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A computational modeling approach for predicting multicell spheroid patterns based on signaling-induced differential adhesion

Physiological and pathological processes including embryogenesis and tumorigenesis rely on the ability of individual cells to work collectively to form multicell patterns. In these heterogeneous multicell systems, cell-cell signaling induces differential adhesion between cells that leads to tissue-l...

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Autores principales: Sivakumar, Nikita, Warner, Helen V., Peirce, Shayn M., Lazzara, Matthew J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9747056/
https://www.ncbi.nlm.nih.gov/pubmed/36441822
http://dx.doi.org/10.1371/journal.pcbi.1010701
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author Sivakumar, Nikita
Warner, Helen V.
Peirce, Shayn M.
Lazzara, Matthew J.
author_facet Sivakumar, Nikita
Warner, Helen V.
Peirce, Shayn M.
Lazzara, Matthew J.
author_sort Sivakumar, Nikita
collection PubMed
description Physiological and pathological processes including embryogenesis and tumorigenesis rely on the ability of individual cells to work collectively to form multicell patterns. In these heterogeneous multicell systems, cell-cell signaling induces differential adhesion between cells that leads to tissue-level patterning. However, the sensitivity of pattern formation to changes in the strengths of signaling or cell adhesion processes is not well understood. Prior work has explored these issues using synthetically engineered heterogeneous multicell spheroid systems, in which cell subpopulations engage in bidirectional intercellular signaling to regulate the expression of different cadherins. While engineered cell systems provide excellent experimental tools to observe pattern formation in cell populations, computational models of these systems may be leveraged to explore more systematically how specific combinations of signaling and adhesion parameters can drive the emergence of unique patterns. We developed and validated two- and three-dimensional agent-based models (ABMs) of spheroid patterning for previously described cells engineered with a bidirectional signaling circuit that regulates N- and P-cadherin expression. Systematic exploration of model predictions, some of which were experimentally validated, revealed how cell seeding parameters, the order of signaling events, probabilities of induced cadherin expression, and homotypic adhesion strengths affect pattern formation. Unsupervised clustering was also used to map combinations of signaling and adhesion parameters to these unique spheroid patterns predicted by the ABM. Finally, we demonstrated how the model may be deployed to design new synthetic cell signaling circuits based on a desired final multicell pattern.
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spelling pubmed-97470562022-12-14 A computational modeling approach for predicting multicell spheroid patterns based on signaling-induced differential adhesion Sivakumar, Nikita Warner, Helen V. Peirce, Shayn M. Lazzara, Matthew J. PLoS Comput Biol Research Article Physiological and pathological processes including embryogenesis and tumorigenesis rely on the ability of individual cells to work collectively to form multicell patterns. In these heterogeneous multicell systems, cell-cell signaling induces differential adhesion between cells that leads to tissue-level patterning. However, the sensitivity of pattern formation to changes in the strengths of signaling or cell adhesion processes is not well understood. Prior work has explored these issues using synthetically engineered heterogeneous multicell spheroid systems, in which cell subpopulations engage in bidirectional intercellular signaling to regulate the expression of different cadherins. While engineered cell systems provide excellent experimental tools to observe pattern formation in cell populations, computational models of these systems may be leveraged to explore more systematically how specific combinations of signaling and adhesion parameters can drive the emergence of unique patterns. We developed and validated two- and three-dimensional agent-based models (ABMs) of spheroid patterning for previously described cells engineered with a bidirectional signaling circuit that regulates N- and P-cadherin expression. Systematic exploration of model predictions, some of which were experimentally validated, revealed how cell seeding parameters, the order of signaling events, probabilities of induced cadherin expression, and homotypic adhesion strengths affect pattern formation. Unsupervised clustering was also used to map combinations of signaling and adhesion parameters to these unique spheroid patterns predicted by the ABM. Finally, we demonstrated how the model may be deployed to design new synthetic cell signaling circuits based on a desired final multicell pattern. Public Library of Science 2022-11-28 /pmc/articles/PMC9747056/ /pubmed/36441822 http://dx.doi.org/10.1371/journal.pcbi.1010701 Text en © 2022 Sivakumar et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Sivakumar, Nikita
Warner, Helen V.
Peirce, Shayn M.
Lazzara, Matthew J.
A computational modeling approach for predicting multicell spheroid patterns based on signaling-induced differential adhesion
title A computational modeling approach for predicting multicell spheroid patterns based on signaling-induced differential adhesion
title_full A computational modeling approach for predicting multicell spheroid patterns based on signaling-induced differential adhesion
title_fullStr A computational modeling approach for predicting multicell spheroid patterns based on signaling-induced differential adhesion
title_full_unstemmed A computational modeling approach for predicting multicell spheroid patterns based on signaling-induced differential adhesion
title_short A computational modeling approach for predicting multicell spheroid patterns based on signaling-induced differential adhesion
title_sort computational modeling approach for predicting multicell spheroid patterns based on signaling-induced differential adhesion
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9747056/
https://www.ncbi.nlm.nih.gov/pubmed/36441822
http://dx.doi.org/10.1371/journal.pcbi.1010701
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