» Articles » PMID: 38645671

Unambiguous Identification of Asymmetric and Symmetric Synapses Using Volume Electron Microscopy

Overview
Journal Front Neuroanat
Date 2024 Apr 22
PMID 38645671
Authors
Affiliations
Soon will be listed here.
Abstract

The brain contains thousands of millions of synapses, exhibiting diverse structural, molecular, and functional characteristics. However, synapses can be classified into two primary morphological types: Gray's type I and type II, corresponding to Colonnier's asymmetric (AS) and symmetric (SS) synapses, respectively. AS and SS have a thick and thin postsynaptic density, respectively. In the cerebral cortex, since most AS are excitatory (glutamatergic), and SS are inhibitory (GABAergic), determining the distribution, size, density, and proportion of the two major cortical types of synapses is critical, not only to better understand synaptic organization in terms of connectivity, but also from a functional perspective. However, several technical challenges complicate the study of synapses. Potassium ferrocyanide has been utilized in recent volume electron microscope studies to enhance electron density in cellular membranes. However, identifying synaptic junctions, especially SS, becomes more challenging as the postsynaptic densities become thinner with increasing concentrations of potassium ferrocyanide. Here we describe a protocol employing Focused Ion Beam Milling and Scanning Electron Microscopy for studying brain tissue. The focus is on the unequivocal identification of AS and SS types. To validate SS observed using this protocol as GABAergic, experiments with immunocytochemistry for the vesicular GABA transporter were conducted on fixed mouse brain tissue sections. This material was processed with different concentrations of potassium ferrocyanide, aiming to determine its optimal concentration. We demonstrate that using a low concentration of potassium ferrocyanide (0.1%) improves membrane visualization while allowing unequivocal identification of synapses as AS or SS.

Citing Articles

Volume electron microscopy reveals unique laminar synaptic characteristics in the human entorhinal cortex.

Plaza-Alonso S, Cano-Astorga N, DeFelipe J, Alonso-Nanclares L Elife. 2025; 14.

PMID: 39882848 PMC: 11867616. DOI: 10.7554/eLife.96144.


Data-driven synapse classification reveals a logic of glutamate receptor diversity.

Micheva K, Simhal A, Schardt J, Smith S, Weinberg R, Owen S bioRxiv. 2024; .

PMID: 39713368 PMC: 11661198. DOI: 10.1101/2024.12.11.628056.


Volume electron microscopy analysis of synapses in primary regions of the human cerebral cortex.

Cano-Astorga N, Plaza-Alonso S, DeFelipe J, Alonso-Nanclares L Cereb Cortex. 2024; 34(8.

PMID: 39106175 PMC: 11302151. DOI: 10.1093/cercor/bhae312.


Tracing nerve fibers with volume electron microscopy to quantitatively analyze brain connectivity.

Turegano-Lopez M, de Las Pozas F, Santuy A, Rodriguez J, DeFelipe J, Merchan-Perez A Commun Biol. 2024; 7(1):796.

PMID: 38951162 PMC: 11217374. DOI: 10.1038/s42003-024-06491-0.

References
1.
Gray E . Electron microscopy of excitatory and inhibitory synapses: a brief review. Prog Brain Res. 1969; 31:141-55. DOI: 10.1016/S0079-6123(08)63235-5. View

2.
Peters A, Sethares C, Luebke J . Synapses are lost during aging in the primate prefrontal cortex. Neuroscience. 2008; 152(4):970-81. PMC: 2441531. DOI: 10.1016/j.neuroscience.2007.07.014. View

3.
Harris K, Spacek J, Bell M, Parker P, Lindsey L, Baden A . A resource from 3D electron microscopy of hippocampal neuropil for user training and tool development. Sci Data. 2015; 2:150046. PMC: 4555877. DOI: 10.1038/sdata.2015.46. View

4.
Mayhew T . How to count synapses unbiasedly and efficiently at the ultrastructural level: proposal for a standard sampling and counting protocol. J Neurocytol. 1996; 25(12):793-804. DOI: 10.1007/BF02284842. View

5.
Cali C, Wawrzyniak M, Becker C, Maco B, Cantoni M, Jorstad A . The effects of aging on neuropil structure in mouse somatosensory cortex-A 3D electron microscopy analysis of layer 1. PLoS One. 2018; 13(7):e0198131. PMC: 6028106. DOI: 10.1371/journal.pone.0198131. View