Summary

Quantitative Analysis of Neuronal Dendritic Arborization Complexity in Drosophila

Published: January 07, 2019
doi:

Summary

This protocol focuses on quantitative analysis of neuronal dendritic arborization complexity (NDAC) in Drosophila, which can be used for studies of dendritic morphogenesis.

Abstract

Dendrites are the branched projections of a neuron, and dendritic morphology reflects synaptic organization during the development of the nervous system. Drosophila larval neuronal dendritic arborization (da) is an ideal model for studying morphogenesis of neural dendrites and gene function in the development of nervous system. There are four classes of da neurons. Class IV is the most complex with a branching pattern that covers almost the entire area of the larval body wall. We have previously characterized the effect of silencing the Drosophila ortholog of SOX5 on class IV neuronal dendritic arborization complexity (NDAC) using four parameters: the length of dendrites, the surface area of dendrite coverage, the total number of branches, and the branching structure. This protocol presents the workflow of NDAC quantitative analysis, consisting of larval dissection, confocal microscopy, and image analysis procedures using ImageJ software. Further insight into da neuronal development and its underlying mechanisms will improve the understanding of neuronal function and provide clues about the fundamental causes of neurological and neurodevelopmental disorders.

Introduction

Dendrites, which are the branched projections of a neuron, cover the field that encompasses the neuron's sensory and synaptic inputs from other neurons1,2. Dendrites are an important component of synapse formation and play a critical role in integrating synaptic inputs, as well as propagating the electrochemical stimulation in a neuron. Dendritic arborization (da) is a process by which neurons form new dendritic trees and branches to create new synapses. The development and morphology of da, such as branch density and grouping patterns, result from multi-step biological processes and are highly correlated to neuronal function. The goal of this protocol is to provide a method for quantitative analysis of neuronal dendritric arborization complexity in Drosophila.

The complexity of dendrites determines the synaptic types, connectivity, and inputs from partner neurons. Branching patterns and the density of dendrites are involved in processing the signals that converge onto the dendritic field3,4. Dendrites have the flexibility for adjustment in development. For instance, synaptic signaling has an effect on dendrite organization in the somatosensory neuron during the developmental phase and in the mature nervous system5. The establishment of neuronal connectivity relies on the morphogenesis and maturation of dendrites. Malformation of dendrites is associated with impaired neuronal function. Studies have shown that the abnormality of da neuron morphogenesis might contribute to the etiologies of multiple neurodegenerative diseases, including Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and Lou Gehrig's disease/Amyotrophic lateral sclerosis (ALS)6,7,8. Synaptic alterations appear in the early stage of AD, in concert with the decline and impairment of neuron function7,8. However, the specifics of how dendrite pathology contributes to pathogenesis in these neurodegenerative diseases remains elusive.

The development of dendrites is regulated by genes that encode a complex network of regulators, such as the Wnt family of proteins9,10, transcription factors, and ligands on cell surface receptors11,12. Drosophila da neurons consist of four classes (Class I, II III, IV), of which class IV da neurons have the most complex branching patterns and have been employed as a powerful experimental system for better understanding morphogenesis13,14. During early morphogenesis, overexpression and/or RNAi silencing of genes in class IV da neurons result in changes in branching patterns and dendrite pruning13. It is important to develop a practical method for quantitative analysis of the neuronal dendritic arborization.

We have previously shown that silencing of the Drosophila ortholog of SOX5, Sox102F, led to shorter dendrites of da neurons and reduced complexity in class IV da neurons15. Here, we present the procedure of quantitative analysis for the neuronal dendritic arborization complexity (NDAC) in Drosophila. This protocol, adapted from the previous described methodology, provides a brief method to assay the development of da sensory neurons. It illustrates the robust image labeling and the da neuron in the third instar larval body wall16,17,18,19. It is a valuable protocol for researchers who wish to investigate the NDAC and developmental differences in vivo.

