Reconstitution of mitochondrial ATP synthase into lipid bilayers for structural analysis

Mitochondrial F(1)F(o)-ATP synthase is a molecular motor that couples the energy generated by oxidative metabolism to the synthesis of ATP. Direct visualization of the rotary action of the bacterial ATP synthase has been well characterized. However, direct observation of rotation of the mitochondrial enzyme has not been reported yet. Here, we describe two methods to reconstitute mitochondrial F(1)F(o)-ATP synthase into lipid bilayers suitable for structure analysis by electron and atomic force microscopy (AFM). Proteoliposomes densely packed with bovine heart mitochondria F(1)F(o)-ATP synthase were obtained upon detergent removal from ternary mixtures (lipid, detergent and protein). Two-dimensional crystals of recombinant hexahistidine-tagged yeast F(1)F(o)-ATP synthase were grown using the supported monolayer technique. Because the hexahistidine-tag is located at the F(1) catalytic subcomplex, ATP synthases were oriented unidirectionally in such two-dimensional crystals, exposing F(1) to the lipid monolayer and the F(o) membrane region to the bulk solution. This configuration opens a new avenue for the determination of the c-ring stoichiometry of unknown hexahistidine-tagged ATP synthases and the organization of the membrane intrinsic subunits within F(o) by electron microscopy and AFM.

Repeatability analysis of global and local metrics of brain structural networks

Computational network analysis provides new methods to analyze the human connectome. Brain structural networks can be characterized by global and local metrics that recently gave promising insights for diagnosis and further understanding of neurological, psychiatric and neurodegenerative disorders. In order to ensure the validity of results in clinical settings the precision and repeatability of the networks and the associated metrics must be evaluated. In the present study, nineteen healthy subjects underwent two consecutive measurements enabling us to test reproducibility of the brain network and its global and local metrics. As it is known that the network topology depends on the network density, the effects of setting a common density threshold for all networks were also assessed. Results showed good to excellent repeatability for global metrics, while for local metrics it was more variable and some metrics were found to have locally poor repeatability. Moreover, between subjects differences were slightly inflated when the density was not fixed. At the global level, these findings confirm previous results on the validity of global network metrics as clinical biomarkers. However, the new results in our work indicate that the remaining variability at the local level as well as the effect of methodological characteristics on the network topology should be considered in the analysis of brain structural networks and especially in networks comparisons.

Isolation and analysis of regulatory and structural mutations in the {\it recA\/} gene of {\it Escherichia coli}

The recA gene is essential for homologous recombination and for inducible DNA repair in Escherichia coli. The level of recA expression is important for these functions. The growth defect of a lambda phage carrying a recA-lacZ fusion was used to select mutations that reduced recA expression. Nine of these mutations were single base changes in the recA promoter; each reduced both induced and basal (repressed) levels of expression, indicating that only one promoter is used under both circumstances. Deletion analysis of the promoter region and S1 mapping of transcripts confirmed that there is only one promoter responsible for both basal and induced expression. Some of the mutants, however, displayed a ratio of induced to repressed expression that was much lower than wild-type. For one of these mutants (recA1270) LexA binding studies showed that this was not due to a change in the affinity of LexA repressor for the operator site. The extent of binding of RNA polymerase to this mutant promoter, however, was much reduced, and the complexes formed were qualitatively different. Further binding experiments provided some evidence that LexA does not block RNA polymerase binding to the recA promoter, but inhibits a later step in initiation. Behavior of the mutants with altered induction ratios could be explained if LexA binding to the operator actually increases RNA polymerase binding to the promoter in a closed complex compensating for defects in polymerase binding caused by the mutations.^ In a study of mutations in the recA structural gene, site-directed mutagenesis was used to replace cysteine codons at positions 90, 116, and 129 with a number of different codons. In vivo analysis of the replacements showed that none of the cysteines is absolutely essential and that they do not have a direct role as catalysts in ATP hydrolysis. Some amino acid substitutions abolished all RecA functions, while a few resulted in partial or altered function. Amino acids at positions 90 and 129 tended to affect all functions equally, while the amino acid at position 116 appeared to have a particular effect on the protease activity of the protein. ^

Validation of network communicability metrics for the analysis of brain structural networks.

Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

The structural substrate of brain function: analysis of brain structural networks based on diffusion-weighted imaging

The brain is a complex neural network with a hierarchical organization and the mapping of its elements and connections is an important step towards the understanding of its function. Recent developments in diffusion-weighted imaging have provided the opportunity to reconstruct the whole-brain structural network in-vivo at a large scale level and to study the brain structural substrate in a framework that is close to the current understanding of brain function. However, methods to construct the connectome are still under development and they should be carefully evaluated. To this end, the first two studies included in my thesis aimed at improving the analytical tools specific to the methodology of brain structural networks. The first of these papers assessed the repeatability of the most common global and local network metrics used in literature to characterize the connectome, while in the second paper the validity of further metrics based on the concept of communicability was evaluated. Communicability is a broader measure of connectivity which accounts also for parallel and indirect connections. These additional paths may be important for reorganizational mechanisms in the presence of lesions as well as to enhance integration in the network. These studies showed good to excellent repeatability of global network metrics when the same methodological pipeline was applied, but more variability was detected when considering local network metrics or when using different thresholding strategies. In addition, communicability metrics have been found to add some insight into the integration properties of the network by detecting subsets of nodes that were highly interconnected or vulnerable to lesions. The other two studies used methods based on diffusion-weighted imaging to obtain knowledge concerning the relationship between functional and structural connectivity and about the etiology of schizophrenia. The third study integrated functional oscillations measured using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) as well as diffusion-weighted imaging data. The multimodal approach that was applied revealed a positive relationship between individual fluctuations of the EEG alpha-frequency and diffusion properties of specific connections of two resting-state networks. Finally, in the fourth study diffusion-weighted imaging was used to probe for a relationship between the underlying white matter tissue structure and season of birth in schizophrenia patients. The results are in line with the neurodevelopmental hypothesis of early pathological mechanisms as the origin of schizophrenia. The different analytical approaches selected in these studies also provide arguments for discussion of the current limitations in the analysis of brain structural networks. To sum up, the first studies presented in this thesis illustrated the potential of brain structural network analysis to provide useful information on features of brain functional segregation and integration using reliable network metrics. In the other two studies alternative approaches were presented. The common discussion of the four studies enabled us to highlight the benefits and possibilities for the analysis of the connectome as well as some current limitations.

Structural and functional analysis of p84N5

Normal development and tissue homeostasis requires the carefully orchestrated balance between cell proliferation and cell death. Cell cycle checkpoints control the extent of cell proliferation. Cell death is coordinated through the activation of a cell suicide pathway that results in the morphologically recognizable form of death, apoptosis. Tumorigenesis requires that the balance between these two pathways be disrupted. The tumor suppressor protein Rb has not only been shown to be involved in the enforcement of cell cycle checkpoints, but has also been implicated in playing a role in the regulation of apoptosis. The manner in which Rb enforces cell cycle checkpoints has been well studied; however, its involvement in the regulation of apoptosis is still very unclear. p84N5 is a novel nuclear death domain containing protein that has been shown to interact with the N-terminus of Rb. The fact that it contains a death domain and the fact that it is nuclear localized possibly provides the first known mechanism for apoptotic signaling from the nucleus. The following study tested the hypothesis that the novel exclusively nuclear death domain containing protein p84N5 is an important mediator of programmed cell death and that its apoptotic function is reliant upon its nuclear localization and is regulated by unique functional domains within the p84N5 protein. We identified the p84N5 nuclear localization signal (NLS), eliminated it, and tested the functional significance of nuclear localization by using wild type and mutant sequences fused to EGFP-C1 (Clontech) to create wild type GFPN5 and subsequent mutants. The results of these assays demonstrated exclusive nuclear localization of GFPN5 is required for normal p84N5 induced apoptosis. We further conducted large-scale mutagenesis of the GFPN5 construct to identify a minimal region within p84N5 capable of interacting with Rb. We were able to identify a minimal sequence containing p84N5 amino acids 318 to 464 that was capable of interacting with Rb in co-immunoprecipitation assays. We continued by conducting a structural and functional analysis to identify the region or regions within p84N5 responsible for inducing apoptosis. Point mutations and small-scale deletions within the death domain of p84N5 lessened the effect but did not eliminate p84N5-induced cytotoxicity. Further analysis revealed that the minimal sequence of 318 to 464 of p84N5 was capable of inducing apoptosis to a similar degree as wild-type GFPN5 protein. Since amino acids 318 to 464 of p84N5 are capable of inducing apoptosis and interacting with Rb, we propose possible mechanisms whereby p84N5 may function in a Rb regulated manner. These results demonstrate that p84N5 induced apoptosis is reliant upon its nuclear localization and is regulated by unique functional domains within the p84N5 protein. ^

Resilience analysis of networked systems-of-systems based on structural and dynamic interdependencies

