Cellular organization in lab-evolved and extant multicellular species obeys a maximum entropy law.
View / Open Files
Authors
Zamani-Dahaj, Seyed A
Yanni, David
Burnetti, Anthony
Pentz, Jennifer
Honerkamp-Smith, Aurelia R
Wioland, Hugo
Sleath, Hannah R
Ratcliff, William C
Publication Date
2022-02-21Journal Title
Elife
ISSN
2050-084X
Publisher
eLife Sciences Publications Ltd
Type
Article
This Version
AM
Later Version(s)
Metadata
Show full item recordCitation
Day, T. C., Höhn, S. S., Zamani-Dahaj, S. A., Yanni, D., Burnetti, A., Pentz, J., Honerkamp-Smith, A. R., et al. (2022). Cellular organization in lab-evolved and extant multicellular species obeys a maximum entropy law.. Elife https://doi.org/10.7554/eLife.72707
Abstract
The prevalence of multicellular organisms is due in part to their ability to form complex structures. How cells pack in these structures is a fundamental biophysical issue, underlying their functional properties. However, much remains unknown about how cell packing geometries arise, and how they are affected by random noise during growth - especially absent developmental programs. Here, we quantify the statistics of cellular neighborhoods of two different multicellular eukaryotes: lab-evolved 'snowflake' yeast and the green alga Volvox carteri. We find that despite large differences in cellular organization, the free space associated with individual cells in both organisms closely fits a modified gamma distribution, consistent with maximum entropy predictions originally developed for granular materials. This 'entropic' cellular packing ensures a degree of predictability despite noise, facilitating parent-offspring fidelity even in the absence of developmental regulation. Together with simulations of diverse growth morphologies, these results suggest that gamma-distributed cell neighborhood sizes are a general feature of multicellularity, arising from conserved statistics of cellular packing.
Sponsorship
Engineering and Physical Sciences Research Council (EP/M017982/1)
Wellcome Trust (207510/Z/17/Z)
Embargo Lift Date
2100-01-01
Identifiers
External DOI: https://doi.org/10.7554/eLife.72707
This record's URL: https://www.repository.cam.ac.uk/handle/1810/332459
Statistics
Total file downloads (since January 2020). For more information on metrics see the
IRUS guide.
Recommended or similar items
The current recommendation prototype on the Apollo Repository will be turned off on 03 February 2023. Although the pilot has been fruitful for both parties, the service provider IKVA is focusing on horizon scanning products and so the recommender service can no longer be supported. We recognise the importance of recommender services in supporting research discovery and are evaluating offerings from other service providers. If you would like to offer feedback on this decision please contact us on: support@repository.cam.ac.uk