Proteasome-Dependent Regulation of Distinct Metabolic States During Long-Term Culture of Human iPSC-Derived Cardiomyocytes

Abstract

Rationale: The immature presentation of human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) is currently a challenge for their application in disease modeling, drug screening, and regenerative medicine. Long-term culture is known to achieve partial maturation of iPSC-CMs. However, little is known about the molecular signaling circuitries that govern functional changes, metabolic output, and cellular homeostasis during long-term culture of iPSC-CMs.

Objective: We aimed to identify and characterize critical signaling events that control functional and metabolic transitions of cardiac cells during developmental progression, as recapitulated by long-term culture of iPSC-CMs.

Methods and results: We combined transcriptomic sequencing with pathway network mapping in iPSC-CMs that were cultured until a late time point, day 200, in comparison to a medium time point, day 90, and an early time point, day 30. Transcriptomic landscapes of long-term cultured iPSC-CMs allowed mapping of distinct metabolic stages during development of maturing iPSC-CMs. Temporally divergent control of mitochondrial metabolism was found to be regulated by cAMP/PKA (protein kinase A)- and proteasome-dependent signaling events. The PKA/proteasome-dependent signaling cascade was mediated downstream by Hsp90 (heat shock protein 90), which in turn modulated mitochondrial respiratory chain proteins and their metabolic output. During long-term culture, this circuitry was found to initiate upregulation of iPSC-CM metabolism, resulting in increased cell contractility that reached a maximum at the day 200 time point.

Conclusions: Our results reveal a PKA/proteasome- and Hsp90-dependent signaling pathway that regulates mitochondrial respiratory chain proteins and determines cardiomyocyte energy production and functional output. These findings provide deeper insight into signaling circuitries governing metabolic homeostasis in iPSC-CMs during developmental progression.

Keywords: homeostasis; induced pluripotent stem cells; mitochondria; proteasome; regenerative medicine.

Figure 1:. Phenotypic analysis of morphological transformations during long-term culture of iPSC-CMs.

(A) Schematic outline of the experimental timeline employed for generation, long-term culture, and experimental analysis of iPSC-CMs. (B) Brightfield images of iPSC-CMs showing single cells, cell clusters, and monolayers after 30 days (D30), 90 days (D90), and 200 days (D200) of long-term culture. Images were taken with a Leica brightfield microscope at 20x magnification (clusters and monolayer, scale bar = 20 μm) and at 40x magnification (single cells, scale bar = 10 μm). (C) Quantification of the iPSC-CM diameter at D30, D90, and D200 was performed using the software Image J for both single cells and cell clusters. Vertical and horizontal region of interests (ROIs) were defined and a quotient of vertical/horizontal was calculated for each cell at D30 (n=23 cells), D90 (n=23 cells), and D200 (n=21 cells). (D) Quantification of iPSC-CM sarcomere length based on confocal images shown in Online Fig IA. (E) Relative mRNA expression levels of genes encoding for cardiac-specific transcripts were established via qRT-PCR. Data are expressed as mean ± s.e.m., n=2 independent cell lines per group, *P <0.05 as calculated by Student’s t-test. For (C), Mann-Whitney testing and Dunńs post-hoc test were performed. For single cells vs. clusters at D30, D90, D200 *P <0.05, **P <0.01, ***P <0.001.

Figure 2:. Adaptation of gene expression landscapes during long-term culture of iPSC-CMs.

(A) Heatmap of unsupervised clustering of iPSC-CM gene expression at D30, D90, and D200, as well as iPSCs, which cluster completely separately from iPSC-CMs. With the different time points, single iPSC-CMs show a trend to segregate into subsets. Relative gene expression based on Ct values is shown for iPSCs and iPSC-CMs at D30, D90, and D200. (B) Time-course analysis of iPSC-CM population heterogeneity, clustering, and segregation. Principal component analysis (PCA) is shown for iPSC-CMs following long-term culture for 30, 90, and 200 days. Expression analysis was normalized per cell for iPSCs and D30, D90, and D200 iPSC-CMs. (C) Relative mRNA expression levels of genes encoding for cardiac-specific, structural, mitochondrial, and metabolic transcripts as established via single-cell PCR. Data are shown for n=2 independent cell lines per group.

Figure 3:. Signaling pathway mapping indicates distinct regulation of metabolic functions during long-term culture of iPSC-CMs.

