New insights into the regulatory mechanisms of the NALP3 inflammasome

Résumé : Les vertébrés ont recours au système immunitaire inné et adaptatif pour combattre les pathogènes. La découverte des récepteurs Toll, il y a dix ans, a fortement augmenté l'intérêt porté à l'immunité innée. Depuis lors, des récepteurs intracellulaires tels que les membres de la famille RIG-like helicase (RLHs) et NOD-like receptor (NLRs) ont été décrits pour leur rôle dans la détection des pathogènes. L'interleukine-1 beta (IL-1β) est une cytokine pro-inflammatoire qui est synthétisée sous forme de précurseur, la proIL-1β. La proIL-1β requiert d'être clivée par la caspase-1 pour devenir active. La caspase-1 est elle-même activée par un complexe appelé inflammasome qui peut être formé par divers membres de la famille NLR. Plusieurs inflammasomes ont été décrits tels que le NALP3 inflammasome ou l'IPAF inflammasome. Dans cette étude nous avons identifié la co-chaperone SGT1 et la chaperone HSP90 comme partenaires d'interaction de NALP3. Ces deux protéines sont bien connues chez les plantes pour leurs rôles dans la régulation des gènes de résistance (gène R) qui sont structurellement apparentés à la famille NLR. Nous avons pu montrer que SGT1 et HSP90 jouent un rôle similaire dans la régulation de NALP3 et des protéines R. En effet, nous avons démontré que les deux protéines sont nécessaires pour l'activité du NALP3 inflammasome. De plus, la HSP90 est également requise pour la stabilité de NALP3. En se basant sur ces observations, nous avons proposé un modèle dans lequel SGT1 et HSP90 maintiennent NALP3 inactif mais prêt à percevoir un ligand activateur qui initierait la cascade inflammatoire. Nous avons également montré une interaction entre SGT1 et HSP90 avec plusieurs NLRs. Cette observation suggère qu'un mécanisme similaire pourrait être impliqué dans la régulation des membres de la famille des NLRs. Ces dernières années, plusieurs PAMPs mais également des DAMPs ont été identifiés comme activateurs du NALP3 inflammasome. Dans la seconde partie de cette étude, nous avons identifié la réponse au stress du réticulum endoplasmique (RE) comme nouvel activateur du NALP3 inflammasome. Cette réponse est initiée lors de l'accumulation dans le réticulum endoplasmique de protéines ayant une mauvaise conformation ce qui conduit, en autre, à l'arrêt de la synthèse de nouvelles protéines ainsi qu'une augmentation de la dégradation des protéines. Les mécanismes par lesquels la réponse du réticulum endoplasmique induit l'activation du NALP3 inflammasome doivent encore être déterminés. Summary : Vertebrates rely on the adaptive and the innate immune systems to fight pathogens. Awarness of the importance of the innate system increased with the identification of Toll-like receptors a decade ago. Since then, intracellular receptors such as the RIG-like helicase (RLH) and the NOD-like receptor (NLR) families have been described for their role in the recognition of microbes. Interleukin- 1ß (IL-1ß) is a key mediator of inflammation. This proinflammatory cytokine is synthesised as an inactive precursor that requires processing by caspase-1 to become active. Caspase-1 is, itself, activated in a complex termed the inflammasome that can be formed by members of the NLR family. Various inflammasome complexes have been described such as the IPAF and the NALP3 inflammasome. In this study, we have identified the co-chaperone SGT1 and the chaperone HSP90 as interacting partners of NALP3. SGT1 and HSP90 are both known for their role in the activity of plant resistance proteins (R proteins) which are structurally related to the NLR family. We have shown that HSP90 and SGT1 play a similar role in the regulation of NALP3 and in the regulation of plant R proteins. Indeed, we demonstrated that both HSP90 and SGT1 are essential for the activity of the NALP3 inflammasome complex. In addition, HSP90 is required for the stability of NALP3. Based on these observations, we have proposed a model in which SGT1 and HSP90 maintain NALP3 in an inactive but signaling-competent state, ready to receive an activating ligand that induces the inflammatory cascade. An interaction between several NLR members, SGTI and HSP90 was also shown, suggesting that similar mechanisms could be involved in the regulation of other NLRs. Several pathogen-associated molecular patterns (PAMPs) but also danger associated molecular patterns (DAMPs) have been identified as NALP3 activators. In the second part of this study, we have identified the ER stress response as a new NALP3 activator. The ER stress response is activated upon the accumulation of unfolded protein in the endoplasmic reticulum and results in a block in protein synthesis and increased protein degradation. The mechanisms of ER stress-mediated NALP3 activation remain to be determined.

