Changes of Metabolic Phenotype of Cardiac Progenitor Cells During Differentiation: Neutral Effect of Stimulation of AMP-Activated Protein Kinase

Abstract

Cardiac progenitor cells (CPCs) in the adult mammalian heart, as well as exogenous CPCs injected at the border zone of infarcted tissue, display very low differentiation rate into cardiac myocytes and marginal repair capacity in the injured heart. Emerging evidence supports an obligatory metabolic shift from glycolysis to oxidative phosphorylation (OXPHOS) during stem cells differentiation, suggesting that pharmacological modulation of metabolism may improve CPC differentiation and, potentially, healing properties. In this study, we investigated the metabolic transition underlying CPC differentiation toward cardiac myocytes. In addition, we tested whether activators of adenosine monophosphate-activated protein kinase (AMPK), known to promote mitochondrial biogenesis in other cell types would also improve CPC differentiation. Stem cell antigen 1 (Sca1⁺) CPCs were isolated from adult mouse hearts and their phenotype compared with more mature neonatal rat cardiac myocytes (NRCMs). Under normoxia, glucose consumption and lactate release were significantly higher in CPCs than in NRCMs. Both parameters were increased in hypoxia together with increased abundance of Glut1 (glucose transporter), of the monocarboxylic transporter Mct4 (lactate efflux mediator) and of Pfkfb3 (key regulator of glycolytic rate). CPC proliferation was critically dependent on glucose and glutamine availability in the media. Oxygen consumption analysis indicates that, compared with NRCMs, CPCs exhibited lower basal and maximal respirations with lower Tomm20 protein expression and mitochondrial DNA content. This CPC metabolic phenotype profoundly changed upon in vitro differentiation, with a decrease of glucose consumption and lactate release together with increased abundance of Tnnt2, Pgc-1α, Tomm20, and mitochondrial DNA content. Proliferative CPCs express both alpha1 and -2 catalytic subunits of AMPK that is activated by A769662. However, A769662 or resveratrol (an activator of Pgc-1α and AMPK) did not promote either mitochondrial biogenesis or CPC maturation during their differentiation. We conclude that although CPC differentiation is accompanied with an increase of mitochondrial oxidative metabolism, this is not potentiated by activation of AMPK in these cells.

Introduction

Although the adult mammalian heart has some regenerative capacity (with a turnover of cardiac myocytes inferior to 1% per year [1]), it is not enough to compensate for the loss of the millions of cells caused by myocardial infarction (a major cause of death worldwide [2]). In the past decades, several reports demonstrated that the mammalian adult heart hosts cardiac progenitor cells (CPCs) with limited healing properties to the infarcted heart [3]. However, their intrinsic capacity for regeneration after myocardial injury is very low [4] and the use of different CPC subtypes in cell therapy generally failed to efficiently restore cardiac function [5], probably because of low survival and differentiation potential of CPCs into cardiac myocytes once injected in the border zone of the infarcted tissue.

Stem cells are known to exhibit a metabolic shift during differentiation. Indeed, cardiac differentiation of embryonic stem cells (ESCs) requires a huge modification of the metabolic infrastructure with mitochondrial network development and a switch from aerobic glycolysis to OXPHOS [6 –8]. This is perhaps not unexpected since the adult heart needs a constant supply of energy to support contraction, which is mostly supplied by mitochondria that occupy about one-third of the cardiac myocyte volume [9].

Although there is a growing literature concerning the metabolic transition underlying the differentiation of ESCs and induced pluripotent stem cells (iPSC), not much is covered about CPCs. In this study, we examined metabolic adaptations of Sca1⁺ CPCs to hypoxia, a condition prevalent in the ischemic myocardium, as well as the metabolic shift accompanying their differentiation. In addition, as mitochondrial network organization is integral to stem cell differentiation into cardiac myocytes, we examined the potential of agents known to induce mitochondrial biogenesis to improve CPC differentiation. Among others, molecules activating the adenosine monophosphate-activated protein kinase (AMPK) is a worthwhile option. Indeed, AMPK is known to promote mitochondrial biogenesis through the stimulation of PGC-1alpha [10]. In parallel, AMPK has been shown to promote stem cell differentiation into specified cells such as osteocytes and endothelial cells [11,12].

Materials and Methods

Animal care

All animal procedures conformed to the Guide for the Care and Use of Laboratory Animals [19] and were approved by the Institutional Ethical Committee of the Université Catholique de Louvain (2012/UCL/MD004).

Cell isolation and differentiation

Sca1⁺ CPCs were isolated from adult mouse hearts by magnetic activated cell sorting separation (Miltenyi Biotec., Bergisch Gladbach, Germany) as previously described in [13] and adapted from [3]. Purity was checked by FACS (fluorescence-activated cell sorting) (Supplementary Fig. S1). They were amplified and cultured in plates coated with gelatin (1/10; Sigma-Aldrich; G1393) in DMEM/F-12 GlutaMAX™ (Thermo Fisher Scientific, Waltham, MA; 31331) supplemented with insulin-transferrin-selenium (ITS) (100 × diluted; Thermo Fisher Scientific; 41400045), rhFGFb (10 ng/mL; R&D System; 233-FB), epidermal growth factor (20 ng/mL; Peprotech; 315-09), leukemia inhibitory factor (LIF) (10^3 U/mL; Millipore; ESG1107), and B27 serum-free supplement (50 × diluted; Thermo Fisher Scientific; 17504044), 4-(2-hydroxyethyl)piperazine-1-ethanesulfonic acid (HEPES) (5 mM; Thermo Fisher Scientific; 15630056), and Penicillin-Streptomycin (100 × diluted; Thermo Fisher Scientific; 15140122). Cardiac myocytes from neonatal rats (NRCMs) were isolated as described in [14] and cultured in Dulbecco's modified Eagle's medium (DMEM; Thermo Fisher Scientific; 61965) with Medium 199 (20%; Thermo Fisher Scientific; 41150), fetal bovine serum (FBS) (10%; Sigma-Aldrich; F7524), and Penicillin-Streptomycin (100 × diluted). Adult cardiac myocytes (ACMs) were isolated from mice, cultured as described in [15] and were only used in Fig. 3j for immunocytochemical comparison of myocyte ultrastructure. Cardiac myocytes from neonatal mice were isolated as described in [16] and were only used in Fig. 6a for comparison of AMPK alpha1 and alpha2 expression. All other experiments used NRCMs as more tractable model, given the propensity of myocytes from neonatal mice to spontaneously dedifferentiate in culture.

