3D Reconstruction and Analysis of Thin Subcellular Neuronal Structures using Focused-Ion Beam Scanning Electron Microscopy Data

Summary

A flexible methodological pipeline to identify, visualize, and quantify thin subcellular neuronal processes within focused ion beam scanning electron microscopy image volumes using user-friendly open-source software packages.

Abstract

Recent advances in scanning electron microscope technologies now permit the rapid three-dimensional (3D) analysis of ultrathin subcellular processes. Here, a methodological pipeline is presented to identify, visualize, and analyze thin neuronal processes, such as those that project into the presynaptic boutons of other neurons (termed 'spinules'). Using freely available software packages, this protocol demonstrates how to use a decision tree to identify common neuronal subcellular structures using morphological criteria within focused ion beam scanning electron microscopy (FIB-SEM) image volumes, with particular attention on identifying a diversity of spinules projecting into presynaptic boutons. In particular, this protocol describes how to trace spinules within neuronal synapses to produce 3D reconstructions of these thin subcellular projections, their parent neurites, and postsynaptic partners. Additionally, the protocol includes a list of freely available open-source software programs for analyzing FIB-SEM data and offers tips (e.g., smoothing, lighting) toward improving 3D reconstructions for visualization and publication. This adaptable protocol offers an entry point into the rapid nanoscale analysis of subcellular structures within FIB-SEM image volumes.

Introduction

Investigations into the structure-function relationships of nanometer-thin subcellular components often benefit from 3D visualization and analysis¹. However, serial section transmission electron microscopy studies have been temporally and spatially constrained by the necessity to use a diamond knife to cut and align hundreds to thousands of ≥40 nm serial ultrathin sections. These constraints have limited the ability to sample and effectively analyze thin (<40 nm in diameter) subcellular structures, and the necessity to become proficient at ultrathin serial sectioning has hampered the application of 3D structural analyses

Protocol

1. Image volume data and subcellular object size: considerations and registration

1. Obtain a quality FIB-SEM image volume of the area of interest containing the subcellular objects of interest.
   NOTE: This protocol uses segments of a FIB-SEM image volume from late adolescent ferret primary visual cortex (24.2 x 16.2 x 2.4 µm, 4 nm isotropic voxels), and a freely accessible FIB-SEM volume from adult rat CA1 hippocampus (10.2 x 7.7 x 5.3 µm; 5 nm isotropic voxels) made available by the Knott laboratory (https://www.epfl.ch/labs/cvlab/data/data-em/). It is critical to prepare tissue blocks for FIB-SEM using a protocol that preserves ultrastructu....

Results

Quantifying the percentage of synaptic spinules within the excitatory presynaptic bouton population in ferret primary visual cortex
Although spinule-like protrusions from neurites into excitatory presynaptic boutons have been observed for decades^19,26, their potential importance for synaptic function has remained obscure. These experiments were designed to determine the proportion of excitatory presynaptic boutons containing spinules througho.......

Discussion

This FIB-SEM image volume analysis pipeline can produce reliable 3D reconstructions and quantitative measurements of thin subcellular structures. While current semi-automated techniques using deep neural network and segmentation algorithms can increase the speed and efficiency in reconstructing cellular structures possessing relatively high membrane contrast within large image volumes³³, many subcellular structures (e.g., spinules, smooth endoplasmic reticula, endosomes) will remain difficult to r.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Fiji (ImageJ)			https://imagej.net/software/fiji/downloads
Reconstruct			https://synapseweb.clm.utexas.edu/software-0
Blender	Blender Foundation		https:/www.blender.org