Triglyceride metabolism controls inflammation and microglial phenotypes associated with APOE4

Abstract

Changes to cellular lipids accompany shifts in microglial cell state, but the functional significance of these metabolic changes remains poorly understood. In human induced pluripotent stem cell-derived microglia, we observed that both extrinsic activation (by lipopolysaccharide treatment) and intrinsic triggers (the Alzheimer's disease-associated APOE4 genotype) result in accumulation of triglyceride-rich lipid droplets. We demonstrate that lipid droplet accumulation is not simply concomitant with changes in the cell state. In fact, both triglyceride biosynthesis and catabolism are critical for the activation-induced transcription and secretion of inflammatory cytokines and chemokines, as well as changes in phagocytosis. In microglia harboring the Alzheimer's disease risk APOE4 genotype, inhibiting triglyceride biosynthesis attenuates disease-associated transcriptional states. Triglyceride biosynthesis inhibition also rescues microglial surveillance defects observed in slices from APOE4 humanized transgenic mice. Together, our findings establish that modulating triglyceride metabolism can tune microglial immune activity in response to extrinsic activation and in APOE4-associated disease.

Keywords: APOE; Alzheimer's; CP: Neuroscience; activation; disease; iPSCs; lipid droplets; lipid metabolism; microglia; motility; neuroinflammation; triglycerides.

Figure 1.. Neutral lipid homeostasis is affected during microglia activation

(A) Fluorescence images of APOE3/APOE3 microglia stained with antibodies against IBA1 and CX3CR1. Scale bar, 50 μm. (B) Fluorescence images of APOE3/APOE3 microglia stained with LipidSPOT. Scale bars, 50 μm. Bottom panels show regions of interest (ROIs) in top panels. (C) Lipid droplet number per cell, with each dot representing a cell. Triangles depict the average number of lipid droplets in n = 3 microglial derivations, data are represented as mean ± SD. *p ≤ 0.05 by two-tailed unpaired t test. (D) Differentially expressed genes associated with lipid synthesis and catabolism. Each column is an independent treatment, n = 4. (E) Spectra of Raman shift of non-nuclear lipids within microglia with and without LPS and DGAT inhibitors. Gray bars: cholesterol ester (CE) and total lipid peaks centered at 2,883 and 2,845 cm ⁻¹, saturated triglycerides at 1,440 cm⁻¹, monounsaturated triglycerides (TAGs) at 1,655 cm⁻¹, and phospholipids (PLs) at 760 cm⁻¹. Data are representative of n = 2 independent microglial derivations.

Figure 2.. DGAT inhibition reduces lipid droplet accumulation during LPS activation

(A) Schematic showing the enzymes, DGAT1 and DGAT2 that control LD biogenesis in microglia. (B) Fluorescence images of APOE3/APOE3 microglia with and without LPS activation and DGAT inhibitors stained with LipidSPOT. Scale bars, 50 μm. Bottom panels show ROI in top panels. (C) Lipid droplet number per cell, with each dot representing an average of at least 6 cells across 3 wells. n ≥ 4 frames per condition. Data are represented as mean ± SD. *p ≤ 0.05, ****p ≤ 0.0001 by two-way ANOVA, with post-hoc Šídák test. (D) Raman imaging microscopy snapshots of microglia with and without LPS activation and DGAT inhibitors. This diagram depicts peak intensity at 2,845 cm⁻¹, representing total lipid content in n = 2 independent microglial derivations. (E) Spectra of Raman shift of non-nuclear lipids within iPSC-derived microglia with and without LPS and DGAT inhibitors. The triglyceride peaks in the zoom correspond to saturated triglycerides (1,440 cm⁻¹) and monounsaturated triglycerides (1,655 cm⁻¹). Vehicle and LPS data are reproduced from Figure 1E for clarity. (F) Expression of DGAT1 and DGAT2 relative to microglia transduced with scrambled shRNA control (scramble shRNA, white; DGAT KD, gray; n = 3 transductions). Data are represented as mean ± SD. *p ≤ 0.05, ***p ≤ 0.001 by two-tailed unpaired t tests. (G) GFP-positive microglia after transduction of scrambled shRNA control or shRNA targeted against DGAT1 and DGAT2 (DGAT KD). Bottom panels show microglia stained with LipidSPOT. Scale bars, 25 μm. (H) Lipid droplet number in GFP-positive cells, with each dot representing an average of at least 5 cells. Triangles depict the average number of lipid droplets in n = 3 transductions, data are represented as mean ± SD. *p ≤ 0.05 by two-way ANOVA, with post-hoc Tukey test.