Differentiation protocol was applied on CPCs using 5-azacytidine (Sigma-Aldrich; A2385) pretreatment during 3 days followed by 2 days of recovery and by 3 weeks of TGF-β1 (PeproTech; 100-21C) and l-ascorbic acid (Sigma-Aldrich; A4403) in normoxia as previously described [17]. Cells were seeded in plates coated with gelatin (1/2; Sigma-Aldrich; G1393) and, after the 3 days of treatment with 5-azacytidine, cultured in DMEM/F-12 GlutaMAX supplemented with ITS (100 × diluted), FBS (5%; Sigma-Aldrich; F7524), Horse serum (5%; Thermo Fisher Scientific; 16050), HEPES (5 mM), MEM Non-Essential Amino Acids Solution (100 × diluted; Thermo Fisher Scientific; 11140035), and Penicillin-Streptomycin (100 × diluted). In some experiments, cells were treated with A769662, an AMPK pharmacological activator (25 μM; Tocris; 3336) or resveratrol (2.5 μM; Sigma-Aldrich; R5010). For differentiation experiments, cells were treated with A769662 three times per week or with resveratrol once or three times per week after the 5-azacytidine treatment and the 2 days of recovery (on top of the TGF-β1/l-ascorbic acid treatment). The use of these concentrations is justified by preliminary observations that higher concentration of A769662 induced unspecific effects and that higher concentration of resveratrol induced lethality. We used DMSO (dimethyl sulfoxide; Sigma-Aldrich; D2660) as solvent control for A769662 and resveratrol.

Proliferation

Four thousand cells per well were plated in 96-well plates coated with gelatin (1/10). After 5 h for adhesion in normoxia, they were rinsed with PBS (phosphate buffered saline; Lonza; 17-516F) then incubated with different combinations of substrates for 48 h in normoxia (21% O₂) or hypoxia (1% O₂, Ruskinn chamber). DMEM (Merck; D5030) was used with d-(+)-glucose (Glc) (17.5 mM; Merck; G8270), sodium pyruvate (Pyr) (0.5 mM; Merck; P2256), sodium l-lactate (Lac) (10 mM; Merck; 71718), or l-glutamine solution (Gln) (2.5 mM; Sigma-Aldrich; G7513). The different media were preincubated in the respective conditions (normoxia or hypoxia) overnight. Cell number as well as cell roundness index were calculated from images taken and analyzed with a SpectraMax miniMax 300 imaging cytometer and software (Molecular Devices, Wokingham, UK). The roundness index indicates the average roundness of each object (cell) automatically identified in the image. The object roundness, also called shape factor, is defined as the ratio of the area of an object to the area of a circle with the same perimeter and is equal to \documentclass{aastex}\usepackage{amsbsy}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{bm}\usepackage{mathrsfs}\usepackage{pifont}\usepackage{stmaryrd}\usepackage{textcomp}\usepackage{portland, xspace}\usepackage{amsmath, amsxtra}\usepackage{upgreek}\pagestyle{empty}\DeclareMathSizes{10}{9}{7}{6}\begin{document}$$ { \frac { 4 { \rm { * \pi *object \;area } } } { { \rm { object \;perimete } } { { \rm { r } } ^2 } } } $$ \end{document} . A factor of 1.00 means the shape of the cell is impeccably round, whereas a factor of 0.00 means the cell is not round at all. The roundness index is inversely related to the amount of attached, spreading and dividing cells.

Metabolic analyses

Metabolite measurements

Cells were seeded in six-well plates coated with gelatin (1/10) and, after 5 h of adhesion, were rinsed with PBS and then cultured in media during 48 h under normoxic (21% O₂) or hypoxic condition (1% O₂, Ruskinn chamber). The media were preincubated in the respective conditions (normoxia or hypoxia) overnight. Glucose and lactate concentrations were measured enzymatically in filtered culture media using a CMA600 analyzer (CMA Microdialysis AB, Solna, Sweden). Proteins were lysed in radio immunoprecipitation assay (RIPA) buffer containing TRIS HCl (50 mM; Sigma-Aldrich; T3253), NaCl (150 mM; VWR; 27810), Triton X-100 (1%; Sigma-Aldrich; T9284), sodium deoxycholate (NaDOC) (0.05%; Sigma-Aldrich; D6750), ethylene diamine tetraacetic acid (EDTA) (1 mM; Sigma-Aldrich; E5134), and sodium dodecyl sulfate (SDS) (0.1%; Sigma-Aldrich; L4390) and quantified for normalization with Pierce™ BCA Protein Assay Kit (Thermo Fisher Scientific; 23225).

Oxidative metabolism measurements

Oxidative metabolism was characterized with the Seahorse XF Analyzer measuring the oxygen consumption rate (OCR) and the extracellular acidification rate (ECAR) with an XF Cell Mito Stress Test kit (Agilent Technologies, Santa Clara, CA). Cells were seeded on plates coated with fibronectin and after 72 h of proliferation, media were changed for unbuffered DMEM (Merck; D5030) with 10 mM d-(+)-glucose and 2 mM l-glutamine. Then, cells were treated with different blockers of mitochondrial function, affecting either adenosine triphosphate (ATP) synthesis (oligomycin, inhibitor of complex V; 1 μM), or stimulating the respiratory chain (FCCP; 0.45 μM) or inhibiting the respiratory chain (rotenone and antimycin A as complex I and III inhibitors, respectively; both at 0.5 μM). Proteins were lysed in NaOH 0.5 M and quantified for normalization using Protein Assay Dye Reagent (Bio-Rad; 5000006).

