A protein interaction atlas for the nuclear receptors: properties and quality of a hub-based dimerisation network.

BACKGROUND: The nuclear receptors are a large family of eukaryotic transcription factors that constitute major pharmacological targets. They exert their combinatorial control through homotypic heterodimerisation. Elucidation of this dimerisation network is vital in order to understand the complex dynamics and potential cross-talk involved. RESULTS: Phylogeny, protein-protein interactions, protein-DNA interactions and gene expression data have been integrated to provide a comprehensive and up-to-date description of the topology and properties of the nuclear receptor interaction network in humans. We discriminate between DNA-binding and non-DNA-binding dimers, and provide a comprehensive interaction map, that identifies potential cross-talk between the various pathways of nuclear receptors. CONCLUSION: We infer that the topology of this network is hub-based, and much more connected than previously thought. The hub-based topology of the network and the wide tissue expression pattern of NRs create a highly competitive environment for the common heterodimerising partners. Furthermore, a significant number of negative feedback loops is present, with the hub protein SHP [NR0B2] playing a major role. We also compare the evolution, topology and properties of the nuclear receptor network with the hub-based dimerisation network of the bHLH transcription factors in order to identify both unique themes and ubiquitous properties in gene regulation. In terms of methodology, we conclude that such a comprehensive picture can only be assembled by semi-automated text-mining, manual curation and integration of data from various sources.

Brain dynamics underlying training-induced improvement in suppressing inappropriate action.

Inhibitory control, a core component of executive functions, refers to our ability to suppress intended or ongoing cognitive or motor processes. Mostly based on Go/NoGo paradigms, a considerable amount of literature reports that inhibitory control of responses to "NoGo" stimuli is mediated by top-down mechanisms manifesting ∼200 ms after stimulus onset within frontoparietal networks. However, whether inhibitory functions in humans can be trained and the supporting neurophysiological mechanisms remain unresolved. We addressed these issues by contrasting auditory evoked potentials (AEPs) to left-lateralized "Go" and right NoGo stimuli recorded at the beginning versus the end of 30 min of active auditory spatial Go/NoGo training, as well as during passive listening of the same stimuli before versus after the training session, generating two separate 2 × 2 within-subject designs. Training improved Go/NoGo proficiency. Response times to Go stimuli decreased. During active training, AEPs to NoGo, but not Go, stimuli modulated topographically with training 61-104 ms after stimulus onset, indicative of changes in the underlying brain network. Source estimations revealed that this modulation followed from decreased activity within left parietal cortices, which in turn predicted the extent of behavioral improvement. During passive listening, in contrast, effects were limited to topographic modulations of AEPs in response to Go stimuli over the 31-81 ms interval, mediated by decreased right anterior temporoparietal activity. We discuss our results in terms of the development of an automatic and bottom-up form of inhibitory control with training and a differential effect of Go/NoGo training during active executive control versus passive listening conditions.

Thermal activation and ATP dependence of the cytoskeleton remodeling dynamics

The cytoskeleton (CSK) is a nonequilibrium polymer network that uses hydrolyzable sources of free energy such as adenosine triphosphate (ATP) to remodel its internal structure. As in inert nonequilibrium soft materials, CSK remodeling has been associated with structural rearrangements driven by energy-activated processes. We carry out particle tracking and traction microscopy measurements of alveolar epithelial cells at various temperatures and ATP concentrations. We provide the first experimental evidence that the remodeling dynamics of the CSK is driven by structural rearrangements over free-energy barriers induced by thermally activated forces mediated by ATP. The measured activation energy of these forces is ~40kBTr (kB being the Boltzmann constant and Tr being the room temperature). Our experiments provide clues to understand the analogy between the dynamics of the living CSK and that of inert nonequilibrium soft materials.

Resting-brain functional connectivity predicted by analytic measures of network communication.

The complex relationship between structural and functional connectivity, as measured by noninvasive imaging of the human brain, poses many unresolved challenges and open questions. Here, we apply analytic measures of network communication to the structural connectivity of the human brain and explore the capacity of these measures to predict resting-state functional connectivity across three independently acquired datasets. We focus on the layout of shortest paths across the network and on two communication measures-search information and path transitivity-which account for how these paths are embedded in the rest of the network. Search information is an existing measure of information needed to access or trace shortest paths; we introduce path transitivity to measure the density of local detours along the shortest path. We find that both search information and path transitivity predict the strength of functional connectivity among both connected and unconnected node pairs. They do so at levels that match or significantly exceed path length measures, Euclidean distance, as well as computational models of neural dynamics. This capacity suggests that dynamic couplings due to interactions among neural elements in brain networks are substantially influenced by the broader network context adjacent to the shortest communication pathways.