Figure 3.. Triglyceride accumulation and lipid droplet biogenesis are necessary for LPS-mediated activation

(A) Differentially expressed genes for APOE3/APOE3 vehicle and LPS-treated microglia in the presence or absence of DGAT inhibitors. Gene groups are sorted based on the Z scores upon DGAT inhibition in activated microglia. Displayed data are average Z scores across n = 3 treatments. (B) Top 5 Gene Ontology (GO) functional annotation terms of the differentially expressed genes in group 1 (A) determined using ShinyGO Web application. Circle size indicates the number of genes in each GO term. Circle color indicates the false discovery rate-corrected p value. (C) Gene expression of cytokines (from normalized read counts) relative to average vehicle controls (vehicle, white; DGAT inhibition, gray; LPS, blue; DGAT inhibition + LPS, green; n = 3 treatments). Data are represented as mean ± SD. ns p > 0.05, **p ≤ 0.01, ****p ≤ 0.0001 by two-way ANOVA, with post-hoc Tukey test. (D) Fluorescence images of microglia, with and without LPS and DGAT inhibitors, immunostained for NF-κB (green) and stained with Hoechst 33258 (magenta), top panel. Dashed lines outline nuclei in the bottom panel. Arrowheads highlight the nuclear NF-κB fluorescence (white) in LPS-treated microglia. Scale bars, 25 μm. (E) Cumulative frequency distribution of nuclear NF-κB fluorescence. Vehicle, black; LPS, blue; DGAT inhibition, gray; DGAT inhibition + LPS, green. (F) Fold change (relative to vehicle) of cytokines secreted by LPS-treated APOE3/APOE3 microglia with and without DGAT inhibitors. Data represent 6 technical replicates across n = 3 microglial derivations.

Figure 4.. Modulating triglyceride accumulation and lipid droplet biogenesis alters uptake in microglia

(A) Overlay of phase contrast and fluorescence images of pHrodo Red Zymosan uptake (red) in vehicle- and LPS-treated APOE3/APOE3 microglia in the presence or absence of DGAT inhibitors. Scale bars, 50 μm. (B) Quantification of pHrodo Red Zymosan fluorescence in (A). Each dot represents an average of at least 45 cells per image. Triangles depict the average uptake hours in vehicle-, LPS-, DGAT inhibitor-, DGAT inhibitor + LPS-treated microglia. n = 3 wells; data are represented as mean ± SD. ns p > 0.05, *p ≤ 0.05, **p ≤ 0.01 by two-way ANOVA, with post-hoc Tukey test. (C) Fluorescence images of dextran (green) uptake and phalloidin (magenta) in vehicle and LPS-treated APOE3/APOE3 microglia in the presence or absence of DGAT inhibitors. Scale bars, 50 μm. High magnification images (bottom panels) show ROI in top panels. (D) Quantification of dextran uptake assay (C) relative to vehicle-treated controls. Each dot represents an average of at least 20 cells per image. Triangles depict the average uptake in n = 3 microglial derivations. Data are represented as mean ± SD. ns p > 0.05, *p ≤ 0.05 by two-way ANOVA, with post-hoc Tukey test. (E) Fluorescence images of amyloid-beta (green) uptake and phalloidin (magenta) in APOE3/APOE3 microglia with and without LPS treatment in the presence or absence of DGAT inhibitors. Scale bars, 50 μm. High-magnification images (bottom panels) show ROI in top panels. (F) Quantification of amyloid-beta uptake (E) relative to vehicle-treated controls. Each dot represents an average of at least 20 cells per image. Triangles depict the average uptake in n = 4 microglial derivations. Data are represented as mean ± SD. ns p > 0.05, *p ≤ 0.05 by two-way ANOVA, with post-hoc Tukey test. (G) Fluorescence images of dextran uptake assay in GFP-positive microglia after transduction of scrambled shRNA control or shRNA targeted against DGAT1 and DGAT2 (DGAT KD). Bottom panels show dextran uptake. Dashed lines outline a representative GFP-positive cell. Scale bars, 50 μm. (H) Quantification of dextran uptake assay (G) relative to scrambled shRNA controls. Each dot represents an average of at least 10 cells per image. Triangles depict the average uptake in n = 3 transductions. Data are represented as mean ± SD. *p ≤ 0.05 by two-way ANOVA, with post-hoc Tukey test.

