Back

PPARdelta signaling activation improves metabolic and contractile maturation of human pluripotent stem cell-derived cardiomyocytes.

Wickramasinghe, N. M.; Sachs, D.; Shewale, B.; Gonzalez, D. M.; Dhanan-Krishnan, P.; Torre, D.; LaMarca, E.; Raimo, S.; Dariolli, R.; Serasinghe, M.; Mayourian, J.; Sebra, R.; Beaumont, K. G.; Iyengar, R.; French, D. L.; Hansen, A.; Eschenhagen, T.; Chipuk, J. E.; Sobie, E. A.; Jacobs, A.; Akbarian, S.; Ischiropoulos, H.; Ma'ayan, A.; Houten, S.; Costa, K.; Dubois, N. C.

2021-07-12 cell biology
10.1101/2021.07.12.451352 bioRxiv
Show abstract

Pluripotent stem cell-derived cardiomyocytes (PSC-CMs) provide an unprecedented opportunity to study human heart development and disease. A major caveat however is that they remain functionally and structurally immature in culture, limiting their potential for disease modeling and regenerative approaches. Here, we address the question of how different metabolic pathways can be modulated in order to induce efficient hPSC-CM maturation. We show that PPAR signaling acts in an isoform-specific manner to balance glycolysis and fatty acid oxidation (FAO). PPARD activation or inhibition results in efficient respective up- or down-regulation of the gene regulatory networks underlying FAO in hPSC-CMs. PPARD induction further increases mitochondrial and peroxisome content, enhances mitochondrial cristae formation and augments FAO flux. Lastly PPARD activation results in enhanced myofibril organization and improved contractility. Transient lactate exposure, commonly used in hPSC-CM purification protocols, induces an independent program of cardiac maturation, but when combined with PPARD activation equally results in a metabolic switch to FAO. In summary, we identify multiple axes of metabolic modifications of hPSC-CMs and a role for PPARD signaling in inducing the metabolic switch to FAO in hPSC-CMs. Our findings provide new and easily implemented opportunities to generate mature hPSC-CMs for disease modeling and regenerative therapy.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

1
Journal of Molecular and Cellular Cardiology
39 papers in training set
Top 0.1%
15.1%
2
Stem Cell Reports
118 papers in training set
Top 0.1%
7.0%
3
Frontiers in Cell and Developmental Biology
218 papers in training set
Top 0.6%
6.5%
4
Cells
232 papers in training set
Top 0.2%
5.0%
5
Stem Cells Translational Medicine
11 papers in training set
Top 0.1%
4.4%
6
Scientific Reports
3102 papers in training set
Top 34%
3.7%
7
Stem Cells
28 papers in training set
Top 0.1%
3.1%
8
Nature Communications
4913 papers in training set
Top 42%
3.1%
9
iScience
1063 papers in training set
Top 6%
3.1%
50% of probability mass above
10
Stem Cell Research & Therapy
30 papers in training set
Top 0.2%
2.8%
11
eLife
5422 papers in training set
Top 33%
2.5%
12
Circulation
66 papers in training set
Top 1%
2.1%
13
Frontiers in Cardiovascular Medicine
49 papers in training set
Top 1%
1.9%
14
Cell Reports
1338 papers in training set
Top 23%
1.7%
15
Cell Death & Disease
126 papers in training set
Top 1%
1.5%
16
Journal of the American Heart Association
119 papers in training set
Top 3%
1.3%
17
Cell Reports Medicine
140 papers in training set
Top 6%
1.1%
18
Advanced Science
249 papers in training set
Top 15%
1.0%
19
PLOS ONE
4510 papers in training set
Top 62%
1.0%
20
Cardiovascular Research
33 papers in training set
Top 0.8%
0.9%
21
Communications Biology
886 papers in training set
Top 18%
0.9%
22
American Journal of Physiology-Cell Physiology
34 papers in training set
Top 0.3%
0.8%
23
Cell Proliferation
12 papers in training set
Top 0.3%
0.8%
24
Biophysical Journal
545 papers in training set
Top 5%
0.8%
25
Circulation Research
39 papers in training set
Top 1%
0.8%
26
EMBO reports
136 papers in training set
Top 6%
0.8%
27
Developmental Cell
168 papers in training set
Top 11%
0.8%
28
JCI Insight
241 papers in training set
Top 7%
0.8%
29
Nature Cardiovascular Research
28 papers in training set
Top 0.5%
0.8%
30
Aging Cell
144 papers in training set
Top 3%
0.8%