Configurational entropy is an intrinsic driver of tissue structural heterogeneity
Abstract
Tissues comprise ordered arrangements of cells that can be surprisingly disordered in their details. How the properties of single cells and their microenvironment contribute to the balance between order and disorder at the tissue-scale remains poorly understood. Here, we address this question using the self-organization of human mammary organoids as a model. We find that organoids behave like a dynamic structural ensemble at the steady state. We apply a maximum entropy formalism to derive the ensemble distribution from three measurable parameters – the degeneracy of structural states, interfacial energy, and tissue activity (the energy associated with positional fluctuations). We link these parameters with the molecular and microenvironmental factors that control them to precisely engineer the ensemble across multiple conditions. Our analysis reveals that the entropy associated with structural degeneracy sets a theoretical limit to tissue order and provides new insight for tissue engineering, development, and our understanding of disease progression.
Copyright and License
Acknowledgement
We thank the members of the Gartner Lab and CZ Biohub Theory Group for their valuable suggestions. We particularly thank Dr. Rob Phillips (Caltech) for guidance on analytical approaches during the early stages of this project. This work was funded by the NCI PS-ON grant (U01CA244109) and Department of Defense Era of Hope Expansion Award (W81XWH-13-1-0221) to Z.J.G., the UCSF Center for Cellular Construction (DBI-1548297), and the Barbara and Gerson Bakar Foundation. Z.J.G. is a Chan Zuckerberg BioHub Investigator. V.S. was supported by the Zena Werb Memorial Fellowship through the Helen Diller Family Cancer Center at UCSF. J.L.H. was supported by the NSF Graduate Research Fellowship. FACS was performed on BD Aria 3, supported in part by HDFCCC Laboratory for Cell Analysis Shared Resource Facility through a grant from NIH (P30CA082103). Most lentivirus particles were generated by the ViraCore at UCSF (https://viracore.ucsf.edu).
Contributions
V.S., J.L.H and Z.J.G. conceptualized and designed the experiments and the model. V.S. and J.L.H conducted experiments on reconstituted human mammary organoids, analyzed all the data and developed the computational lattice model. J.L.H wrote the script for the quantification of organoid images. V.S., J.L.H and B.V. developed the analytical model. S.F.S. collected and conducted immunostaining on tissue sections of the human breast. J.C.G. and M.A.L provided patient-derived human mammary epithelial cells and assisted in their culture. D.Y. and G.H. provided feedback on the theory and analytical models. V.S. and Z.J.G. wrote the manuscript. All other authors reviewed the manuscript and provided feedback.
Data Availability
All source data will be made available upon publication. Custom MATLAB and R scripts are publicly available through GitHub as:
Code for image analysis - https://github.com/Gartner-Lab/Organoid_Image_Processing.
Code for lattice models - https://github.com/Gartner-Lab/BCC_Lattice_Model.
Additional Information
Detailed descriptions for all experimental, analytical, and computational approaches are provided in the Supplemental Information.
Conflict of Interest
Z.J.G. is an equity holder in Scribe biosciences, Provenance Bio, and Serotiny.
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Additional details
- PMCID
- PMC10327153
- Caltech groups
- Division of Biology and Biological Engineering, Tianqiao and Chrissy Chen Institute for Neuroscience