Optimal network topologies for local search with congestion

The problem of searchability in decentralized complex networks is of great importance in computer science, economy, and sociology. We present a formalism that is able to cope simultaneously with the problem of search and the congestion effects that arise when parallel searches are performed, and we obtain expressions for the average search cost both in the presence and the absence of congestion. This formalism is used to obtain optimal network structures for a system using a local search algorithm. It is found that only two classes of networks can be optimal: starlike configurations, when the number of parallel searches is small, and homogeneous-isotropic configurations, when it is large.

Comparative genomics of the vertebrate insulin/TOR signal transduction pathway: A network-level analysis of selective pressures

Complexity of biological function relies on large networks of interacting molecules. However, the evolutionary properties of these networks are not fully understood. It has been shown that selective pressures depend on the position of genes in the network. We have previously shown that in the Drosophila insulin/target of rapamycin (TOR) signal transduction pathway there is a correlation between the pathway position and the strength of purifying selection, with the downstream genes being most constrained. In this study, we investigated the evolutionary dynamics of this well-characterized pathway in vertebrates. More specifically, we determined the impact of natural selection on the evolution of 72 genes of this pathway. We found that in vertebrates there is a similar gradient of selective constraint in the insulin/TOR pathway to that found in Drosophila. This feature is neither the result of a polarity in the impact of positive selection nor of a series of factors affecting selective constraint levels (gene expression level and breadth, codon bias, protein length, and connectivity). We also found that pathway genes encoding physically interacting proteins tend to evolve under similar selective constraints. The results indicate that the architecture of the vertebrate insulin/TOR pathway constrains the molecular evolution of its components. Therefore, the polarity detected in Drosophila is neither specific nor incidental of this genus. Hence, although the underlying biological mechanisms remain unclear, these may be similar in both vertebrates and Drosophila.

Roles of astrocytic sodium dynamics in the neurometabolic coupling : a study by cellular imaging