Gene expression and protein abundance measurements

Western blotting

Cells were lysed with RIPA buffer containing proteases and phosphatases inhibitors, then quantified with Pierce BCA Protein Assay Kit (Thermo Fisher Scientific; 23225). Equal amounts of proteins were loaded in each well of the gels. Immunoblotted signals were measured using antibodies against GLUT1 (Abcam; ab652), MCT4 (Santa Cruz Biotechnology, Inc.; sc-50329), TOMM20 (Invitrogen; PA5-52843), PGC-1alpha (Abcam; ab54481), cardiac troponin T (TNNT2; Abcam; ab33589), acetyl CoA carboxylase (ACC; Cell signaling; 3662), phospho-acetyl-CoA carboxylase (pACC; Ser79; Cell signaling; 3661), AMPK subunits alpha-1 (Millipore; 07-350), and alpha-2 (Thermo Fisher Scientific; PA5-21494). The specificity of these last two was verified in mouse embryonic fibroblast (MEF) genetically deficient in the two isoforms (MEF knockout vs. MEF wild type; provided by Prof. Luc Bertrand) as negative controls. Anti-Pfkfb3 (iPfk2) antibody was kindly provided by Prof. Salvador Moncada. The data were normalized to Heat Shock Protein 90 abundance (anti-HSP90; BD; 610419) used as loading control.

Antibodies were incubated at dilutions of 1/1,000, overnight at 4°C. Mouse and rabbit peroxidase-conjugated secondary antibodies (Jackson; 115-035-003 and 111-005-003) were incubated at a dilution of 1/5,000 during 1 h at room temperature. After chemiluminescent reaction with luminol from the ECL™ reagent (GE Healthcare, Diegem, BE or Chicago, IL; 0155854), proteins were revealed with Amersham Imager 600 (GE Healthcare) and signals were quantified using the Image J software (NIH, Bethesda, MD).

Immunofluorescence

Cells were seeded in Nunc™ Lab-Tek™ II chamber slides (VWR; 734-2049) coated with fibronectin (1/50; Sigma-Aldrich; F0895), then fixed with 4% paraformaldehyde, permeabilized with 0,1% triton and blocked with 5% BSA (bovine serum albumin; Roth; 8076). Immunofluorescence was performed using anti-TOMM20 antibody (Invitrogen; PA5-52843) to observe mitochondrial network and anti-TNNT2 (Abcam; ab33589) as a cardiac marker (both diluted 1/200). Goat anti-Rabbit Alexa488 (Invitrogen; A-11034) and goat anti-Mouse Alexa568 (Invitrogen; A-11031) were used as secondary antibodies (both diluted 1/1,000). DAPI (4′,6-diamidino-2-phenylindole) (1 μg/mL; Sigma-Aldrich; D9542) was used for the detection of nuclei. Slides were mounted with fluorescent mounting medium (Agilent-Dako; S3023). Negative controls were prepared from cells incubated with secondary antibodies and DAPI only (not shown). Images were obtained using an AxioImager fluorescence microscope with an ApoTome module (Carl Zeiss, Oberkochen, Germany).

Flow cytometry

Cells were detached with Trypsin-EDTA (0.05%) (GibcoTM; 25300054) or with Liberase™ TL Research Grade (2 min at 37°C; Roche; 5401020001) for differentiated cells, neutralized with PBS/FBS, fixed with 4% paraformaldehyde, blocked and permeabilized simultaneously with a solution (PBS, 2% FBS, 2% BSA, 1% saponin) then resuspended in FACS buffer (PBS, 0.5% BSA, 1 mM EDTA). Cells were co-stained for TOMM20 and TNNT2 (0.4 μg/100,000 cells) with associated secondary antibodies: goat anti-Rabbit secondary antibody, Alexa Fluor 488 (Invitrogen; A-11034), and goat anti-Mouse secondary antibody, Alexa Fluor 647 (Invitrogen; A-21236) (both dilution 1/1,000). Then, cells were analyzed with a FACSCanto II flow cytometer (BD Biosciences, San Jose, CA). At least 10,000 events were collected (in the fluorescein isothiocyanate [FITC] channel and allophycocyanin [APC] channel) discriminating the doublets. Mean fluorescence intensity was calculated after subtraction of the autofluorescence of the negative unstained control. Analysis was performed using FlowJo software (BD Biosciences, Franklin Lakes, NJ).

Quantitative polymerase chain reaction

mRNA

RNA was isolated from cells using Maxwell^® RSC simplyRNA Tissue Kit (Promega, Madison, WI; AS1340) with a Maxwell RSC instrument (Promega). RNA was quantified using a Nanodrop 1000 spectrophotometer (Thermo Fisher Scientific). Reverse transcription was performed with 1 μg of RNA from each sample with RevertAid RT Reverse Transcriptase (EP0441; Thermo Fisher Scientific). Quantitative real-time polymerase chain reaction (RT-qPCR) was performed with Takyon Low ROX SYBR MasterMix (Eurogentec; UF-LSMT-B0701) on a ViiA™ 7 Real-Time PCR System (Life Technologies, Carlsbad, CA, USA). Relative gene expression was determined using Livak's method [18]. Actb was used as reference gene. Each experiment was normalized to the differentiation condition (without A769662 or resveratrol treatment). The primers used to amplify cDNA sequence of interest by RT-qPCR in Mus musculus samples are listed in Table 1.

Table 1.

