Back

Mechanical control of cell proliferation patterns in growing tissues

Carpenter, L. C.; Perez-Verdugo, F.; Banerjee, S.

2023-07-27 biophysics
10.1101/2023.07.25.550581 bioRxiv
Show abstract

Cell proliferation plays a crucial role in regulating tissue homeostasis and development. However, our understanding of how cell proliferation is controlled in densely packed tissues is limited. Here we develop a computational framework to predict the patterns of cell proliferation in growing tissues, connecting single-cell behaviors and cell-cell interactions to tissue-level growth. Our model incorporates probabilistic rules governing cell growth, division, and elimination, while also taking into account their feedback with tissue mechanics. In particular, cell growth is suppressed and apoptosis is enhanced in regions of high cell density. With these rules and model parameters calibrated using experimental data, we predict how tissue confinement influences cell size and proliferation dynamics, and how single-cell physical properties influence the spatiotemporal patterns of tissue growth. Our findings indicate that mechanical feedback between tissue confinement and cell growth leads to enhanced cell proliferation at tissue boundaries, whereas cell growth in the bulk is arrested. By tuning cellular elasticity and contact inhibition of proliferation we can regulate the emergent patterns of cell proliferation, ranging from uniform growth at low contact inhibition to localized growth at higher contact inhibition. Furthermore, mechanical state of the tissue governs the dynamics of tissue growth, with cellular parameters affecting tissue pressure playing a significant role in determining the overall growth rate. Our computational study thus underscores the impact of cell mechanical properties on the spatiotemporal patterns of cell proliferation in growing tissues.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
PLOS Computational Biology
1633 papers in training set
Top 2%
16.7%
2
Biophysical Journal
545 papers in training set
Top 0.6%
9.6%
3
PRX Life
34 papers in training set
Top 0.1%
8.7%
4
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 13%
6.0%
5
Biomechanics and Modeling in Mechanobiology
25 papers in training set
Top 0.1%
6.0%
6
Bulletin of Mathematical Biology
84 papers in training set
Top 0.3%
6.0%
50% of probability mass above
7
Physical Review Research
46 papers in training set
Top 0.1%
4.1%
8
Physical Review Letters
43 papers in training set
Top 0.1%
4.1%
9
Physical Biology
43 papers in training set
Top 0.5%
3.4%
10
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
15 papers in training set
Top 0.2%
2.5%
11
Scientific Reports
3102 papers in training set
Top 47%
2.5%
12
PLOS ONE
4510 papers in training set
Top 49%
2.0%
13
Nature Communications
4913 papers in training set
Top 49%
1.8%
14
iScience
1063 papers in training set
Top 13%
1.8%
15
Journal of The Royal Society Interface
189 papers in training set
Top 2%
1.7%
16
Nature Physics
39 papers in training set
Top 0.7%
1.6%
17
Physical Review E
95 papers in training set
Top 0.9%
1.3%
18
Journal of Theoretical Biology
144 papers in training set
Top 1%
1.2%
19
PNAS Nexus
147 papers in training set
Top 0.7%
1.2%
20
Cytoskeleton
23 papers in training set
Top 0.3%
1.2%
21
Development
440 papers in training set
Top 3%
1.1%
22
Frontiers in Physics
20 papers in training set
Top 0.7%
0.9%
23
Physical Review X
23 papers in training set
Top 0.5%
0.9%
24
eLife
5422 papers in training set
Top 60%
0.7%
25
Soft Matter
50 papers in training set
Top 0.5%
0.7%
26
Frontiers in Computational Neuroscience
53 papers in training set
Top 2%
0.7%
27
Molecular Biology of the Cell
272 papers in training set
Top 3%
0.7%
28
Science Advances
1098 papers in training set
Top 34%
0.6%