Redifferentiated cardiomyocytes retain residual dedifferentiation signatures and are protected against ischemic injury.
Avraham ShakkedZachary PetroverAlla AharonovMatteo GhiringhelliKfir-Baruch UmanskyDavid KainJacob ElkahalYalin DivinskyPhong Dang NguyenShoval MiyaraGilgi FriedlanderAlon SavidorLingling ZhangDahlia E PerezRachel SarigDaria LendengoltsHanna Bueno-LevyNathaniel KastanYishai LevinJeroen BakkersLior GepsteinEldad TzahorPublished in: Nature cardiovascular research (2023)
Cardiomyocyte proliferation and dedifferentiation have fueled the field of regenerative cardiology in recent years, whereas the reverse process of redifferentiation remains largely unexplored. Redifferentiation is characterized by the restoration of function lost during dedifferentiation. Previously, we showed that ERBB2-mediated heart regeneration has these two distinct phases: transient dedifferentiation and redifferentiation. Here we survey the temporal transcriptomic and proteomic landscape of dedifferentiation-redifferentiation in adult mouse hearts and reveal that well-characterized dedifferentiation features largely return to normal, although elements of residual dedifferentiation remain, even after the contractile function is restored. These hearts appear rejuvenated and show robust resistance to ischemic injury, even 5 months after redifferentiation initiation. Cardiomyocyte redifferentiation is driven by negative feedback signaling and requires LATS1/2 Hippo pathway activity. Our data reveal the importance of cardiomyocyte redifferentiation in functional restoration during regeneration but also protection against future insult, in what could lead to a potential prophylactic treatment against ischemic heart disease for at-risk patients.
Keyphrases
- stem cells
- single cell
- genome wide
- angiotensin ii
- end stage renal disease
- ejection fraction
- heart failure
- mesenchymal stem cells
- skeletal muscle
- ischemia reperfusion injury
- electronic health record
- prognostic factors
- signaling pathway
- cross sectional
- young adults
- dna methylation
- machine learning
- rna seq
- big data
- cardiac surgery
- oxidative stress
- smoking cessation
- smooth muscle
- deep learning