Protocol

1. Experimental Preparation

  1. Prepare the following reagents: Dulbecco's phosphate buffered saline (PBS); Triton X-100; 0.2% PBST (PBS + 0.2% Triton X-100); 32% paraformaldehyde (PFA), diluted into 4% before use; silicone elastomer base and curing agent; antifade mounting medium (e.g., ProLong Gold); and fingernail polish.
  2. Prepare the following equipment: dissection microscope, two sharp forceps and a pair of scissors for microdissection, a number of pins for microdissection, a Petri dish for making the dissection dish, microscope slides and coverslips, a confocal microscope, and a computer with Fiji ImageJ software installed.

2. Larvae Collection

  1. Mate UAS-Sox102F-RNAi flies with UAS-GFP, ppk-GAL4, or W1118 wild type flies, respectively. Culture flies in standard conditions at 25 °C.
  2. In ~5 – 6 days, collect the third instar larvae of UAS-Sox102F-RNAi/ ppk-GAL4, UAS-GFP or UAS-GFP, and ppk-GAL4 /+ control carefully with forceps for dissection.

3. Dissection of Larvae

NOTE: All procedures in this section are operated under a microdissection microscope. The magnification is up to the investigators. Try to adjust to the optimal sight view. ~4 – 6X magnification is recommended.

  1. Place a larva on a dissection dish made of silicone elastomer base and a tissue culture Petri dish.
  2. Pin the larva mouth hook to allow the dorsal side to face up, and then pin the tail of larva. Place the dorsal side in the middle as much as possible to expose the midline, which will be the open-up marker.
  3. Add 200 µL of PBS to the larva to maintain body moisture.
  4. Make a cut with a pair of scissors along the dorsal midline between the two tracheas, from caudal to rostral. Make a small cut at each of the four corners of the larva body.
  5. Place a pin at each of the four corners of the body so the body lies flat.
  6. Fix the larva body wall in 4% PFA for 25 min at room temperature.
  7. Wash in PBST for 5 min. Repeat twice more.
  8. Remove the pins from the tissue. Then transfer the tissue onto a glass slide, cover with antifade mounting medium, and mount with a cover slip. Air dry for 1 h and seal the edges with fingernail polish.

4. Imaging Processing

NOTE: Images were taken using an inverted confocal microscope system. The user can photograph the sample using a 20X objective (recommended).

  1. Capture Z-series images. Open the "Capture Z-series" dialog box in the confocal microscope software. Determine the range for capturing the Z series images.
    1. Click the "Top and Bottom" button. Determine the top and bottom position and input the values to "Bottom:" and "Top:" boxes. Set the "Step" in "Capture Z-series" dialog box as 0.5 µm. Then click the "Run now" button to acquire the Z-series images.
  2. Save the obtained images as *.tiff or *.nd2 files.
  3. Store the slides in a dark holder at 4 °C after imaging.

5. Dendrite Evaluation

Note: GFP protein was co-overexpressed in UAS-GFP and ppk-GAL4 flies in the da neurons for GFP fluorescence imaging analysis. The length, branching, and structure of da neurons in the third instar larvae were quantified. Analysis parameters include length of dendrites (µm), surface area (µm2), total number of branches, and branching structure (%). Figure 1 shows the analysis parameters in detail.

