arthritic mice was evaluated by microarray technology. PreproET-1 mRNA expression in the lymph nodes of mice and in peripheral blood mononuclear cells (PBMCs) was evaluated by real-time PCR. The differences were evaluated by one-way ANOVA or Student's t test. Oral treatment with bosentan markedly ameliorated the clinical aspects of CIA (visual clinical score, paw swelling and hyperalgesia). Bosentan treatment also reduced joint damage, leukocyte infiltration and pro-inflammatory cytokine levels (IL-1 beta, TNF alpha and IL-17) in the joint tissues. Changes in gene expression in the lymph nodes of arthritic mice returned to the levels of the control mice after bosentan treatment. PreproET mRNA expression increased in PBMCs from rheumatoid arthritis (RA) patients but returned to basal level in PBMCs from patients under anti-TNF therapy. In-vitro treatment of PBMCs with TNF alpha upregulated ET system genes. These findings indicate that ET receptor antagonists, such as bosentan, might be useful in controlling RA. Moreover, it seems that ET mediation of arthritis is triggered by TNF alpha.

Prenatal and Neonatal Adaptations with a Focus on the Respiratory System

Contents Among the modifications that occur during the neonatal period, pulmonary development is the most critical. The neonate's lungs must be able to perform adequate gas exchange, which was previously accomplished by the placenta. Neonatal respiratory distress syndrome is defined as insufficient surfactant production or pulmonary structural immaturity and is specifically relevant to preterm newborns. Prenatal maternal betamethasone treatment of bitches at 55days of gestation leads to structural changes in the neonatal lung parenchyma and consequently an improvement in the preterm neonatal respiratory condition, but not to an increase in pulmonary surfactant production. Parturition represents an important challenge to neonatal adaptation, as the uterine and abdominal contractions during labour provoke intermittent hypoxia. Immediately after birth, puppies present venous mixed acidosis (low blood pH and high dioxide carbon saturation) and low but satisfactory Apgar scores. Thus, the combination of physiological hypoxia during birth and the initial effort of filling the pulmonary alveoli with oxygen results in anaerobiosis. As a neonatal adaptation follow-up, the Apgar analysis indicates a tachypnoea response after 1h of life, which leads to a shift in the blood acidbase status to metabolic acidosis. One hour is sufficient for canine neonates to achieve an ideal Apgar score; however, a haemogasometric imbalance persists. Dystocia promotes a long-lasting bradycardia effect, slows down Apgar score progression and aggravates metabolic acidosis and stress. The latest data reinforce the need to accurately intervene during canine parturition and offer adequate medical treatment to puppies that underwent a pathological labour.

Reconstruction and analysis of the NF-kB pathway interactome: a systems biology approach

Background. One of the phenomena observed in human aging is the progressive increase of a systemic inflammatory state, a condition referred to as “inflammaging”, negatively correlated with longevity. A prominent mediator of inflammation is the transcription factor NF-kB, that acts as key transcriptional regulator of many genes coding for pro-inflammatory cytokines. Many different signaling pathways activated by very diverse stimuli converge on NF-kB, resulting in a regulatory network characterized by high complexity. NF-kB signaling has been proposed to be responsible of inflammaging. Scope of this analysis is to provide a wider, systemic picture of such intricate signaling and interaction network: the NF-kB pathway interactome. Methods. The study has been carried out following a workflow for gathering information from literature as well as from several pathway and protein interactions databases, and for integrating and analyzing existing data and the relative reconstructed representations by using the available computational tools. Strong manual intervention has been necessarily used to integrate data from multiple sources into mathematically analyzable networks. The reconstruction of the NF-kB interactome pursued with this approach provides a starting point for a general view of the architecture and for a deeper analysis and understanding of this complex regulatory system. Results. A “core” and a “wider” NF-kB pathway interactome, consisting of 140 and 3146 proteins respectively, were reconstructed and analyzed through a mathematical, graph-theoretical approach. Among other interesting features, the topological characterization of the interactomes shows that a relevant number of interacting proteins are in turn products of genes that are controlled and regulated in their expression exactly by NF-kB transcription factors. These “feedback loops”, not always well-known, deserve deeper investigation since they may have a role in tuning the response and the output consequent to NF-kB pathway initiation, in regulating the intensity of the response, or its homeostasis and balance in order to make the functioning of such critical system more robust and reliable. This integrated view allows to shed light on the functional structure and on some of the crucial nodes of thet NF-kB transcription factors interactome. Conclusion. Framing structure and dynamics of the NF-kB interactome into a wider, systemic picture would be a significant step toward a better understanding of how NF-kB globally regulates diverse gene programs and phenotypes. This study represents a step towards a more complete and integrated view of the NF-kB signaling system.

