TITLE: Quantitative analyses of the ultrastructural features of dopaminergic axon terminals. Protocol #2: Acquisition and analysis of electron microscopy images
AUTHORS: Natalie M Doig, Max Larsson, Peter J Magill

[DESCRIPTION]
The release of dopamine from axons is critical for normative brain function and behaviour. Impaired or otherwise inappropriate dopamine release often correlates with changes in the ultrastructure of dopamine neuron axons that can assessed with electron microscopy. Here, we provide two protocols that can be used serially to, first, help the user process animal brain tissue for electron microscopy and, secondly, help the user undertake quantitative analyses of the ultrastructural features of dopaminergic axon terminals in the brain. 

This Protocol #2 details how to examine and image pre-prepared ultrathin sections of brain tissue using a transmission electron microscope, and then how to analyse the digital images.

In this protocol, digital electron microscope images are analysed. We describe a method involving the use of freely available open-source software; ImageJ (Rueden et al., 2017; Schindelin et al., 2012) and custom designed plugins for electron microscopic image analysis, PointDensity and PointDensitySyn (Anwar et al., 2011; Connor-Robson et al., 2019; Janezic et al., 2013;Kosillo et al., 2019; Larsson et al., 2015). This software allows the user to analyse electron micrographs and obtain data on multiple variables including axon terminal size, incidence of synapses, number and density of neurotransmitter vesicles, distance of vesicles to the cell membrane, distance of vesicles to the active zone (if present) and the inter-vesicle distance as an indicator of clustering (See Figure 1).

  
The partner Protocol #1 describes how to prepare brain tissue, carry out pre-embedding immunohistochemistry for tyrosine hydroxylase as a marker of dopaminergic axons, and then make tissue sections ready for electron microscopy.

Protocol #1 and #2 are part of the collection "Quantitative analyses of the ultrastructural features of dopaminergic axon terminals". 

[BEFORE_START]
The analysis method presented in this protocol requires the user to manually delineate and register ultrastructural features in electron microscope images. It is likely that you will become more proficient at delineating axon terminals and marking vesicles with practice over time. It is important to account for this effect in your analysis. For example, if you were to begin your analysis with an animal in your control group, you may falsely get the impression that there are fewer vesicles in this dataset, as compared subsequent datasets obtained from other animals, simply because you got better at marking vesicles over time. One way to mitigate is to ‘train’ yourself with a random set of images before starting your intended analyses, and then to randomize the experimental animal you begin with, as well as the order in which you subsequently analyse data from additional animals. As the analysed images are saved as copies of the original micrographs with the recorded coordinates visible, it is also possible to go back and re-evaluate the accuracy of the analysis at a later time. All analyses should be performed blinded wherever possible.

[STEPS]
SECTION: Examination of Sections in the Electron Microscope
1. Sampling: One of the challenges for EM is to design a sampling strategy to ensure your data sample is representative, reflecting the true distribution/occurrence of a particular structure, and robust enough to detect effects of e.g., experimental manipulations.

The striatum is so densely packed with dopaminergic terminals that one could obtain hundreds of images from a very small volume of tissue, but this would not be representative of the striatum as a whole and could easily bias your data. Here, we describe a sampling strategy based on previous work (Kosillo et al., 2019). An example sampling strategy is laid out in Figure 2. 

If you are examining dopaminergic axon terminals in the dorsolateral striatum, we would recommend re-embedding tissue from at least two sections at different rostrocaudal planes per animal. From each of these sections, you can re-embed tissue from at least two regions of interest, making two blocks. From each block, you would then sample from at least two grids, and then from each grid take multiple images from at least two ultrathin sections (Fig 2). 

This is a guideline; the optimum strategy (where possible) would be to carry out a pilot study to acquire some initial data so that you can perform a power analysis and estimate the sample size required.

  
SECTION: Examination of Sections in the Electron Microscope
2. Image Acquisition: This protocol describes a random systematic sampling strategy to acquire digital images for analysis using a transmission electron microscope (TEM) fitted with a digital camera.
SECTION: Examination of Sections in the Electron Microscope
2.1. Place grids into the specimen holder and insert into electron microscope. 
SECTION: Examination of Sections in the Electron Microscope
2.2. Image the whole grid and choose 2 sections to sample from. Pick sections that are as distant as possible from each other (opposite ends of the ribbon) or examine different regions on the 2 different sections; this will decrease the likelihood of imaging the same terminals in both sections. 
SECTION: Examination of Sections in the Electron Microscope
2.3. Determine a magnification at which you can locate immunolabelled axon profiles, but you cannot see individual synapses, this is your ‘searching magnification’. Define a criterion for these ‘immunopositive’ structures depending on the level of background labelling, e.g., a minimum of, for example, 5 silver-enhanced gold particles per profile. 
SECTION: Examination of Sections in the Electron Microscope
2.4. Immunogold labelling has limited penetration into the tissue but is also non-specific at the tissue surface. In order to avoid imaging non-specific labelling, locate the surface of the tissue (where tissue meets the covering resin) and move a set distance (e.g., 2-5 µm) from there before starting with image acquisition. 
SECTION: Examination of Sections in the Electron Microscope
2.5. Once at a safe distance from the surface, pick a random starting point and move in a straight line until you locate an immunopositive axon terminal, increase the magnification so that it is possible to visualize synapses and vesicles and take an image the profile. When imaging, keep your immunopositive terminal in the centre of the frame and make sure you do not crop off any of the plasma membrane. 
SECTION: Examination of Sections in the Electron Microscope
2.6. Decrease to your searching magnification and move in a straight line until you locate the next immunopositive terminal, increase your magnification and image.
SECTION: Examination of Sections in the Electron Microscope
2.7. Repeat this until you have at least the required number of images from that section.
SECTION: Examination of Sections in the Electron Microscope
2.8. Move to the second ultrathin section on the grid that you have chosen to image from and repeat the procedure. 
SECTION: Examination of Sections in the Electron Microscope
2.9. Once you have enough images from the sections on that grid, move to the next grid and repeat the steps above. 
SECTION: Analysis of Electron Micrographs
3. Software: All the software for electron micrograph analysis described here is open-source and freely available. 