  1. Length of Dendrites
    NOTE: The length of dendrites is the sum of all dendrites labeled in tracer plugin.
    1. Setup and run Fiji ImageJ (https://fiji.sc/)20 software. Then split images into separate channels, if there are several channels of images.
      ​NOTE: The image in this protocol only has one channel of GFP.
    2. Run "Image | Stacks | Z project" to get a Z projection; a new window will appear with the name 'Z-projection.' Click "max intensity" for projection type, and organize numbers between start slice and stop slice depending upon individual preferences. Click "OK." A Z-projection image will appear presenting the dendrite projection clearly.
    3. Trace the neurites.
      1. Select "Plugins | Segmentation | Simple Neurites Tracer" in the window to trace the dendrites. Find the neuron soma, and then click one point at a dendrite starting from the cell body, and another point at the tip of this dendrite.
        NOTE: The program will connect the two points with a blue line.
      2. Press "Y" in the plug-in window if the path is clear; the dendrite path is traced until the endpoints of the selected path in the visible images. Click "complete path" on the same plugin window; the segment is completed (Figure 2).
        NOTE: Some dendrites ended farther from the starting points, in which the pathway was divided into smaller segments. The segments were combined to provide a complete path for the tracer.
    4. After a path is completed, go back to a new point where the branches are. The new path can be built on; the "All paths" window box will show the length values of all the paths (Figure 3). Save the tracing file, and continue with unfinished traces as shown in Figure 2.
    5. Export the dendrite length data by clicking, "File | Export as *.cvs" in the 'Plugin' window. Then sum up all the path lengths, and export the data to a data analysis/spreadsheet software. (Figure 3).
  2. Surface Area of the da Neurons
    1. Select the Freehand drawing tool in the 'Fiji ImageJ' window. Trace the path, and then connect the endpoints. From the 'Analyze' menu, select "Set Measurements | Area." Click "measure" from the 'Analyze' menu. The result appears in a new box with the value for the area selected (Figure 4). Copy it to the data analysis software.
  3. Total Number of Branches and Branching Structure of the da Neurons
    1. Calculate the total number of branches by opening "Analysis" and then "Render | Analyze Skeletonized Paths" in the plugin window of tracing (Figure 5).
      NOTE: The structure of the arbor is the sum of the levels of branches. The path was defined between the cell body and the dendrite tips, and one path can include multiple branches, such as the primary arbors are the dendrites from the neuron cell body. The secondary arbors are branches from the primary and so on with the tertiary, quaternary, and quinary arbors. The structure of dendrite branching is separated depending on the levels of branches. For instance, the primary % is the number of branches divided by total number of branching, and so on.

Representative Results

The dendrites of da neurons were labeled by co-overexpressing GFP (UAS-GFP; ppk-GAL4) in the da neural soma and dendritic arbors for GFP fluorescence imaging analysis. The morphology of da neuron dendrites was imaged by an inverted confocal microscope (Figure 2).

The dendrites of da neurons were traced using Fiji ImageJ software. The file was used to estimate the dendrite length (Figure 3). Silencing of Sox102F in da neurons (N=21) (UAS-Sox102F-RNAi/ppk-GAL4; UAS-GFP) led to a significant reduction in the number of dendrites and a shorter branch length with a simpler structure compared to controls (N = 20) (UAS-GFP; ppk-GAL4 /+) in the third instar larva (Figure 6). Specifically, flies in which Sox102F was silenced exhibited a reduction in average dendrite length to 127 µm compared to 249 µm in controls (p = 0.02), and had a smaller average arbor surface area of 552,476 µm2 compared to 847,571 µm2 in controls (p = 0.04). In addition, silencing of Sox102F resulted in a smaller number of branches and a simpler branching structure of arbors with total branches of 17 (17.3 ± 6.7), compared with 28 (28.4 ± 9.5) in controls (p = 0.04). Student t-tests were performed to compare the differences between the groups, and the significance level was set to 0.05.

Figure 1
Figure 1: Schematics of dendrite analysis parameters of Drosophila da neuron. Panel (A) is the original image of a da neuron. (B) Dendrite length was the average of all dendrite lengths in all measured da neurons. (C) The surface area of da neuron dendrite was manually defined by the ImageJ freehand tool. (D) This schematic shows how to count the total number of branches and analyze branching structure of a da neuron. 1: Primary arbor. 2: Secondary arbor. 3: Tertiary arbor. 4: Quaternary arbor. Please click here to view a larger version of this figure.

Figure 2
Figure 2: Representative tracing of the dendrites of a da neuron. A da neuron was imaged with a confocal fluorescence microscope system. (A) The first tracing was created with a start point from the cell body and the end point of a dendrite by using the plugin/segmentation tool. The blue line (white arrow) represents the path defined. After clicking "Yes" (red arrow), the line changes color from blue to red. (B) Clicking on "Finish Path" it will appear purple (C). (A-C) Shows the process of tracing a single dendrite; (D) The complete traced image. Please click here to view a larger version of this figure.

Figure 3
Figure 3: Measurement of traced paths. The image on the left shows how to measure the trace paths after running the "Analysis |Measure Paths." Export path length values into a spreadsheet file, and calculate the sum of the length. Please click here to view a larger version of this figure.

