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A quantitative high-resolution computational mechanics cell model for growing and regenerating tissues.
Biomech Model Mechanobiol. 2020 Feb; 19(1):189-220.BM

Abstract

Mathematical models are increasingly designed to guide experiments in biology, biotechnology, as well as to assist in medical decision making. They are in particular important to understand emergent collective cell behavior. For this purpose, the models, despite still abstractions of reality, need to be quantitative in all aspects relevant for the question of interest. This paper considers as showcase example the regeneration of liver after drug-induced depletion of hepatocytes, in which the surviving and dividing hepatocytes must squeeze in between the blood vessels of a network to refill the emerged lesions. Here, the cells' response to mechanical stress might significantly impact the regeneration process. We present a 3D high-resolution cell-based model integrating information from measurements in order to obtain a refined and quantitative understanding of the impact of cell-biomechanical effects on the closure of drug-induced lesions in liver. Our model represents each cell individually and is constructed by a discrete, physically scalable network of viscoelastic elements, capable of mimicking realistic cell deformation and supplying information at subcellular scales. The cells have the capability to migrate, grow, and divide, and the nature and parameters of their mechanical elements can be inferred from comparisons with optical stretcher experiments. Due to triangulation of the cell surface, interactions of cells with arbitrarily shaped (triangulated) structures such as blood vessels can be captured naturally. Comparing our simulations with those of so-called center-based models, in which cells have a largely rigid shape and forces are exerted between cell centers, we find that the migration forces a cell needs to exert on its environment to close a tissue lesion, is much smaller than predicted by center-based models. To stress generality of the approach, the liver simulations were complemented by monolayer and multicellular spheroid growth simulations. In summary, our model can give quantitative insight in many tissue organization processes, permits hypothesis testing in silico, and guide experiments in situations in which cell mechanics is considered important.

Authors+Show Affiliations

Inria Paris & Sorbonne Université LJLL, 2 Rue Simone IFF, 75012, Paris, France. paul.van_liedekerke@inria.fr. IfADo - Leibniz Research Centre for Working Environment and Human Factors, Ardeystrasse 67, Dortmund, Germany. paul.van_liedekerke@inria.fr.Interdisciplinary Centre for Bioinformatics, Leipzig University, Härtelstr. 16-18, 04107, Leipzig, Germany.IfADo - Leibniz Research Centre for Working Environment and Human Factors, Ardeystrasse 67, Dortmund, Germany.Faculty of Physics and Earth Science, Peter Debye Institute for Soft Matter Physics, Leipzig University, Linnéstraβe 5, 04103, Leipzig, Germany.M2be, University of Zaragoza, C/ Maria de Luna s/n, 50018, Zaragoza, Spain.Interdisciplinary Centre for Bioinformatics, Leipzig University, Härtelstr. 16-18, 04107, Leipzig, Germany. Institute for Computer Science, Leipzig University, Härtelstr. 16-18, 04107, Leipzig, Germany.Faculty of Physics and Earth Science, Peter Debye Institute for Soft Matter Physics, Leipzig University, Linnéstraβe 5, 04103, Leipzig, Germany.Faculty of Physics and Earth Science, Peter Debye Institute for Soft Matter Physics, Leipzig University, Linnéstraβe 5, 04103, Leipzig, Germany.Inria Paris & Sorbonne Université LJLL, 2 Rue Simone IFF, 75012, Paris, France. dirk.drasdo@inria.fr. IfADo - Leibniz Research Centre for Working Environment and Human Factors, Ardeystrasse 67, Dortmund, Germany. dirk.drasdo@inria.fr. Interdisciplinary Centre for Bioinformatics, Leipzig University, Härtelstr. 16-18, 04107, Leipzig, Germany. dirk.drasdo@inria.fr.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

31749071

Citation

Van Liedekerke, Paul, et al. "A Quantitative High-resolution Computational Mechanics Cell Model for Growing and Regenerating Tissues." Biomechanics and Modeling in Mechanobiology, vol. 19, no. 1, 2020, pp. 189-220.
Van Liedekerke P, Neitsch J, Johann T, et al. A quantitative high-resolution computational mechanics cell model for growing and regenerating tissues. Biomech Model Mechanobiol. 2020;19(1):189-220.
Van Liedekerke, P., Neitsch, J., Johann, T., Warmt, E., Gonzàlez-Valverde, I., Hoehme, S., Grosser, S., Kaes, J., & Drasdo, D. (2020). A quantitative high-resolution computational mechanics cell model for growing and regenerating tissues. Biomechanics and Modeling in Mechanobiology, 19(1), 189-220. https://doi.org/10.1007/s10237-019-01204-7
Van Liedekerke P, et al. A Quantitative High-resolution Computational Mechanics Cell Model for Growing and Regenerating Tissues. Biomech Model Mechanobiol. 2020;19(1):189-220. PubMed PMID: 31749071.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - A quantitative high-resolution computational mechanics cell model for growing and regenerating tissues. AU - Van Liedekerke,Paul, AU - Neitsch,Johannes, AU - Johann,Tim, AU - Warmt,Enrico, AU - Gonzàlez-Valverde,Ismael, AU - Hoehme,Stefan, AU - Grosser,Steffen, AU - Kaes,Josef, AU - Drasdo,Dirk, Y1 - 2019/11/20/ PY - 2018/11/21/received PY - 2019/07/16/accepted PY - 2019/11/22/pubmed PY - 2019/11/22/medline PY - 2019/11/22/entrez KW - Cell mechanics KW - Cell-based model KW - High resolution cell model KW - Liver regeneration KW - Optical stretcher SP - 189 EP - 220 JF - Biomechanics and modeling in mechanobiology JO - Biomech Model Mechanobiol VL - 19 IS - 1 N2 - Mathematical models are increasingly designed to guide experiments in biology, biotechnology, as well as to assist in medical decision making. They are in particular important to understand emergent collective cell behavior. For this purpose, the models, despite still abstractions of reality, need to be quantitative in all aspects relevant for the question of interest. This paper considers as showcase example the regeneration of liver after drug-induced depletion of hepatocytes, in which the surviving and dividing hepatocytes must squeeze in between the blood vessels of a network to refill the emerged lesions. Here, the cells' response to mechanical stress might significantly impact the regeneration process. We present a 3D high-resolution cell-based model integrating information from measurements in order to obtain a refined and quantitative understanding of the impact of cell-biomechanical effects on the closure of drug-induced lesions in liver. Our model represents each cell individually and is constructed by a discrete, physically scalable network of viscoelastic elements, capable of mimicking realistic cell deformation and supplying information at subcellular scales. The cells have the capability to migrate, grow, and divide, and the nature and parameters of their mechanical elements can be inferred from comparisons with optical stretcher experiments. Due to triangulation of the cell surface, interactions of cells with arbitrarily shaped (triangulated) structures such as blood vessels can be captured naturally. Comparing our simulations with those of so-called center-based models, in which cells have a largely rigid shape and forces are exerted between cell centers, we find that the migration forces a cell needs to exert on its environment to close a tissue lesion, is much smaller than predicted by center-based models. To stress generality of the approach, the liver simulations were complemented by monolayer and multicellular spheroid growth simulations. In summary, our model can give quantitative insight in many tissue organization processes, permits hypothesis testing in silico, and guide experiments in situations in which cell mechanics is considered important. SN - 1617-7940 UR - https://www.unboundmedicine.com/medline/citation/31749071/A_quantitative_high-resolution_computational_mechanics_cell_model_for_growing_and_regenerating_tissues L2 - https://dx.doi.org/10.1007/s10237-019-01204-7 DB - PRIME DP - Unbound Medicine ER -
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