Ketogenic diet uncovers differential metabolic plasticity of brain cells

Tim Düking, Lena Spieth, Stefan A Berghoff, Lars Piepkorn, Annika M Schmidke, Miso Mitkovski, Nirmal Kannaiyan, Leon Hosang, Patricia Scholz, Ali H Shaib, Lennart V Schneider, Dörte Hesse, Torben Ruhwedel, Ting Sun, Lisa Linhoff, Andrea Trevisiol, Susanne Köhler, Adrian Marti Pastor, Thomas Misgeld, Michael Sereda, Imam Hassouna, Moritz J Rossner, Francesca Odoardi, Till Ischebeck, Livia de Hoz, Johannes Hirrlinger, Olaf Jahn, Gesine Saher, Tim Düking, Lena Spieth, Stefan A Berghoff, Lars Piepkorn, Annika M Schmidke, Miso Mitkovski, Nirmal Kannaiyan, Leon Hosang, Patricia Scholz, Ali H Shaib, Lennart V Schneider, Dörte Hesse, Torben Ruhwedel, Ting Sun, Lisa Linhoff, Andrea Trevisiol, Susanne Köhler, Adrian Marti Pastor, Thomas Misgeld, Michael Sereda, Imam Hassouna, Moritz J Rossner, Francesca Odoardi, Till Ischebeck, Livia de Hoz, Johannes Hirrlinger, Olaf Jahn, Gesine Saher

Abstract

To maintain homeostasis, the body, including the brain, reprograms its metabolism in response to altered nutrition or disease. However, the consequences of these challenges for the energy metabolism of the different brain cell types remain unknown. Here, we generated a proteome atlas of the major central nervous system (CNS) cell types from young and adult mice, after feeding the therapeutically relevant low-carbohydrate, high-fat ketogenic diet (KD) and during neuroinflammation. Under steady-state conditions, CNS cell types prefer distinct modes of energy metabolism. Unexpectedly, the comparison with KD revealed distinct cell type-specific strategies to manage the altered availability of energy metabolites. Astrocytes and neurons but not oligodendrocytes demonstrated metabolic plasticity. Moreover, inflammatory demyelinating disease changed the neuronal metabolic signature in a similar direction as KD. Together, these findings highlight the importance of the metabolic cross-talk between CNS cells and between the periphery and the brain to manage altered nutrition and neurological disease.

