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Size scaling in collective cell growth
Rocky Diegmiller1,2, Caroline A Doherty2,3, Tomer Stern2,3
1Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ 08544, USA.
Development (Cambridge, England)
|August 31, 2021
Summary
We developed a new supervised learning method to quantify cell growth dynamics in multicellular structures. This approach reveals linear scaling laws in nurse cell growth during oogenesis.
Area of Science:
- Developmental Biology
- Quantitative Biology
- Cell Biology
Background:
- Size is crucial for biological function, with scaling laws historically applied to single cells.
- Quantitative studies of multicellular growth dynamics have been limited by imaging and processing challenges.
Purpose of the Study:
- To present a supervised learning approach for quantifying germline cyst growth during oogenesis.
- To uncover groupwise developmental dynamics and differential organelle growth rates.
Main Methods:
- Utilized a supervised learning framework for image analysis.
- Quantified growth dynamics of germline cysts and their constituent cells and organelles.
- Identified inter-organelle volumetric scaling laws.
Main Results:
- Discovered groupwise developmental dynamics influencing cell growth patterns.
- Observed differential growth rates among organelles within cells.
- Identified linear volumetric scaling laws for nurse cell growth over several orders of magnitude.
Conclusions:
- The developed supervised learning method effectively quantifies multicellular growth dynamics.
- Findings provide insights into coordinated cell growth and organelle scaling in oogenesis.
- The approach is adaptable for studying collective cell growth in other developmental contexts, such as mammalian embryogenesis.
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