Nucleotide Sequences for Primers Used in Polymerase Chain Reaction

Gene symbol	Gene description	Sequences (5′ to 3′)
Mfn1	Mitofusin 1	Forward: TTGCCACAAGCTGTGTTCGG
Mfn1	Mitofusin 1	Reverse: TCTAGGGACCTGAAAGATGGGC
Mfn2	Mitofusin 2	Forward: AGAGGCAGTTTGAGGAGTGC
Mfn2	Mitofusin 2	Reverse: ATGATGAGACGAACGGCCTC
Dmn1L (Drp1)	Dynamin 1 like	Forward: TCACCCGGAGACCTCTCATT
Dmn1L (Drp1)	Dynamin 1 like	Reverse: TGCTTCAACTCCATTTTCTTCTCC
Ppargc1A (Pgc-1α)	Peroxisome proliferator-activated receptor gamma coactivator 1-alpha	Forward: CACTTCAATCCACCCAGAAAG
Ppargc1A (Pgc-1α)		Reverse: TATGGAGTGACATAGAGTGTGCTG
Actb	Actin beta	Forward: GCTTCTAGGCGGACTGTTACTGA
Actb	Actin beta	Reverse: GCCATGCCAATGTTGTCTCTTAT
Tnnt2	Troponin T2, cardiac type	Forward: GTTGGTCCTGATGAAGAAG
Tnnt2	Troponin T2, cardiac type	Reverse: GAGTCTGTAGCTCATTCAG
Myh7	Myosin heavy chain 7	Forward:ACCAACCTGTCCAAGTTCCG
Myh7	Myosin heavy chain 7	Reverse: ACTCCTCATTCAGGCCCTTG
Nkx2-5	NK2 homeobox 5	Forward: ACCCGGGAGCCTACGGTGAC
Nkx2-5	NK2 homeobox 5	Reverse: GCGCCATCCGTCTCGGCTTT

Mitochondrial DNA

Total DNA was extracted from cells using a Maxwell RSC Cell DNA Purification Kit (Promega; AS1620) with Maxwell RSC instrument (Promega). DNA quantity and purity was measured with a Nanodrop 1000 spectrophotometer (Thermo Fisher Scientific). Relative mitochondrial DNA abundance was estimated by RT-qPCR using primers for a mitochondrial gene (Mt-CO1) and normalized to the genomic DNA (Becn1). RT-qPCR was performed with 4 ng DNA with Takyon Low ROX SYBR MasterMix blue dTTP (Eurogentec; UF-LSMT-B0701) on a ViiA 7 Real-Time PCR System (Life Technologies). The primers used to amplify DNA of interest by RT-qPCR in Mus musculus and Rattus norvegicus samples are listed in Table 2.

Table 2.

Nucleotide Sequences for Primers Used in Polymerase Chain Reaction for Mitochondrial Genes (and Genomic DNA Control).

Gene symbol	Gene description	Sequences (5′ to 3′)
Mt-co1	Mitochondrially encoded cytochrome C oxidase I	Forward: GCCCCAGATATAGCATTCCC
Mm	Mitochondrially encoded cytochrome C oxidase I	Reverse: GTTCATCCTGTTCCTGCTCC
Becn1	Beclin 1	Forward: GCGGATGCAAGCTCCTAGAT
Mm	Beclin 1	Reverse: CTCGATGGCCTTATCACCCC
Mt-co1	Mitochondrially encoded cytochrome C oxidase I	Forward: ACTACTTTCTTCGACCCCGC
Rn	Mitochondrially encoded cytochrome C oxidase I	Reverse: CCAAACCCTGGAAGAATTAAGATGT
Becn1	Beclin 1	Forward: ATCCTCCAGCCTTTTGGCTC
Rn	Beclin 1	Reverse: GCCCTCACTCCTTCAGCAAT

Statistical analysis

Statistical tests were performed using GraphPadPrism (GraphPad Software, Inc., San Diego, CA). Results are reported as mean and standard error of the mean. Statistical analysis was performed using parametric or nonparametric tests where appropriate after verifying normality of values distribution. P value <0.05 is considered as significant with * meaning P value <0.05, ** meaning P value <0.01, and *** meaning P value <0.001.

Results

CPCs are highly glycolytic and tolerant to hypoxia

We first compared the basal metabolism of undifferentiated CPCs with that of more mature NRCMs in vitro and more specifically their adaptations to a hypoxic environment. Under normoxic conditions (21% O₂), glucose consumption was accompanied by a significant lactate release (Fig. 1a, b) in CPCs, whereas lactate production was very low in NRCMs. Both glucose consumption and lactate release were increased in hypoxia (1% O₂) in both cell types. The ratio of metabolites (Fig. 1c) was close to 2 mol of lactate released per mole of glucose consumed in normoxia as well as in hypoxia for CPCs, supporting a high glycolytic metabolism in both conditions. In search of key regulators of glycolytic metabolism underlying this phenotype, we next looked at the abundance of GLUT1 (Fig. 1d) that mediates the transport of glucose across the cytoplasmic membrane and of MCT4 (Fig. 1e), a monocarboxylic transporter that facilitates lactate efflux. These two transporters were expressed in CPCs as well as in NRCMs and were increased in hypoxic conditions in both cell types. Consistently, the expression of Pfkfb3 (iPfk2) (Fig. 1f), the inducible isoform of 6-phosphofructo-2-kinase, a key metabolic stimulator of glycolysis was also expressed in CPCs and NRCMs and was upregulated under hypoxia.

FIG. 1.

Effect of hypoxia on the glycolytic metabolism of CPCs compared with NRCMs. Supernatants of CPCs and of NRCMs were analyzed after 48 h of incubation in normoxia or in hypoxia. (a) Glucose consumption and (b) lactate release were measured and then normalized using protein quantification; (c) lactate/glucose ratios were calculated from (a) and (b) (n ≥ 6, mean ± SEM; one-way ANOVA followed by Holm–Sidak correction for multiple comparisons, *P < 0.05 or **P < 0.01 or ***P < 0.001: normoxic vs. hypoxic conditions; ^### P < 0.001 vs. CPCs in normoxia). The expression of (d) Glut1, (e) Mct4, and (f) iPfk2 were analyzed by western blotting (normalized to Hsp90) in CPCs and in NRCMs after 72 h of incubation in normoxia and in hypoxia. Within a cell type, the expression of proteins in hypoxia was compared with the expression in normoxic conditions (n ≥ 3; mean ± SEM; Mann–Whitney test; *P < 0.05: normoxic vs. hypoxic conditions). Representative blots for each immunoblotted protein are shown at the bottom of each bar graph. ANOVA, analysis of variance; CPCs, cardiac progenitor cells; NRCMs, neonatal rat cardiac myocytes; SEM, standard error of the mean.