The role of dentritic cells in leishmania infection : use of novel DC lines for the development of monoclonal antibodies

Les cellules dendritiques (DCs) sont des cellules multifonctionnelles qui font le lien entre le sytème immunitaire inné et adaptatif chez les mammifères. Il existe plusieurs sous-types de DCs basés sur leurs fonctions et l'endroit où elles se situent dans le corps. Dans le cadre de cette thèse, nous avons étudié le rôle de ces cellules face à une infection parasitaire. La Leishmania est un parasite causant une maladie appelée Leishmaniose, maladie endémique de l'Afrique, de l'Asie et de certaines régions de l'Amérique du Sud. Certaines espèces causent des lésions cutanées, alors que d'autres causent des lésions dans les muqueuses ou dans les organes internes. Le système immunitaire répond en générant une réponse inflammatoire qui élimine l'infection. Lors d'une réponse non-inflammatoire (de type cytokines, chemokines), cela va amener à une persistance du parasite sur le long terme. Les DC s'activant en présence du parasite dans la peau, vont le transporter vers un ganglion. A cet endroit, se trouvent différents sous-types de DC qui ont la particularité de présenter l'antigène (spécifique à la Leishmaniose) aux lymphocytes T, ce qui va alors amener à une réponse immunitaire puissante contre le parasite. Nous avons comparé différentes espèces de Leishmaniose dans leur façon d'activer les DC et différents modèles de souris ont été utilisé dans ce but-là. Les souris du type C57BL/6 sont connues pour être résistantes à L. major et sensibles à L. mexicana, alors qu'au contraire, les souris Balb/c sont connues pour être sensibles à ces deux espèces. En utilisant des parasites fluorescents transgéniques, nous avons comparé ces deux espèces de parasites (L. major et L. mexicana) en recherchant quelles cellules elles sont capables d'infecter in-vivo dans un modèle murin. Le rôle général des DC dans une infection à L. major a déjà été décrit. Dans notre étude, nous avons étudié le besoin en DC CD8a+ dans les ganglions afin d'engendrer une réponse face à une infection à L. major. Les souris qui n'ont pas ce sous-type de DC sont beaucoup plus sensibles à l'infection : elles ont des marqueurs inflammatoires plus bas et des lésions plus grandes. Nous avons également remarqué que les DC CD8a+ jouent un rôle crucial dans une phase plus avancée de l'infection. Dans notre laboratoire, nous avons la chance d'avoir une source illimitée de DCs de sous-type CD8a+ provenant d'une souris génétiquement modifiée par nos soin. Grâce à cela, nous avons utilisé ces cellules CD8a+ pour immuniser des rats afin de produire des anticorps monoclonaux ayant des propriétés spécifiques comme l'identification de protéines uniques présentes à la surface des DC et qui ensuite, modulent une réponse immunitaire in-vivo. Nous sommes actuellement en phase de caractérisation de plus de 750 hybridomes générés dans notre laboratoire. - Les cellules dendritiques (DCs) constituent le lien entre le système inné et adaptatif de la réponse immunitaire, car elles sont capables de présenter l'antigène, de donner la co- stimulation et de relâcher des cytokines et chimokines. Au cours de cette thèse, nous avons exploré différentes familles de DC lors d'infections parasitaires, telles que la Leishmaniose, parasite intracellulaire qui infecte les mammifères. La plupart des lésions cutanées résistantes sont caractérisées par une réponse pro-inflammatoire générée par l'IL-12. A l'inverse, pour la forme non résistante, la réponse est générée par l'IL-4 et l'IL-10, dans les modèles murins vulnérables. L'infection avec Lmajor a été caractérisée chez la souris C57BL/6 (Thl) et chez la souris Balb/c (Th2). Chez la souris C57BL/6 la lésion guérit, alors que chez la souris Balb/c, la lésion est au contraire non-cicatrisante. Nous avons comparé l'activation causée dans l'ensemble des DC par différentes espéces de Leishmania, et plus spécifiquement dans les DC CD8a+ présentes dans les ganglions lymphatiques et leur rôle dans la vulnérabilité à L. major. Ces cellules sont spécialisées dans la présentation croisée d'antigènes exogènes par le CMH-I et le haut taux de production d'IL-12 après activation. En utilisant des DC dérivées de moelle osseuse, nous avons constaté que L. guyanensis V+ (transportant un retrovirus) était le plus efficace pour l'activation des DC in-vitro comparé à L. major, L. mexicana et L. guyanensis (V-). Toutefois, in-vivo, les souris infectées avec L. major ont vu la taille de leur ganglions lymphatiques drainants augmentée, 3-6 semaines après l'infection dans les deux