Background

Heart disease is the number one cause of death and has become a significant issue to public health. Due to differences in physiology among species, animal models have limitations in modeling human pathological conditions—thus encouraging the exploration of more human relevant resources. Following the breakthrough in the development of human-induced pluripotent stem cells (hiPSCs), hiPSC-derived cardiomyocytes (hiPSC-CMs) have emerged as an unprecedented opportunity to overcome the limitations of current models in modeling human diseases and drug discovery. However, compared with primary human cardiomyocytes, hiPSC-CMs resemble fetal cardiomyocytes more closely in structure and function, imposing limitations in the use of hiPSC-CMs [1, 2]. Therefore, further enhancement of hiPSC-CMs maturity in a scalable manner has become paramount to improve applications of these cells. We and others have demonstrated that combining HIF-1α inhibition with molecules that target key pathways involved in energy metabolism could significantly promote hiPSC-CMs to be both structurally and functionally more mature [3, Full size image

GO term analysis was performed using the differentially expressed proteins. Notably, in E10-treated hiPSC-CMs, top upregulated GO terms of biological process (BP) were associated with mitochondrial function and fatty acid metabolism (Fig. 6B). Based on cellular component (CC) and molecular function (MF), top GO terms were also related to mitochondrial metabolism (Fig. 6C). KEGG pathway analysis of the upregulated proteins in the E10-treated cells indicated upregulation of pathways associated with oxidative phosphorylation, metabolic pathways and citrate cycle (Fig. 6C). In addition, fatty acid degradation, cardiac contraction and PPAR signaling were also present in the upregulated KEGG pathways.

The String protein–protein interaction analysis identified a large number of differentially expressed proteins that are involved in the oxidative phosphorylation pathway. The high connectivity among these proteins further indicated their important roles in oxidative phosphorylation (Fig. 6D).

Detailed examination of the upregulated differentially expressed proteins identified the key proteins associated with mitochondrial biogenesis, TCA cycle and oxidative phosphorylation (Fig. 6E). These upregulated proteins included eight enzymes that catalyze the TCA cycle—CS, ACO2, IDH3A, IDH3B (isocitrate dehydrogenase (NAD(+)) 3 non-catalytic subunit beta), IDH3G (isocitrate dehydrogenase (NAD(+)) 3 non-catalytic subunit gamma), OGDHL (oxoglutarate dehydrogenase L), OGDH, DLST, DLD, SUCLG1 (succinate-CoA ligase GDP/ADP-forming subunit alpha), SUCLA2 (succinate-CoA ligase ADP-forming subunit beta), SDHA, SDHB, FH and MDH2 (malate dehydrogenase 2). In agreement with RNA-seq, E10 treatment upregulated SLC2A4, MT-CO2, CKMT2, PDHA1, PDHX, DLAT, DLD and another PDH E1 subunit PDHB.

In agreement with the observation in RNA-seq data, many important proteins in mitochondrial electron transport chains were upregulated in E10-treated cells. Specifically, we observed upregulated proteins in complex I—NADH dehydrogenase MT-ND2 and MT-ND5—and several NADH:ubiquinone oxidoreductase subunits—NDUFAF3, NDUFA12, NDUFA4, NDUFS2, NDUFA9, NDUFA5, NDUFAB1, NDUFA1, NDUFA3, NDUFS5, NDUFA8, NDUFC2, NDUFAF4, NDUFS8, NDUFB9, NDUFB1, NDUFB8, NDUFB11, NDUFS4, NDUFB3, NDUFB5, NDUFA2, NDUFA7, NDUFA11, NDUFA10 and NDUFS7. Upregulation of SDHA and SDHB in complex II was detected with upregulated SDHB being detected by RNA-seq as well. Additionally, UQCR subunits—UQCR10, UQCRB, UQCRC1 and UQCRH—in complex III and terminal components of the respiratory chain—COA6, COX6B1, COX6C, COX7A2 and COX7B—were upregulated. In line with our RNA-seq data, several subunits of ATP synthase F1 and F0 complex were upregulated, including ATP5A1, ATP5B, ATP5C1, ATP5O (ATP5PO, ATP synthase F1 subunit OSCP), ATP5H (ATP5PD, mitochondrial F0 complex, subunit D), ATP5I (ATP5ME, mitochondrial F0 complex, subunit E), ATP5L (ATP5MG, mitochondrial F0 complex, subunit G) and ATP5J (ATP5PF, mitochondrial F0 complex, subunit F). Also, E10-treated cells had increased expression of several solute carriers (SLC) family 25 members, including SLC25A24, SLC25A11, SLC25A5, SLC25A13 and SLC25A4. These results indicated an increased capacity of electron translocation for respiration and ATP synthesis in E10-treated cells.