CPC proliferation is critically dependent on glucose and glutamine availability

As healing properties of CPCs probably depend in part on their capacity to proliferate in the ischemic myocardium, we next examined their metabolic dependence in normoxic and hypoxic conditions. To assess on which substrates CPCs rely to proliferate, we measured their proliferation for 48 h in different combinations of substrates (Fig. 2a). The minimum combination of glucose and glutamine was essential for proliferation at a rate similar to the one obtained in the complete CPC proliferation medium. In contrast, lactate and pyruvate did not seem to influence CPC count. Furthermore, hypoxia did not affect the proliferation of CPCs after 48 h of incubation. The roundness index (Fig. 2b), inversely related to the spreading of cultured cells, similarly indicated that glucose and glutamine are necessary for the normal spreading and proliferation of CPCs.

FIG. 2.

Effect of hypoxia on CPC proliferation in presence of different combinations of substrates. (a) CPCs were counted after 48 h in normoxia (21% O₂) or in hypoxia (1% O₂) (Glc 17.5 mM; Gln 2.5 mM; Lac 10 mM; Pyr 0.5 mM; minimal medium = without Glc, Gln, Pyr, Lac; full medium = complete CPC proliferation medium; see Methods section). Measurements are expressed in percentage of cells counted at the 0 time point (% of T0). (b) The roundness index of CPC, which is inversely related to proliferation (see Methods section), was measured at the same moment (n ≥ 3; two-way ANOVA followed by Dunnett's multiple comparisons test; the absence of interaction indicated that the effect of specific media conditions did not differ between normoxia and hypoxia *P < 0.05 or **P < 0.01 or ***P < 0.001 vs. minimal medium in normoxia). Glc, glucose; Gln, glutamine; Lac, lactate; Pyr, pyruvate.

CPCs display active mitochondrial ATP production but lower basal respiration, maximal respiration, mitochondrial abundance, and branching

We next examined the oxidative metabolism of CPCs in normoxic conditions. The results showed that although CPCs, as NRCMs, displayed active mitochondrial ATP production (Fig. 3a), basal respiration, maximal respiration, and spare capacity (Fig. 3b–d) were lower in CPCs compared with NRCMs (Fig. 3e).

FIG. 3.

Oxidative metabolism in CPCs compared with NRCMs. Oxygen consumption rate allocated to (a) adenosine triphosphate production, (b) basal respiration, (c) maximal respiration, and (d) spare capacity were measured and then normalized using protein quantification (n ≥ 6, mean ± SEM; Mann–Whitney test, **P < 0.01 or ***P < 0.001). Time course curves of OCR profiles are represented in (e) (n ≥ 6, mean ± SEM). The mitochondrial abundance was evaluated with (f) the expression of Tomm20 normalized by Hsp90 in both cell types by western blot (n = 4, mean ± SEM; Mann–Whitney test, *P < 0.05) and with (g) mitochondrial DNA content (Mt-co1) normalized to nuclear DNA content (Becn1) (n = 6, mean ± SEM; Mann–Whitney test, **P < 0.01). Mitochondrial network morphology and structure were resolved after staining with anti-Tomm20 antibody in (h) CPCs, in (i) NRCMs, and in (j) ACMs. Sarcomeric structure is shown with anti-Tnnt2 antibody in red in (i) NRCMs and in (j) ACMs. ACMs, adult cardiac myocytes; OCR, oxygen consumption rate.

In search of structural changes that account for this differential oxidative metabolism, we more closely looked at mitochondrial structures. By comparison with NRCMs, CPCs exhibited a two-third decrease in expression of the outer mitochondrial membrane protein, Tomm20 (Fig. 3f) as well as a strong decrease in Mt-co1 DNA content, a component of mitochondrial DNA (Fig. 3g). Tomm20 immunofluorescent staining revealed different mitochondrial morphology and structure in CPCs and in NRCMs compared with ACMs (Fig. 3h–j). Indeed, mitochondria appeared shaped in small spheres in CPCs, slightly more branched in NRCMs, whereas they appear regularly stacked between sarcomeres in ACMs, reflecting differentially organized organelles between these three cell types.

CPCs show a decrease in glycolytic metabolism after differentiation

Having observed these specificities of proliferative CPCs (PROLIF), we next looked for potential changes under induced differentiation toward “cardiac myocytes-like” cells. After in vitro induction of CPC differentiation, their metabolic phenotype dramatically changed with a reduction by more than two-thirds of glucose consumption and lactate release (Fig. 4a, b) compared with proliferative cells. The ratio between lactate and glucose close to two in proliferative cells dramatically dropped to 1.2 mol of lactate released per mole of glucose consumed in differentiated cells (Fig. 4c). Concomitantly, the expression of Glut1, Mct4 and iPfk2 (Fig. 4d–f) was downregulated after differentiation. As expected, there was no immunodetection of Tnnt2 in nondifferentiated CPCs (Fig. 4g), whereas we could clearly detect sarcomeric organization in DIF (Fig. 4h).

FIG. 4.