espèces de souris (les C57BL/6 résistantes et les Balb/c sensibles). En utilisant un parasite fluorescent transgénique, nous avons trouvé que les souris C57BL/6 sensibles à Lmexicana ont un nombre plus important de cellules Β infectées et un plus petit nombre de DC dérivées des monocytes inflammatoires, comparé au souris infectées avec L. major. Les conséquences de ces observations sont encore à l'étude. Des souris déficientes en CD8ct+DC et CD103+ sont plus sensibles à L. major que les souris WT: leurs lésions sont plus grandes et la charge parasitaire est plus importante. Nous avons généré une chimère de moelles osseuse CD11-DTR et Batf3-/- en mélangeant les moelles de ces deux souris, afin de déterminer le temps après infection où le manque de DC's CD8a+ contribue le plus à l'augmentation de la vulnérabilité chez la souris KO. Ces souris produisent plus d'IgG1 et IgE, font une réponse Th2 plus forte et Thl moins forte. Nous avons constaté que les souris déficientes en DC CD8a+ au début de la réponse immunitaire adaptive (trois semaines après injection) maintiennent un haut taux de lésions de grande taille, semblable à celui des souris chez qui les cellules ont été déplétées avant l'injection. Cela indique que les DC CD8a+ sont nécessaires pour l'efficacité de l'immunité dans la phase chronique de l'infection à L. major. Parallèlement à cela, nous avons aussi commencé une génération d'anticorps monoclonaux dirigés contre les DC CD8a+ activés en utilisant des souches établies dans notre laboratoire. En partant d'une librairie de 763 hybridomes, nous avons identifié plusieurs clones dignes d'intérêt avec une capacité fonctionnelle à moduler la prolifération et la sécrétion de cytokines des cellules T, ainsi que les molécules de co-stimulation présentes à la surface des DC activées elle-même. - Dendritic cells (DCs) are the bridge between the innate and the adaptive arms of the immune systems. They are professional antigen presentation cells and have important cytokine/chemokine release functions. In this dissertation we have focussed on the study of the different subsets of DCs in parasitic infection immunity. Leishmania are intra-cellular parasites of many different species that infect mammals. Most cutaneous lesions that are self- healing are characterized with a pro-inflammatory response with IL-12 while high levels of cytokines such as IL-4 and IL-10 characterized in susceptible mouse models. In mice L. major infection has been well characterized in C57BL/6 mice (Thl) that form healing lesions while Balb/c mice (Th2) form non-healing lesions. This thesis is focussed on comparing DC activation at large by different strains of Leishmania and more specifically, dLN resident CD8a+ DCs and their role in L. major susceptibility. This subset is specialized in cross- presentation of exogenous antigens in the MHC-I pathway and produce high levels of EL-12. Using bone marrow derived DCs we found that L. guyanensis V+ (carrying a retro-virus) was the most efficient at activating DCs in-vitro. In-vivo however L. major infected mice had the largest dLNs 3-6 weeks after infection in both genetically resistant C57BL/6 and susceptible Balb/c mice. Using transgenic fluorescent parasites, we found that C57BL/6 mice which are susceptible to L. mexicana had more number of infected Β cells and fewer number of infected inflammatory monocyte derived DCs in contrast to L. major infection. Using mice deficient in CD8a+ DCs, we found that these mice were more susceptible to L. major than their WT counterparts. They made larger lesions, had higher parasite burdens, higher levels of Th2 indicating immunolgloblins as measured by higher serie IgE levels and lower CD4+ IFNy+ cells. A mixed bone marrow chimera system of CDllc-DTR and Batf3~'~ was generated to determine the time point at which the lack of CD8a+ DCs most contributes to the increased susceptibility in KO mice. We found that mice depleted of CD8a+ DCs at the advent of the adaptive response (3 weeks after infection) maintained the significantly higher lesion size similar to mice whose cells were depleted from the onset of infection. This indicates that CD8a+ DCs are required for effective immunity in the chronic phase of L. major infection. We also began the generation of a valuable tool of monoclonal antibodies against activated CD8a+ DCs using our in-house DC line. From a library of 763 hybridomas we have identified several interesting clones with a functional ability to modulate Τ cell proliferation and cytokine secretion as well as down-modulating co-stimulatory molecules on activated DC cells themselves.