Figure 4
Figure 4: An example of defining the dendrite surface area manually. A defined image was obtained by using the freehand tool in the ImageJ window menu (shown by red arrow). Set the measurements by selecting Area. Run the "Measure" function to obtain the area shown in the red box. Please click here to view a larger version of this figure.

Figure 5
Figure 5: An example of analysis of branching. Run "Analysis_Render | Analyze Skeletonized Paths" in the "Segmentation" plugin window. The rendered paths and their number were obtained by selecting "Render all paths | Obtain summary." The path was defined between the cell body and the dendrite tips, and one path can include multiple branches; for example, the primary arbors were the dendrites from the neuron cell body; the secondary arbors were branches from the primary and so on with the tertiary, quaternary, and quinary arbors. The structure of dendrite branching was separated depending on the levels of branches. For instance, primary % was the number of branches divided by total number of branching, and so on. Please click here to view a larger version of this figure.

Figure 6
Figure 6: Representative results of silencing of Sox102F in da neurons. Silencing of Sox102F in da neurons (UAS-Sox102F-RNAi/UAS-GFP; ppk-GAL4) led to significantly reduced dendrite length and shorter branching with simpler structure in the third instar larva compared to controls. The differences between Sox102F-RNAi flies (UAS-Sox102F-RNAi/UAS-GFP; ppk-GAL4, N = 21) and control (UAS-GFP;ppk-GAL4/+, N = 20) flies were on (A) dendrite length (B) arbor surface area (C) total number of branches, and (D, E) branching structure of the da neurons. Student T-test was perfomed for statistical analysis. * indicates statistical significance (p <0.05). The error bars are mean ± standard deviation. Please click here to view a larger version of this figure.

Discussion

Dendrites that innervate the epidermis are the input regions of neurons, and their morphologies determine how information is received and processed by individual neurons. Development dendrite morphology reflects gene modulation of dendrite organization. The Drosophila larval da neuron of the peripheral nervous system is an important model for studying dendrite development because of: 1) the functional similarity with mammals11,12; 2) four class distinctions based on dendrite structure11,12; and 3) the genetic factors that regulate morphogenesis. In this protocol, we present the workflow from larvae preparation to image analysis of Drosophila da neurons. The methods describe the four important parameters for analyzing dendrites in da neurons in detail, which are the length of dendrites, the surface area, the total numbers of branches, and the branching structure. The critical step was to remove as many tissues from the larva body wall as possible to fully expose the da neurons for imaging and analyses. There might be some short branches cut off because of the limited number of Z-projection images. As this method is the relative measurement of dendrites length in comparison with the controls, a large number of images for each group of da neurons should be taken to increase the coverage areas of Z-projection images.

Drosophila class IV da neurons have been the focus of research concerning dendrite arbor morphology15,21,22,23. Morphogenesis of dendritic arbor development might be disrupted by loss or gain of gene function, demonstrating that da neuron development is sensitive to genetic changes24. For genetic studies, it is important to analyze morphology accurately in order to understand its impact on da neurons. Class IV da neurons are complex but still accessible for high-quality imaging because they are located just beneath the semi-transparent body wall and branch, almost entirely in two dimensional space. The dynamic GFP fluorescence labeled da neurons (ppk-GAL4; UAS-GFP) provide a readily visualized model to investigate neuronal development. The direction of morphology change varies, arbors can become overbranched or simplified. Here, we categorized these morphological changes by quantitive parameters, e.g. the dendrite length, the surface area, the total numbers of branches, and the branching structure of da neurons. The results reflect the response in Sox102F expression regulating neuronal development, as shown in this study.

Our protocol was used to show the morphological changes of class IV da neurons in flies in which the Drosophila ortholog of SOX5, Sox102F, was silenced, indicating an important functional role of SOX5 in dendrite development and morphogenesis. The Wnt proteins are a family of secreted glycoproteins that have been implicated in regulating dendrite morphogeneis. Wnt2 and Wnt7b promote da and neuronal complexity9,10. In the Wnt canonical pathway, this activation is followed by activation of GSK3β, a serine-threonine kinase, which in turn activates β-catenin mediated transcription10,25. We have previously found that silencing of SOX5 in human SH-SY5Y neuroblastoma cells resulted in a significant repression of Wnt signaling activity and regulated the expression of a number of Wnt genes including an overexpression of GSK3β15.Increased expression of GSK3β has been associated with the hallmark characteristics of AD, including memory loss, β-amyloid plagues, and abnormal hyperphosphorylation of tau26. Silencing of SOX5 increased GSK3β expression, which might indicate a functional link between SOX5 and GSK3β.