Each software tool is composed of two components: 
Java plugin for ImageJ (or its Fiji distribution (Schindelin et al., 2012)
A program written in Python. 

As such, the software can run on any platform where ImageJ and Python are available, including Windows, macOS and Linux. 

Installation of the ImageJ plugin entails downloading a .jar file, placing it in the plugins folder of ImageJ and restarting ImageJ. A Windows executable is available for the Python component, whereas for other platforms the program is run from the source code via the Python interpreter. 

See https://liu.se/medfak/forskning/larsson-max/software or https://github.com/maxdl for download links and more detailed installation instructions, and (Larsson et al., 2015) for general usage. 
SECTION: Analysis of Electron Micrographs
4. Image Analysis: The first stage of the image analysis entails delineating the dopaminergic axon profiles, vesicles, and any synapses in ImageJ with the custom-built plugins. The second part of the analysis is to take the co-ordinates generated from the image files and to compute the various measurements of interest, such as axon terminal cross-sectional area, inter-vesicle distances, density of vesicles, distances of vesicles to profile borders etc. (see Fig. 1). All dopaminergic axon profiles are analysed with the PointDensity tools; and any profiles that are forming synapses can be analysed with the PointDensitySyntools. The order in which you analyse the images should be considered before beginning analyses (see “Before Start”).
SECTION: Analysis of Electron Micrographs
5. Analysis of non-synaptic axon profiles:
 

SECTION: Analysis of Electron Micrographs
5.1. Open the first EM image for analysis in ImageJ and load the PointDensity plugin.
SECTION: Analysis of Electron Micrographs
5.2. Trace the plasma membrane of the immunopositive axon profile using the ImageJ polygon tool. Close the border. Designate the selection as ‘Profile border’ in the PointDensity panel (See Figure 3). 
SECTION: Analysis of Electron Micrographs
5.3. Place a point marker in the centre of each vesicle using the ImageJ multi-point tool. Vesicles should be counted if at least 50% of the vesicle membrane is visible. Define the selection as ‘Particles’ on the PointDensity panel (Fig 3). 
SECTION: Analysis of Electron Micrographs
5.4. Carefully name and save all data. 
SECTION: Analysis of Electron Micrographs
6. Analysis of synapse-forming axon profiles: All axon terminals that are forming synapses can be analysed with the PointDensitySyn tool. Dopaminergic terminals in the striatum normally form symmetric synapses (Gray’s type II) which are characterized by the presence of presynaptic and postsynaptic membrane specializations of similar thickness, a widened synaptic cleft and cleft material.
 

SECTION: Analysis of Electron Micrographs
6.1. Open EM image in ImageJ and load the PointDensitySyn plugin.
SECTION: Analysis of Electron Micrographs
6.2. As before, draw around and define the profile border and then mark and define all vesicles (See Figure 4). 
SECTION: Analysis of Electron Micrographs
6.3. Trace the length of the active zone(s) with the ImageJ segmented line tool. The active zone is defined as the length of plasma membrane directly opposing the postsynaptic density, on the presynaptic side of the synaptic cleft (Fig 4).
SECTION: Analysis of Electron Micrographs
6.4. Name and save all data. 
SECTION: Analysis of Electron Micrographs
7. Processing coordinate files: To compute the values of interest from the co-ordinates saved for each analyzed EM image, the text files need to be processed with the second (Python) component (Larsson et al., 2015). 
SECTION: Analysis of Electron Micrographs
7.1. Once all images have been analysed in ImageJ, with either the PointDensity or PointDensitySyn plugins you can run the related Python component of the tool, i.e., PointDensity or PointDensitySyn. 
SECTION: Analysis of Electron Micrographs
7.2. Add all profile coordinate files to the input file list, check your options, and run (Larsson et al., 2015).
SECTION: Analysis of Electron Micrographs
7.3. Values can be exported to Excel or tabulated text files depending on your preference.