Molecular interactions: metal ions and protein chaperones in the urease system from Helicobacter pylori

Although nickel is a toxic metal for living organisms in its soluble form, its importance in many biological processes recently emerged. In this view, the investigation of the nickel-dependent enzymes urease and [NiFe]-hydrogenase, especially the mechanism of nickel insertion into their active sites, represent two intriguing case studies to understand other analogous systems and therefore to lead to a comprehension of the nickel trafficking inside the cell. Moreover, these two enzymes have been demonstrated to ensure survival and colonization of the human pathogen H. pylori, the only known microorganism able to proliferate in the gastric niche. The right nickel delivering into the urease active site requires the presence of at least four accessory proteins, UreD, UreE, UreF and UreG. Similarly, analogous process is principally mediated by HypA and HypB proteins in the [NiFe]-hydrogenase system. Indeed, HpHypA and HpHypB also have been proposed to act in the activation of the urease enzyme from H. pylori, probably mobilizing nickel ions from HpHypA to the HpUreE-HpUreG complex. A complete comprehension of the interaction mechanism between the accessory proteins and the crosstalk between urease and hydrogenase accessory systems requires the determination of the role of each protein chaperone that strictly depends on their structural and biochemical properties. The availability of HpUreE, HpUreG and HpHypA proteins in a pure form is a pre-requisite to perform all the subsequent protein characterizations, thus their purification was the first aim of this work. Subsequently, the structural and biochemical properties of HpUreE were investigated using multi-angle and quasi-elastic light scattering, as well as NMR and circular dichroism spectroscopy. The thermodynamic parameters of Ni2+ and Zn2+ binding to HpUreE were principally established using isothermal titration calorimetry and the importance of key histidine residues in the process of binding metal ions was studied using site-directed mutagenesis. The molecular details of the HpUreE-HpUreG and HpUreE-HpHypA protein-protein assemblies were also elucidated. The interaction between HpUreE and HpUreG was investigated using ITC and NMR spectroscopy, and the influence of Ni2+ and Zn2+ metal ions on the stabilization of this association was established using native gel electrophoresis, light scattering and thermal denaturation scanning followed by CD spectroscopy. Preliminary HpUreE-HpHypA interaction studies were conducted using ITC. Finally, the possible structural architectures of the two protein-protein assemblies were rationalized using homology modeling and docking computational approaches. All the obtained data were interpreted in order to achieve a more exhaustive picture of the urease activation process, and the correlation with the accessory system of the hydrogenase enzyme, considering the specific role and activity of the involved protein players. A possible function for Zn2+ in the chaperone network involved in Ni2+ trafficking and urease activation is also envisaged.

Multi-level models and infrastructures for simulating biological system development

The hierarchical organisation of biological systems plays a crucial role in the pattern formation of gene expression resulting from the morphogenetic processes, where autonomous internal dynamics of cells, as well as cell-to-cell interactions through membranes, are responsible for the emergent peculiar structures of the individual phenotype. Being able to reproduce the systems dynamics at different levels of such a hierarchy might be very useful for studying such a complex phenomenon of self-organisation. The idea is to model the phenomenon in terms of a large and dynamic network of compartments, where the interplay between inter-compartment and intra-compartment events determines the emergent behaviour resulting in the formation of spatial patterns. According to these premises the thesis proposes a review of the different approaches already developed in modelling developmental biology problems, as well as the main models and infrastructures available in literature for modelling biological systems, analysing their capabilities in tackling multi-compartment / multi-level models. The thesis then introduces a practical framework, MS-BioNET, for modelling and simulating these scenarios exploiting the potential of multi-level dynamics. This is based on (i) a computational model featuring networks of compartments and an enhanced model of chemical reaction addressing molecule transfer, (ii) a logic-oriented language to flexibly specify complex simulation scenarios, and (iii) a simulation engine based on the many-species/many-channels optimised version of Gillespie’s direct method. The thesis finally proposes the adoption of the agent-based model as an approach capable of capture multi-level dynamics. To overcome the problem of parameter tuning in the model, the simulators are supplied with a module for parameter optimisation. The task is defined as an optimisation problem over the parameter space in which the objective function to be minimised is the distance between the output of the simulator and a target one. The problem is tackled with a metaheuristic algorithm. As an example of application of the MS-BioNET framework and of the agent-based model, a model of the first stages of Drosophila Melanogaster development is realised. The model goal is to generate the early spatial pattern of gap gene expression. The correctness of the models is shown comparing the simulation results with real data of gene expression with spatial and temporal resolution, acquired in free on-line sources.