Figures

Fig. 1.. Preferred metabolic pathways in cortical…
Fig. 1.. Preferred metabolic pathways in cortical cell types.
(A) Scheme of the experimental approach. Cell types were isolated from the cortex (Ctx) of individual P42 mice (n = 4) using magnetic beads and analyzed by proteomic profiling. m/z, mass/charge ratio. (B) Pearson correlation of cell type–specific proteome datasets as in (A). (C) PCA of cell type–specific proteomes calculated from 722 complete cases of a total of 3541 proteins. (D) Normalized enrichment score (NES) of the gene sets “metabolic pathways” by gene set enrichment analysis (GSEA), comparing z scores of cell type–specific proteomes from P42 mice (AA, amino acid; FA, fatty acid; FDR, false discovery rate; OXPHOS, oxidative phosphorylation; PPP, pentose phosphate pathway; TCA, tricarboxylic acid cycle). (E) Heatmaps showing the mean cell type–specific abundance of proteins related to metabolic pathways (n = 4). (F) Cell type–specific abundance of mitochondrial proteins plotted as the relative abundance of each of the 274 identified mitochondrial proteins. (G) Violin plot of the density of mitochondria per cell soma volume, by quantification of SCOT+ mitochondria colabeled with cellular markers [n = 10 to 20 visual fields with 20 to 28 cells from four animals; one-way analysis of variance (ANOVA) with Tukey’s posttest showing significant differences to astrocytes, **P < 0.01 and ***P < 0.001]. (H) Violin plot of the relative mitochondrial volume (calculated from genetically labeled GFP fluorescence in the outer mitochondrial membrane) per cell soma volume in astrocytes (GFAP-Cre*MitoTag) and neurons (Rbp4-Cre*MitoTag) colabeled with cellular markers (n = 18 to 34 visual fields with 27 to 52 cells from three animals; Mann-Whitney test, ***P < 0.001). (I) Top five GO term processes of the 67 mitochondrial proteins found exclusively in astrocytes by overrepresentation analysis.
Fig. 2.. Metabolic changes during postnatal brain…
Fig. 2.. Metabolic changes during postnatal brain maturation.
(A) Pearson correlation of cell type–specific proteome datasets from P14 mice comprising a total of 3787 proteins, ranging from 1770 proteins in oligodendrocytes to 2664 proteins in neurons. (B) PCA of cell type–specific proteomes from P14 mice calculated from 1144 complete cases. (C) NES of the gene sets “metabolic pathways” by GSEA, shown as log2 fold changes (LFC) of cell type–specific proteomes from P42 versus P14 mice. (D) NES of gene set “cell function” by GSEA, comparing LFC of cell type–specific proteomes from P42 versus P14 mice. (E) Bubble plot of proteins related to glycolysis showing percent z scores at P42 (size), LFC of P42 versus P14 (color) with significant differences marked by the outline (q-mod values from moderated t statistics with FDR-based correction for multiple comparisons). (F) Bubble plot of proteins related to ketolysis in isolated cell types showing the percent z scores, LFC with significant differences marked by the outline as in (E).
Fig. 3.. Cortical changes in mice weaned…
Fig. 3.. Cortical changes in mice weaned to a KD.
(A) Experimental setup. At P14, SD or KD was administered in boxes with small holes rendering this food only accessible for pups. Mice were weaned at P17 (arrow) and kept on the respective diet. (B) Blood 3HB and glucose in mice treated as in (A) (n = 20, two-way ANOVA with Sidak’s posttest, ***P < 0.001). (C) Schematic of the Audiobox test (top left) and the learning paradigm (top right) (n = 5). Mean total number of visits ± SEM shows comparable activity of mice in both treatments (bottom left). Mean percentage of visits without nose poke ± SEM under safe (circle) and conditioned (square) conditions of mice fed KD or SD at 5 weeks of age reveal similar neurocognitive abilities (bottom right). (D) Mean levels of glycolysis metabolites with individual data points, by GC-MS in cortex of KD-fed P42 mice normalized to SD-fed controls (Gluc, glucose; G6P, glucose-6-phosphate; F6P, fructose-6-phosphate; Pyr, pyruvate; Lac, lactate; t statistics with Benjamini-Hochberg correction, ***Padj < 0.001). (E) Representative immunoblot for MCT1 in P42 cortex of mice fed SD or KD with quantification normalized to reprobed actin signals (unpaired Student’s t test, *P < 0.05). (F) Representative immunolabeling of MCT1 (green), S100b (red, astrocyte marker), and 4′,6-diamidino-2-phenylindole (DAPI) (blue, nuclei) in cortex of SD and KD-fed P42 mice. Scale bar, 10 μm. (G) Representative immunoblot for SCOT in cortex of P21 to P42 mice fed SD or KD with quantification normalized to reprobed actin signals relative to P21 SD values (two-way ANOVA with Sidak’s posttest, *P < 0.05, **P < 0.005, and ***P < 0.001). (H) Mean cortical 3HB levels with individual data points measured by GC-MS (t statistics with Benjamini-Hochberg correction, ***Padj < 0.001). (D to H) Each ring represents an individual data point (one mouse).
Fig. 4.. Cell type–specific strategies of metabolic…
Fig. 4.. Cell type–specific strategies of metabolic adaptations to feeding a KD.
