Clonal dynamics of surface-driven growing tissues
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2023
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| _version_ | 1866911813777489920 |
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| author | Mukhamadiarov, Ruslan Ciarchi, Matteo Olmeda, Fabrizio Rulands, Steffen |
| author_facet | Mukhamadiarov, Ruslan Ciarchi, Matteo Olmeda, Fabrizio Rulands, Steffen |
| contents | The self-organization of cells into complex tissues relies on a tight coordination of cell behavior. Identifying the cellular processes driving tissue growth is key to understanding the emergence of tissue forms and devising targeted therapies for aberrant growth, such as in cancer. Inferring the mode of tissue growth, whether it is driven by cells on the surface or cells in the bulk, is possible in cell culture experiments, but difficult in most tissues in living organisms (in vivo). Genetic tracing experiments, where a subset of cells is labeled with inheritable markers have become important experimental tools to study cell fate in vivo. Here, we show that the mode of tissue growth is reflected in the size distribution of the progeny of marked cells. To this end, we derive the clone-size distributions using analytical calculations in the limit of negligible cell migration and cell death, and we test our predictions with an agent-based stochastic sampling technique. We show that for surface-driven growth the clone-size distribution takes a characteristic power-law form with an exponent determined by fluctuations of the tissue surface. Our results show how the mode of tissue growth can be inferred from genetic tracing experiments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_01923 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Clonal dynamics of surface-driven growing tissues Mukhamadiarov, Ruslan Ciarchi, Matteo Olmeda, Fabrizio Rulands, Steffen Quantitative Methods Biological Physics Cell Behavior Tissues and Organs The self-organization of cells into complex tissues relies on a tight coordination of cell behavior. Identifying the cellular processes driving tissue growth is key to understanding the emergence of tissue forms and devising targeted therapies for aberrant growth, such as in cancer. Inferring the mode of tissue growth, whether it is driven by cells on the surface or cells in the bulk, is possible in cell culture experiments, but difficult in most tissues in living organisms (in vivo). Genetic tracing experiments, where a subset of cells is labeled with inheritable markers have become important experimental tools to study cell fate in vivo. Here, we show that the mode of tissue growth is reflected in the size distribution of the progeny of marked cells. To this end, we derive the clone-size distributions using analytical calculations in the limit of negligible cell migration and cell death, and we test our predictions with an agent-based stochastic sampling technique. We show that for surface-driven growth the clone-size distribution takes a characteristic power-law form with an exponent determined by fluctuations of the tissue surface. Our results show how the mode of tissue growth can be inferred from genetic tracing experiments. |
| title | Clonal dynamics of surface-driven growing tissues |
| topic | Quantitative Methods Biological Physics Cell Behavior Tissues and Organs |
| url | https://arxiv.org/abs/2312.01923 |