Signaux électriques des îlots pancréatiques enregistrés sur matrices de microélectrodes : caractérisation et application au phénotypage d'animaux transgéniques

Pancreatic β cells are central to glucose homeostasis because they are the only cell that secretes insulin, the sole hypoglycemic hormone in the organism. The β cell is a glucose sensor that regulates its secretory response and gene expression according to ambient glucose levels. The coupling between glucose metabolism and insulin granule exocytosis involves the generation of electrical activity. An investigation of this activity is important to decipher how β cells encode the organism’s insulin demand. In order to overcome the limits of classically used electrophysiological approaches that are not compatible with long-term studies, extracellular recordings using multielectrode arrays (MEA) have been set-up.My thesis aim was to better understand the complex signals recorded with MEA. This study revealed the existence of a new electrical signature of islet cells: slow potentials (SP) that reflect the coupling function of β cells. SP play an important role in glucose homeostasis and represent a biomarker of normal functioning of islets. The observed hysteretic response of islets to glucose suggests the existence of an algorithm encoding the insulin demand embedded at the microorgan level. Moreover, this new signal was used for the phenotyping of GluK2 deficient mouse islets that were employed as an α-to-β cell interaction model. The characterization of this new signal is an important progress in the development of a biosensor intended to be integrated in an artificial pancreas in the future.Les cellules β des îlots de Langerhans jouent un rôle central dans l’homéostasie glucidique car elles seules sécrètent l’insuline, unique hormone hypoglycémiante de l’organisme. La cellule β est un détecteur du glucose qui couple sa réponse sécrétoire et son expression génique aux niveaux ambiants de glucose. Le couplage entre le métabolisme du glucose et l’exocytose des granules d’insuline implique la génération d’une activité électrique. Son étude est importante pour déchiffrer la façon dont la cellule β encode la demande en insuline de l’organisme. Afin de contourner les limites des approches électrophysiologiques classiques incompatibles avec les études à long-terme, les enregistrements extracellulaires par matrice de microélectrodes (MEA) ont été mis en place.L’objectif de ma thèse était de mieux comprendre les signaux complexes enregistrés par MEAs. Cette étude a révélé l’existence d’une nouvelle signature électrique des cellules des îlots, les slow potentials (SP), qui reflète la fonction de couplage des cellules β. Les SP jouent un rôle important dans l’homéostasie du glucose et représentent un biomarqueur de la fonction normale des îlots. La réponse en hystérèse des îlots au glucose suggère l’existence d’un algorithme d’encodage de la demande en insuline intégrée au niveau du micro-organe. De plus, ce nouveau signal a été exploité pour le phénotypage d’îlots de souris invalidées pour le gène GluK2, que nous avons utilisées comme modèle d’interaction entre les cellules α et β. La caractérisation de ce nouveau type de signal constitue aussi une avancée importante pour le développement d’un biocapteur destiné à être intégré dans le futur à un pancréas artificiel

The glutamate receptor GluK2 contributes to the regulation of glucose homeostasis and its deterioration during aging

OBJECTIVE: Islets secrete neurotransmitters including glutamate which participate in fine regulation of islet function. The excitatory ionotropic glutamate receptor GluK2 of the kainate receptor family is widely expressed in brain and also found in islets, mainly in alpha and gamma cells. alpha cells co-release glucagon and glutamate and the latter increases glucagon release via ionotropic glutamate receptors. However, neither the precise nature of the ionotropic glutamate receptor involved nor its role in glucose homeostasis is known. As isoform specific pharmacology is not available, we investigated this question in constitutive GluK2 knock-out mice (GluK2-/-) using adult and middle-aged animals to also gain insight in a potential role during aging. METHODS: We compared wild-type GluK2+/+ and knock-out GluK2-/- mice using adult (14-20 weeks) and middle-aged animals (40-52 weeks). Glucose (oral OGTT and intraperitoneal IPGTT) and insulin tolerance as well as pyruvate challenge tests were performed according to standard procedures. Parasympathetic activity, which stimulates hormones secretion, was measured by electrophysiology invivo. Isolated islets were used invitro to determine islet beta-cell electrical activity on multi-electrode arrays and dynamic secretion of insulin as well as glucagon was determined by ELISA. RESULTS: Adult GluK2-/- mice exhibit an improved glucose tolerance (OGTT and IPGTT), and this was also apparent in middle-aged mice, whereas the outcome of pyruvate challenge was slightly improved only in middle-aged GluK2-/- mice. Similarly, insulin sensitivity was markedly enhanced in middle-aged GluK2-/- animals. Basal and glucose-induced insulin secretion invivo was slightly lower in GluK2-/- mice, whereas fasting glucagonemia was strongly reduced. Invivo recordings of parasympathetic activity showed an increase in basal activity in GluK2-/- mice which represents most likely an adaptive mechanism to counteract hypoglucagonemia rather than altered neuronal mechanism. Invitro recording demonstrated an improvement of glucose-induced electrical activity of beta-cells in islets obtained from GluK2-/- mice at both ages. Finally, glucose-induced insulin secretion invitro was increased in GluK2-/- islets, whereas glucagon secretion at 2mmol/l of glucose was considerably reduced. CONCLUSIONS: These observations indicate a general role for kainate receptors in glucose homeostasis and specifically suggest a negative effect of GluK2 on glucose homeostasis and preservation of islet function during aging. Our observations raise the possibility that blockade of GluK2 may provide benefits in glucose homeostasis especially during aging.Transistors multimodaux sensibles aux ions à polymères ambivalents pour biocapteurs hybridesIdentification de biomarqueurs du stress et de l'inflammation des cellules B pancréatiques en explorant les communications inter-organes dans des modèles précliniques d'obésité et de diabète de type