Figure 5.. Utilization of lipid droplets through triglyceride catabolism is essential for LPS-mediated microglial activation

(A) Schematic of inhibition of lipid droplet catabolism using atglistatin. (B) Transcript abundance of adipose triglyceride lipase (ATGL) in LPS-treated microglia relative to vehicle-treated controls (vehicle, white; LPS, blue; n = 3 independent treatments). Data are represented as mean ± SD. *p ≤ 0.05 by two-tailed unpaired t test. (C) Fluorescence images of APOE3/APOE3 microglia treated with vehicle or ATGL inhibitor and stained with LipidSPOT. Bottom panels show ROI in top panels. Scale bars, 50 μm. (D) Lipid droplet number per cell, quantified across 3 wells with at least 40 cells analyzed per well. n ≥ 6 frames per condition. Data are represented as mean ± SD. **p ≤ 0.01 by two-tailed unpaired t test. (E) Fold change of cytokines secreted by LPS-treated APOE3/APOE3 microglia with and without DGAT inhibitor treatment. Data represent 6 technical replicates across n = 3 microglial derivations. (F) Fluorescence images of amyloid-beta (green) uptake and phalloidin (magenta) in vehicle and LPS-treated APOE3/APOE3 microglia in the presence or absence of ATGL inhibitor. High magnification images (bottom panels) show ROI in top panels. Scale bars, 50 μm. (G) Quantification of amyloid-beta uptake (F) relative to vehicle-treated controls. Each dot represents an average of at least 5 cells per image. Triangles depict the average uptake across n = 3 microglial derivations, data are represented as mean ± SD. ns p > 0.05, *p ≤ 0.05 by two-way ANOVA, with post-hoc Tukey test.

Figure 6.. Modulating triglyceride flux controls the immune state of APOE4 microglia

(A) Venn diagram showing the overlap of the differentially expressed genes upon treatment with DGAT inhibitors in APOE3/APOE3 and APOE4/APOE4 microglia. (B) Overlap of the GO terms defined by DEGs from the APOE3/APOE3 microglia and APOE4/APOE4 microglia treated with DGAT inhibitors relative to vehicle-treated controls. GO terms were determined using Metascape. Bandwidth for each GO term represents its p value calculated based on the cumulative hypergeometric distribution. The scale bar represents −log₁₀ (p value) = 5. (C) Gene expression levels of cytokines (from normalized read counts) from APOE4/APOE4 microglia relative to average vehicle-treated controls (vehicle, white; LPS, blue; DGAT inhibition, gray; DGAT inhibition + LPS, green. n = 3 treatments). Data are represented as mean ± SD. ns p > 0.05, *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, ****p ≤ 0.0001 by two-way ANOVA and post-hoc Tukey test. (D) Fold change (relative to vehicle controls) of cytokines secreted by APOE4/APOE4 microglia treated DGAT inhibitors or vehicle. Data represent 6 technical replicates across n = 3 microglial derivations. (E) Differential gene expression results for homeostatic and disease-associated microglia marker genes identified across multiple studies. Color indicates log₂ fold change of gene expression in DGAT inhibitor-treated APOE4/APOE4 microglia compared with vehicle-treated microglia. Dot size indicates the false discovery rate adjusted p value. (F) Fluorescence images of microglia in the entorhinal cortex of APOE4 KI:CX3CR1-GFP mice. Vehicle-treated brain slices, top; slices treated with DGAT inhibitors, bottom. Magenta circle represents 70 μm² area circle surrounding the tip of the pipette. Scale bar, 25 μm. (G) CX3CR1-GFP fluorescence within the circle over time. APOE4 KI:CX3CR1-GFP vehicle, light red; APOE4 KI:CX3CR1-GFP treated with DGAT inhibitors, dark red; APOE3 KI:CX3CR1-GFP vehicle, blue. n = 5 slices each from a different animal; shaded regions show SEM. (H) CX3CR1-GFP fluorescence within the circle at indicated time points. APOE4 KI:CX3CR1-GFP vehicle, light red; APOE4 KI:CX3CR1-GFP treated with DGAT inhibitors, dark red; APOE3 KI:CX3CR1-GFP vehicle, blue. Error bars represent SEM. n = 5 mice; *p ≤ 0.05, **p ≤ 0.01 by multiple two-tailed unpaired t tests with post-hoc Holm-Šídá test.