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Configurational entropy is an intrinsic driver of tissue structural heterogeneity
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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10327153/ https://www.ncbi.nlm.nih.gov/pubmed/37425903 http://dx.doi.org/10.1101/2023.07.01.546933 |
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author | Srivastava, Vasudha Hu, Jennifer L. Garbe, James C. Veytsman, Boris Shalabi, Sundus F. Yllanes, David Thomson, Matt LaBarge, Mark A. Huber, Greg Gartner, Zev J. |
author_facet | Srivastava, Vasudha Hu, Jennifer L. Garbe, James C. Veytsman, Boris Shalabi, Sundus F. Yllanes, David Thomson, Matt LaBarge, Mark A. Huber, Greg Gartner, Zev J. |
author_sort | Srivastava, Vasudha |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10327153 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-103271532023-07-08 Configurational entropy is an intrinsic driver of tissue structural heterogeneity Srivastava, Vasudha Hu, Jennifer L. Garbe, James C. Veytsman, Boris Shalabi, Sundus F. Yllanes, David Thomson, Matt LaBarge, Mark A. Huber, Greg Gartner, Zev J. bioRxiv Article 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. Cold Spring Harbor Laboratory 2023-07-02 /pmc/articles/PMC10327153/ /pubmed/37425903 http://dx.doi.org/10.1101/2023.07.01.546933 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Srivastava, Vasudha Hu, Jennifer L. Garbe, James C. Veytsman, Boris Shalabi, Sundus F. Yllanes, David Thomson, Matt LaBarge, Mark A. Huber, Greg Gartner, Zev J. Configurational entropy is an intrinsic driver of tissue structural heterogeneity |
title | Configurational entropy is an intrinsic driver of tissue structural heterogeneity |
title_full | Configurational entropy is an intrinsic driver of tissue structural heterogeneity |
title_fullStr | Configurational entropy is an intrinsic driver of tissue structural heterogeneity |
title_full_unstemmed | Configurational entropy is an intrinsic driver of tissue structural heterogeneity |
title_short | Configurational entropy is an intrinsic driver of tissue structural heterogeneity |
title_sort | configurational entropy is an intrinsic driver of tissue structural heterogeneity |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10327153/ https://www.ncbi.nlm.nih.gov/pubmed/37425903 http://dx.doi.org/10.1101/2023.07.01.546933 |
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