1Department of Cell Biology and Neuroscience, Rutgers University, 2Graduate Program in Biomedical Engineering, Rutgers University
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Kutzing, M. K., Langhammer, C. G., Luo, V., Lakdawala, H., Firestein, B. L. Automated Sholl Analysis of Digitized Neuronal Morphology at Multiple Scales. J. Vis. Exp. (45), e2354, doi:10.3791/2354 (2010).
Neuronal morphology plays a significant role in determining how neurons function and communicate1-3. Specifically, it affects the ability of neurons to receive inputs from other cells2 and contributes to the propagation of action potentials4,5. The morphology of the neurites also affects how information is processed. The diversity of dendrite morphologies facilitate local and long range signaling and allow individual neurons or groups of neurons to carry out specialized functions within the neuronal network6,7. Alterations in dendrite morphology, including fragmentation of dendrites and changes in branching patterns, have been observed in a number of disease states, including Alzheimer's disease8, schizophrenia9,10, and mental retardation11. The ability to both understand the factors that shape dendrite morphologies and to identify changes in dendrite morphologies is essential in the understanding of nervous system function and dysfunction.
Neurite morphology is often analyzed by Sholl analysis and by counting the number of neurites and the number of branch tips. This analysis is generally applied to dendrites, but it can also be applied to axons. Performing this analysis by hand is both time consuming and inevitably introduces variability due to experimenter bias and inconsistency. The Bonfire program is a semi-automated approach to the analysis of dendrite and axon morphology that builds upon available open-source morphological analysis tools. Our program enables the detection of local changes in dendrite and axon branching behaviors by performing Sholl analysis on subregions of the neuritic arbor. For example, Sholl analysis is performed on both the neuron as a whole as well as on each subset of processes (primary, secondary, terminal, root, etc.) Dendrite and axon patterning is influenced by a number of intracellular and extracellular factors, many acting locally. Thus, the resulting arbor morphology is a result of specific processes acting on specific neurites, making it necessary to perform morphological analysis on a smaller scale in order to observe these local variations12.
The Bonfire program requires the use of two open-source analysis tools, the NeuronJ plugin to ImageJ and NeuronStudio. Neurons are traced in ImageJ, and NeuronStudio is used to define the connectivity between neurites. Bonfire contains a number of custom scripts written in MATLAB (MathWorks) that are used to convert the data into the appropriate format for further analysis, check for user errors, and ultimately perform Sholl analysis. Finally, data are exported into Excel for statistical analysis. A flow chart of the Bonfire program is shown in Figure 1.
1. Before You Begin:
1) E18 rat dissection:
Standard dissection methods of E18 hippocampal neurons have previously been described13. In order to use the Bonfire program to analyze the morphological characteristics of the neurites, 8 bit .tif images of individual neurons must be obtained. This can be accomplished in a number of ways depending on the experimental protocol you are following. Neurons can be plated at a low enough density so that single neurons appear in the microscope field. Alternatively, to image individual neurons that are grown in a dense culture, neurons can be transfected using a variety of transfection methods with a plasmid encoding a fluorescent protein.
2) Software Requirements and Installation:
3) Image Resolution Adjustment:
You will need to adjust the Bonfire program based on the image resolution of the images that you wish to analyze. In the bonfire_parameters portion of the Bonfire program, replace the current value for the variable pix_conv with the value of the image resolution (μm/pixel) of your images.
2. File Structure:
In order for Bonfire to analyze your data, the files must be organized in this specific structure (Figure 2). You will have:
3. Tracing Neurons in NeuronJ:
4. Use Bonfire to Build Preliminary .swc Files from NeuronJ Data:
5. Use NeuronStudio to Finalize .swc Files:
6. Use 'bonfire' to Extract Morphological Data from .swc Files:
7. Use 'bonfire_results' to View the Data:
8. Use 'bonfire_export' to Export Data to Excel:
9. Representative Results:
An example of the data generated by the Bonfire program on a data set containing two conditions is shown in Figure 3. In this example, Condition 1 neurons contain more neurites distal to the cell body. This phenomenon can be observed in the example images (Figure 3B) as well as in the Sholl curve of the total dendritic arbor (Figure 3A) and in the graph of the number of terminal points (Figure 3C). Additionally, because the Bonfire program also performs Sholl analysis on subregions of the images, we are able to identify more specifically the identity of the neurites that have increased. Both the total number of intersections of 3rd order or greater neurites (Figure 3F) and the total number of both intermediary and terminal neurites (Figure 3G) are increased distal to the cell body. These trends can also be observed in Figures 3D and 3E.
Figure 1: Flow chart of the Bonfire program. Neurons are traced using ImageJ. The data are then exported and converted by the Bonfire program into preliminary .swc files. NeuronStudio is used to define the connectivity of the neurites. Bonfire checks for errors and then calculates Sholl curves, the number of primary, secondary, and higher order neurites, and the number of branch points and neurite tips. Finally, the data are exported to Excel for statistical analysis.
Figure 2: File structure required for Bonfire analysis. The file structure must match this or the program will not run correctly. The names of the folders and files and the quantity of the folders and files can be changed.
Figure 3: Example output data from Bonfire program. A) Total Sholl curves. B) Example inverted images of both conditions. C) Average number of branch points and terminal points/cell. D) Average number of processes/cell for primary, secondary, and tertiary or greater neurites. E) Average number of processes/cell for root, intermediate, and terminal neurites. F) Segment identity-specific Sholl analysis curves. Segments are grouped as primary, secondary, or tertiary or greater. G) Segment identity-specific Sholl analysis curves. Segments are grouped as root segments, intermediate segments, or terminal segments.
The Bonfire program is a semi-automated program for the analysis of dendrite and axon morphology. It greatly increases the efficiency and accuracy of Sholl analysis over performing the analysis manually. In addition, the Bonfire program saves the data at every step of the process, making it possible to audit the data and to verify the accuracy of the analysis. Therefore, the task of data analysis can be distributed to numerous individuals without compromising accuracy. Lastly, by performing the analysis on subregions of the images, the program is able to identify local changes in branching that are missed when Sholl analysis is run only on the entire dendrite or axon arbor. Our program is able to identify how specific subsets of neurites are arranged in reference to the cell body. As a result, the branching patterns in the images are well- represented by the data that are generated by the Bonfire program.
The authors declare no competing interests. The funding agencies had no scientific role in the development of Bonfire.
This work was supported in part by a Busch Biomedical Grant, NSF grant IBN-0548543, NSF grant IBN-0919747, March of Dimes Foundation Grant 1-FY04-107, March of Dimes Foundation Grant 1-FY08-464 (to B.L.F). M.K.K. and C.G.L. were supported by NIH Biotechnology Training Grant T32 GM008339-20, and C.G.L. was also supported by a NJ Commission on Spinal Cord Research Predoctoral Fellowship 08-2941-SCR-E-0.