RESUME LARGE PUBLIC Le système nerveux central est principalement composé de deux types de cellules :les neurones et les cellules gliales. Ces dernières, bien que l'emportant en nombre sur les neurones, ont longtemps été considérées comme des cellules sans intérêts par les neuroscientifiques. Hors, les connaissances modernes à leurs sujets indiquent qu'elles participent à la plupart des tâches physiologiques du cerveau. Plus particulièrement, elles prennent part aux processus énergétiques cérébraux. Ceux-ci, en plus d'être vitaux, sont particulièrement intrigants puisque le cerveau représente seulement 2 % de la masse corporelle mais consomme environ 25 % du glucose (substrat énergétique) corporel. Les astrocytes, un type de cellules gliales, jouent un rôle primordial dans cette formidable utilisation de glucose par le cerveau. En effet, l'activité neuronale (transmission de l'influx nerveux) est accompagnée d'une augmentation de la capture de glucose, issu de la circulation sanguine, par les astrocytes. Ce phénomène est appelé le «couplage neurométabolique » entre neurones et astrocytes. L'ion sodium fait partie des mécanismes cellulaires entrant en fonction lors de ces processus. Ainsi, dans le cadre de cette thèse, les aspects dynamiques de la régulation du sodium astrocytaire et leurs implications dans le couplage neurométabolique ont été étudiés par des techniques d'imagerie cellulaires. Ces études ont démontré que les mitochondries, machineries cellulaires convertissant l'énergie contenue dans le glucose, participent à la régulation du sodium astrocytaire. De plus, ce travail de thèse a permis de découvrir que les astrocytes sont capables de se transmettre, sous forme de vagues de sodium se propageant de cellules en cellules, un message donnant l'ordre d'accroître leur consommation d'énergie. Cette voie de signalisation leur permettrait de fournir de l'énergie aux neurones suite à leur activation. RESUME Le glutamate libéré dans la fente synaptique pendant l'activité neuronale, est éliminé par les astrocytes environnants. Le glutamate est co-transporté avec des ions sodiques, induisant une augmentation intracellulaire de sodium (Na+i) dans les astrocytes. Cette élévation de Na+i déclenche une cascade de mécanismes moléculaires qui aboutissent à la production de substrats énergétiques pouvant être utilisés par les neurones. Durant cette thèse, la mesure simultanée du sodium mitochondrial (Na+mit) et cytosolique par des techniques d'imagerie utilisant des sondes fluorescentes spécifiques, a indiqué que les variations de Na+i induites par le transport du glutamate sont transmises aux mitochondries. De plus, les voies d'entrée et de sortie du sodium mitochondrial ont été identifiées. L'échangeur de Na+ et de Ca2+ mitochondrial semble jouer un rôle primordial dans l'influx de Na+mit, alors que l'efflux de Na+mit est pris en charge par l'échangeur de Na+ et de H+ mitochondrial. L'étude du Na+mit a nécessité l'utilisation d'un système de photoactivation. Les sources de lumière ultraviolette (UV) classiques utilisées à cet effet (lasers, lampes à flash) ayant plusieurs désavantages, une alternative efficace et peu coûteuse a été développée. Il s'agit d'un système compact utilisant une diode électroluminescente (LED) à haute puissance et de longueur d'onde de 365nm. En plus de leurs rôles dans le couplage neurométabolique, les astrocytes participent à la signalisation multicellulaire en transmettant des vagues intercellulaires de calcium. Ce travail de thèse démontre également que des vagues intercellulaires de sodium peuvent être évoquées en parallèle à ces vagues calciques. Le glutamate, suite à sa libération par un mécanisme dépendent du calcium, est réabsorbé par les transporteurs au glutamate. Ce mécanisme a pour conséquence la génération de vagues sodiques se propageant de cellules en cellules. De plus, ces vagues sodiques sont corrélées spatialement avec une consommation accrue de glucose par les astrocytes. En conclusion, ce travail de thèse a permis de montrer que le signal sodique astrocytaire, déclenché en réponse au glutamate, se propage à la fois de façon intracellulaire aux mitochondries et de façon intercellulaire. Ces résultats suggèrent que les astrocytes fonctionnent comme un réseau de cellules nécessaire au couplage énergétique concerté entre neurones et astrocytes et que le sodium est un élément clé dans les mécanismes de signalisations cellulaires sous-jacents. SUMMARY Glutamate, released in the synaptic cleft during neuronal activity, is removed by surrounding astrocytes. Glutamate is taken-up with Na+ ions by specific transporters, inducing an intracellular Na+ (Na+i) elevation in astrocytes which triggers a cascade of molecular mechanisms that provides metabolic substrates to neurons. Thus, astrocytic Na+i homeostasis represents a key component of the so-called neurometabolic coupling. In this context, the first part of this thesis work was aimed at investigating whether cytosolic Na+ changes are transmitted to mitochondria, which could therefore influence their function and contribute to the overall intracellular Na+ regulation. Simultaneous monitoring of both mitochondrial Na+ (Na+mit) and cytosolic Na+ changes with fluorescent dyes revealed that glutamate-evoked cytosolic Na+ elevations are indeed transmitted to mitochondria. The mitochondrial Na+/Ca2+ exchangers have a prominent role in the regulation of Na+mit influx pathway, and Na+mit extrusion appears to be mediated by Na+/H+ exchangers. To demonstrate the implication of Na+/Ca2+ exchangers, this study has required the technical development of an UV-flash photolysis system. Because light sources for flash photolysis have to be powerful and in the near UV range, the use of UV lasers or flash lamps is usually required. As an alternative to these UV sources that have several drawbaks, we developped a compact, efficient and lowcost flash photolysis system which employs a high power 365nm light emitting diode. In addition to their role in neurometabolic coupling, astrocytes participate in multicellular signaling by transmitting intercellular Ca2+ waves. The third part of this thesis show that intercellular Na+ waves can be evoked in parallel to Ca2+ waves. Glutamate released by a Ca2+ wave-dependent mechanism is taken up by glutamate transporters, resulting in a regenerative propagation of cytosolic Na+ increases. Na+ waves in turn lead to a spatially correlated increase in glucose uptake. In conclusion, the present thesis demonstrates that glutamate-induced Na+ changes occurring in the cytosol of astrocytes propagate to both the mitochondrial matrix and the astrocytic network. These results furthermore support the view that astrocytic Na+ is a signal coupled to the brain energy metabolism.

Differences of Functional Connectivity Brain Network in Emotional Judgment

Using combined emotional stimuli, combining photos of faces and recording of voices, we investigated the neural dynamics of emotional judgment using scalp EEG recordings. Stimuli could be either combioned in a congruent, or a non-congruent way.. As many evidences show the major role of alpha in emotional processing, the alpha band was subjected to be analyzed. Analysis was performed by computing the synchronization of the EEGs and the conditions congruent vs. non-congruent were compared using statistical tools. The obtained results demonstrate that scalp EEG ccould be used as a tool to investigate the neural dynamics of emotional valence and discriminate various emotions (angry, happy and neutral stimuli).