Spatial prediction of monthly wind speeds in complex terrain with adaptive general regression neural networks

This paper presents the general regression neural networks (GRNN) as a nonlinear regression method for the interpolation of monthly wind speeds in complex Alpine orography. GRNN is trained using data coming from Swiss meteorological networks to learn the statistical relationship between topographic features and wind speed. The terrain convexity, slope and exposure are considered by extracting features from the digital elevation model at different spatial scales using specialised convolution filters. A database of gridded monthly wind speeds is then constructed by applying GRNN in prediction mode during the period 1968-2008. This study demonstrates that using topographic features as inputs in GRNN significantly reduces cross-validation errors with respect to low-dimensional models integrating only geographical coordinates and terrain height for the interpolation of wind speed. The spatial predictability of wind speed is found to be lower in summer than in winter due to more complex and weaker wind-topography relationships. The relevance of these relationships is studied using an adaptive version of the GRNN algorithm which allows to select the useful terrain features by eliminating the noisy ones. This research provides a framework for extending the low-dimensional interpolation models to high-dimensional spaces by integrating additional features accounting for the topographic conditions at multiple spatial scales. Copyright (c) 2012 Royal Meteorological Society.

Stimulus statistics shape oscillations in nonlinear recurrent neural networks.

Rhythmic activity plays a central role in neural computations and brain functions ranging from homeostasis to attention, as well as in neurological and neuropsychiatric disorders. Despite this pervasiveness, little is known about the mechanisms whereby the frequency and power of oscillatory activity are modulated, and how they reflect the inputs received by neurons. Numerous studies have reported input-dependent fluctuations in peak frequency and power (as well as couplings across these features). However, it remains unresolved what mediates these spectral shifts among neural populations. Extending previous findings regarding stochastic nonlinear systems and experimental observations, we provide analytical insights regarding oscillatory responses of neural populations to stimulation from either endogenous or exogenous origins. Using a deceptively simple yet sparse and randomly connected network of neurons, we show how spiking inputs can reliably modulate the peak frequency and power expressed by synchronous neural populations without any changes in circuitry. Our results reveal that a generic, non-nonlinear and input-induced mechanism can robustly mediate these spectral fluctuations, and thus provide a framework in which inputs to the neurons bidirectionally regulate both the frequency and power expressed by synchronous populations. Theoretical and computational analysis of the ensuing spectral fluctuations was found to reflect the underlying dynamics of the input stimuli driving the neurons. Our results provide insights regarding a generic mechanism supporting spectral transitions observed across cortical networks and spanning multiple frequency bands.

Artificial neural network study of whole-cell bacterial bioreporter response determined using fluorescence flow cytometry.