Critical infrastructures support everyday activities in modern societies, facilitating the exchange of services and quantities of various nature. Their functioning is the result of the integration of diverse technologies, systems and organizations into a complex network of interconnections. Benefits from networking are accompanied by new threats and risks. In particular, because of the increased interdependency, disturbances and failures may propagate and render unstable the whole infrastructure network. This paper presents a methodology of resilience analysis of networked systems of systems. Resilience generalizes the concept of stability of a system around a state of equilibrium, with respect to a disturbance and its ability of preventing, resisting and recovery. The methodology provides a tool for the analysis of off-equilibrium conditions that may occur in a single system and propagate through the network of dependencies. The analysis is conducted in two stages. The first stage of the analysis is qualitative. It identifies the resilience scenarios, i.e. the sequence of events, triggered by an initial disturbance, which include failures and the system response. The second stage is quantitative. The most critical scenarios can be simulated, for the desired parameter settings, in order to check if they are successfully handled, i.e recovered to nominal conditions, or they end into the network failure. The proposed methodology aims at providing an effective support to resilience-informed design.

Comparison of numerical models for vibro-acoustic analysis of structural panels in low modal density range engaging air layers

During launch, satellite and their equipment are subjected to loads of random nature and with a wide frequency range. Their vibro-acoustic response is an important issue to be analysed, for example for folded solar arrays and antennas. The main issue at low modal density is the modelling combinations engaging air layers, structures and external fluid. Depending on the modal density different methodologies, as FEM, BEM and SEA should be considered. This work focuses on the analysis of different combinations of the methodologies previously stated used in order to characterise the vibro-acoustic response of two rectangular sandwich structure panels isolated and engaging an air layer between them under a diffuse acoustic field. Focusing on the modelling of air layers, different models are proposed. To illustrate the phenomenology described and studied, experimental results from an acoustic test on an ARA-MKIII solar array in folded configuration are presented along with numerical results.

Analysis and Modelling of the Structural Components of the Elbow Joint

A recent application of computer simulation is its use for the human body, which resembles a mechanism that is complemented by torques in the joints that are caused by the action of muscles and tendons. Among others, the application can be used to provide training in surgical procedures or to learn how the body works. Some of the other applications are to make a biped walk upright, to build robots that are designed on the human body or to make prostheses or robot arms to perform specific tasks. One of the uses of simulation is to optimise the movement of the human body by examining which muscles are activated and which should or should not be activated in order to improve a person?s movements. This work presents a model of the elbow joint, and by analysing the constraint equations using classic methods we go on to model the bones, muscles and tendons as well as the logic linked to the force developed by them when faced with a specific movement. To do this, we analyse the reference bibliography and the software available to perform the validation.

Functional, structural and phylogenetic analysis of domains underlying the Al sensitivity of the aluminum-activated malate/anion transporter, TaALMT1.

Triticum aestivum aluminum-activated malate transporter (TaALMT1) is the founding member of a unique gene family of anion transporters (ALMTs) that mediate the efflux of organic acids. A small sub-group of root-localized ALMTs, including TaALMT1, is physiologically associated with in planta aluminum (Al) resistance. TaALMT1 exhibits significant enhancement of transport activity in response to extracellular Al. In this study, we integrated structure–function analyses of structurally altered TaALMT1 proteins expressed in Xenopus oocytes with phylogenic analyses of the ALMT family. Our aim is to re-examine the role of protein domains in terms of their potential involvement in the Al-dependent enhancement (i.e. Al-responsiveness) of TaALMT1 transport activity, as well as the roles of all its 43 negatively charged amino acid residues. Our results indicate that the N-domain, which is predicted to form the conductive pathway, mediates ion transport even in the absence of the C-domain. However, segments in both domains are involved in Al3+ sensing. We identified two regions, one at the N-terminus and a hydrophobic region at the C-terminus, that jointly contribute to the Al-response phenotype. Interestingly, the characteristic motif at the N-terminus appears to be specific for Al-responsive ALMTs. Our study highlights the need to include a comprehensive phylogenetic analysis when drawing inferences from structure–function analyses, as a significant proportion of the functional changes observed for TaALMT1 are most likely the result of alterations in the overall structural integrity of ALMT family proteins rather than modifications of specific sites involved in Al3+ sensing.

Mathematical foundations for efficient structural controllability and observability analysis of complex systems

The relationship between structural controllability and observability of complex systems is studied. Algebraic and graph theoretic tools are combined to prove the extent of some controller/observer duality results. Two types of control design problems are addressed and some fundamental theoretical results are provided. In addition new algorithms are presented to compute optimal solutions for monitoring large scale real networks.

Some examples of the simultaneous use of closed-form and numerical solutions in shell structural analysis

The computational advantages of the use of different approaches -numerical and analytical ones- to the analysis of different parts of the same shell structure are discussed. Examples of large size problems that can be reduced to those more suitable to be handled by a personal related axisyrometric finite elements, local unaxisymmetric shells, geometric quasi-regular shells, infinite elements and homogenization techniques are described