Use of E. coli OMVs as delivery system to elicit neutralizing antibodies against Chlamydia infectivity: the HtrA protein example

The obligate intracellular pathogen Chlamydia trachomatis is a gram negative bacterium which infects epithelial cells of the reproductive tract. C. trachomatis is the leading cause of bacterial sexually transmitted disease worldwide and a vaccine against this pathogen is highly needed. Many evidences suggest that both antigen specific-Th1 cells and antibodies may be important to provide protection against Chlamydia infection. In a previous study we have identified eight new Chlamydia antigens inducing CD4-Th1 and/or antibody responses that, when combined properly, can protect mice from Chlamydia infection. However, all selected recombinant antigens, upon immunization in mice, elicited antibodies not able to neutralize Chlamydia infectivity in vitro. With the aim to improve the quality of the immune response by inducing effective neutralizing antibodies, we used a novel delivery system based on the unique capacity of E. coli Outer Membrane Vesicles (OMV) to present membrane proteins in their natural composition and conformation. We have expressed Chlamydia antigens, previously identified as vaccine candidates, in the OMV system. Among all OMV preparations, the one expressing HtrA Chlamydia antigen (OMV-HtrA), showed to be the best in terms of yield and quantity of expressed protein, was used to produce mice immune sera to be tested in neutralization assay in vitro. We observed that OMV-HtrA elicited specific antibodies able to neutralize efficiently Chlamydia infection in vitro, indicating that the presentation of the antigens in their natural conformation is crucial to induce an effective immune response. This is one of the first examples in which antibodies directed against a new Chlamydia antigen, other than MOMP (the only so far known antigen inducing neutralizing antibodies), are able to block the Chlamydia infectivity in vitro. Finally, by performing an epitope mapping study, we investigated the specificity of the antibody response induced by the recombinant HtrA and by OMV-HtrA. In particular, we identified some linear epitopes exclusively recognized by antibodies raised with the OMV-HtrA system, detecting in this manner the antigen regions likely responsible of the neutralizing effect.

Enabling a direct path from end-user specifications to executable protocols in a biology laboratory environment

Biomedical analyses are becoming increasingly complex, with respect to both the type of the data to be produced and the procedures to be executed. This trend is expected to continue in the future. The development of information and protocol management systems that can sustain this challenge is therefore becoming an essential enabling factor for all actors in the field. The use of custom-built solutions that require the biology domain expert to acquire or procure software engineering expertise in the development of the laboratory infrastructure is not fully satisfactory because it incurs undesirable mutual knowledge dependencies between the two camps. We propose instead an infrastructure concept that enables the domain experts to express laboratory protocols using proper domain knowledge, free from the incidence and mediation of the software implementation artefacts. In the system that we propose this is made possible by basing the modelling language on an authoritative domain specific ontology and then using modern model-driven architecture technology to transform the user models in software artefacts ready for execution in a multi-agent based execution platform specialized for biomedical laboratories.

Medicalgenomics.org : an open source database and retrieval system for biomedical analysis