Effect of in vitro differentiation of CPCs on their glycolytic metabolism. (a) Glucose consumption and (b) lactate release were measured from supernatants of PROLIF compared with DIF (after 48 h of incubation in normoxia). Results were normalized using protein quantification. (c) The ratios lactate/glucose were calculated from (a) and (b) (n ≥ 6, mean ± SEM; Mann–Whitney test, ***P < 0.001). The expression of (d) Glut1, (e) Mct4, and (f) iPfk2 were analyzed by western blotting in PROLIF compared with DIF. Results were normalized using Hsp90 (n = 6; mean ± SEM; Mann–Whitney test; **P < 0.01). Anticardiac Troponin T antibody (Tnnt2; red) staining in non-DIF (g) compared with DIF (h) by fluorescent microscopy. DIF, differentiated CPCs; PROLIF, proliferative CPCs.

CPCs show higher mitochondrial content and activity after differentiation

Under basal conditions, CPCs differentiated in vitro show a higher OCR/ECAR ratio (ratio between respiration and glycolysis) compared with PROLIF (Fig. 5a). These results confirm that the latter exhibited a proportionally higher aerobic glycolysis. In parallel, Tomm20 expression (Fig. 5b), Mt-co1 DNA content (Fig. 5c), as well as Pgc-1α expression (a master regulator of mitochondrial biogenesis) (Fig. 5d) were upregulated during differentiation. Moreover, flow cytometry analysis and immunofluorescence both revealed that “cardiac myocytes-like” cells (identified as Tnnt2 positive; Supplementary Fig. S2) display more mitochondria than Tnnt2 negative cells (Fig. 5e, f).

FIG. 5.

Effect of in vitro differentiation of CPCs on their oxidative metabolism and mitochondrial content. The (a) ratio of the OCR over the extracellular acidification rate in proliferating (PROLIF) versus DIF (n = 6, mean ± SEM; Wilcoxon matched-pairs signed rank test, *P < 0.05). The mitochondrial abundance was evaluated by measuring (b) the expression of Tomm20 in both cell states by western blot (n = 6, mean ± SEM; Mann–Whitney test, **P < 0.01; results were normalized using Hsp90 as loading control, as illustrated in the representative immunoblot); and (c) the mitochondrial Mt-co1 DNA content (n = 6, mean ± SEM; Wilcoxon matched-pairs signed rank test, *P < 0.05; results were normalized to Becn1). (d) Representative western blot for the immunodetection of Pgc1-α in PROLIF and at weeks 2, 3, and 4 of differentiation. (e) Flow cytometric measurement of Tomm20 compared between DIF (Tnnt2-positive) and Tnnt2-negative cells (n = 6, mean ± SEM; Wilcoxon matched-pairs signed rank test, ***P < 0.001). Tomm20 mean fluorescence intensity was normalized to Tnnt2-negative cells. (f) Differentiation of CPCs assessed using anticardiac Troponin T antibody (Tnnt2; red) by fluorescent microscopy. The mitochondrial abundance was assessed using anti-Tomm20 antibody (green).

AMPK is present in CPCs and is activated with A769662

We next tested whether inducers of mitochondrial biogenesis would increase the differentiation of CPCs. Activation of AMPK is known to increase mitochondrial biogenesis in other progenitors [20], as well as in skeletal muscle cells [10]. Among other properties, resveratrol is also known to activate AMPK in several cell types [21,22]. We first verified the expression of AMPK in undifferentiated CPCs. These cells indeed expressed both alpha1 and alpha2 catalytic subunits of AMPK, as illustrated in (Fig. 6a). Treatment of CPCs with the specific and direct AMPK activator A769662 induced a sustained phosphorylation of ACC (a downstream target of AMPK and reflective of AMPK activation) from 10 min to at least 6 h of incubation (Fig. 6b). However, resveratrol failed to do so in CPCs (Fig. 6c).

FIG. 6.

Effect of AMPK activation on the glycolytic metabolism of CPCs. (a) Specific immunoblotted signals for AMPK subunit α1 and α2 were detected in extracts of proliferating CPCs as well as in neonatal mouse cardiac myocytes. The specificity of the signals was tested against the negative control in MEF genetically deficient in the two isoforms (MEF knockout vs. MEF wild type). The effect of (b) A769662 (compared with its control DMSO) and of (c) resveratrol was assessed at different time points [10 min, 1 h, 6 h, 24 h (48 h only for resveratrol)] on the phosphorylation of the AMPK target ACC (measured as the ratio of phosphorylated over total abundance of ACC) (n ≥ 3, two-way ANOVA, Sidak's multiple comparisons test). (d) Glucose (Glc) consumption and (e) lactate (Lac) release after 48 h of incubation were measured from supernatants of PROLIF compared with DIF treated with or without A769662 (A; 25 μM, three times a week) and resveratrol (R1*: 2.5 μM, once weekly; R3*: 2.5 μM, three times a week) (n = 6, mean ± SEM); (f) lactate/glucose ratios calculated from (d) and (e) (n = 6, mean ± SEM) (d–f: one-way ANOVA followed by Holm–Sidak correction for multiple comparisons; *P < 0.05 or **P < 0.01 or ***P < 0.001 vs. DIF). ACC, acetyl CoA carboxylase; AMPK, adenosine monophosphate-activated protein kinase; DMSO, dimethyl sulfoxide; MEF, mouse embryonic fibroblast.

Pharmacological activation of AMPK has no effect on glucose metabolism or mitochondrial biogenesis in CPCs under differentiation

Neither A769662 nor resveratrol exerted any additional modification of glucose consumption, lactate release, or of the lactate over glucose ratio on top of the background in vitro differentiation treatment (Fig. 6d–f). Moreover, treatment with A769662 (or resveratrol) did not enhance the abundance of transcripts of Mfn1 (Fig. 7a), Mfn2 (Fig. 7b) and of the transcriptional coactivator Pgc-1α (Fig. 7d) or its proteins (Fig. 7e) over the levels observed in differentiation medium.

FIG. 7.