Genetically engineered bioreporters are an excellent complement to traditional methods of chemical analysis. The application of fluorescence flow cytometry to detection of bioreporter response enables rapid and efficient characterization of bacterial bioreporter population response on a single-cell basis. In the present study, intrapopulation response variability was used to obtain higher analytical sensitivity and precision. We have analyzed flow cytometric data for an arsenic-sensitive bacterial bioreporter using an artificial neural network-based adaptive clustering approach (a single-layer perceptron model). Results for this approach are far superior to other methods that we have applied to this fluorescent bioreporter (e.g., the arsenic detection limit is 0.01 microM, substantially lower than for other detection methods/algorithms). The approach is highly efficient computationally and can be implemented on a real-time basis, thus having potential for future development of high-throughput screening applications.

Morphometric shape analysis using learning vector quantization neural networks - an example distinguishing two microtine vole species

Closely related species may be very difficult to distinguish morphologically, yet sometimes morphology is the only reasonable possibility for taxonomic classification. Here we present learning-vector-quantization artificial neural networks as a powerful tool to classify specimens on the basis of geometric morphometric shape measurements. As an example, we trained a neural network to distinguish between field and root voles from Procrustes transformed landmark coordinates on the dorsal side of the skull, which is so similar in these two species that the human eye cannot make this distinction. Properly trained neural networks misclassified only 3% of specimens. Therefore, we conclude that the capacity of learning vector quantization neural networks to analyse spatial coordinates is a powerful tool among the range of pattern recognition procedures that is available to employ the information content of geometric morphometrics.

Incremental neural networks for function approximation

A new strategy for incremental building of multilayer feedforward neural networks is proposed in the context of approximation of functions from R-p to R-q using noisy data. A stopping criterion based on the properties of the noise is also proposed. Experimental results for both artificial and real data are performed and two alternatives of the proposed construction strategy are compared.

Neural networks as mechanisms to regulate division of labor.

Abstract In social insects, workers perform a multitude of tasks, such as foraging, nest construction, and brood rearing, without central control of how work is allocated among individuals. It has been suggested that workers choose a task by responding to stimuli gathered from the environment. Response-threshold models assume that individuals in a colony vary in the stimulus intensity (response threshold) at which they begin to perform the corresponding task. Here we highlight the limitations of these models with respect to colony performance in task allocation. First, we show with analysis and quantitative simulations that the deterministic response-threshold model constrains the workers' behavioral flexibility under some stimulus conditions. Next, we show that the probabilistic response-threshold model fails to explain precise colony responses to varying stimuli. Both of these limitations would be detrimental to colony performance when dynamic and precise task allocation is needed. To address these problems, we propose extensions of the response-threshold model by adding variables that weigh stimuli. We test the extended response-threshold model in a foraging scenario and show in simulations that it results in an efficient task allocation. Finally, we show that response-threshold models can be formulated as artificial neural networks, which consequently provide a comprehensive framework for modeling task allocation in social insects.

Neural substrates of social emotion regulation: a FMRI study on imitation and expressive suppression to dynamic facial signals.

Emotion regulation is crucial for successfully engaging in social interactions. Yet, little is known about the neural mechanisms controlling behavioral responses to emotional expressions perceived in the face of other people, which constitute a key element of interpersonal communication. Here, we investigated brain systems involved in social emotion perception and regulation, using functional magnetic resonance imaging (fMRI) in 20 healthy participants. The latter saw dynamic facial expressions of either happiness or sadness, and were asked to either imitate the expression or to suppress any expression on their own face (in addition to a gender judgment control task). fMRI results revealed higher activity in regions associated with emotion (e.g., the insula), motor function (e.g., motor cortex), and theory of mind (e.g., [pre]cuneus) during imitation. Activity in dorsal cingulate cortex was also increased during imitation, possibly reflecting greater action monitoring or conflict with own feeling states. In addition, premotor regions were more strongly activated during both imitation and suppression, suggesting a recruitment of motor control for both the production and inhibition of emotion expressions. Expressive suppression (eSUP) produced increases in dorsolateral and lateral prefrontal cortex typically related to cognitive control. These results suggest that voluntary imitation and eSUP modulate brain responses to emotional signals perceived from faces, by up- and down-regulating activity in distributed subcortical and cortical networks that are particularly involved in emotion, action monitoring, and cognitive control.