Upregulation of many important proteins involved in fatty acid metabolism was also indicated. These included fatty acid-binding proteins FABP3 and FABP7, which are the intracellular fatty acid-binding proteins that regulate the uptake and transport of long-chain fatty acids into cells. The expression of SLC27A4 also increased, suggesting enhanced capacity of fatty acid uptake in E10-treated cells upon entry in cells and within cells. E10-treated cells had increased expression of acyl-CoA synthases (ACSs, which catalyze the process of fatty acid activation into fatty acyl-CoAs), including long-chain family members ACSL1, ACSL3 and short-chain family members ACSS2, ACSS3. Intriguingly, we found the upregulation of CPT1B (carnitine palmitoyltransferase 1B), carnitine acyl-carnitine translocase SLC25A20 and CPT2 (carnitine palmitoyltransferase 2). All of which are essential proteins in transporting long-chain fatty acyl-CoAs from the cytoplasm into mitochondria. Notably, E10-treated cells had upregulated MYLCD (malonyl-CoA decarboxylase, which catalyzes the breakdown of malonyl-CoA that inhibits CPT1, thus increasing the rate of CPT1-mediated fatty acid transport). E10 treatment also resulted in the upregulation of several enzymes which are essential to FAO process, including ACOX1 (acyl-CoA oxidase 1), ACADM, HADHA (hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex subunit alpha), HADHB and HADH (hydroxyacyl-CoA dehydrogenase). In addition, CROT (carnitine O-octanoyltransferase) and CRAT (carnitine O-acetyltransferase), BDH1 (3-hydroxybutyrate dehydrogenase 1) and ACAA1 (acetyl-CoA acyltransferase 1) involved in peroxisomal fatty acid oxidation as well as the key enzymes EC1 and EC2 in β-oxidation of unsaturated fatty acids were also upregulated. Collectively, the upregulation of the above essential proteins in E10-treated cells demonstrated increased consumption of fatty acid for the cell energy demand. Furthermore, comparison of the RNA-seq with proteomic data revealed a subset of overlap** genes and proteins that were differentially expressed in E10-treated cells. Specifically, 90 of them were upregulated and 25 were downregulated, respectively (Fig. 6G).

Together, these results revealed that E10 upregulated key regulators of mitochondrial function and FAO, which was consistent with improved metabolic maturation in E10-treated 3D hiPSC-CMs.

Metabolomics identified enhanced energy-related metabolic pathways in E10-treated hiPSC-CMs

To gain additional understanding of the metabolic differences associated with AMPK activation, we performed untargeted metabolomic analysis using HILIC (ultra-high-resolution mass spectrometry with hydrophilic interaction liquid chromatography) to compare the metabolic profile of E10-treated hiPSC-CMs with their DMSO-treated counterparts. Of the 9903 features analyzed, 917 features significantly changed in E10-treated hiPSC-CMs from DMSO controls (P < 0.05). Principal component analysis (PCA) of the metabolic profiles between E10-treated hiPSC-CMs and DMSO controls showed a clear separation of metabolome between the two cultures (Fig. 7A). Unsupervised two-way hierarchical analysis of the significant features confirmed the distinction of metabolic profiles between the E10-treated hiPSC-CMs and DMSO controls (Fig. 7C, Metabolic feature table in Additional file 3).