Effect of AMPK activation on the abundance of factors implicated in mitochondrial fusion and biogenesis. Comparative effect of differentiation medium (DIF) with or without A769662 (A; 25 μM, three times a week) and resveratrol (R1*: 2.5 μM, once weekly; R3*: 2.5 μM, three times a week) on mRNA levels of (a) Mfn1, (b) Mfn2, (c) Drp1, and (d) Pgc-1α (n ≥ 6, mean ± SEM; one-way ANOVA test followed by Dunnett or Holm–Sidak correction for multiple comparisons, ***P < 0.001 vs. DIF) and on protein abundance of (e) Pgc1-α and (f) Tomm20 (n = 6, mean ± SEM; one-way ANOVA test followed by Holm–Sidak correction for multiple comparisons, *P < 0.05 or **P < 0.01 or ***P < 0.001 vs. DIF); representative immunoblotted signals for the latter two proteins is shown as follows under (e) and (f).

Pharmacological activation of AMPK has no effect on the expression of differentiation markers in CPCs

Although differentiation of CPCs induces the expression of early (Nkx2-5) or later (Tnnt2, Myh7) cardiac lineage markers, addition of A769662 or resveratrol to the differentiation medium did not increase their abundance (Fig. 8a–d).

FIG. 8.

Effect of AMPK activation on the expression of cardiac differentiation markers. Comparative effect of differentiation medium (DIF) with or without A769662 (A; 25 μM, three times a week) and resveratrol (R1*: 2.5 μM, once weekly; R3*: 2.5 μM, three times a week) on mRNA levels of (a) Nkx2-5, (b) Tnnt2, and (c) Myh7 (n ≥ 6, mean ± SEM; one-way ANOVA test or Kruskal–Wallis test, *P < 0.05 or **P < 0.01 or ***P < 0.001 vs. DIF) and on protein abundance of (d) Tnnt2 (normalized to Hsp90 and expressed as fold of DIF condition n = 6, mean ± SEM; one-way ANOVA test followed by Dunnett test, ***P < 0.001 vs. DIF). A representative immunoblot is shown in (e).

Discussion

In this study, we show that (1) Sca1⁺ CPCs are highly glycolytic, even in normoxic conditions; (2) this glycolytic activity is decreasing with differentiation, whereas (3) their mitochondrial mass is increasing; (4) activation of AMPK is not sufficient to improve mitochondrial biogenesis in CPCs during differentiation nor to ameliorate their differentiation in vitro.

Although it becomes clearer that the beneficial effect of CPCs for cardiac function after infarction might be due to paracrine effects [23 –25], it remains essential to study CPC metabolism to enhance their survival, proliferation and differentiation to improve therapeutic interventions.

Our results support that, during proliferation, Sca1⁺ adult CPCs rely on both glucose and glutamine to proliferate. Consistently, it was shown that the inhibition of glutaminolysis reduces the proliferation in CPCs [26]. Furthermore, we demonstrate that CPCs perform aerobic glycolysis, that is, a major proportion of glucose is dedicated to lactate production, even in presence of oxygen. This characteristic is commonly observed in proliferative cells such as cancer cells [27] and different types of stem cells, for example, ESCs [28] and mesenchymal stem cells (MSCs) [20] to provide the building blocks needed for their proliferation. However, aerobic glycolysis does not seem to be due to defective mitochondrial respiration given CPC ability to display active mitochondrial ATP production in normoxia, as shown in our study. Accordingly, MSCs and human PSC (hPSC) display functional respiratory complexes while they also perform aerobic glycolysis [20,29].

Under normoxic conditions, we observed that Sca1⁺ CPCs express iPfk2 and Glut1, which were also observed in other CPC lines [26,30]. Similarly, Mct4, responsible for the elimination of the excess of intracellular lactate, was also found in MSCs [31]. Furthermore, they are adapting to hypoxia partly through the upregulation of these three proteins and by upregulating their glycolytic rate. Not surprisingly, these proteins are all regulated by the hypoxia-inducible factor (HIF) signaling pathway activated by hypoxia in the ischemic region after myocardial infarction [32]. A similar HIF1-dependent increase in Pfkfb3/Glut1 expression and glycolysis stimulation was previously depicted in MSCs [20].

After in vitro differentiation, we show that Glut1 and iPfk2, as well as the CPC high glycolytic capacity, are downregulated. A causal relationship between reduced glycolysis and differentiation was suggested from experiments where chemical or siRNA inhibition of the HIF1α-lactate dehydrogenase A axis lead to a shift toward OXPHOS and to an improved maturation of hPSC-CM [33]. Conversely, stimulation of glycolysis promotes the reprogramming of mouse embryonic fibroblasts to iPSC [34].

We also demonstrate that the appearance of sarcomeric proteins in DIF is concomitant with an increase of their mitochondrial abundance, similarly to what is described in hESC or human iPSC (hiPSC), respectively, after spontaneous or induced differentiation [35,36]. Mitochondrial biogenesis is indeed a crucial process to ensure that the mitochondrial mass matches the cells' energy demands.

The increase in mitochondrial biogenesis is sustained by an upregulation of the transcriptional coactivator Pgc-1α, as observed in MSCs undergoing osteogenic differentiation [37] as well as in ESC differentiation [35,38]. shRNA downregulation of Pgc-1α in ESC tends to decrease mitochondrial respiration during their differentiation to cardiac myocytes and their beating rate [39]. However, although a recent study showed that the overexpression of different isoforms of Pgc-1α improved skeletal myoblasts differentiation in cattle [40], the effect of the overexpression of Pgc-1α in the heart is less convincing. In fact, a previous study showed that it induces uncontrolled mitochondrial proliferation of cardiac myocytes leading to altered sarcomeric structure and to dilated cardiomyopathy [38]. Therefore, the benefit of activating Pgc-1α and mitochondrial biogenesis to enhance the differentiation of CPCs is unclear.

