scholarly journals Ultrastructural distribution of presynaptic active zones and dense core vesicles in olfactory projection neurons of Drosophila

2021 ◽  
Author(s):  
Kai Yang ◽  
He Liu ◽  
Zengru Di ◽  
Aike Guo ◽  
Ke Zhang
Keyword(s):  
Neurotrophic Factors ◽  
Release Site ◽  
Dense Core ◽  
Projection Neurons ◽  
Dense Core Vesicles ◽  
Positive Linear Correlation ◽  
Input Region ◽  
Active Zones ◽  
Coarse Coding ◽  
Open Question

AbstractIn Drosophila melanogaster, olfactory projection neurons (PNs) convey odor information from peripheral olfactory center, antenna lobe, to central olfactory center, mushroom body (MB), and lateral horn (LH). In MB, the mechanisms underlining the transformation from coarse-coding PNs to sparse-coding MB intrinsic Kenyon cells (KCs) remain an open question. Here, we used HRP-labeled electron microscopy (EM) to volume reconstruct 89 PN axonal boutons in a reference area of the input region, the calyx of MB. The results showed that the number of presynaptic active zones (PAZs), neurotransmitter release site, is in positive linear correlation with the surface area of PN axonal boutons, while the number of dense core vesicles (DCVs), vesicles that containing neuropeptides, monoamines, or neurotrophic factors, is weakly related to the morphology of PN axonal boutons. Further analysis illustrated that DCVs preferentially exist in PN axonal boutons labeled by GH146-GAL4, a most widely used genetic marker for studying olfactory PNs. Our data suggest that synapses are uniformly distributed on the surface of all PN boutons, thus the neurotransmission capability of a PN axonal bouton could be predicted by its size, and PN subtypes release neuropeptides, monoamines, or neurotrophic factors, as well as classical neurotransmitters, to mediate the PN-KC transformation.

Keeping Neuronal Cargoes on the Right Track: New Insights into Regulators of Axonal Transport

2016 ◽  
Vol 23 (3) ◽  
pp. 232-250 ◽  
Author(s):  
Kenneth G. Miller
Keyword(s):  
Retrograde Transport ◽  
Dense Core ◽  
System Model ◽  
Dense Core Vesicles ◽  
C Elegans ◽  
Early Endosomes ◽  
New Findings ◽  
Active Zones ◽  
The Right ◽  
Suppressor Screen

In neurons, a single motor (dynein) transports large organelles as well as synaptic and dense core vesicles toward microtubule minus ends; however, it is unclear why dynein appears more active on organelles, which are generally excluded from mature axons, than on synaptic and dense core vesicles, which are maintained at high levels. Recent studies in Zebrafish and Caenorhabditis elegans have shown that JIP3 promotes dynein-mediated retrograde transport to clear some organelles (lysosomes, early endosomes, and Golgi) from axons and prevent their potentially harmful accumulation in presynaptic regions. A JIP3 mutant suppressor screen in C. elegans revealed that JIP3 promotes the clearance of organelles from axons by blocking the action of the CSS system (Cdk5, SAD Kinase, SYD-2/Liprin). A synthesis of results in vertebrates with the new findings suggests that JIP3 blocks the CSS system from disrupting the connection between dynein and organelles. Most components of the CSS system are enriched at presynaptic active zones where they normally contribute to maintaining optimal levels of captured synaptic and dense core vesicles, in part by inhibiting dynein transport. The JIP3-CSS system model explains how neurons selectively regulate a single minus-end motor to exclude specific classes of organelles from axons, while at the same time ensuring optimal levels of synaptic and dense core vesicles.

