55 research outputs found
Live imaging of effector cell trafficking and autoantigen recognition within the unfolding autoimmune encephalomyelitis lesion
We tracked pathogenic myelin basic protein-specific CD4+ effector T cells in early central nervous system (CNS) lesions of experimental autoimmune encephalomyelitis (EAE) by combining two-photon imaging and fluorescence video microscopy. We made two key observations: (a) the majority of the cells (65%) moved fast (maximal speed 25 μm/min) and apparently nondirected through the compact tissue; and (b) a second group of effector T cells (35%) appeared tethered to a fixed point. Polarization of T cell receptor and adhesion molecules (lymphocyte function-associated antigen 1) towards this fixed point suggests the formation of immune synapses. Nonpathogenic, ovalbumin-specific T cells were not tethered in the CNS and did not form synapse-like contacts, but moved through the tissue. After intrathecal injection of antigen, 40% of ovalbumin-specific T cells became tethered. Conversely, injection of anti–major histocompatibility complex class II antibodies profoundly reduced the number of stationary pathogenic T cells within the CNS (to 15%). We propose that rapid penetration of the CNS parenchyma by numerous autoimmune effector T cells along with multiple autoantigen-presentation events are responsible for the fulminate development of clinical EAE
Control of Ca²⁺ signals by astrocyte nanoscale morphology at tripartite synapses
Much of the Ca²⁺ activity in astrocytes is spatially restricted to microdomains and occurs in fine processes that form a complex anatomical meshwork, the so-called spongiform domain. A growing body of literature indicates that those astrocytic Ca²⁺ signals can influence the activity of neuronal synapses and thus tune the flow of information through neuronal circuits. Because of technical difficulties in accessing the small spatial scale involved, the role of astrocyte morphology on Ca²⁺ microdomain activity remains poorly understood. Here, we use computational tools and idealized 3D geometries of fine processes based on recent super-resolution microscopy data to investigate the mechanistic link between astrocytic nanoscale morphology and local Ca²⁺ activity. Simulations demonstrate that the nano-morphology of astrocytic processes powerfully shapes the spatio-temporal properties of Ca²⁺ signals and promotes local Ca²⁺ activity. The model predicts that this effect is attenuated upon astrocytic swelling, hallmark of brain diseases, which we confirm experimentally in hypo-osmotic conditions. Upon repeated neurotransmitter release events, the model predicts that swelling hinders astrocytic signal propagation. Overall, this study highlights the influence of the complex morphology of astrocytes at the nanoscale and its remodeling in pathological conditions on neuron-astrocyte communication at so-called tripartite synapses, where astrocytic processes come into close contact with pre- and postsynaptic structures
Simulation of Astrocytic Calcium Dynamics in Lattice Light Sheet Microscopy Images
International audienceAstrocytes regulate neuronal information processing through a variety of spatio-temporal calcium signals. Advances in calcium imaging started to reveal astrocytic activities, but the complexity of the recorded data strongly call for computational analysis tools. Their development is hindered by the lack of reliable annotations that are essential for their evaluation and for the design of learning-based methods. To overcome the labeling problem, we present a framework to simulate realistic astrocytic calcium signals in 3D+time lattice light sheet microscopy (LLSM) images by closely modeling calcium kinetics in real astrocytes
Convergence of hippocampal pathophysiology in <i>Syngap<sup>+/-</sup> </i>and <i>Fmr1</i><sup><i>-/y</i> </sup>mice
Previous studies have hypothesized that diverse genetic causes of intellectual disability (ID) and autism spectrum disorders (ASDs) converge on common cellular pathways. Testing this hypothesis requires detailed phenotypic analyses of animal models with genetic mutations that accurately reflect those seen in the human condition (i.e., have structural validity) and which produce phenotypes that mirror ID/ASDs (i.e., have face validity). We show that SynGAP haploinsufficiency, which causes ID with co-occurring ASD in humans, mimics and occludes the synaptic pathophysiology associated with deletion of the Fmr1 gene. Syngap[superscript +/−] and Fmr1[superscript −/y] mice show increases in basal protein synthesis and metabotropic glutamate receptor (mGluR)-dependent long-term depression that, unlike in their wild-type controls, is independent of new protein synthesis. Basal levels of phosphorylated ERK1/2 are also elevated in Syngap[superscript +/−] hippocampal slices. Super-resolution microscopy reveals that Syngap[superscript +/−] and Fmr1[superscript −/y] mice show nanoscale alterations in dendritic spine morphology that predict an increase in biochemical compartmentalization. Finally, increased basal protein synthesis is rescued by negative regulators of the mGlu subtype 5 receptor and the Ras–ERK1/2 pathway, indicating that therapeutic interventions for fragile X syndrome may benefit patients with SYNGAP1 haploinsufficiency
Spine neck plasticity regulates compartmentalization of synapses
Dendritic spines have been proposed to transform synaptic signals through chemical and electrical compartmentalization. However, the quantitative contribution of spine morphology to synapse compartmentalization and its dynamic regulation are still poorly understood. We used time-lapse super-resolution stimulated emission depletion (STED) imaging in combination with fluorescence recovery after photobleaching (FRAP) measurements, two-photon glutamate uncaging, electrophysiology and simulations to investigate the dynamic link between nanoscale anatomy and compartmentalization in live spines of CA1 neurons in mouse brain slices. We report a diversity of spine morphologies that argues against common categorization schemes and establish a close link between compartmentalization and spine morphology, wherein spine neck width is the most critical morphological parameter. We demonstrate that spine necks are plastic structures that become wider and shorter after long-term potentiation. These morphological changes are predicted to lead to a substantial drop in spine head excitatory postsynaptic potential (EPSP) while preserving overall biochemical compartmentalization
Machine learning-based evaluation of spontaneous pain and analgesics from cellular calcium signals in the mouse primary somatosensory cortex using explainable features
IntroductionPain that arises spontaneously is considered more clinically relevant than pain evoked by external stimuli. However, measuring spontaneous pain in animal models in preclinical studies is challenging due to methodological limitations. To address this issue, recently we developed a deep learning (DL) model to assess spontaneous pain using cellular calcium signals of the primary somatosensory cortex (S1) in awake head-fixed mice. However, DL operate like a “black box”, where their decision-making process is not transparent and is difficult to understand, which is especially evident when our DL model classifies different states of pain based on cellular calcium signals. In this study, we introduce a novel machine learning (ML) model that utilizes features that were manually extracted from S1 calcium signals, including the dynamic changes in calcium levels and the cell-to-cell activity correlations.MethodWe focused on observing neural activity patterns in the primary somatosensory cortex (S1) of mice using two-photon calcium imaging after injecting a calcium indicator (GCaMP6s) into the S1 cortex neurons. We extracted features related to the ratio of up and down-regulated cells in calcium activity and the correlation level of activity between cells as input data for the ML model. The ML model was validated using a Leave-One-Subject-Out Cross-Validation approach to distinguish between non-pain, pain, and drug-induced analgesic states.Results and discussionThe ML model was designed to classify data into three distinct categories: non-pain, pain, and drug-induced analgesic states. Its versatility was demonstrated by successfully classifying different states across various pain models, including inflammatory and neuropathic pain, as well as confirming its utility in identifying the analgesic effects of drugs like ketoprofen, morphine, and the efficacy of magnolin, a candidate analgesic compound. In conclusion, our ML model surpasses the limitations of previous DL approaches by leveraging manually extracted features. This not only clarifies the decision-making process of the ML model but also yields insights into neuronal activity patterns associated with pain, facilitating preclinical studies of analgesics with higher potential for clinical translation
Plus vive, plus nette : la microscopie STED du cerveau
La microscopie à super-résolution (SRM) désigne une nouvelle catégorie de techniques de microscopie optique qui permettent de surmonter la barrière de diffraction classique,- barrière qui a rendu difficile l’observation des structures et des activités qui constituent la base de la vie cellulaire biologique. La microscopie STED, qui est l'une des techniques SRM, a attiré l'attention des neurobiologistes, car elle permet de révéler la nanostructure des cellules cérébrales non seulement dans une boîte de Pétri, mais aussi à l'intérieur du tissu cérébral réel, voire dans le cerveau intact in vivo
Turning up the Green Light
International audienceFluorescent proteins (FPs) have become indispensable tools in biological research for labeling cells and proteins and sensing their biochemical activity. By introducing 'folding mutations', Campbell et al. engineered a new GFP variant with dramatically enhanced cellular brightness and stability, facilitating advanced cellular bioimaging applications in neuroscience and beyond
- …