skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: The Synaptic Vesicle Cycle Revisited: New Insights into the Modes and Mechanisms
Neurotransmission is sustained by endocytosis and refilling of synaptic vesicles (SVs) locally within the presynapse. Until recently, a consensus formed that after exocytosis, SVs are recovered by either fusion pore closure (kiss-and-run) or clathrin-mediated endocytosis directly from the plasma membrane. However, recent data have revealed that SV formation is more complex than previously envisaged. For example, two additional recycling pathways have been discovered, ultrafast endocytosis and activity-dependent bulk endocytosis, in which SVs are regenerated from the internalized membrane and synaptic endosomes. Furthermore, these diverse modes of endocytosis appear to influence both the molecular composition and subsequent physiological role of individual SVs. In addition, previously unknown complexity in SV refilling and reclustering has been revealed. This review presents a modern view of the SV life cycle and discusses how neuronal subtype, physiological temperature, and individual activity patterns can recruit different endocytic modes to generate new SVs and sculpt subsequent presynaptic performance.  more » « less
Award ID(s):
1727260
PAR ID:
10190503
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
The journal of neuroscience
Volume:
39
Issue:
42
ISSN:
0270-6474
Page Range / eLocation ID:
8209-8216
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract Functional and structural elements of synaptic plasticity are tightly coupled, as has been extensively shown for dendritic spines. Here, we interrogated structural features of presynaptic terminals in 3DEM reconstructions from CA1 hippocampal axons that had undergone control stimulation or theta-burst stimulation (TBS) to produce long-term potentiation (LTP). We reveal that after LTP induction, the synaptic vesicle (SV) cluster is less dense, and SVs are more dispersed. The distances between neighboring SVs are greater in less dense terminals and have more SV-associated volume. We characterized the changes to the SV cluster by measuring distances between neighboring SVs, distances to the active zone, and the dispersion of the SV cluster. Furthermore, we compared the distribution of SVs with randomized ones and provided evidence that SVs gained mobility after LTP induction. With a computational model, we can predict the increment of the diffusion coefficient of the SVs in the cluster. Moreover, using a machine learning approach, we identify presynaptic terminals that were potentiated after LTP induction. Lastly, we show that the local SV density is a volume-independent property under strong regulation. Altogether, these results provide evidence that the SV cluster is undergoing a transition during LTP. 
    more » « less
  2. Synaptic membrane-remodeling events such as endocytosis require force-generating actin assembly. The endocytic machinery that regulates these actin and membrane dynamics localizes at high concentrations to large areas of the presynaptic membrane, but actin assembly and productive endocytosis are far more restricted in space and time. Here we describe a mechanism whereby autoinhibition clamps the presynaptic endocytic machinery to limit actin assembly to discrete functional events. We found that collective interactions between theDrosophilaendocytic proteins Nwk/FCHSD2, Dap160/intersectin, and WASp relieve Nwk autoinhibition and promote robust membrane-coupled actin assembly in vitro. Using automated particle tracking to quantify synaptic actin dynamics in vivo, we discovered that Nwk-Dap160 interactions constrain spurious assembly of WASp-dependent actin structures. These interactions also promote synaptic endocytosis, suggesting that autoinhibition both clamps and primes the synaptic endocytic machinery, thereby constraining actin assembly to drive productive membrane remodeling in response to physiological cues. 
    more » « less
  3. Abstract Chromatin remodeling proteins of the chromodomain DNA-binding protein family, CHD7 and CHD8, mediate early neurodevelopmental events including neural migration and differentiation. As such, mutations in either protein can lead to neurodevelopmental disorders. How chromatin remodeling proteins influence the activity of mature synapses, however, is relatively unexplored. A critical feature of mature neurons is well-regulated endocytosis, which is vital for synaptic function to recycle membrane and synaptic proteins enabling the continued release of synaptic vesicles. Here we show that Kismet, theDrosophilahomolog of CHD7 and CHD8, regulates endocytosis. Kismet positively influenced transcript levels and bound todap160andendophilin Btranscription start sites and promoters in whole nervous systems and influenced the synaptic localization of Dynamin/Shibire. In addition,kismetmutants exhibit reduced VGLUT, a synaptic vesicle marker, at stimulated but not resting synapses and reduced levels of synaptic Rab11. Endocytosis is restored atkismetmutant synapses by pharmacologically inhibiting the function of histone deacetyltransferases (HDACs). These data suggest that HDAC activity may oppose Kismet to promote synaptic vesicle endocytosis. A deeper understanding of how CHD proteins regulate the function of mature neurons will help better understand neurodevelopmental disorders. 
    more » « less
  4. Abstract Background Structural variants (SVs) play a causal role in numerous diseases but are difficult to detect and accurately genotype (determine zygosity) in whole-genome next-generation sequencing data. SV genotypers that assume that the aligned sequencing data uniformly reflect the underlying SV or use existing SV call sets as training data can only partially account for variant and sample-specific biases. Results We introduce NPSV, a machine learning–based approach for genotyping previously discovered SVs that uses next-generation sequencing simulation to model the combined effects of the genomic region, sequencer, and alignment pipeline on the observed SV evidence. We evaluate NPSV alongside existing SV genotypers on multiple benchmark call sets. We show that NPSV consistently achieves or exceeds state-of-the-art genotyping accuracy across SV call sets, samples, and variant types. NPSV can specifically identify putative de novo SVs in a trio context and is robust to offset SV breakpoints. Conclusions Growing SV databases and the increasing availability of SV calls from long-read sequencing make stand-alone genotyping of previously identified SVs an increasingly important component of genome analyses. By treating potential biases as a “black box” that can be simulated, NPSV provides a framework for accurately genotyping a broad range of SVs in both targeted and genome-scale applications. 
    more » « less
  5. Abstract Advances in whole-genome sequencing (WGS) promise to enable the accurate and comprehensive structural variant (SV) discovery. Dissecting SVs from WGS data presents a substantial number of challenges and a plethora of SV detection methods have been developed. Currently, evidence that investigators can use to select appropriate SV detection tools is lacking. In this article, we have evaluated the performance of SV detection tools on mouse and human WGS data using a comprehensive polymerase chain reaction-confirmed gold standard set of SVs and the genome-in-a-bottle variant set, respectively. In contrast to the previous benchmarking studies, our gold standard dataset included a complete set of SVs allowing us to report both precision and sensitivity rates of the SV detection methods. Our study investigates the ability of the methods to detect deletions, thus providing an optimistic estimate of SV detection performance as the SV detection methods that fail to detect deletions are likely to miss more complex SVs. We found that SV detection tools varied widely in their performance, with several methods providing a good balance between sensitivity and precision. Additionally, we have determined the SV callers best suited for low- and ultralow-pass sequencing data as well as for different deletion length categories. 
    more » « less