The Class IV da neurons have the most highly complex dendrites of all sensory neurons. In this protocol, we have developed a method to analyze the complexity of arbor and branches to abstract the properties of class IV da neurons in Drosophila based on conventionally available plugins and software. Images that were taken from a confocal microscope were analyzed, and the plugin segmentation of a simple neurite tracer provided an ideal tool to trace the dendrite branches27,28. In addition, this quantification method allows for the detailed analysis of dendrite complexity by presenting the ratios of various levels of branching from the soma to the more distant dendrite. Moreover, this method might be used to analyze other classes of da neurons. For instance, class I da neurons extend secondary dendrites to one side of the body wall; class II has bifurcating branches symmetrically; and class III da neurons have more complexity of branching and spikes. In summary, we have provided a protocol of imaging and analysis of class IV da neurons for neuronal dendrite analyses in Drosophila.

Divulgaciones

The authors have nothing to disclose.

Acknowledgements

We would like to thank William A. Eimer for imaging technical assistance. This work was supported by the Cure Alzheimer’s Fund [to R.E.T], the National Institute of Health [R01AG014713 and R01MH60009 to R.E.T; R03AR063271 and R15EB019704 to A.L.], and the National Science Foundation [NSF1455613 to A.L.].

Materials

Phosphate buffered saline(PBS) Gibco Life Sciences 10010-023
TritonX-100 Fisher Scientific 9002-93-1
Paraformaldehyde(PFA) Electron Microscopy Sciences 15714-S
Sylgard 184 silicone elastomer base and curing agent Dow Corning Corportation 3097366-0516;3097358-1004
ProLong Gold Antifade Mountant Thermo Fisher Scientific P36931
Fingernail polish  CVS 72180
Stereo microscope Nikon SMZ800
Confocal microscope Nikon Eclipse Ti-E
Petri dish Falcon 353001
Forceps Dumont 11255-20
Scissors  Roboz Surgical Instrument Co RS-5611
Insect Pins  Roboz Surgical Instrument Co RS-6082-25
Microscope slides and cover slips Fisher Scientific 15-188-52

