Article Figures & Data
Figures
- Figure 1.
Analysis pipeline. Flowchart summarising the steps taken to optimize analysis parameters and then to detect and classify fluorescently labeled cells in whole mouse brain sections in QuPath.
- Figure 2.
Stages of QuPath analysis on whole mouse brain sections. A, Imported image following correction of channel colors. B, Initial tissue detection (left) and following subtraction of large vessels and edges (right). C, Brain regions intersected with detected tissue. D, Overlay of detected nuclei (gray) on tissue. E, High-magnification view of a region of the thalamus (indicated by box in D). F, With annotation boundaries in cyan and detected nuclei outlined in magenta (DsRed), green (GFP), and gray (other). Scale bars: 5 mm (A–D) and 10 μm (E–F). DAPI, GFP, and DsRed signal are colored blue, green, and magenta, respectively. Extended Data Figure 2-1 shows an example of the placing of annotations for manual cell counting.
- Figure 3.
Examples of detected cells. DsRed-positive pericytes are indicated with arrows, GFP-positive microglia with arrowheads. Each cell detected using DAPI staining is shown as an inner ring (nucleus) and outer ring (2 μm expansion) colored according to classification (magenta, DsRed-positive; green, GFP-positive; brown, DsRed-positive and GFP-positive; gray, DsRed-negative and GFP-negative). A–C, Appropriately classified cells. D, The pericyte is classified appropriately, but the microglia is not detected because of the nucleus being out of the plane of the section. E, A microglia and pericyte that are in close contact and were not able to be separated by the nuclear detection leading to a dual classification. F, The pericyte is appropriately classified, but some DsRed fluorescence has overlapped with a microglia to cause a dual classification. This figure illustrates two of the possible reasons for cells to be dual-classified; however, overall occurrence of dual-classified cells is low (see Fig. 5B). Scale bars: 5 μm.
- Figure 4.
Optimization of cell detection and classification thresholds. Counts generated by QuPath’s cell detection/positive cell detection algorithm were compared with manual cell counts to generate a % difference (dotted line at 0%) with a range of intensity thresholds across six brain regions for (A) DAPI, (B) DsRed, and (C) GFP (n = 8, mean ± SD). Insets show more detail at thresholds where the percentage difference crosses zero. For DsRed and GFP, data for thresholds with SDs over 200 have been excluded from the graphs to more clearly visualize the optimum threshold for each brain region. Extended Data Figure 4-1 shows intensity threshold analyses for annotations of individual brain regions. Example correlations of automated counts to manual counts for the thalamus using the final optimized values for (D) DAPI, (E) DsRed, and (F) GFP. Extended Data Figure 4-2 includes correlation charts for all optimized brain regions. Correlations between automated and manual counts were calculated using the Pearson’s correlation coefficient (r). **p < 0.01, ***p < 0.001, ****p < 0.0001.
- Figure 5.
Detection and classification of cells. A, Total cells detected per mm2 tissue area in each brain region by DAPI nuclei staining. B, Percentage of cells by classification across all brain regions measured. DsRed-positive cells by brain region (C) as percentage of total cell detections and (D) per mm2. GFP-positive cells by brain region (E) as percentage of total cell detections and (F) per mm2. Statistical analysis by repeated measures one-way ANOVA with post hoc Tukey’s multiple comparison test. All data passed the Shapiro–Wilk test for normality except hypothalamus in C. An outlier was identified and removed from this group and data from the same brain slice was removed across all brain regions, which subsequently passed normality. All data underwent the Geisser–Greenhouse correction to account for variation in sphericity; *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Extended Data Figure 5-1 shows detection and classification analyses comparing male and female mice with no statistically significant differences observed.
Tables
Male (n = 3) Female (n = 5) p value Weight (g) 27.77 ± 2.37 19.74 ± 1.05 p = 0.0005 *** Age (d) # 87.67 ± 2.52 85.00 ± 0.00 p = 0.2079 ns Tissue slice
area (mm2)42.17 ± 0.86 42.03 ± 1.25 p = 0.8739 ns All statistics are mean ± SD. Male and female groups were compared with an unpaired t test (# with a Welch’s correction when variances were inhomogeneous between groups); ***p < 0.001; ns, not significant.
- Table 2
Optimized intensity thresholds for cell detection and classification by brain region
DAPI DsRed GFP Cortex 150 375 250 Hippocampus 75 350 225 Thalamus 150 325 200 Hypothalamus 150 400 250
Extended Data 1
Scripts and classifiers. Zip file containing the scripts (.groovy files) and classifiers (.json files) that were developed for use in QuPath in this study. Download Extended Data 1, ZIP file.
Extended Data Figure 2-1
Example of optimization annotations. We placed 300 × 200-μm regions of interest in the upper cortex (layers 1–3), lower cortex (layers 4–6), hippocampus (including dentate gyrus), hippocampus (including CA1/CA3 boundary), thalamus, and hypothalamus of each brain section for the purposes of manually counting cells. Scale bar: 800 μm. Download Figure 2-1, TIF file.
Extended Data Figure 4-1
Detailed optimization of cell detection and classification thresholds. Counts generated by QuPath’s cell detection/positive cell detection algorithm were compared to manual cell counts to generate a % difference (dotted line at 0%) with a range of intensity thresholds across six brain regions for DAPI, DsRed, GFP (n = 8, mean ± SD). Data for lower thresholds with large SDs have been excluded from the graphs in order to clearly visualize the optimum threshold for each region and channel (indicated with an arrow). Download Figure 4-1, TIF file.
Extended Data Figure 4-2
Correlation of manual counts to automated counts at final optimized thresholds. For each optimized threshold, the Pearson’s correlation coefficient (r) between cells counted manually and automated counts by QuPath was calculated. Download Figure 4-2, TIF file.
Extended Data Figure 5-1
Detection and classification of cells by sex. Total cells (A), DsRed-positive cells (B), and GFP-positive cells (C) detected per mm2 tissue area. No effect of sex was found by two-way ANOVA. Download Figure 5-1, TIF file.
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