Die Molekularbiologie von Menschen ist ein hochkomplexes und vielfältiges Themengebiet, in dem in vielen Bereichen geforscht wird. Der Fokus liegt hier insbesondere auf den Bereichen der Genomik, Proteomik, Transkriptomik und Metabolomik, und Jahre der Forschung haben große Mengen an wertvollen Daten zusammengetragen. Diese Ansammlung wächst stetig und auch für die Zukunft ist keine Stagnation absehbar. Mittlerweile aber hat diese permanente Informationsflut wertvolles Wissen in unüberschaubaren, digitalen Datenbergen begraben und das Sammeln von forschungsspezifischen und zuverlässigen Informationen zu einer großen Herausforderung werden lassen. Die in dieser Dissertation präsentierte Arbeit hat ein umfassendes Kompendium von humanen Geweben für biomedizinische Analysen generiert. Es trägt den Namen medicalgenomics.org und hat diverse biomedizinische Probleme auf der Suche nach spezifischem Wissen in zahlreichen Datenbanken gelöst. Das Kompendium ist das erste seiner Art und sein gewonnenes Wissen wird Wissenschaftlern helfen, einen besseren systematischen Überblick über spezifische Gene oder funktionaler Profile, mit Sicht auf Regulation sowie pathologische und physiologische Bedingungen, zu bekommen. Darüber hinaus ermöglichen verschiedene Abfragemethoden eine effiziente Analyse von signalgebenden Ereignissen, metabolischen Stoffwechselwegen sowie das Studieren der Gene auf der Expressionsebene. Die gesamte Vielfalt dieser Abfrageoptionen ermöglicht den Wissenschaftlern hoch spezialisierte, genetische Straßenkarten zu erstellen, mit deren Hilfe zukünftige Experimente genauer geplant werden können. Infolgedessen können wertvolle Ressourcen und Zeit eingespart werden, bei steigenden Erfolgsaussichten. Des Weiteren kann das umfassende Wissen des Kompendiums genutzt werden, um biomedizinische Hypothesen zu generieren und zu überprüfen.

Modelling and simulating in systems biology: an approach based on multi-agent systems

Systems Biology is an innovative way of doing biology recently raised in bio-informatics contexts, characterised by the study of biological systems as complex systems with a strong focus on the system level and on the interaction dimension. In other words, the objective is to understand biological systems as a whole, putting on the foreground not only the study of the individual parts as standalone parts, but also of their interaction and of the global properties that emerge at the system level by means of the interaction among the parts. This thesis focuses on the adoption of multi-agent systems (MAS) as a suitable paradigm for Systems Biology, for developing models and simulation of complex biological systems. Multi-agent system have been recently introduced in informatics context as a suitabe paradigm for modelling and engineering complex systems. Roughly speaking, a MAS can be conceived as a set of autonomous and interacting entities, called agents, situated in some kind of nvironment, where they fruitfully interact and coordinate so as to obtain a coherent global system behaviour. The claim of this work is that the general properties of MAS make them an effective approach for modelling and building simulations of complex biological systems, following the methodological principles identified by Systems Biology. In particular, the thesis focuses on cell populations as biological systems. In order to support the claim, the thesis introduces and describes (i) a MAS-based model conceived for modelling the dynamics of systems of cells interacting inside cell environment called niches. (ii) a computational tool, developed for implementing the models and executing the simulations. The tool is meant to work as a kind of virtual laboratory, on top of which kinds of virtual experiments can be performed, characterised by the definition and execution of specific models implemented as MASs, so as to support the validation, falsification and improvement of the models through the observation and analysis of the simulations. A hematopoietic stem cell system is taken as reference case study for formulating a specific model and executing virtual experiments.

Phage therapy: A software system for phage quantification and kinetic model inference.

One of the most serious problems of the modern medicine is the growing emergence of antibiotic resistance among pathogenic bacteria. In this circumstance, different and innovative approaches for treating infections caused by multidrug-resistant bacteria are imperatively required. Bacteriophage Therapy is one among the fascinating approaches to be taken into account. This consists of the use of bacteriophages, viruses that infect bacteria, in order to defeat specific bacterial pathogens. Phage therapy is not an innovative idea, indeed, it was widely used around the world in the 1930s and 1940s, in order to treat various infection diseases, and it is still used in Eastern Europe and the former Soviet Union. Nevertheless, Western scientists mostly lost interest in further use and study of phage therapy and abandoned it after the discovery and the spread of antibiotics. The advancement of scientific knowledge of the last years, together with the encouraging results from recent animal studies using phages to treat bacterial infections, and above all the urgent need for novel and effective antimicrobials, have given a prompt for additional rigorous researches in this field. In particular, in the laboratory of synthetic biology of the department of Life Sciences at the University of Warwick, a novel approach was adopted, starting from the original concept of phage therapy, in order to study a concrete alternative to antibiotics. The innovative idea of the project consists in the development of experimental methodologies, which allow to engineer a programmable synthetic phage system using a combination of directed evolution, automation and microfluidics. The main aim is to make “the therapeutics of tomorrow individualized, specific, and self-regulated” (Jaramillo, 2015). In this context, one of the most important key points is the Bacteriophage Quantification. Therefore, in this research work, a mathematical model describing complex dynamics occurring in biological systems involving continuous growth of bacteriophages, modulated by the performance of the host organisms, was implemented as algorithms into a working software using MATLAB. The developed program is able to predict different unknown concentrations of phages much faster than the classical overnight Plaque Assay. What is more, it gives a meaning and an explanation to the obtained data, making inference about the parameter set of the model, that are representative of the bacteriophage-host interaction.