Referencias

  1. Wassle, H., Boycott, B. B. Functional architecture of the mammalian retina. Physiol Rev. 71 (2), 447-480 (1991).
  2. MacNeil, M. A., Masland, R. H. Extreme diversity among amacrine cells: implications for function. Neuron. 20 (5), 971-982 (1998).
  3. Losonczy, A., Makara, J. K., Magee, J. C. Compartmentalized dendritic plasticity and input feature storage in neurons. Nature. 452 (7186), 436-441 (2008).
  4. Spruston, N. Pyramidal neurons: dendritic structure and synaptic integration. Nat Rev Neurosci. 9 (3), 206-221 (2008).
  5. Jaworski, J., et al. Dynamic microtubules regulate dendritic spine morphology and synaptic plasticity. Neuron. 61 (1), 85-100 (2009).
  6. Kweon, J. H., Kim, S., Lee, S. B. The cellular basis of dendrite pathology in neurodegenerative diseases. BMB Rep. 50 (1), 5-11 (2016).
  7. Baloyannis, S. J. Dendritic pathology in Alzheimer’s disease. J Neurol Sci. 283 (1-2), 153-157 (2009).
  8. Masliah, E., Terry, R. D., Alford, M., DeTeresa, R., Hansen, L. A. Cortical and subcortical patterns of synaptophysinlike immunoreactivity in Alzheimer’s disease. Am J Pathol. 138 (1), 235-246 (1991).
  9. Wayman, G. A., et al. Activity-dependent dendritic arborization mediated by CaM-kinase I activation and enhanced CREB-dependent transcription of Wnt-2. Neuron. 50 (6), 897-909 (2006).
  10. Rosso, S. B., Sussman, D., Wynshaw-Boris, A., Salinas, P. C. Wnt signaling through Dishevelled, Rac and JNK regulates dendritic development. Nat Neurosci. 8 (1), 34-42 (2005).
  11. Grueber, W. B., Jan, L. Y., Jan, Y. N. Different levels of the homeodomain protein cut regulate distinct dendrite branching patterns of Drosophila multidendritic neurons. Cell. 112 (6), 805-818 (2003).
  12. Sugimura, K., Satoh, D., Estes, P., Crews, S., Uemura, T. Development of morphological diversity of dendrites in Drosophila by the BTB-zinc finger protein abrupt. Neuron. 43 (6), 809-822 (2004).
  13. Jan, Y. N., Jan, L. Y. Branching out: mechanisms of dendritic arborization. Nat Rev Neurosci. 11 (5), 316-328 (2010).
  14. Sears, J. C., Broihier, H. T. FoxO regulates microtubule dynamics and polarity to promote dendrite branching in Drosophila sensory neurons. Dev Biol. 418 (1), 40-54 (2016).
  15. Li, A., et al. Silencing of the Drosophila ortholog of SOX5 leads to abnormal neuronal development and behavioral impairment. Hum Mol Genet. 26 (8), 1472-1482 (2017).
  16. Misra, M., et al. A Genome-Wide Screen for Dendritically Localized RNAs Identifies Genes Required for Dendrite Morphogenesis. G3 (Bethesda). 6 (8), 2397-2405 (2016).
  17. Emoto, K., et al. Control of dendritic branching and tiling by the Tricornered-kinase/Furry signaling pathway in Drosophila sensory neurons. Cell. 119 (2), 245-256 (2004).
  18. Olesnicky, E. C., et al. Extensive use of RNA-binding proteins in Drosophila sensory neuron dendrite morphogenesis. G3 (Bethesda). 4 (2), 297-306 (2014).
  19. Parrish, J. Z., Xu, P., Kim, C. C., Jan, L. Y., Jan, Y. N. The microRNA bantam functions in epithelial cells to regulate scaling growth of dendrite arbors in drosophila sensory neurons. Neuron. 63 (6), 788-802 (2009).
  20. Schindelin, J., et al. Fiji: an open-source platform for biological-image analysis. Nat Methods. 9 (7), 676-682 (2012).
  21. Corty, M. M., Matthews, B. J., Grueber, W. B. Molecules and mechanisms of dendrite development in Drosophila. Development. 136 (7), 1049-1061 (2009).
  22. Jinushi-Nakao, S., et al. Knot/Collier and cut control different aspects of dendrite cytoskeleton and synergize to define final arbor shape. Neuron. 56 (6), 963-978 (2007).
  23. Crozatier, M., Vincent, A. Control of multidendritic neuron differentiation in Drosophila: the role of Collier. Dev Biol. 315 (1), 232-242 (2008).
  24. Copf, T. Importance of gene dosage in controlling dendritic arbor formation during development. Eur J Neurosci. 42 (6), 2234-2249 (2015).
  25. Rosso, S. B., Inestrosa, N. C. WNT signaling in neuronal maturation and synaptogenesis. Front Cell Neurosci. 7, 103 (2013).
  26. Engel, T., Hernandez, F., Avila, J., Lucas, J. J. Full reversal of Alzheimer’s disease-like phenotype in a mouse model with conditional overexpression of glycogen synthase kinase-3. J Neurosci. 26 (19), 5083-5090 (2006).
  27. Longair, M. H., Baker, D. A., Armstrong, J. D. Simple Neurite Tracer: open source software for reconstruction, visualization and analysis of neuronal processes. Bioinformatics. 27 (17), 2453-2454 (2011).
  28. Pool, M., Thiemann, J., Bar-Or, A., Fournier, A. E. NeuriteTracer: a novel ImageJ plugin for automated quantification of neurite outgrowth. J Neurosci Methods. 168 (1), 134-139 (2008).

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Wang, S., Tanzi, R. E., Li, A. Quantitative Analysis of Neuronal Dendritic Arborization Complexity in Drosophila. J. Vis. Exp. (143), e57139, doi:10.3791/57139 (2019).

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