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock

Electrical signals from pancreatic islets recorded on multielectrode arrays : characterization and application to the phenotyping of transgenic animals

Les cellules β des îlots de Langerhans jouent un rôle central dans l’homéostasie glucidique car elles seules sécrètent l’insuline, unique hormone hypoglycémiante de l’organisme. La cellule β est un détecteur du glucose qui couple sa réponse sécrétoire et son expression génique aux niveaux ambiants de glucose. Le couplage entre le métabolisme du glucose et l’exocytose des granules d’insuline implique la génération d’une activité électrique. Son étude est importante pour déchiffrer la façon dont la cellule β encode la demande en insuline de l’organisme. Afin de contourner les limites des approches électrophysiologiques classiques incompatibles avec les études à long-terme, les enregistrements extracellulaires par matrice de microélectrodes (MEA) ont été mis en place.L’objectif de ma thèse était de mieux comprendre les signaux complexes enregistrés par MEAs. Cette étude a révélé l’existence d’une nouvelle signature électrique des cellules des îlots, les slow potentials (SP), qui reflète la fonction de couplage des cellules β. Les SP jouent un rôle important dans l’homéostasie du glucose et représentent un biomarqueur de la fonction normale des îlots. La réponse en hystérèse des îlots au glucose suggère l’existence d’un algorithme d’encodage de la demande en insuline intégrée au niveau du micro-organe. De plus, ce nouveau signal a été exploité pour le phénotypage d’îlots de souris invalidées pour le gène GluK2, que nous avons utilisées comme modèle d’interaction entre les cellules α et β. La caractérisation de ce nouveau type de signal constitue aussi une avancée importante pour le développement d’un biocapteur destiné à être intégré dans le futur à un pancréas artificiel.Pancreatic β cells are central to glucose homeostasis because they are the only cell that secretes insulin, the sole hypoglycemic hormone in the organism. The β cell is a glucose sensor that regulates its secretory response and gene expression according to ambient glucose levels. The coupling between glucose metabolism and insulin granule exocytosis involves the generation of electrical activity. An investigation of this activity is important to decipher how β cells encode the organism’s insulin demand. In order to overcome the limits of classically used electrophysiological approaches that are not compatible with long-term studies, extracellular recordings using multielectrode arrays (MEA) have been set-up.My thesis aim was to better understand the complex signals recorded with MEA. This study revealed the existence of a new electrical signature of islet cells: slow potentials (SP) that reflect the coupling function of β cells. SP play an important role in glucose homeostasis and represent a biomarker of normal functioning of islets. The observed hysteretic response of islets to glucose suggests the existence of an algorithm encoding the insulin demand embedded at the microorgan level. Moreover, this new signal was used for the phenotyping of GluK2 deficient mouse islets that were employed as an α-to-β cell interaction model. The characterization of this new signal is an important progress in the development of a biosensor intended to be integrated in an artificial pancreas in the future

From parliamentary history to digital and computational history : a NLP-friendly TEI model for historical and contemporary parliamentary proceedings

