Integrated molecular-phenotypic profiling reveals metabolic control of morphological variation in a stem-cell-based embryo model
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.
Authors
- Jesse V. Veenvliet (ORCID: https://orcid.org/0000-0002-1191-2975)
- Kathrin Schmeißer (ORCID: https://orcid.org/0000-0002-4061-3034)
- Lisa M. Bauer (ORCID: https://orcid.org/0000-0002-9461-7284)
- Sofia Traikov
- Seher Ipek Gassaloglu (ORCID: https://orcid.org/0000-0002-6307-378X)
- Aydan Bulut-Karslıoğlu (ORCID: https://orcid.org/0000-0002-0413-9718)
- Aayush Poddar (ORCID: https://orcid.org/0000-0002-8030-8851)
- Tiago C. Alves (ORCID: https://orcid.org/0000-0002-4431-5886)
- Jonathan Rodenfels (ORCID: https://orcid.org/0000-0003-3538-8482)
- Ryan Savill (ORCID: https://orcid.org/0009-0000-0420-7074)
- Adriano Bolondi (ORCID: https://orcid.org/0000-0002-1096-9435)
- Natalia López-Anguita (ORCID: https://orcid.org/0000-0003-3373-7191)
- Sumit Garai (ORCID: https://orcid.org/0009-0007-0818-2207)
- Triantafyllos Chavakis
- Alba Villaronga-Luque
- Roua Rouatbi
Institutions
- Max Planck Institute for Molecular Genetics (DE)
- Center for Systems Biology Dresden (DE)
- Max Planck Institute of Molecular Cell Biology and Genetics (DE)
- Technische Universität Dresden (DE)
Publication Details
- Journal
- Cell stem cell
- Published
- 2025-04-16
- DOI
- https://doi.org/10.1016/j.stem.2025.03.012
- Citations
- 20
- Primary Topic
- 3D Printing in Biomedical Research
- Type
- article
- Field-Weighted Citation Impact
- 13.48
Funders
- Alexander von Humboldt-Stiftung
- Bundesministerium für Bildung und Forschung
- Max-Planck-Gesellschaft
- Sächsisches Staatsministerium für Wissenschaft und Kunst
- Stiftung zur Förderung der Erforschung von Ersatz- und Ergänzungsmethoden zur Einschränkung von Tierversuchen
- HORIZON EUROPE European Innovation Council