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Mar Drugs
2018 Dec 20;171:. doi: 10.3390/md17010002.
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Spinochrome D Attenuates Doxorubicin-Induced Cardiomyocyte Death via Improving Glutathione Metabolism and Attenuating Oxidative Stress.
Yoon CS
,
Kim HK
,
Mishchenko NP
,
Vasileva EA
,
Fedoreyev SA
,
Stonik VA
,
Han J
.
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Doxorubicin, an anthracycline from Streptomyces peucetius, exhibits antitumor activity against various cancers. However, doxorubicin is cardiotoxic at cumulative doses, causing increases in intracellular reactive oxygen species in the heart. Spinochrome D (SpD) has a structure of 2,3,5,6,8-pentahydroxy-1,4-naphthoquinone and is a structural analogue of well-known sea urchin pigment echinochrome A. We previously reported that echinochrome A is cardioprotective against doxorubicin toxicity. In the present study, we assessed the cardioprotective effects of SpD against doxorubicin and determined the underlying mechanism. ¹H-NMR-based metabolomics and mass spectrometry-based proteomics were utilized to characterize the metabolites and proteins induced by SpD in a human cardiomyocyte cell line (AC16) and human breast cancer cell line (MCF-7). Multivariate analyses identified 12 discriminating metabolites (variable importance in projection > 1.0) and 1814 proteins from SpD-treated AC16 cells. Proteomics and metabolomics analyses showed that glutathione metabolism was significantly influenced by SpD treatment in AC16 cells. SpD treatment increased ATP production and the oxygen consumption rate in D-galactose-treated AC16 cells. SpD protected AC16 cells from doxorubicin cytotoxicity, but it did not affect the anticancer properties. With SpD treatment, the mitochondrial membrane potential and mitochondrial calcium localization were significantly different between cardiomyocytes and cancer cell lines. Our findings suggest that SpD could be cardioprotective against the cytotoxicity of doxorubicin.
Figure 2. Mass spectrometry-based proteomics of SpD-treated AC16 cells. Liquid Chromatography–Mass Spectrometry-MS (LC-MS/MS) spectrometry-based proteomics detected proteins from SpD (10 μM, 24 h) (A) and SpD/doxorubicin (B) treated AC16 cells; (C) Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) analysis showed that altered metabolic proteins clustered around “mitochondria†which are represented as red colored nodes. All filled nodes represent the 3D structures of proteins are known; and, (D) The top 10 influenced metabolic pathways are shown from the STRING analysis (Kyoto Encyclopedia of Genes and Genomes (KEGG) database).
Figure 3. Normalization of 1H-NMR aquired metabolite concentrations. The concentrations of metabolites were normalized by log-transformation followed by Pareto scaling (mean-centered and divided by the square root of the standard deviation of each variable). Changes of metabolites are represented as ratios of control metabolites.
Figure 4. Volcano plots for SpD-induced metabolic changes compared with controls (n = 3). Metabolites are considered significant if log2(fold change) > 1.2. The p-value threshold was 0.05. The significantly changed metabolites included acetate, glutamine, myo-inositol, glutathione, taurine, O-phosphocholine, and sn-Glycero-3-phosphocholine (GPC).
Figure 5. 1H-NMR metabolomics for SpD-treated AC16 cells. (A) Principal component analysis (PCA) indicated that metabolites from the SpD-treated (10 μM, 24 h) group were significantly different from those in the control group; (B) Heat-map analysis of metabolites with variable importance in projection (VIP) score > 1.0. The logarithmic fold changes are shown below. GPC, sn-glycero-3-phosphocholine; (C) The loading plots from orthogonal partial least-squares discriminant analysis (OPLS-DA) for SpD metabolites compared with the control group.
Figure 6. Network analysis of metabolites altered by SpD (10 μM, 24 h) treatment of AC16 cells. Networks of metabolites according to their Pearson’s correlation coefficients were drawn using Cytoscape program. The networks with significantly increased GPC and decreased acetate are marked as red lines. (A) control and (B) SpD-treated cell metabolites; and, (C) Pathway impact analysis shows the most affected metabolic pathways affected by SpD. Varying colors from yellow to red represent metabolites’ significance in the data.
Figure 8. SpD caused increased ATP production and oxygen consumption rate (OCR) in AC16 cells. (A) SpD (10 μM) increased ATP production in AC16 cells. D-galactose (10 mM) was added to reduce cytosolic glycolytic ATP production. By changing energy metabolism in cardiomyocytes by replacing glucose with galactose, high concentrations of galactose could prevent ATP production except that of mitochondria by oxidative phosphorylation (OXPHOS); (B) SpD (10 μM) increased OCR. Antimycin A (Ant, 1 μM, a Complex III inhibitor) was used as a cell-based negative control and glucose oxidase (GOx, 1 mg/mL) was used as a cell-free positive control. (C) SpD increased ATP levels under H2O2 induced oxidative stress. (D) SpD increased ATP production in the presence of doxorubicin (0.1 μM). * p < 0.05 compared with untreated controls, # p < 0.05 compared with the D-galactose-treated group.
Figure 9. SpD attenuated doxorubicin-induced mitochondrial membrane potential and mitochondrial calcium changes in AC16 cells. (A) Mitochondrial membrane potential (Δψm) in AC16 cells was indicated by TMRE fluorescence. The cells were treated with doxorubicin (0.1–1.0 μM) with/without SpD (10 μM); (B) The intensity of tetramethylrhodamine (TMRE) staining was measured using fluorometry at 550Ex/590Em nm. Doxorubicin decreased mitochondrial membrane potential in a dose-dependent manner. Co-treatment with SpD attenuated the membrane potential loss; (C) Mitochondrial calcium was localized using rhod-2, a selective indicator for mitochondrial Ca2+; and, (D) The intensity of rhod-2 was measured at 552Ex/581Em nm. Doxorubicin induced diffusion of mitochondrial Ca2+ to the cytosolic space but SpD co-treatment attenuated the Ca2+ diffusion. * p < 0.05 compared with the doxorubicin-treated group.
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