This paper introduces a new method for the digital and computational analysis of historical and contemporary parliamentary proceedings. It addresses the dichotomy in the utilization of these resources between historians and other disciplines, and emphasizes the significance of continuity in studying long-term phenomena. The paper presents an XML-TEI model specifically designed for encoding parliamentary documents from diverse temporal and regional contexts. This model is exemplified through the analysis of parliamentary debates from the French Chamber of Deputies (1889-1893). The first part of the paper discusses the motivations behind the model's development. The second part outlines the methodological choices in constructing the model and the need for schema adaptation. We subsequently detail our method for automatic encoding of such extensive corpora. Finally, we propose an approach to annotate parliamentary debates using natural language processing analyses, focusing on topic modeling. This study aims to enhance computational research in humanities, especially historical and political studies, by providing an efficient tool to harness the potential of the massive digitized parliamentary data

From parliamentary history to digital and computational history : a NLP-friendly TEI model for historical and contemporary parliamentary proceedings

This paper introduces a new method for the digital and computational analysis of historical and contemporary parliamentary proceedings. It addresses the dichotomy in the utilization of these resources between historians and other disciplines, and emphasizes the significance of continuity in studying long-term phenomena. The paper presents an XML-TEI model specifically designed for encoding parliamentary documents from diverse temporal and regional contexts. This model is exemplified through the analysis of parliamentary debates from the French Chamber of Deputies (1889-1893). The first part of the paper discusses the motivations behind the model's development. The second part outlines the methodological choices in constructing the model and the need for schema adaptation. We subsequently detail our method for automatic encoding of such extensive corpora. Finally, we propose an approach to annotate parliamentary debates using natural language processing analyses, focusing on topic modeling. This study aims to enhance computational research in humanities, especially historical and political studies, by providing an efficient tool to harness the potential of the massive digitized parliamentary data

From parliamentary history to digital and computational history : a NLP-friendly TEI model for historical and contemporary parliamentary proceedings

This paper introduces a new method for the digital and computational analysis of historical and contemporary parliamentary proceedings. It addresses the dichotomy in the utilization of these resources between historians and other disciplines, and emphasizes the significance of continuity in studying long-term phenomena. The paper presents an XML-TEI model specifically designed for encoding parliamentary documents from diverse temporal and regional contexts. This model is exemplified through the analysis of parliamentary debates from the French Chamber of Deputies (1889-1893). The first part of the paper discusses the motivations behind the model's development. The second part outlines the methodological choices in constructing the model and the need for schema adaptation. We subsequently detail our method for automatic encoding of such extensive corpora. Finally, we propose an approach to annotate parliamentary debates using natural language processing analyses, focusing on topic modeling. This study aims to enhance computational research in humanities, especially historical and political studies, by providing an efficient tool to harness the potential of the massive digitized parliamentary data

"Ectopic" theta oscillations and interictal activity during slow-wave state in the R6/1 mouse model of Huntington's disease

The pathophysiology of Huntington's disease (HD) is primarily associated with striatal degeneration and a number of behavioral symptoms such as involuntary movements, cognitive decline, psychiatric disorders, and in the most juvenile-onset cases with epilepsy. In addition to several changes in cellular and synaptic properties previously reported in HD, attention was recently driven towards the potential relationships between cognitive deficits and sleep disturbances in patients and animal models of Huntington's disease. In the present study, we have investigated whether the population-activity patterns normally expressed by the hippocampal and neocortical circuits during active and slow-wave states are affected in R6/1 mice, a model of Huntington's disease. By performing electrophysiological recordings from the hippocampus and neocortex of R6/1 mice that were either freely moving, head restrained or anesthetized, we observed an altered segregation of active and slow wave brain states, in relation with an epileptic phenotype. Slow-wave state (SWS) in R6/1 was characterized by the intrusion of active-state features (increased 6-10 Hz theta power and depressed 2-3 Hz delta power) and transient, temporally misplaced ("ectopic") theta oscillations. The epileptic phenotype, in addition to previously reported occasional ictal seizures, was characterized by the systematic presence of interictal activity, confined to SWS. Ectopic theta episodes, which could be reversed by the cholinergic antagonist atropine, concentrated interictal spikes and phase-locked hippocampal sharp-wave-ripples. These results point to major alterations of neuronal activity during rest in R6/1 mice, potentially involving anomalous activation of the cholinergic system, which may contribute to the cognitive deficits observed in Huntington's disease