Abstract

How paracrine signals are interpreted to yield multiple cell fate decisions in a dynamic context during human development in vivo and in vitro remains poorly understood. Here we report an automated tracking method to follow signaling histories linked to cell fate in large numbers of human pluripotent stem cells (hPSCs). Using an unbiased statistical approach, we discover that measured BMP signaling history correlates strongly with fate in individual cells. We find that BMP response in hPSCs varies more strongly in the duration of signaling than the level. However, both the level and duration of signaling activity control cell fate choices only by changing the time integral. Therefore, signaling duration and level are interchangeable in this context. In a stem cell model for patterning of the human embryo, we show that signaling histories predict the fate pattern and that the integral model correctly predicts changes in cell fate domains when signaling is perturbed. Our data suggest that mechanistically, BMP signaling is integrated by SOX2.

The interpretation of the key developmental signal BMP remains poorly understood. Here, the authors show that the total time-integrated signaling controls differentiation in a stem cell embryo model and provide a possible mechanism.

Details

Title
Time-integrated BMP signaling determines fate in a stem cell model for early human development
Author
Teague, Seth 1   VIAFID ORCID Logo  ; Primavera, Gillian 1 ; Chen, Bohan 2   VIAFID ORCID Logo  ; Liu, Zong-Yuan 3 ; Yao, LiAng 3 ; Freeburne, Emily 3 ; Khan, Hina 3 ; Jo, Kyoung 3 ; Johnson, Craig 3 ; Heemskerk, Idse 4   VIAFID ORCID Logo 

 University of Michigan, Department of Biomedical Engineering, Ann Arbor, USA (GRID:grid.214458.e) (ISNI:0000 0004 1936 7347) 
 University of Michigan Medical School, Department of Computational Medicine and Bioinformatics, Ann Arbor, USA (GRID:grid.214458.e) (ISNI:0000000086837370) 
 University of Michigan Medical School, Department of Cell and Developmental Biology, Ann Arbor, USA (GRID:grid.214458.e) (ISNI:0000000086837370) 
 University of Michigan, Department of Biomedical Engineering, Ann Arbor, USA (GRID:grid.214458.e) (ISNI:0000 0004 1936 7347); University of Michigan Medical School, Department of Computational Medicine and Bioinformatics, Ann Arbor, USA (GRID:grid.214458.e) (ISNI:0000000086837370); University of Michigan Medical School, Department of Cell and Developmental Biology, Ann Arbor, USA (GRID:grid.214458.e) (ISNI:0000000086837370); University of Michigan Medical School, Center for Cell Plasticity and Organ Design, Ann Arbor, USA (GRID:grid.214458.e) (ISNI:0000000086837370); University of Michigan, Department of Physics, Ann Arbor, USA (GRID:grid.214458.e) (ISNI:0000 0004 1936 7347) 
Pages
1471
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2927882597
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.