2025-04-16 マックス・プランク研究所(MPI)
<関連情報>
- https://www.mpg.de/24551303/metabolism-shapes-life
- https://www.sciencedirect.com/science/article/pii/S193459092500102X
- https://www.sciencedirect.com/science/article/pii/S1934590925001018
幹細胞を用いた胚モデルで、分子と表現型を統合したプロファイリングにより、形態変異の代謝制御が明らかになる Integrated molecular-phenotypic profiling reveals metabolic control of morphological variation in a stem-cell-based embryo model
Alba Villaronga-Luque, Ryan G. Savill, Natalia López-Anguita, Adriano Bolondi, Sumit Garai, Seher Ipek Gassaloglu, Roua Rouatbi, Kathrin Schmeisser, Aayush Poddar, Lisa Bauer, Tiago Alves, Sofia Traikov, Jonathan Rodenfels, Triantafyllos Chavakis, Aydan Bulut-Karslioglu, Jesse V. Veenvliet
Cell Stem Cell Published: April 16, 2025
DOI:https://doi.org/10.1016/j.stem.2025.03.012
Graphical abstract
Highlights
- Profiling of molecular and phenotypic variation in a model of the embryonic trunk
- Identification of early features and pathways associated with end-state morphology
- Balance of oxidative phosphorylation and glycolysis governs phenotypic end state
- Early metabolic interventions can tune the phenotypic end state
Summary
Considerable phenotypic variation under identical culture conditions limits the potential of stem-cell-based embryo models (SEMs) in basic and applied research. The biological processes causing this seemingly stochastic variation remain unclear. Here, we investigated the roots of phenotypic variation by parallel recording of transcriptomic states and morphological history in individual structures modeling embryonic trunk formation. Machine learning and integration of time-resolved single-cell RNA sequencing with imaging-based phenotypic profiling identified early features predictive of phenotypic end states. Leveraging this predictive power revealed that early imbalance of oxidative phosphorylation and glycolysis results in aberrant morphology and a neural lineage bias, which we confirmed by metabolic measurements. Accordingly, metabolic interventions improved phenotypic end states. Collectively, our work establishes divergent metabolic states as drivers of phenotypic variation and offers a broadly applicable framework to chart and predict phenotypic variation in organoids and SEMs. The strategy can be used to identify and control underlying biological processes, ultimately increasing reproducibility.
NodalシグナルとWntシグナルの制御を通じて、解糖活性が生殖細胞層の比率を指示する Glycolytic activity instructs germ layer proportions through regulation of Nodal and Wnt signaling
Kristina S. Stapornwongkul, Elisa Hahn, Patryk Poliński, Laura Salamó Palau, Krisztina Arató, LiAng Yao, Kate Williamson, Nicola Gritti, Kerim Anlas, Mireia Osuna Lopez, Kiran R. Patil, Idse Heemskerk, Miki Ebisuya, Vikas Trivedi
Cell Stem Cell Published: April 16, 2025
DOI:https://doi.org/10.1016/j.stem.2025.03.011
Graphical abstract
Highlights
- Glycolysis is needed for mesoderm and endoderm formation in gastruloids
- Exogenous glucose levels have a dose-dependent effect on germ layer proportions
- Nodal, Wnt, and Fgf signaling pathway activity is dependent on glycolysis
- Glycolysis-inhibited gastruloids can be rescued by Nodal or Wnt signaling activation
Summary
Metabolic pathways can influence cell fate decisions, yet their regulative role during embryonic development remains poorly understood. Here, we demonstrate an instructive role of glycolytic activity in regulating signaling pathways involved in mesoderm and endoderm specification. Using a mouse embryonic stem cell (mESC)-based in vitro model for gastrulation, we found that glycolysis inhibition increases ectodermal cell fates at the expense of mesodermal and endodermal lineages. We demonstrate that this relationship is dose dependent, enabling metabolic control of germ layer proportions through exogenous glucose levels. We further show that glycolysis acts as an upstream regulator of Nodal and Wnt signaling and that its influence on cell fate specification can be decoupled from its effects on growth. Finally, we confirm the generality of our findings using a human gastrulation model. Our work underscores the dependence of signaling pathways on metabolic conditions and provides mechanistic insight into the nutritional regulation of cell fate decision-making.