Fig. 7
figure 7

Metabolomics analysis identifies enhanced energy-related metabolic pathways in E10-treated hiPSC-CMs. A Three-dimensional principal component analysis (PCA) score plot based on metabolite abundance measured as ion peak intensities showing a significant separation between E10-treated and DMSO-treated hiPSC-CMs (n = 6 cultures). B Volcano plot illustrating discriminatory metabolites between E10-treated and DMSO-treated hiPSC-CMs. C Hierarchical clustering using the top 600 discriminatory features. D Enriched metabolic pathways using the 84 discriminatory metabolites. Significantly affected pathways were identified based on negative Log10 (P value < 0.05) and comprising of ≥ 3 metabolites per pathway. Comparison of E intermediates in glycolysis pathway, F lipoamide in TCA cycle, intermediates in carnitine shuttle including, G long-chain and H medium- or short-chain acyl-carnitines between E10-treated and DMSO-treated hiPSC-CMs. Data are presented as mean ± SEM. *P < 0.05; **P < 0.01; ***P < 0.001 and ****P < 0.0001 (two-sided unpaired t-test)

To identify the significantly affected pathways, we performed pathway enrichment analysis on the 917 metabolic features that were different between the groups and identified 12 pathways that were enriched in E10-treated hiPSC-CMs. Top pathways included multiple mitochondria and energy metabolism-related activities, including lysine metabolism, carnitine shuttle, vitamin B12 (cyanocobalamin) metabolism, glycerophospholipid metabolism, ubiquinone biosynthesis, arginine and proline metabolism, pentose phosphate pathway, TCA cycle, phosphatidylinositol phosphate metabolism, urea cycle/amino group metabolism, androgen and estrogen biosynthesis and metabolism, pentose and glucuronate interconversions (Fig. 7D).

In E10-treated cells, two intermediates of the glycolysis pathway, D-glucose-6-phosphate and fructose-1,6-bisphosphate, were significantly decreased, while the level of D-glucose and pyruvate was not significantly different compared with DMSO-treated cells (Fig. 7E). In addition, the level of lipoamide was significantly increased in E10-treated cells (Fig. 7F). Lipoamide acts as an essential cofactor for mitochondrial 2-ketoacid dehydrogenases that are key enzymes in TCA cycle, which include PDH, OGDH and branched-chain ketoacid dehydrogenase (BCKDH) [20,21,22]. Combined results in  RNA-seq and Proteomics on upregulated PDH, OGDH and BCKDH, the increased level of lipoamide further suggested an enhanced TCA cycle in E10-treated hiPSC-CMs based on our findings in GO and KEGG pathway analysis.

Among the upregulated pathways, carnitine shuttle system is responsible for the transport of fatty acids into mitochondria for subsequent β-oxidation. Upon cellular entry, fatty acids are activated into fatty acyl-CoAs by ACSs followed by conjugation to carnitine forming fatty acyl-carnitines catalyzed by CPT1B and located in the outer mitochondrial membrane. Fatty acyl-carnitines then diffuse across the mitochondrial membrane by action of carnitine acyl-carnitine translocase (SLC25A20) located on inner mitochondrial membrane. Once within mitochondria, carnitine is released from fatty acyl-carnitines by CPT2 and transferred back to cytoplasm, while fatty acyl-CoAs enter β-oxidation. Interestingly, E10 treatment significantly reduced the level of fatty acyl-carnitines in E10-treated cells compared to DMSO control (Fig. 7G and H). Specifically, we found marked, lower levels of short-chain fatty acyl-carnitine propionyl-carnitine, two medium-chain fatty acyl-carnitines (octadecenoyl-carnitine and hexadecenoyl-carnitine) and five long-chain fatty acyl-carnitines (L-palmitoyl-carnitine, linoelaidyl-carnitine, stearoyl-carnitine, arachidyl-carnitine and myristoyl-carnitine). Together, they imply elevated fatty acid β-oxidation in E10-treated cells.

Overall, these findings suggested AMPK activation-induced metabolic changes and promoted metabolic flux in energy-related metabolisms in hiPSC-CMs. These results demonstrate consistency with our findings in RNA-seq and proteomics analyses and reveal the upregulated expression profile of key regulators in carnitine shuttle system which remarkably facilitated fatty acids transportation and β-oxidation.

