Manipulating energy metabolism differentially affects rod and cone photoreceptors.

(A) Immunofluorescence staining of in vivo retina (magenta): (A1) negative control, (A2) RPE65, (A3) glucose transporter-1 (GLUT1), (A4) pyruvate kinase M2 (PKM2), (A5) mitochondrial cytochrome oxidase (COX). (B) Overview of experimental manipulations. Organotypic retinal explants were cultured for 6 days in vitro with or without RPE or treated with 1,9-DDF, Shikonin, or FCCP. (C) TUNEL assay performed on in vitro retina (cyan) marking dying cells in the five experimental conditions. (D) Quantification of TUNEL-positive cells in outer nuclear layer (ONL). Data represented as mean ± SD. (E) Cone-arrestin labelling (green) in the ONL. (F) Quantification of arrestin-positive cones. Data represented as mean ± SD. (G) Table giving percentages of cones and rods lost for each treatment. (H) Pie charts illustrate cone to rod cell death ratios. (I) Principal component analysis (PCA) of retinal samples investigated with 1H-NMR spectroscopy-based metabolomics. Dots in graphs represent individual retinal explants. Statistical testing: One-way ANOVA with Tukey’s post-hoc test. Asterisks indicate significance levels; p-values: *** < 0.001, ** < 0.01 * < 0.05. RPE = retinal pigment epithelium; INL = inner nuclear layer; GCs = ganglion cells.

1H-NMR spectroscopy-based metabolomic analysis of retina subjected to interventions in energy metabolism.

(A) Heatmap based on unsupervised hierarchical cluster analysis by Ward’s linkage, showing auto-scaled metabolite concentrations (red – high, blue – low) in five different experimental conditions: control - red, no RPE - green, 1,9-DDF - dark blue, Shikonin - light blue, FCCP purple (n = 5 samples per condition). (B) Metabolic profiles of each intervention were compared to control. Metabolites significantly changed in at least one experimental condition were grouped according to functions and pathways. Data show p-values and fold change (FC) over control. Statistical comparison: Student’s unpaired t-test (group variance equal); p-values: **** < 0.0001, *** < 0.001, ** < 0.01 * < 0.05. See also Supplementary Figure 3.

Absence of RPE dramatically changes retinal metabolism.

(A) Heatmap, based on unsupervised hierarchical cluster analysis by Ward’s linkage, illustrating statistically significant changes for 25 metabolites (unpaired t-test, fold change (FC) > 1.2, raw p value < 0.05). (B) Pattern hunter for citrate, showing the top 25 correlating metabolites, correlation coefficient given as Pearson r distance. (C) Metabolic pathways most affected in no RPE condition compared to control, based on KEGG-pathway database. (D) Immunodetection of enzymes and metabolites (green) on in vivo retina. (D1) citrate synthase (CS), (D2) fumarase, (D3), ATP synthase γ, (D4) taurine, (D5) alanine transaminase (ALT). Co-staining for ALT and cone arrestin (Arr3; magenta) showed high expression in cone inner segments. DAPI (grey) was used as a nuclear counterstain. See also Supplementary Figure 5.

Comparison between no RPE and FCCP conditions.

(A) Heatmap, based on unsupervised hierarchical cluster analysis by Ward’s linkage, illustrating statistically significant metabolite changes (unpaired t-test, fold change > 1.2, raw p-value < 0.05). (B) Pattern hunter for guanosine triphosphate (GTP) showing the top 25 correlating compounds. Correlation coefficient given as Pearson r distance. (C) KEGG-based pathway analysis, comparison between no RPE and FCCP. (D) Immunofluorescence for succinate-CoA ligase-1 (SUCLG1, green) labelled photoreceptor inner segments and colocalized with COX. DAPI (grey) was used as a nuclear counterstain. (E) PAR positive photoreceptors (black) in the outer nuclear layer (ONL) of FCCP treated retina. (F) Compared to no RPE, NAD+ levels were lower in the FCCP group, while the percentage of PAR positive cells was higher. Data represented as mean ± SD. Statistical testing: Student’s two-tailed t-test. p-values: *** < 0.001, * < 0.05. See also Supplementary Figure 7.

Metabolomic analysis of no RPE vs. 1,9-DDF treatment and Shikonin vs. FCCP treatment.

Heatmap illustrating statistically significant metabolite changes (unpaired t-test, fold change (FC) > 1.2, raw p value < 0.05) for (A) no RPE vs. 1,9-DDF and (C) Shikonin vs. FCCP. Pattern hunter for (B) ATP and (D) glutathione, showing the top 25 correlating compounds. Correlation coefficient given as Pearson r distance. See also Supplementary Figures 8 and 9.

Metabolomic comparison between control, 1,9-DDF, and FCCP treatment.

(A) Heatmap illustrating 29 statistically significant metabolite changes (parametric one-way ANOVA, Fisher’s LSD post-hoc analysis). Three main clusters of metabolite changes were evident (dashed lines). (B) Immunostaining (green) for enzymes related to glutamine metabolism. DAPI (grey) was used as nuclear counterstain. (B1) Glutamine synthase (GS), (B2) glutaminase C (GAC); co-localization with cone-arrestin (Arr3; magenta). (B3) phosphoenolpyruvate carboxykinase 1 (PCK1) did not co-localize with cone marker peanut-agglutinin (PNA) while (B4) PCK2 did. (C) Ratios between metabolites representing glycolysis (lactate vs. GTP), anaplerotic metabolism (GTP vs. BCAA), and serine synthesis pathway (serine vs. lactate). Data represented as individual data points with mean ± SD. Statistical testing: One-way ANOVA with Tukey’s post-hoc test; p-values: **** < 0.0001, *** < 0.001, ** < 0.01 * < 0.05. See also Supplementary Figure 10.

Metabolic pathways in the retina, key metabolites, and expression of aspartate amino transferase (AST).

(A) Overview of main metabolic pathways and metabolites. Execution of Cori-(green arrows), Cahill-(brown), or mini-Krebs-cycle (blue) releases the signature metabolites lactate, alanine, and N-acetylaspartate (NAA), respectively. Key enzymes of the Cahill- and mini-Krebs-cycle are phosphoenolpyruvate carboxykinase (PCK), pyruvate kinase M (PKM), alanine transaminase (ALT) and AST. (B) Hierarchical clustering of eight metabolites connected to Krebs and mini-Krebs cycle. (C) Ratio NAA vs. citrate, representing full and mini-Krebs-cycle. Data represented as ratio of individual data points with mean ± SD. Statistical comparison using one-way ANOVA, Tukey’s multiple comparisons test; p-values: **** < 0.0001, *** < 0.001. (D) Immunostaining for aspartate amino transferase-1 and −2 (AST1, AST2; green) co-stained with the rod photoreceptor outer segment marker rhodopsin (RHO; magenta), DAPI (grey) was used as nuclear counterstain.

Comparison of metabolic pathways and their energetic efficiencies.

Compared to the Cori-cycle, both Cahill- and mini-Krebs-cycles are highly efficient. Their key enzymes – alanine transaminase (ALT) and aspartate amino transferase (AST), respectively – generate alanine and aspartate/N-acetylaspartate (NAA). Pyruvate carboxy kinase (PCK), either in cytoplasm or within mitochondria, may reconstitute pyruvate from oxalacetate. Note that energy output of each pathway was calculated based on input of pyruvate (three carbons) or glutamate/branched-chain-amin-acid/acetyl-CoA (three carbons).