Relationship between golgi apparatus and axonal reticulum in sympathetic ganglion cells

1978 ◽  
Vol 36 (2) ◽  
pp. 598-599
Author(s):  
J. Quatacker ◽  
W. De Potter
Keyword(s):  
Golgi Apparatus ◽  
Sympathetic Ganglion ◽  
Phosphotungstic Acid ◽  
Ganglion Cells ◽  
Low Ph ◽  
Dense Core ◽  
Dense Core Vesicles ◽  
Large Dense Core Vesicles ◽  
Cervical Ganglia ◽  
Axoplasmic Reticulum

Mucopolysaccharides have been demonstrated biochemically in catecholamine-containing subcellular particles in different rat, cat and ox tissues. As catecholamine-containing granules seem to arise from the Golgi apparatus and some also from the axoplasmic reticulum we examined wether carbohydrate macromolecules could be detected in the small and large dense core vesicles and in structures related to them. To this purpose superior cervical ganglia and irises from rabbit and cat and coeliac ganglia and their axons from dog were subjected to the chromaffin reaction to show the distribution of catecholamine-containing granules. Some material was also embedded in glycolmethacrylate (GMA) and stained with phosphotungstic acid (PTA) at low pH for the detection of carbohydrate macromolecules.The chromaffin reaction in the perikarya reveals mainly large dense core vesicles, but in the axon hillock, the axons and the terminals, the small dense core vesicles are more prominent. In the axons the small granules are sometimes seen inside a reticular network (fig. 1).

scholarly journals HID-1 controls formation of large dense core vesicles by influencing cargo sorting and trans-Golgi network acidification

2017 ◽  
Vol 28 (26) ◽  
pp. 3870-3880 ◽  
Author(s):  
Blake H. Hummer ◽  
Noah F. de Leeuw ◽  
Christian Burns ◽  
Lan Chen ◽  
Matthew S. Joens ◽  
...  
Keyword(s):  
Biochemical Properties ◽  
Neuroendocrine Cells ◽  
Dense Core ◽  
Core Formation ◽  
Dense Core Vesicles ◽  
Atpase Subunit ◽  
Trans Golgi Network ◽  
Large Dense Core Vesicles ◽  
Golgi Network ◽  
Cargo Sorting

Large dense core vesicles (LDCVs) mediate the regulated release of neuropeptides and peptide hormones. They form at the trans-Golgi network (TGN), where their soluble content aggregates to form a dense core, but the mechanisms controlling biogenesis are still not completely understood. Recent studies have implicated the peripheral membrane protein HID-1 in neuropeptide sorting and insulin secretion. Using CRISPR/Cas9, we generated HID-1 KO rat neuroendocrine cells, and we show that the absence of HID-1 results in specific defects in peptide hormone and monoamine storage and regulated secretion. Loss of HID-1 causes a reduction in the number of LDCVs and affects their morphology and biochemical properties, due to impaired cargo sorting and dense core formation. HID-1 KO cells also exhibit defects in TGN acidification together with mislocalization of the Golgi-enriched vacuolar H+-ATPase subunit isoform a2. We propose that HID-1 influences early steps in LDCV formation by controlling dense core formation at the TGN.

scholarly journals Synaptotagmin VII Is Targeted to Dense-core Vesicles and Regulates Their Ca2+-dependent Exocytosis in PC12 Cells

2004 ◽  
Vol 279 (50) ◽  
pp. 52677-52684 ◽  
Author(s):  
Mitsunori Fukuda ◽  
Eiko Kanno ◽  
Megumi Satoh ◽  
Chika Saegusa ◽  
Akitsugu Yamamoto
Keyword(s):  
Plasma Membrane ◽  
Neuropeptide Y ◽  
Cell Line ◽  
Pc12 Cells ◽  
Pc12 Cell ◽  
Small Interfering Rna ◽  
Dense Core ◽  
Dense Core Vesicles ◽  
Pc12 Cell Line ◽  
Interfering Rna

