Astrocytes are the most abundant glial cell type in the brain. Although not apposite for long-range rapid electrical communication, astrocytes share with neurons the capacity of chemical signaling via Ca²⁺-dependent transmitter exocytosis. Despite this recent finding, little is known about the specific properties of regulated secretion and vesicle recycling in astrocytes. Important differences may exist with the neuronal exocytosis, starting from the fact that stimulus-secretion coupling in astrocytes is voltage independent, mediated by G-protein-coupled receptors and the release of Ca²⁺from internal stores. Elucidating the spatiotemporal properties of astrocytic exo-endocytosis is, therefore, of primary importance for understanding the mode of communication of these cells and their role in brain signaling. We here take advantage of fluorescent tools recently developed for studying recycling of glutamatergic vesicles at synapses (Voglmaier et al., 2006; Balaji and Ryan, 2007); we combine epifluorescence and total internal reflection fluorescence imaging to investigate with unprecedented temporal and spatial resolution, the stimulus-secretion coupling underlying exo-endocytosis of glutamatergic synaptic-like microvesicles (SLMVs) in astrocytes. Our main findings indicate that (1) exo-endocytosis in astrocytes proceeds with a time course on the millisecond time scale (τ_exocytosis= 0.24 ± 0.017 s; τ_endocytosis= 0.26 ± 0.03 s) and (2) exocytosis is controlled by local Ca²⁺microdomains. We identified submicrometer cytosolic compartments delimited by endoplasmic reticulum tubuli reaching beneath the plasma membrane and containing SLMVs at which fast (time-to-peak, ∼50 ms) Ca²⁺events occurred in precise spatial-temporal correlation with exocytic fusion events. Overall, the above characteristics of transmitter exocytosis from astrocytes support a role of this process in fast synaptic modulation.

Astrocytes orchestrate neural development by powerfully coordinating synapse formation and function and, as such, may be critically involved in the pathogenesis of neurodevelopmental abnormalities and cognitive deficits commonly observed in psychiatric disorders. Here, we report the identification of a subset of cortical astrocytes that are competent for regulating dopamine (DA) homeostasis during postnatal development of the prefrontal cortex (PFC), allowing for optimal DA-mediated maturation of excitatory circuits. Such control of DA homeostasis occurs through the coordinated activity of astroglial vesicular monoamine transporter 2 (VMAT2) together with organic cation transporter 3 and monoamine oxidase type B, two key proteins for DA uptake and metabolism. Conditional deletion of VMAT2 in astrocytes postnatally produces loss of PFC DA homeostasis, leading to defective synaptic transmission and plasticity as well as impaired executive functions. Our findings show a novel role for PFC astrocytes in the DA modulation of cognitive performances with relevance to psychiatric disorders.

With the rapid evolution in the automation of serial electron microscopy in life sciences, the acquisition of terabyte-sized datasets is becoming increasingly common. High resolution serial block-face imaging (SBEM) of biological tissues offers the opportunity to segment and reconstruct nanoscale structures to reveal spatial features previously inaccessible with simple, single section, two-dimensional images. In particular, we focussed here on glial cells, whose reconstruction efforts in literature are still limited, compared to neurons. We imaged a 750,000 cubic micron volume of the somatosensory cortex from a juvenile P14 rat, with 20 nm accuracy. We recognized a total of 186 cells using their nuclei, and classified them as neuronal or glial based on features of the soma and the processes. We reconstructed for the first time 4 almost complete astrocytes and neurons, 4 complete microglia and 4 complete pericytes, including their intracellular mitochondria, 186 nuclei and 213 myelinated axons. We then performed quantitative analysis on the three-dimensional models. Out of the data that we generated, we observed that neurons have larger nuclei, which correlated with their lesser density, and that astrocytes and pericytes have a higher surface to volume ratio, compared to other cell types. All reconstructed morphologies represent an important resource for computational neuroscientists, as morphological quantitative information can be inferred, to tune simulations that take into account the spatial compartmentalization of the different cell types.

Advances in the application of electron microscopy (EM) to serial imaging are opening doors to new ways of analyzing cellular structure. New and improved algorithms and workflows for manual and semiautomated segmentation allow us to observe the spatial arrangement of the smallest cellular features with unprecedented detail in full three‐dimensions. From larger samples, higher complexity models can be generated; however, they pose new challenges to data management and analysis. Here we review some currently available solutions and present our approach in detail. We use the fully immersive virtual reality (VR) environment CAVE (cave automatic virtual environment), a room in which we are able to project a cellular reconstruction and visualize in 3D, to step into a world created with Blender, a free, fully customizable 3D modeling software with NeuroMorph plug‐ins for visualization and analysis of EM preparations of brain tissue. Our workflow allows for full and fast reconstructions of volumes of brain neuropil using ilastik, a software tool for semiautomated segmentation of EM stacks. With this visualization environment, we can walk into the model containing neuronal and astrocytic processes to study the spatial distribution of glycogen granules, a major energy source that is selectively stored in astrocytes. The use of CAVE was key to the observation of a nonrandom distribution of glycogen, and led us to develop tools to quantitatively analyze glycogen clustering and proximity to other subcellular features. J. Comp. Neurol. 524:23–38, 2016.

Serialelectron microscopy imaging is crucial for exploring the structure of cells and tissues. The development of block face scanning electron microscopy methods and their ability to capture large image stacks, some with near isotropic voxels, is proving particularly useful for the exploration of brain tissue. This has led to the creation of numerous algorithms and software for segmenting out different features from the image stacks. However, there are few tools available to view these results and make detailed morphometric analyses on all, or part, of these 3D models. We have addressed this issue by constructing a collection of software tools, called NeuroMorph, with which users can view the segmentation results, in conjunction with the original image stack, manipulate these objects in 3D, and make measurements of any region. This approach to collecting morphometric data provides a faster means of analysing the geometry of structures, such as dendritic spines and axonal boutons. This bridges the gap that currently exists between rapid reconstruction techniques, offered by computer vision research, and the need to collect measurements of shape and form from segmented structures that is currently done using manual segmentation methods.