Fig 1.
Overall neurodegeneration algorithm schematic.
The algorithm requires the user to provide maximum intensity projection image(s] of the CEP neurons and the pixel size in microns. Once the images and pixel size are set, the algorithm automatically detects dendrite locations and crops the image accordingly. Next, the cropped image undergoes a preprocessing step, which permits feature detection and dendrite tracking. An error check follows this step to ensure the dendrites were correctly identified. Using the tracks and feature locations, dendrite loss and feature metrics are quantified and stored for an overall neurodegeneration report. Max projection scale bar = 15 μm.
Fig 2.
Key steps in neurodegeneration detection algorithm.
A. Dendrite detection steps. The original image is first contrast adjusted and binarized to detect the location of the cell body (Scale bar = 25 μm). Next, the image is split into two images (Scale bar = 25 μm). Using the structures obtained through binarizing these images, the algorithm detects which image contains the dendrites (Scale bar = 10 μm). B. Feature detection steps. First, the cropped image undergoes local contrast adjustment to improve the subsequent global thresholding and binarization step. Feature locations are obtained using horizontal image erosion. Lastly, active contour segmentation of these features improves feature shape definition. C. Dendrite tracking. The local contrast adjusted image is used as a starting point to track dendrites. Each row of pixel intensities is analyzed to obtain 4 local maximum points, which correspond to the four dendrites. The resulting binary image is then closed with a vertical structuring element to connect points where no local maxima is detected. Next, for each row, every foreground point is binned and labeled into its respective dendrite and extra foreground points are removed. Lastly, rows with missing dendrites are interpolated and smoothed to create the final tracks.
Fig 3.
Neurodegeneration induced by rotenone exposure in BY200 worms.
A. Example images and detection of (i) control, (ii) 0.03 μm rotenone exposed, and (iii) 0.5 μM rotenone exposed worms (scale bar = 10 μm). Each dendrite is labeled as a star, square, triangle, or circle. N = 1 represents a single dendrite. B-E. Selected neurodegeneration metrics for control (N = 204), 0.03 μM rotenone (N = 168), and 0.5 μM rotenone exposed worms (N = 208). B. Number of detected features (blebs) per dendrite length. (0.03 μM rotenone to 0.05 μM rotenone; p = 0.066). C. Dendrite lengths obtained from tracked dendrites D. Percentage of dendrite remaining and E. Dendrite intensities. The neurodegeneration results for each dendrite in panel (A) are overlaid. (One-way ANOVA. *p < 0.05; **p < 0.01; ***p < 0.001).
Fig 4.
Neurodegeneration induced by cold shock at 4°C.
N = 1 represents a single dendrite. A. Example confocal images of CEP neurons and detected features for pre-cold shock, control (16 hrs. at 20°C), and cold shocked (16 hrs. at 4°C) worms (Scale bar = 10 μm). B-F. Neurodegeneration metrics for pre-cold shock (N = 72), control (N = 56) and cold-shocked worms (N = 68). B. Feature count per dendrite length. C. Normalized feature location and distance from the cell body. D. Minimum caliper diameters of detected features. E. Feature extent. F. Percentage of dendrite remaining. (One-way ANOVA. *p < 0.05; **p < 0.01; ***p < 0.001).
Fig 5.
Neurodegeneration quantification of 6-OHDA exposed worms.
N = 1 represents a single dendrite. A. Representative images of CEP dendrites under 6-OHDA exposure. Insets show zoomed-in views of detected features. B-D. Neurodegeneration metrics for control (N = 52, 56, and 76 for wildtype, tub-1, and tub-2, respectively), 10 mM (N = 60, 68, and 56 for wildtype, tub-1, and tub-2, respectively), 25 mM (N = 48, 56, and 64 for wildtype, tub-1, and tub-2, respectively), and 50 mM (N = 32, 76, and 60 for BY200, tub-1, and tub-2, respectively) 6-OHDA exposures. B. Feature count on dendrites weighted by the amount of dendrite remaining. C. Percentage of dendrite remaining. D. Intensity of detected features. E. Comparison of the neurodegeneration algorithm’s detection compared to manual dendrite scoring. (One-way ANOVA. *p < 0.05; **p < 0.01; ***p < 0.001, additional statistical information provided in S2 and S3 Tables).
Fig 6.
Experimental comparison across different exposure groups compared to their respective control.
A. Heat map of z scores for each exposure and its metrics obtained from AUDDIT to show directionality. B. Metrics that were significantly affected for each exposure with p < 0.05. (One-way ANOVA, Dunnett’s multiple comparisons).