(A) Heatmap showing transcriptomic profiling of iPSC-CMs at D30, D90, and D200. Cluster analysis was performed via Euclidean distance with complete linkage. Only genes that are significant in at least one pairwise comparison are shown. (B) Venn diagram of commonly expressed genes between the indicated pairwise comparison groups. Polygons show all significantly differentially expressed (SDE) genes in the pairwise group comparisons (D200 vs D90, D200 vs D30, and D90 vs D30). Overlap area between polygons highlights the indicated intra-group comparisons (D200 vs D90 and D200 vs D30; D200 vs D90 and D90 vs D30; D200 vs D30 and D90 vs D30). (C) Profiles of relative gene expression values for significantly differentially expressed transcripts between the intra-group comparisons of D200 vs D90 and D200 vs D30. Shown are directional changes of significantly differentially expressed genes as a function of time. X-axis, day 30, day 90, and day 200; y-axis, log2 (gene expression value). Blue: downregulated; red: upregulated. Directional changes are marked in blue (decrease of expression) and red (increase of expression). (D) Top networks changed for the comparison D200 vs D90 as identified by IPA analysis (Qiagen). (E) Relative alterations in IPA pathway categories (1–7) are shown for the p-value ranges of the group comparisons D30 vs. D90, D90 vs D200, and D30 vs D200. For each comparison, p-values are shown based on significantly altered transcripts in the indicated pathways and networks, as well as the p-value ranges for given functional categories generated by IPA core analysis (Qiagen, Right-Tailed Fisher’s Exact Test). 1, Cardiovascular System Development and Function; 2, Lipid Metabolism; 3, Small Molecule Biochemistry; 4, Metabolic Disease; 5, Cell-To-Cell Signaling and Interaction; 6, Cellular Assembly and Organization; and 7, Cellular Function and Maintenance. (F) Heatmap of AmpliSeq data showing the regulation of metabolism-related transcripts in iPSC-CMs at indicated time points. (G) Cellular metabolic viability following long-term culture of iPSC-CMs. Shown are measurements of absorbance at 450 nm (relative units) of the colorimetric reaction resulting from cleavage of the XTT reagent to formazan by mitochondrial respiratory chaińs succinate dehydrogenase system. Data are shown for n=2 independent cell lines per group. (H) The mitochondrial membrane potential (MMP) is analyzed via a potential sensor dye, JC-1; 590/525 nm fluorescence ratios are shown. Potential-dependent localization of JC-1 to mitochondria is causing a shift in JC-1 fluorescence emission from 525 nm to 590 nm. A lower 590/525 nm ratio indicates mitochondrial membrane depolarization. Data are expressed as mean ± s.e.m., n=2 independent cell lines as well as 2 independent experiments per group, *P <0.05, **P <0.01, ns = not significant, as calculated by Student’s t-test.

Figure 4:. cAMP-/PKA-dependent regulation of distinct metabolic stages during long-term iPSC-CM culture.

(A) Interactome mapping for PKA using the STRING database. Relevant interaction partners previously identified via transcriptomic sequencing and IPA pathway mapping to be significantly changed at D90 and D200 (D90 vs D200) are highlighted in orange. Additional node colors are assigned by STRING database pre-sets for first shell of interactors. Second shell interactors are shown in grey. (B) PKA activity is measured in iPSC-CM lysates at indicated time points using a PKA activity assay kit (Promega). Data are expressed as mean ± s.e.m. Shown are n=2 independent cell lines as well as 2 independent experiments per group. *P <0.05, **P <0.01 as calculated by Student’s t-test. (C, D) Measurement of proteasome activity in iPSC-CMs following long-term culture. Fluorescence activity of the proteasome-specific molecule Suc-LLVY-AMC is detected following hydrolysis at 354 nm, indicating activity of (C) 20S and (D) 26S proteasome machinery. Data are expressed as mean ± s.e.m. Shown are n=2 independent cell lines as well as 2 independent experiments per group. *P <0.05, **P <0.01, ***P <0.001 as calculated by Student’s t-test. For (C-D), Mann-Whitney testing and Dunńs post-hoc test were performed. **P <0.01, ***P <0.001.

Figure 5:. Distinct metabolic stages in long-term cultured iPSC-CMs are regulated in a PKA- and proteasome-dependent manner.