Contribution of neural networks to Alzheimer disease's progression.

The neuropathology of Alzheimer disease is characterized by senile plaques, neurofibrillary tangles and cell death. These hallmarks develop according to the differential vulnerability of brain networks, senile plaques accumulating preferentially in the associative cortical areas and neurofibrillary tangles in the entorhinal cortex and the hippocampus. We suggest that the main aetiological hypotheses such as the beta-amyloid cascade hypothesis or its variant, the synaptic beta-amyloid hypothesis, will have to consider neural networks not just as targets of degenerative processes but also as contributors of the disease's progression and of its phenotype. Three domains of research are highlighted in this review. First, the cerebral reserve and the redundancy of the network's elements are related to brain vulnerability. Indeed, an enriched environment appears to increase the cerebral reserve as well as the threshold of disease's onset. Second, disease's progression and memory performance cannot be explained by synaptic or neuronal loss only, but also by the presence of compensatory mechanisms, such as synaptic scaling, at the microcircuit level. Third, some phenotypes of Alzheimer disease, such as hallucinations, appear to be related to progressive dysfunction of neural networks as a result, for instance, of a decreased signal to noise ratio, involving a diminished activity of the cholinergic system. Overall, converging results from studies of biological as well as artificial neural networks lead to the conclusion that changes in neural networks contribute strongly to Alzheimer disease's progression.

Synchronizability of EEG-Based Functional Networks in Early Alzheimer's Disease.

Recently graph theory and complex networks have been widely used as a mean to model functionality of the brain. Among different neuroimaging techniques available for constructing the brain functional networks, electroencephalography (EEG) with its high temporal resolution is a useful instrument of the analysis of functional interdependencies between different brain regions. Alzheimer's disease (AD) is a neurodegenerative disease, which leads to substantial cognitive decline, and eventually, dementia in aged people. To achieve a deeper insight into the behavior of functional cerebral networks in AD, here we study their synchronizability in 17 newly diagnosed AD patients compared to 17 healthy control subjects at no-task, eyes-closed condition. The cross-correlation of artifact-free EEGs was used to construct brain functional networks. The extracted networks were then tested for their synchronization properties by calculating the eigenratio of the Laplacian matrix of the connection graph, i.e., the largest eigenvalue divided by the second smallest one. In AD patients, we found an increase in the eigenratio, i.e., a decrease in the synchronizability of brain networks across delta, alpha, beta, and gamma EEG frequencies within the wide range of network costs. The finding indicates the destruction of functional brain networks in early AD.

Neural regulation of pancreatic islet cell mass and function.

Intracellular glucose signalling pathways control the secretion of glucagon and insulin by pancreatic islet α- and β-cells, respectively. However, glucose also indirectly controls the secretion of these hormones through regulation of the autonomic nervous system that richly innervates this endocrine organ. Both parasympathetic and sympathetic nervous systems also impact endocrine pancreas postnatal development and plasticity in adult animals. Defects in these autonomic regulations impair β-cell mass expansion during the weaning period and β-cell mass adaptation in adult life. Both branches of the autonomic nervous system also regulate glucagon secretion. In type 2 diabetes, impaired glucose-dependent autonomic activity causes the loss of cephalic and first phases of insulin secretion, and impaired suppression of glucagon secretion in the postabsorptive phase; in diabetic patients treated with insulin, it causes a progressive failure of hypoglycaemia to trigger the secretion of glucagon and other counterregulatory hormones. Therefore, identification of the glucose-sensing cells that control the autonomic innervation of the endocrine pancreatic and insulin and glucagon secretion is an important goal of research. This is required for a better understanding of the physiological control of glucose homeostasis and its deregulation in diabetes. This review will discuss recent advances in this field of investigation.