(A) Experimental paradigm. (B) PCA of cell type–specific proteomes from mice fed SD or KD, calculated from 546 complete cases from a total of 3621 detected proteins. (C) Bubble plot of proteins related to ketolysis in isolated cell types from KD- versus SD-fed mice. (D) Maximum intensity projection (1-μm optical section in all dimensions) of SCOT (red) and enhanced green fluorescent protein (EGFP) (green) colabeling of brain sections from ALDH1L1-EGFP transgenes fed KD or SD with quantification of the density and relative fluorescence intensity (Fi) of SCOT+ mitochondria per volume in soma and processes (Mann-Whitney test, ***P < 0.001). ALDH1L1-EGFP mice express EGFP under the astrocyte Aldh1l1 promotor. Scale bar, 5 μm. (E) LFC of proteins related to glycolysis in astrocytes from mice fed KD versus SD (n = 4). (F) Median intracellular lactate levels (Laconic nanosensor) with 5 to 95 percentiles in astrocytes that had been exposed to SD-mimicking (5 mM glucose, Ctrl) or KD-mimicking (0.4 mM glucose and 4 mM 3HB, Keto) conditions for 1 week before measuring in 2 mM glucose, showing baseline lactate levels and the rate of lactate production after inhibiting MCT transporters (AR-C 155858) (n = 41 to 60 cells from three independent experiments; Mann-Whitney test, *P < 0.05 and **P < 0.01). (G) Mean intracellular ATP relative light units (RLU) with individual values in acutely isolated astrocytes from KD- and SD-fed animals, measured in 2 mM glucose with or without inhibition of glycolysis [2-deoxyglucose (2-DG)] or OXPHOS by oligomycin (Oligo) (n = 3 measurements pooled from two mice per group). (H) Bubble plot of proteins related to intermediary metabolism in cell types isolated from mice fed KD versus SD. (C, E, and F) Significant changes in protein abundance were determined by moderated t statistics with FDR-based correction for multiple comparisons (*q mod < 0.05, **q-mod < 0.005, and ***q-mod < 0.001).
Fig. 5.. Feeding KD alters synapse remodeling.
Fig. 5.. Feeding KD alters synapse remodeling.
(A) Maximum intensity projection (1 μm) of SCOT (red) and NeuN (green) colabeling with quantification of the density and relative fluorescence intensity of SCOT+ mitochondria per soma volume (Mann-Whitney test, ***P < 0.001; scale bar, 5 μm). (B) Mean TCA intermediates by GC-MS (n = 6; Cit, citrate; aKG, α-ketoglutarate; Succ, succinate; Fum, fumarate; Mal, malate). (C) LFC of neuronal TCA proteins (n = 4). (D) LFC of proteins related to neuronal glycolysis (n = 4). (E) Heatmap of proteins related to synaptic transmission in neurons (n = 4 mice). (F) Maximum intensity projection of Shank2 (magenta) and VGluT1 (yellow) colabeling (scale bars, 5 μm) with fluorescence intensity scan of the dashed line. Global or synaptic (colocalized with the postsynaptic marker Shank2) VGluT1 immunofluorescence with median and interquartile ranges (n = 20 images of four mice; Mann Whitney test, *P > 0.05). (G) Representative image and quantification of synapse density on electron microscopic images (n = 3 mice; scale bars, 100 nm). (H) Mean cortical neurotransmitter levels measured by GC-MS (n = 5 to 6 mice). (I) Steady-state axonal ATP levels in optic nerves from Thy1-ATeam ATP sensor mice fed KD or SD, showing the F/C intensity ratio, the sensor lifetime, and the mean normalized fluorescence decay time ± SEM [n = 6 (KD) and n = 8 (SD) nerves from three to four mice]. (J) Open-field test. Representative traces of P42 mice fed SD and KD with quantification shown as mean with individual values (n = 12 to 15 mice; two-way ANOVA with Sidak’s posttest, ***P < 0.001). (C to E) Moderated t statistics with FDR-based correction for multiple comparisons (*q mod < 0.05, **q mod < 0.005, and ***q mod < 0.001). (B and H) T statistics with Benjamini-Hochberg correction; *Padj < 0.05, **Padj < 0.01, and ***Padj < 0.001. ns, not significant. n.d., not detected.
Fig. 6.. Feeding KD supports neuronal metabolism…
Fig. 6.. Feeding KD supports neuronal metabolism in EAE.
(A) Mean blood glucose and 3HB with individual values of EAE mice fed SD or KD (n = 8 to 16 mice; one-way ANOVA with Dunnet’s posttest compared to control mice). (B) Bubble plot of ketolysis and glycolysis proteins in neurons from EAE mice and controls. (C) Representative immunolabeling of SCOT and NeuN in cortex of EAE mice and controls with quantification (n = 5 mice, one-way ANOVA with Tukey’s posttest; scale bars, 20 μm). (D) Mean clinical score ± SEM of EAE mice. KD was applied therapeutically starting with disease onset (n = 8 SD, n = 16 KD mice). (E) Mean lesion size ± SEM in lumbar spinal cord of EAE mice (n = 6 to 8 mice; unpaired two-sided Student’s t test). (F) Mean density of inflammatory cells ± SEM in spinal cord of EAE mice fed KD or SD analyzed by flow cytometry (n = 6 mice; unpaired two-sided Student’s t test). (G) Bubble plot of disease defense and homeostatic markers in cortical neurons from EAE mice and controls. *P < 0.05, **P < 0.01, and ***P < 0.001.

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