(A-D) Levels of catalytic and regulatory subunits, as well as phosphorylated PKA levels (PKAcat threonine Thr197), at indicated time points following proteasome inhibition (epoximycin) and PKA activation (8-CPT) compared to control vehicle (DMSO). (A) Immunoblot analysis and (B-D) quantification of (A), normalized to loading control (tubulin). (E) Inhibition of PKA (H89) significantly reduces proteasome activity. (F-G) Metabolic viability was measured via cleavage of the XTT reagent by mitochondrial respiratory chaińs succinate dehydrogenase system, resulting in absorbance at 450 nm (relative units) for iPSC-CMs at indicated time points. Response of iPSC-CMs to modulation of the mitochondrial respiratory chain via FCCP at indicated time points is shown. XTT-based absorbance was measured at 450 nM (relative units). (F) Proteasome inhibition (epoximycin) as well as (G) PKA inhibition (H89) decrease metabolic function of iPSC-CMs at D90. (H) Oxygen consumption measured for iPSC-CMs at indicated time points. Relative fluorescence units are shown. (I-K) Human iPSC-CMs were cultured until D30 (I), D90 (J), or D200 (K), followed by culture in presence of DMSO (control vehicle) or indicated chemical modulators. All data are expressed as mean ± s.e.m. Shown are n=2 independent cell lines as well as 2 independent experiments per group. *P <0.05, **P <0.01, ***P <0.001, ns = not significant as calculated by Student’s t-test. For (F-G), Mann-Whitney testing and Dunńs post-hoc test or Studentś t-test and Sidakś post-hoc test were performed. *P <0.05, **P <0.01, ***P <0.001. Data are expressed as mean ± s.e.m.

Figure 6:. Hsp90 contributes to regulation of metabolism via the mitochondrial respiratory chain complex I.

(A-B) Human iPSC-CMs (D30) were cultured for 72 h in presence of DMSO (control vehicle) or geldanamycin (gelda) as indicated. (A) Metabolic viability was measured via the XTT reagent in iPSC-CMs at indicated time points in presence or absence of FCCP, a respiratory chain uncoupler. XTT cleavage by mitochondrial respiratory chaińs succinate dehydrogenase system results in absorbance detected at 450 nm (relative units). (B) Measurement of mitochondrial complex I activity in iPSC-CM (D30) lysates based on oxidation of NADH to NAD⁺ and simultaneous reduction of dye, resulting in increased absorbance (450 nm). (C-D) Oxygen consumption measured for iPSC-CMs at D30, shown as relative fluorescence units. (C) Treatment with DMSO (control vehicle) or geldanamycin (gelda). (D) siRNA knock-down of PKAreg vs. silencer control siRNA (siRNA control). (E-F) Cellular ATP production measured in D30 treated iPSC-CMs as indicated. Shown is % luminescence of control for (E) siRNA knock-down of PKAreg and Hsp90 vs. silencer control siRNA (siRNA control) and (F) PKA inhibition via H89 and control vehicle (DMSO). Data are expressed as mean ± s.e.m. Shown are n=2 independent cell lines as well as 2 independent experiments per group. *P <0.05, ***P <0.001 as calculated by Student’s t-test. For (A), Mann-Whitney testing and Dunńs post-hoc test were performed. *P <0.05, **P <0.01, ***P <0.001.

Figure 7:. Hsp90 contributes to metabolic regulation via modulation of the mitochondrial respiratory chain in iPSC-derived endothelial cells (iPSC-ECs).

(A-D) Human iPSC-ECs were derived from iPSC lines 1 and 2. (A) Uptake of low-density lipoprotein was detected using Dil-acetylated low-density lipoprotein followed by imaging with a brightfield microscope. Scale bar, 20 μm. (B) Quantification of (A) in 324 cells (line 1) and 227 cells (line 2) using Image J software. (C-D) Human iPSC-ECs were cultured for 48 hr in presence of 20 nM DMSO (control vehicle), geldanamycin (gelda) or epoximycin (epoxi) as indicated. (C) Metabolic viability was measured in iPSC-ECs was measured via XTT cleavage by mitochondrial respiratory chaińs succinate dehydrogenase system, resulting in absorbance at 450 nm (relative units). (D) Detection of mitochondrial complex I activity in iPSC-EC lysates as described above, followed by measurement of absorbance (450 nm). Data are expressed as mean ± s.e.m. Shown are n=2 independent cell lines as well as 2 independent experiments per group. (E) Schematic model of the PKA-proteasome-Hsp90 dependent axis of metabolic governance of cellular functions at D30, D90, and D200 of long-term culture. Geldanamycin treatment inhibits Hsp90 activity, which reduces its negative regulation of the mitochondrial respiratory chain, resulting in upregulation of metabolism and cardiomyocyte function.