Validity of an automatic measure protocol in distal femur for allograft selection from a three-dimensional virtual bone bank system

Osteoarticular allograft is one possible treatment in wide surgical resections with large defects. Performing best osteoarticular allograft selection is of great relevance for optimal exploitation of the bone databank, good surgery outcome and patient’s recovery. Current approaches are, however, very time consuming hindering these points in practice. We present a validation study of a software able to perform automatic bone measurements used to automatically assess the distal femur sizes across a databank. 170 distal femur surfaces were reconstructed from CT data and measured manually using a size measure protocol taking into account the transepicondyler distance (A), anterior-posterior distance in medial condyle (B) and anterior-posterior distance in lateral condyle (C). Intra- and inter-observer studies were conducted and regarded as ground truth measurements. Manual and automatic measures were compared. For the automatic measurements, the correlation coefficients between observer one and automatic method, were of 0.99 for A measure and 0.96 for B and C measures. The average time needed to perform the measurements was of 16 h for both manual measurements, and of 3 min for the automatic method. Results demonstrate the high reliability and, most importantly, high repeatability of the proposed approach, and considerable speed-up on the planning.

Computer Aided Surgery for Percutaneous Nephrolithotomy: Clinical Requirement Analysis and System Design

Percutaneous nephrolithotomy (PCNL) for the treatment of renal stones and other related renal diseases has proved its efficacy and has stood the test of time compared with open surgical methods and extracorporal shock wave lithotripsy. However, access to the collecting system of the kidney is not easy because the available intra-operative image modalities only provide a two dimensional view of the surgical scenario. With this lack of visual information, several punctures are often necessary which, increases the risk of renal bleeding, splanchnic, vascular or pulmonary injury, or damage to the collecting system which sometimes makes the continuation of the procedure impossible. In order to address this problem, this paper proposes a workflow for introduction of a stereotactic needle guidance system for PCNL procedures. An analysis of the imposed clinical requirements, and a instrument guidance approach to provide the physician with a more intuitive planning and visual guidance to access the collecting system of the kidney are presented.

Biology of FGFRL1, the fifth fibroblast growth factor receptor

FGFRL1 (fibroblast growth factor receptor like 1) is the most recently discovered member of the FGFR family. It contains three extracellular Ig-like domains similar to the classical FGFRs, but it lacks the protein tyrosine kinase domain and instead contains a short intracellular tail with a peculiar histidine-rich motif. The gene for FGFRL1 is found in all metazoans from sea anemone to mammals. FGFRL1 binds to FGF ligands and heparin with high affinity. It exerts a negative effect on cell proliferation, but a positive effect on cell differentiation. Mice with a targeted deletion of the Fgfrl1 gene die perinatally due to alterations in their diaphragm. These mice also show bilateral kidney agenesis, suggesting an essential role for Fgfrl1 in kidney development. A human patient with a frameshift mutation exhibits craniosynostosis, arguing for an additional role of FGFRL1 during bone formation. FGFRL1 contributes to the complexity of the FGF signaling system.

E-Health towards ecumenical framework for personalized medicine via Decision Support System

The purpose of the present manuscript is to present the advances performed in medicine using a Personalized Decision Support System (PDSS). The models used in Decision Support Systems (DSS) are examined in combination with Genome Information and Biomarkers to produce personalized result for each individual. The concept of personalize medicine is described in depth and application of PDSS for Cardiovascular Diseases (CVD) and Type-1 Diabetes Mellitus (T1DM) are analyzed. Parameters extracted from genes, biomarkers, nutrition habits, lifestyle and biological measurements feed DSSs, incorporating Artificial Intelligence Modules (AIM), to provide personalized advice, medication and treatment.