Article Figures & Data
Figures
Visual Abstract
- Figure 1.
Study overview. A, Outline of steps involved in MicrogliaMorphology and MicrogliaMorphologyR. B, Experimental mouse model used for dataset described throughout paper, made using Biorender. Example images from the dorsal hippocampus with individual microglia insets for each treatment condition. Microglia (Iba1) in yellow and DAPI nuclear stain in blue. Full size images scale bar 200 µm, insets 30 µm.
- Figure 2.
Comparison of 3D versus EDF versus single-plane 2D image types. A, Samples represented in principal components space and colored by image type or morphology class. Each point is either a 2D, 3D, or EDF representation of 1 of 20 different cells. B, Comparison of changes across morphological classes when cells are represented in 2D, 3D, or EDF forms. Values on plots are z-scores (centered and scaled) calculated within image type. C, Spearman's correlation of PCs 1–2 after dimensionality reduction across image types. D, Individual Pearson’s correlations between image types for specific morphology features measured using AnalyzeSkeleton. E, Visual description of morphology features measured using AnalyzeSkeleton. See Extended Data Figure 2-1 and Extended Data Tables 2-1 and 2-2 for additional data.
- Figure 3.
Characterization of morphological clusters in 2xLPS dataset. A, Spearman's correlation matrix of 27 features measured by MicrogliaMorphology [*abs(R) ≥ 0.8; p < 0.05]. B, Spearman's correlation of morphology measures to first three PCs after dimensionality reduction [*abs(R) ≥ 0.75; p < 0.05]. C, Cluster classes displayed in PCs 1–2 space. D, Average values for all 27 morphology features, scaled across clusters. E, Individual cells spatially registered back to original images and visually annotated by morphological class using ColorByCluster feature. See Extended Data Figure 3-1 and Extended Data Tables 3-1–3-4 for additional data.
- Figure 4.
Analysis of morphological clusters and individual morphology measures across brain regions and antibody markers in 2xLPS dataset. A, LPS-induced shifts in morphological populations across antibodies and within brain regions (*p < 0.05; Bonferroni). B, Immunofluorescent images of the same microglial cells stained with Cx3cr1, Iba1, and P2ry12 in PBS and 2xLPS conditions. Scale bars, 50 µm. C, LPS-induced changes in cell area across antibodies and within brain regions (*p < 0.05; Bonferroni) See Extended Data Figure 4-1 and Extended Data Tables 4-1–4-4 for additional data.
Extended Data
Figure 2-1
Extended comparison of 3D vs. 2D image types. (A) Changes in the raw values of AnalyzeSkeleton measures across 3D, EDF, and 2D image types. Each line is an individual cell represented in 3D, EDF, and 2D. (B) Individual Pearson’s correlations between image types for specific morphology features measured using AnalyzeSkeleton. (C) Spearman’s correlation of skeletal morphology measures to first 5 PCs after dimensionality reduction. (*abs(R) ≥ 0.8, p < 0.05). Download Figure 2-1, TIF file.
Table 2-1
Pearson’s correlation of principal components and p-values for correlations, related to Fig. 2C. Download Table 2-1, DOC file.
Table 2-2
Spearman’s correlation of morphology measures to principal components and p-values for correlations, related to Fig. 2-1C. Download Table 2-2, DOC file.
Figure 3-1
Analysis of 1xLPS morphology measures and clusters. (A) Spearman’s correlation matrix of 27 features measured by MicrogliaMorphology. (*abs(R) ≥ 0.8, p < 0.05) (B) Spearman’s correlation of morphology measures to first 3 PCs after dimensionality reduction. (*abs(R) ≥ 0.75, p < 0.05) (C) Optimal k-means clustering parameters determined using within sum of squares and gap statistic techniques. Cluster classes displayed in PC space. (D) Average values for all 27 morphology features, scaled across clusters. Download Figure 3-1, TIF file.
Table 3-1
Spearman’s correlation of morphology measures and p-values for correlations, related to Fig. 3A. Download Table 3-1, DOC file.
Table 3-2
Spearman’s correlation of morphology measures and p-values for correlations, relate to Fig. 3-1A. Download Table 3-2, DOC file.
Table 3-3
Spearman’s correlation of morphology measures to principal components and p-values for correlations, related to Fig. 3-1B. Download Table 3-3, DOC file.
Table 3-4
Spearman’s correlation of morphology measures to principal components and p-values for correlations, related to Fig. 3B. Download Table 3-4, DOC file.
Figure 4-1
Extended analysis of 2xLPS dataset. (A) Cells from dataset visualized in PCs 1-2 space and colored by different experimental variables. (B) Elbow plot depicting percentage of the variance in dataset explained by each Principal Component. (C) LPS-induced shifts in morphological populations across subregions and antibodies. Download Figure 4-1, TIF file.
Table 4-1
Analysis of Deviance (Type II Wald chisquare tests) on models fit for each brain region separately: percentage ∼ Cluster*Treatment*Antibody + (1|MouseID). Significance denoted at Pr(>Chisq) < 0.05, related to Fig. 4A. Download Table 4-1, DOC file.
Table 4-2
Tests between treatments across clusters and antibodies (∼Treatment|Cluster|Antibody), bonferroni-corrected for each brain region. Significance denoted at adjusted p-values (or q-values) < 0.05, related to Fig. 4A. Download Table 4-2, DOC file.
Table 4-3
Analysis of Deviance (Type II Wald chisquare tests) on models fit for each brain region separately for area measure: Value ∼ Treatment*Antibody + (1|MouseID). Significance denoted at Pr(>Chisq) < 0.05, related to Fig. 4C. Download Table 4-3, DOC file.
Table 4-4
Tests between treatments across antibodies (∼Treatment|Antibody), Bonferroni-corrected for each brain region. Significance denoted at adjusted p-values (or q-values) < 0.05, related to Fig. 4C. Download Table 4-4, DOC file.
In this issue