It has recently been proposed that synaptotagmin (Syt) VII functions as a plasma membrane Ca2+sensor for dense-core vesicle exocytosis in PC12 cells based on the results of transient overexpression studies using green fluorescent protein (GFP)-tagged Syt VII; however, the precise subcellular localization of Syt VII is still a matter of controversy (plasma membraneversussecretory granules). In this study we established a PC12 cell line “stably expressing” the Syt VII-GFP molecule and demonstrated by immunocytochemical and immunoelectron microscopic analyses that the Syt VII-GFP protein is localized on dense-core vesicles as well as in other intracellular membranous structures, such as thetrans-Golgi network and lysosomes. Syt VII-GFP forms a complex with endogenous Syts I and IX, but not with Syt IV, and it colocalize well with Syts I and IX in the cellular processes (where dense-core vesicles are accumulated) in the PC12 cell line. We further demonstrated by an N-terminal antibody-uptake experiment that Syt VII-GFP-containing dense-core vesicles undergo Ca2+-dependent exocytosis, the same as endogenous Syt IX-containing vesicles. Moreover, silencing of Syt VII-GFP with specific small interfering RNA dramatically reduced high KCl-dependent neuropeptide Y secretion from the stable PC12 cell line (∼60% of the control cells), whereas the same small interfering RNA had little effect on neuropeptide Y secretion from the wild-type PC12 cells (∼85–90% of the control cells), indicating that the level of endogenous expression of Syt VII molecules must be low. Our results indicate that the targeting of Syt VII-GFP molecules to specific membrane compartment(s) is affected by the transfection method (transient expressionversusstable expression) and suggested that Syt VII molecule on dense-core vesicles functions as a vesicular Ca2+sensor for exocytosis in endocrine cells.

scholarly journals Automated classification of synaptic vesicles in electron tomograms of C. elegans using machine learning

2018 ◽  
Author(s):  
Kristin Verena Kaltdorf ◽  
Maria Theiss ◽  
Sebastian Matthias Markert ◽  
Mei Zhen ◽  
Thomas Dandekar ◽  
...  
Keyword(s):  
Machine Learning ◽  
Synaptic Vesicles ◽  
Egg Laying ◽  
Dense Core ◽  
Dense Core Vesicles ◽  
Ground Truth Data ◽  
Neuronal Signaling ◽  
C Elegans ◽  
Morphological Criteria ◽  
Combine Machine

1.AbstractSynaptic vesicles (SVs) are a key component of neuronal signaling and fulfil different roles depending on their composition. In electron micrograms of neurites, two types of vesicles can be distinguished by morphological criteria, the classical “clear core” vesicles (CCV) and the typically larger “dense core” vesicles (DCV), with differences in electron density due to their diverse cargos. Compared to CCVs, the precise function of DCVs is less defined. DCVs are known to store neuropeptides, which function as neuronal messengers and modulators [1]. In C. elegans, they play a role in locomotion, dauer formation, egg-laying, and mechano- and chemosensation [2]. Another type of DCVs, also referred to as granulated vesicles, are known to transport Bassoon, Piccolo and further constituents of the presynaptic density in the center of the active zone (AZ), and therefore are important for synaptogenesis [3].To better understand the role of different types of SVs, we present here a new automated approach to classify vesicles. We combine machine learning with an extension of our previously developed vesicle segmentation workflow, the ImageJ macro 3D ART VeSElecT. With that we reliably distinguish CCVs and DCVs in electron tomograms of C. elegans NMJs using image-based features. Analysis of the underlying ground truth data shows an increased fraction of DCVs as well as a higher mean distance between DCVs and AZs in dauer larvae compared to young adult hermaphrodites. Our machine learning based tools are adaptable and can be applied to study properties of different synaptic vesicle pools in electron tomograms of diverse model organisms.2.Author summaryVesicles are important components of the cell, and synaptic vesicles are central for neuronal signaling. Two types of synaptic vesicles can be distinguished by electron microscopy: the classical “clear core” vesicles (CCVs) and the typically larger “dense core” vesicles (DCVs). The distinct appearance of vesicles is caused by their different cargos. To rapidly distinguish between both vesicle types, we present here a new automated approach to classify vesicles in electron tomograms. We combine machine learning with an extension of our previously developed vesicle segmentation workflow, an ImageJ macro, to reliably distinguish CCVs and DCVs using specific image-based features. The approach was trained and validated using data-sets that were hand curated by microscopy experts. Our technique can be transferred to more extensive comparisons in both stages as well as to other neurobiology questions regarding synaptic vesicles.

Sign in / Sign up

Export Citation Format

Share Document