Correlations between negative-induced cerebral dynamics and idiopathic intellectual disability: an EEG study

Intellectual disability has long been associated with deficits in socio-emotional processing. However, studies investigating brain dynamics of maladaptive socio-emotional skills associated with intellectual disability are scarce. Here, we compared differences in brain activity between low intelligence quotient (I.Q.<75, N=13) and normal controls (N=15) while evaluating their subjective emotions. Positive (P) and negative (N) valenced pictures were presented one at a time to participants of both groups, at a rate of ¾. The task required that each participant evaluate their subjective emotion and press a predefined push-button when done, alternatively P and N. Electroencephalographic (EEG) signals were continuously recorded, and the 1000ms time window following each picture was analyzed offline for power in frequency domain. Alpha low (8-10Hz) and upper (10-13Hz) frequency bands were then compared for both groups and for both P and N emotions in 12 distributed scalp electrodes. The qualitative evaluation of emotions was similar between both groups, with constant longer reaction times for the low IQ participants. The EEG signal comparison shows marked power decrease in upper alpha frequency range for N emotions in low intelligence group. Otherwise no significant difference was noticed between low and normal IQ. Main findings of the present study are (1) results do not support the hypothesis that impairment in developmental intelligence roots in maladaptive emotional processing; (2) the strong alpha power suppression during negative-induced emotions suggests the involvement of an extended neural network and more effortful inhibition processes than positive ones. We call for further studies with a larger sample.

Diffusion dynamics on multiplex networks

We study the time scales associated with diffusion processes that take place on multiplex networks, i.e., on a set of networks linked through interconnected layers. To this end, we propose the construction of a supra-Laplacian matrix, which consists of a dimensional lifting of the Laplacian matrix of each layer of the multiplex network. We use perturbative analysis to reveal analytically the structure of eigenvectors and eigenvalues of the complete network in terms of the spectral properties of the individual layers. The spectrum of the supra-Laplacian allows us to understand the physics of diffusionlike processes on top of multiplex networks.

Using Pareto optimality to explore the topology and dynamics of the human connectome.

Graph theory has provided a key mathematical framework to analyse the architecture of human brain networks. This architecture embodies an inherently complex relationship between connection topology, the spatial arrangement of network elements, and the resulting network cost and functional performance. An exploration of these interacting factors and driving forces may reveal salient network features that are critically important for shaping and constraining the brain's topological organization and its evolvability. Several studies have pointed to an economic balance between network cost and network efficiency with networks organized in an 'economical' small-world favouring high communication efficiency at a low wiring cost. In this study, we define and explore a network morphospace in order to characterize different aspects of communication efficiency in human brain networks. Using a multi-objective evolutionary approach that approximates a Pareto-optimal set within the morphospace, we investigate the capacity of anatomical brain networks to evolve towards topologies that exhibit optimal information processing features while preserving network cost. This approach allows us to investigate network topologies that emerge under specific selection pressures, thus providing some insight into the selectional forces that may have shaped the network architecture of existing human brains.

Review of quantitative phase-digital holographic microscopy: promising novel imaging technique to resolve neuronal network activity and identify cellular biomarkers of psychiatric disorders.

Quantitative phase microscopy (QPM) has recently emerged as a new powerful quantitative imaging technique well suited to noninvasively explore a transparent specimen with a nanometric axial sensitivity. In this review, we expose the recent developments of quantitative phase-digital holographic microscopy (QP-DHM). Quantitative phase-digital holographic microscopy (QP-DHM) represents an important and efficient quantitative phase method to explore cell structure and dynamics. In a second part, the most relevant QPM applications in the field of cell biology are summarized. A particular emphasis is placed on the original biological information, which can be derived from the quantitative phase signal. In a third part, recent applications obtained, with QP-DHM in the field of cellular neuroscience, namely the possibility to optically resolve neuronal network activity and spine dynamics, are presented. Furthermore, potential applications of QPM related to psychiatry through the identification of new and original cell biomarkers that, when combined with a range of other biomarkers, could significantly contribute to the determination of high risk developmental trajectories for psychiatric disorders, are discussed.

Cooperative and Competitive Spreading Dynamics on the Human Connectome.

Increasingly detailed data on the network topology of neural circuits create a need for theoretical principles that explain how these networks shape neural communication. Here we use a model of cascade spreading to reveal architectural features of human brain networks that facilitate spreading. Using an anatomical brain network derived from high-resolution diffusion spectrum imaging (DSI), we investigate scenarios where perturbations initiated at seed nodes result in global cascades that interact either cooperatively or competitively. We find that hub regions and a backbone of pathways facilitate early spreading, while the shortest path structure of the connectome enables cooperative effects, accelerating the spread of cascades. Finally, competing cascades become integrated by converging on polysensory associative areas. These findings show that the organizational principles of brain networks shape global communication and facilitate integrative function.

Nature of the Epidemic Threshold for the Susceptible-Infected-Susceptible Dynamics in Networks

We develop an analytical approach to the susceptible-infected-susceptible epidemic model that allows us to unravel the true origin of the absence of an epidemic threshold in heterogeneous networks. We find that a delicate balance between the number of high degree nodes in the network and the topological distance between them dictates the existence or absence of such a threshold. In particular, small-world random networks with a degree distribution decaying slower than an exponential have a vanishing epidemic threshold in the thermodynamic limit.

Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns.

The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs-locomotor bouts-matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior.