ABSTRACT
Exocytosis is a fundamental process used by eukaryotes to regulate the composition of the plasma membrane and facilitate cell-cell communication. To investigate exocytosis in neuronal morphogenesis, previously we developed computational tools with a graphical user interface to enable the automatic detection and analysis of exocytic events from fluorescence timelapse images. Although these tools were useful, we found the code was brittle and not easily adapted to different experimental conditions. Here, we developed and validated a robust and versatile toolkit, named pHusion, for the analysis of exocytosis, written in ImageTank, a graphical programming language that combines image visualization and numerical methods. We tested pHusion using a variety of imaging modalities and pH-sensitive fluorophores, diverse cell types and various exocytic markers, to generate a flexible and intuitive package. Using this system, we show that VAMP3-mediated exocytosis occurs 30-times more frequently in melanoma cells compared with primary oligodendrocytes, that VAMP2-mediated fusion events in mature rat hippocampal neurons are longer lasting than those in immature murine cortical neurons, and that exocytic events are clustered in space yet random in time in developing cortical neurons.
Subject(s)
Exocytosis , Animals , Rats , Mice , Neurons/metabolism , Neurons/cytology , Humans , Hydrogen-Ion Concentration , Software , Hippocampus/metabolism , Hippocampus/cytologyABSTRACT
Live-cell super-resolution microscopy enables the imaging of biological structure dynamics below the diffraction limit. Here we present enhanced super-resolution radial fluctuations (eSRRF), substantially improving image fidelity and resolution compared to the original SRRF method. eSRRF incorporates automated parameter optimization based on the data itself, giving insight into the trade-off between resolution and fidelity. We demonstrate eSRRF across a range of imaging modalities and biological systems. Notably, we extend eSRRF to three dimensions by combining it with multifocus microscopy. This realizes live-cell volumetric super-resolution imaging with an acquisition speed of ~1 volume per second. eSRRF provides an accessible super-resolution approach, maximizing information extraction across varied experimental conditions while minimizing artifacts. Its optimal parameter prediction strategy is generalizable, moving toward unbiased and optimized analyses in super-resolution microscopy.
Subject(s)
Artifacts , Microscopy, Fluorescence/methodsABSTRACT
Adult neurogenesis is a process by which the brain produces new neurons once development has ceased. Adult hippocampal neurogenesis has been linked to the relational processing of spatial information, a role attributed to the contribution of newborn neurons to long-term potentiation (LTP). However, whether newborn neurons also influence long-term depression (LTD), and how synaptic transmission and plasticity are affected as they incorporate their network, remain to be determined. To address these issues, we took advantage of a genetic model in which a majority of adult-born neurons can be selectively ablated in the dentate gyrus (DG) and, most importantly, in which neurogenesis can be restored on demand. Using electrophysiological recordings, we show that selective reduction of adult-born neurons impairs synaptic transmission at medial perforant pathway synapses onto DG granule cells. Furthermore, LTP and LTD are largely compromised at these synapses, probably as a result of an increased induction threshold. Whereas the deficits in synaptic transmission and plasticity are completely rescued by restoring neurogenesis, these synapses regain their ability to express LTP much faster than their ability to express LTD. These results demonstrate that both LTP and LTD are influenced by adult neurogenesis. They also indicate that as newborn neurons integrate their network, the ability to express bidirectional synaptic plasticity is largely improved at these synapses. These findings establish that adult neurogenesis is an important process for synaptic transmission and bidirectional plasticity in the DG, accounting for its role in efficiently integrating novel incoming information and in forming new memories.
Subject(s)
Dentate Gyrus/metabolism , Long-Term Potentiation , Neurogenesis , Neurons/metabolism , Synapses/metabolism , Synaptic Transmission , Animals , Animals, Newborn , Dentate Gyrus/pathology , Female , Male , Memory , Mice , Mice, Transgenic , Neurons/pathology , Synapses/genetics , Synapses/pathologyABSTRACT
Coordinated assembly of individual components into higher-order structures is a defining theme in biology, but underlying principles are not well-understood. In neurons, α/ß spectrins, adducin, and actinfilaments assemble into a lattice wrapping underneath the axonal plasma membrane, but mechanistic events leading to this periodic axonal structure (PAS) are unclear. Visualizing PAS components in axons as they develop, we found focal patches in distal axons containing spectrins and adducin (but sparse actin filaments) with biophysical properties reminiscent of biomolecular condensation. Overexpressing spectrin-repeats - constituents of α/ß-spectrins - in heterologous cells triggered condensate formation, and preventing association of ßII-spectrin with actin-filaments/membranes also facilitated condensation. Finally, overexpressing condensate-triggering spectrin repeats in neurons before PAS establishment disrupted the lattice, presumably by competing with innate assembly, supporting a functional role for biomolecular condensation. We propose a condensation-assembly model where PAS components form focal phase-separated condensates that eventually unfurl into a stable lattice-structure by associating with subplasmalemmal actin. By providing local 'depots' of assembly parts, biomolecular condensation may play a wider role in the construction of intricate cytoskeletal structures.
