Microscopic biophysical model of self-organization in tissue due to feedback between cell- and macroscopic-scale forces
We develop a microscopic biophysical model for self-organization and reshaping of artificial tissue, that is codriven by microscopic active forces between cells and an extracellular matrix (ECM), and macroscopic forces that develop within the tissue, finding close agreement with experiment. Microsco...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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American Physical Society
2020-11-01
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| Series: | Physical Review Research |
| Online Access: | http://doi.org/10.1103/PhysRevResearch.2.043217 |
| _version_ | 1797211236871438336 |
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| author | J. P. Hague P. W. Mieczkowski C. O'Rourke A. J. Loughlin J. B. Phillips |
| author_facet | J. P. Hague P. W. Mieczkowski C. O'Rourke A. J. Loughlin J. B. Phillips |
| author_sort | J. P. Hague |
| collection | DOAJ |
| description | We develop a microscopic biophysical model for self-organization and reshaping of artificial tissue, that is codriven by microscopic active forces between cells and an extracellular matrix (ECM), and macroscopic forces that develop within the tissue, finding close agreement with experiment. Microscopic active forces are stimulated by μm-scale interactions between cells and the ECM within which they exist, and when large numbers of cells act together these forces drive, and are affected by, macroscopic-scale self-organization and reshaping of tissues in a feedback loop. To understand this loop, there is a need to (1) construct microscopic biophysical models that can simulate these processes for the very large number of cells found in tissues, (2) validate and calibrate those models against experimental data, and (3) understand the active feedback between cells and the extracellular matrix, and its relationship to macroscopic self-organization and reshaping of tissue. Our microscopic biophysical model consists of a contractile network representing the ECM, that interacts with a large number of cells via dipole forces, to describe macroscopic self-organization and reshaping of tissue. We solve the model using simulated annealing, finding close agreement with experiments on artificial neural tissue. We discuss the calibration of model parameters. We conclude that feedback between microscopic cell-ECM dipole interactions and tissue-scale forces is a key factor in driving macroscopic self-organization and reshaping of tissue. We discuss the application of the biophysical model to the simulation and rational design of artificial tissues. |
| first_indexed | 2024-04-24T10:23:17Z |
| format | Article |
| id | doaj.art-e53505b5184c40b7a136d0a45f39b645 |
| institution | Directory Open Access Journal |
| issn | 2643-1564 |
| language | English |
| last_indexed | 2024-04-24T10:23:17Z |
| publishDate | 2020-11-01 |
| publisher | American Physical Society |
| record_format | Article |
| series | Physical Review Research |
| spelling | doaj.art-e53505b5184c40b7a136d0a45f39b6452024-04-12T17:03:45ZengAmerican Physical SocietyPhysical Review Research2643-15642020-11-012404321710.1103/PhysRevResearch.2.043217Microscopic biophysical model of self-organization in tissue due to feedback between cell- and macroscopic-scale forcesJ. P. HagueP. W. MieczkowskiC. O'RourkeA. J. LoughlinJ. B. PhillipsWe develop a microscopic biophysical model for self-organization and reshaping of artificial tissue, that is codriven by microscopic active forces between cells and an extracellular matrix (ECM), and macroscopic forces that develop within the tissue, finding close agreement with experiment. Microscopic active forces are stimulated by μm-scale interactions between cells and the ECM within which they exist, and when large numbers of cells act together these forces drive, and are affected by, macroscopic-scale self-organization and reshaping of tissues in a feedback loop. To understand this loop, there is a need to (1) construct microscopic biophysical models that can simulate these processes for the very large number of cells found in tissues, (2) validate and calibrate those models against experimental data, and (3) understand the active feedback between cells and the extracellular matrix, and its relationship to macroscopic self-organization and reshaping of tissue. Our microscopic biophysical model consists of a contractile network representing the ECM, that interacts with a large number of cells via dipole forces, to describe macroscopic self-organization and reshaping of tissue. We solve the model using simulated annealing, finding close agreement with experiments on artificial neural tissue. We discuss the calibration of model parameters. We conclude that feedback between microscopic cell-ECM dipole interactions and tissue-scale forces is a key factor in driving macroscopic self-organization and reshaping of tissue. We discuss the application of the biophysical model to the simulation and rational design of artificial tissues.http://doi.org/10.1103/PhysRevResearch.2.043217 |
| spellingShingle | J. P. Hague P. W. Mieczkowski C. O'Rourke A. J. Loughlin J. B. Phillips Microscopic biophysical model of self-organization in tissue due to feedback between cell- and macroscopic-scale forces Physical Review Research |
| title | Microscopic biophysical model of self-organization in tissue due to feedback between cell- and macroscopic-scale forces |
| title_full | Microscopic biophysical model of self-organization in tissue due to feedback between cell- and macroscopic-scale forces |
| title_fullStr | Microscopic biophysical model of self-organization in tissue due to feedback between cell- and macroscopic-scale forces |
| title_full_unstemmed | Microscopic biophysical model of self-organization in tissue due to feedback between cell- and macroscopic-scale forces |
| title_short | Microscopic biophysical model of self-organization in tissue due to feedback between cell- and macroscopic-scale forces |
| title_sort | microscopic biophysical model of self organization in tissue due to feedback between cell and macroscopic scale forces |
| url | http://doi.org/10.1103/PhysRevResearch.2.043217 |
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