In this study, we tested the hypothesis that pharmacological activation of mitochondrial biogenesis could improve differentiation in CPCs. There are different activators of Pgc-1α. Among them, resveratrol is known to promote mitochondrial biogenesis both in vitro and in vivo in different cell types [41]. For example, it induces mitochondrial biogenesis through activation of SIRT1 deacetylating activity both in CAEC [42] and in HUVEC [43], which may be relevant in the context of acetylation-dependent regulation of Pgc-1α activity. The same SIRT1-mediated deacetylation of LKB1 also activates AMPK in C2C12 at moderate doses (25 μM), whereas a higher dose (50 μM) activates AMPK independently of SIRT1 [44]. AMPK is a recognized activator of mitochondrial biogenesis, in part through activation of Pgc-1α in skeletal muscle cells [10] and of differentiation, at least in some cell types such as vascular smooth muscle cell [45]. Resveratrol was shown to improve the healing properties of Sca1⁺ CPCs through upregulation of vascular endothelial growth factor (VEGF) and SDF1α, resulting in proangiogenic effects [46]. It may also increase the differentiation of hiPSC into cardiac myocytes [47], although the involvement of mitochondrial biogenesis in these effects was not specifically tested. As resveratrol has pleiotropic effects on many other signaling pathways, in our study, we decided to use a more specific agonist of AMPK, that is, A769662 [20,48].

Although we demonstrated an increase of pACC/ACC with A769662, we did not observe increased mitochondrial biogenesis with neither resveratrol nor A769662 during in vitro differentiation. Note that pACC/ACC slightly decreases at 24 h of A769662 treatment perhaps due to compensatory counter-regulation by phosphatases. Moreover, both AMPK activators combined to our classical differentiation protocol did not improve differentiation efficacy. Although we previously showed that A769662 is able to increase the expression of some mitochondrial biogenesis markers in MSCs, AMPK activation was not sufficient to switch their metabolism to OXPHOS [20]. In contrast, AMPK phosphorylation by 5-aminoimidazole-4-carboxamide-1-β-d-ribofuranosyl monophosphate (AICAR) decreases the differentiation of myoblasts into myotubes, through Pgc-1α-Foxo3A-p21 pathway [49]. Of interest, the effect of resveratrol appears to be dependent on the differentiation state, at least in PC12 cells where resveratrol exhibits a positive effect on mitochondrial number only in differentiated cells [50]. Conversely, a recent study showed that resveratrol actually enhances pluripotency of mouse embryonic stem cells (mESC) through AMPK/Ulk1 pathway activation [51]. Therefore, the lack of effect in our study may relate to the different cell type (CPC vs. PC12) or their relative immaturity in our experimental setting. Furthermore, mitochondrial biogenesis may not have been maximally stimulated despite our use of highest dose of pharmacological agents that would not induce toxicity or off-target effects.

An equally valid possibility is that mitochondrial biogenesis is simply not enough for differentiation and must be accompanied by other cellular processes. Some recent studies highlight the importance of mitophagy during CPC differentiation. Indeed, it would allow CPCs to reorganize properly their mitochondrial network during their maturation [52]. Some data show that fusion [53], fission [54], and mitochondrial dynamics in general are important for differentiation, as recently reviewed [55,56].

Given the bidirectional link between mitochondrial reactive oxygen species (ROS) and the regulation of glucose metabolism, the role of cell compartment-specific ROS production in CPC differentiation would deserve examination beyond this study. Indeed, analysis of the metabolome of ESCs indicates a shift toward a more oxidized state after differentiation [57] while differentiation of ESCs to embryoid bodies is improved with pro-oxidants and impaired by ROS scavengers [58]. Furthermore, Nox2 and Nox4 (two nicotinamide adenine dinucleotide phosphate [NADPH] oxidases) are shown to be upregulated during CPC differentiation while their targeted inhibition with adenoviruses in CPC impairs cardiac and smooth muscle differentiation [59].

In addition to glucose metabolism, as examined in this study, fatty acids may also play a key role in CPC maturation [60]. Accordingly, in hPSC-derived cardiac organoids, shifting the metabolism to fatty acid oxidation is essential for mitochondrial biogenesis, expression of sarcomeric proteins, and cell cycle exit [61]. Using hPSC-CM, others demonstrated that a change of medium from glucose to galactose and fatty acid promotes their oxidative metabolism and improves their maturation into CM [62]. Notably, oleic acids caused a strong increase of Pgc-1α in CPC-like cells after 1 week of incubation and improved their differentiation when added to their usual differentiation medium [60].

Finally, metabolism has well-recognized effects on chromatin modifications and epigenetics [63], which profoundly influence cardiac differentiation of iPSC [64]. For example, the conversion of glucose into acetyl-CoA after glycolysis was shown to induce specific histone acetylation critical for keeping the pluripotent state of ESCs [65]. Also, TP53 inducible glycolysis and apoptosis regulator (TIGAR) promote neural stem cell differentiation through acetyl-CoA-mediated histone acetylation [66]. Not surprisingly, many protocols for the differentiation of Sca1⁺ CPCs [3,67] or MSCs [68] in culture use epigenetic modulators, such as the hypomethylating agent 5-azacitydine to inhibit DNA methyltransferases allowing expression of genes usually silenced by hypermethylation in progenitors.

In conclusion, CPC glycolytic activity is dramatically downregulated upon differentiation together with an increase in mitochondrial content. However, pharmacological activation of the PGC-1α/AMPK pathway did not improve either mitochondrial biogenesis or CPC maturation during their differentiation.

Footnotes

Acknowledgments

We thank Delphine De Mulder, Roxane Verdoy, Thibaut Vazeille, Lucie Caërou, and Adrien Strapart for excellent technical support.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This study was funded by grants from the Fonds National de la Recherche Scientifique (FNRS; PDR 1.B089.14 and 3.4643.10 to JLB) and the Federation Wallonie-Bruxelles (Action de Recherche Concertée, ARC 16/21-074) to J.L.B. and L.B. A.D.P. was Chargée de Recherche and L.B. is Senior Research Director of FNRS. J.L.B. is a WELBIO investigator funded by the Walloon Region.

Supplementary Material

Supplementary Figure S1

Supplementary Figure S2

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