AMPK activator-treated hiPSC-CMs enabled pathological modeling

Based on aforementioned assessments of multiple features associated with metabolic maturation and extensive omic analyses, we concluded that E10 treatment could drive significantly increased FAO and metabolic maturation in 3D hiPSC-CMs. In addition, the expression of ADRB1 (adrenergic receptor B1) was significantly upregulated in AMPK-activated hiPSC-CMs (Fig. 8A). Given that the metabolic switch from FAO to glycolysis is associated with heart failure [23], we examined if E10-treated 3D hiPSC-CMs could model pathological response and recapitulate some of the changes related to heart failure including glycolysis enhancement, lipid accumulation and apoptosis. Three-dimensional hiPSC-CMs were first treated with E10 for 7 days to promote cardiomyocyte maturation. The cells were then treated with isoproterenol (100 µM), a small molecule adrenergic agonist to simulate pathological conditions for 6 days in hypoxic environment and low-glucose medium. The treatment with pathological stimuli increased glycolysis, glycolytic capacity and glycolytic reserve compared with no pathological stimuli in E10-treated cells, as detected by the extracellular acidification rate (ECAR; index of glycolytic activity) using the Seahorse assay (Fig. 8B). In contrast, the treatment of pathological stimuli did not alter glycolysis, glycolytic capacity and glycolytic reserve in immature cells (without E10 treatment) (Fig. 8B). Consistently, E10-treated cells but not immature cells had significant upregulation of the glycolysis-related genes including SLC2A1, GAPDH, LDHA and PKM2 under the treatment with pathological stimuli compared with cells without the treatment with pathological stimuli (Fig. 8C). These results indicate that E10-treated hiPSC-CMs had increased glycolysis when challenged with pathological stimuli, a pathological response associated with heart failure [7].

Fig. 8
figure 8

E10-treated hiPSC-CMs enhance pathological modeling. E10-treated and immature (without E10 treatment) hiPSC-CMs were subjected to pathological stimulation (H + ISO) and analyzed for pathological outcomes. A Expression of ADRB1 (n = 3 cultures). B Representative kinetics of ECAR and quantification of glycolysis, glycolytic capacity and glycolytic reserve (n = 4 cultures). C Expression of genes associated with glycolysis and D biosynthesis of triacylglycerol CD36, PLIN2 and HSL (n = 3 cultures). E Quantitative analysis of Nile red staining by ArrayScan (n = 5 cultures). F Relative ATP content (n = 7 cultures), G relative cell viability (n = 5 cultures), H cell count (n = 3 cultures) and I caspase 3/7 activity (n = 6 cultures). Data are presented as mean ± SEM. *P < 0.05; **P < 0.01; ***P < 0.001 and ****P < 0.0001 (two-sided unpaired t-test). 2-DG, 2-Deoxy-d-glucose; CD36, cluster of differentiation 36; E10, EX229 at 10 µM; ECAR, Extracellular acidification rate; GAPDH, Glyceraldehyde-3-phosphate dehydrogenase; H, Hypoxia; ISO, Isoproterenol; HSL, Lipase E, hormone-sensitive type; LDHA, Lactate dehydrogenase A; Oligo, Oligomycin; PKM2, Pyruvate kinase M1/2; PLIN2, Perilipin 2 and SLC2A1, Solute carrier family 2 member 1

The pathological stimuli also induced the upregulation of triacylglycerol synthesis-associated gene CD36 (cluster of differentiation 36) and PLIN2 (Perilipin 2; a marker of lipid accumulation) in E10-treated 3D hiPSC-CMs but not in immature cells (Fig. 8D). In addition, the expression of HSL (LIPE; Lipase E, hormone-sensitive type) that hydrolyzes stored triglycerides to free fatty acids was downregulated in E10-treated hiPSC-CMs when challenged with pathological stimuli (Fig. 8D). Consistently, an increased accumulation of lipid droplets was observed in E10-treated hiPSC-CMs when challenged with pathological stimuli as detected by ArrayScan analysis of Nile red staining (Fig. 8E). Increased accumulation of lipid droplets is also a pathological response associated with heart failure [24].

In addition to the change in glycolysis and lipid accumulation, the pathological stimuli resulted in significantly increased cell death (Fig. 8F–I). Following the treatment of pathological stimuli, E10-treated cells had twofold decreased ATP content while immature hiPSC-CMs had 29% decreased ATP content compared with parallel cultures without the treatment of pathological stimuli. Similarly, the treatment of pathological stimuli resulted in higher magnitude of decrease in cell viability and cell counts in E10-treated cells compared with immature cells. In addition, increased caspase 3/7 activity was observed in E10-treated cells when challenged with the pathological stimuli.

These results suggest that E10-treated hiPSC-CMs responded to pathological stimuli, which was not achievable in immature hiPSC-CMs. Thus, E10-treated hiPSC-CMs have advantages for pathological modeling.