ABSTRACT
Super-resolution fluorescence microscopy methods enable the characterization of nanostructures in living and fixed biological tissues. However, they require the adjustment of multiple imaging parameters while attempting to satisfy conflicting objectives, such as maximizing spatial and temporal resolution while minimizing light exposure. To overcome the limitations imposed by these trade-offs, post-acquisition algorithmic approaches have been proposed for resolution enhancement and image-quality improvement. Here we introduce the task-assisted generative adversarial network (TA-GAN), which incorporates an auxiliary task (for example, segmentation, localization) closely related to the observed biological nanostructure characterization. We evaluate how the TA-GAN improves generative accuracy over unassisted methods, using images acquired with different modalities such as confocal, bright-field, stimulated emission depletion and structured illumination microscopy. The TA-GAN is incorporated directly into the acquisition pipeline of the microscope to predict the nanometric content of the field of view without requiring the acquisition of a super-resolved image. This information is used to automatically select the imaging modality and regions of interest, optimizing the acquisition sequence by reducing light exposure. Data-driven microscopy methods like the TA-GAN will enable the observation of dynamic molecular processes with spatial and temporal resolutions that surpass the limits currently imposed by the trade-offs constraining super-resolution microscopy.
ABSTRACT
Exocytosis is a fundamental process used by eukaryotic cells to regulate the composition of the plasma membrane and facilitate cell-cell communication. To investigate the role exocytosis plays in neuronal morphogenesis, previously we developed computational tools with a graphical user interface (GUI) to enable the automatic detection and analysis of exocytic events (ADAE GUI) from fluorescence timelapse images. Though these tools have proven useful, we found that the code was brittle and not easily adapted to different experimental conditions. Here, we have developed and validated a robust and versatile toolkit, named pHusion, for the analysis of exocytosis written in ImageTank, a graphical programming language that combines image visualization and numerical methods. We tested this method using a variety of imaging modalities and pH-sensitive fluorophores, diverse cell types, and various exocytic markers to generate a flexible and intuitive package. Using pHusion, we show that VAMP3-mediated exocytosis occurs 30-times more frequently in melanoma cells compared with primary oligodendrocytes, that VAMP2-mediated fusion events in mature rat hippocampal neurons are longer lasting than those in immature murine cortical neurons, and that exocytic events are clustered in space yet random in time in developing cortical neurons. Summary Statement: Exocytosis is an essential process by which cells change shape, alter membrane composition, and communicate with other cells. Though all eukaryotic cells carry out exocytosis, the regulation of vesicle fusion, the cargo of vesicles, and the role exocytosis plays in cell fate differ greatly across cell types. Here, we developed a flexible and robust set of tools to enable automatic identification and analysis of exocytic events across a wide range of cell types, vesicle types, and imaging conditions.
ABSTRACT
The organization of proteins in the apposed nanodomains of pre- and postsynaptic compartments is thought to play a pivotal role in synaptic strength and plasticity. As such, the alignment between pre- and postsynaptic proteins may regulate, for example, the rate of presynaptic release or the strength of postsynaptic signaling. However, the analysis of these structures has mainly been restricted to subsets of synapses, providing a limited view of the diversity of synaptic protein cluster remodeling during synaptic plasticity. To characterize changes in the organization of synaptic nanodomains during synaptic plasticity over a large population of synapses, we combined STimulated Emission Depletion (STED) nanoscopy with a Python-based statistical object distance analysis (pySODA), in dissociated cultured hippocampal circuits exposed to treatments driving different forms of synaptic plasticity. The nanoscale organization, characterized in terms of coupling properties, of presynaptic (Bassoon, RIM1/2) and postsynaptic (PSD95, Homer1c) scaffold proteins was differently altered in response to plasticity-inducing stimuli. For the Bassoon - PSD95 pair, treatments driving synaptic potentiation caused an increase in their coupling probability, whereas a stimulus driving synaptic depression had an opposite effect. To enrich the characterization of the synaptic cluster remodeling at the population level, we applied unsupervised machine learning approaches to include selected morphological features into a multidimensional analysis. This combined analysis revealed a large diversity of synaptic protein cluster subtypes exhibiting differential activity-dependent remodeling, yet with common features depending on the expected direction of plasticity. The expanded palette of synaptic features revealed by our unbiased approach should provide a basis to further explore the widely diverse molecular mechanisms of synaptic plasticity.
Subject(s)
Dendritic Spines/metabolism , Neuronal Plasticity , Neurons/metabolism , Presynaptic Terminals/metabolism , Synapses/metabolism , Animals , Dendritic Spines/pathology , Hippocampus/cytology , Image Processing, Computer-Assisted , Microscopy , Neurons/cytology , Presynaptic Terminals/pathology , Rats , Synapses/pathology , Unsupervised Machine LearningABSTRACT
The nanoscale organization of the F-actin cytoskeleton in neurons comprises membrane-associated periodical rings, bundles, and longitudinal fibers. The F-actin rings have been observed predominantly in axons but only sporadically in dendrites, where fluorescence nanoscopy reveals various patterns of F-actin arranged in mixed patches. These complex dendritic F-actin patterns pose a challenge for investigating quantitatively their regulatory mechanisms. We developed here a weakly supervised deep learning segmentation approach of fluorescence nanoscopy images of F-actin in cultured hippocampal neurons. This approach enabled the quantitative assessment of F-actin remodeling, revealing the disappearance of the rings during neuronal activity in dendrites, but not in axons. The dendritic F-actin cytoskeleton of activated neurons remodeled into longitudinal fibers. We show that this activity-dependent remodeling involves [Formula: see text] and NMDA receptor-dependent mechanisms. This highly dynamic restructuring of dendritic F-actin based submembrane lattice into longitudinal fibers may serve to support activity-dependent membrane remodeling, protein trafficking and neuronal plasticity.
Subject(s)
Actins/metabolism , Axons/metabolism , Cell Membrane/metabolism , Dendrites/metabolism , Hippocampus/cytology , Actin Cytoskeleton/metabolism , Animals , Animals, Newborn , Calcium/metabolism , Deep Learning , Models, Neurological , Nanostructures/chemistry , Rats, Sprague-Dawley , Receptors, N-Methyl-D-Aspartate/metabolism , Synapses/metabolismABSTRACT
Traditional approaches for finding well-performing parameterizations of complex imaging systems, such as super-resolution microscopes rely on an extensive exploration phase over the illumination and acquisition settings, prior to the imaging task. This strategy suffers from several issues: it requires a large amount of parameter configurations to be evaluated, it leads to discrepancies between well-performing parameters in the exploration phase and imaging task, and it results in a waste of time and resources given that optimization and final imaging tasks are conducted separately. Here we show that a fully automated, machine learning-based system can conduct imaging parameter optimization toward a trade-off between several objectives, simultaneously to the imaging task. Its potential is highlighted on various imaging tasks, such as live-cell and multicolor imaging and multimodal optimization. This online optimization routine can be integrated to various imaging systems to increase accessibility, optimize performance and improve overall imaging quality.
ABSTRACT
Expression of aversive memories is key for survival, but the underlying brain mechanisms are not fully understood. Medial habenular (MHb) axons corelease glutamate and acetylcholine onto target postsynaptic interpeduncular (IPN) neurons, but their role in aversive memories has not been addressed so far. We found that cannabinoid type 1 receptors (CB1R), key regulators of aversive responses, are present at presynaptic terminals of MHb neurons in the IPN. Conditional deletion of CB1R from MHb neurons reduces fear-conditioned freezing and abolishes conditioned odor aversion in mice, without affecting neutral or appetitively motivated memories. Interestingly, local inhibition of nicotinic, but not glutamatergic receptors in the target region IPN before retrieval, rescues these phenotypes. Finally, optogenetic electrophysiological recordings of MHb-to-IPN circuitry revealed that blockade of CB1R specifically enhances cholinergic, but not glutamatergic, neurotransmission. Thus, presynaptic CB1R control expression of aversive memories by selectively modulating cholinergic transmission at MHb synapses in the IPN.
Subject(s)
Avoidance Learning/physiology , Fear/physiology , Habenula/physiology , Receptor, Cannabinoid, CB1/physiology , Animals , Fear/psychology , Male , Mice , Mice, Inbred C57BL , Mice, Knockout , Receptor, Cannabinoid, CB1/deficiencyABSTRACT
Hunger arouses sensory perception, eventually leading to an increase in food intake, but the underlying mechanisms remain poorly understood. We found that cannabinoid type-1 (CB1) receptors promote food intake in fasted mice by increasing odor detection. CB1 receptors were abundantly expressed on axon terminals of centrifugal cortical glutamatergic neurons that project to inhibitory granule cells of the main olfactory bulb (MOB). Local pharmacological and genetic manipulations revealed that endocannabinoids and exogenous cannabinoids increased odor detection and food intake in fasted mice by decreasing excitatory drive from olfactory cortex areas to the MOB. Consistently, cannabinoid agonists dampened in vivo optogenetically stimulated excitatory transmission in the same circuit. Our data indicate that cortical feedback projections to the MOB crucially regulate food intake via CB1 receptor signaling, linking the feeling of hunger to stronger odor processing. Thus, CB1 receptor-dependent control of cortical feedback projections in olfactory circuits couples internal states to perception and behavior.