Fall 2023 Undergraduate Research Symposium
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30: Optimal Resource Allocation in Organelle Biogenesis


Presenter(s)

Ronan Hanley

Faculty research mentor

Shankar Mukherji

Presentation session

Poster session B; 11:30am-12:30pm

Acknowledgments

Deepthi Kailish, Kiandokht Panjtan Amiri, Asa Kalish, NIH R35142704 (to S.M.), Undergraduate Physics Fellowship

Abstract or Description

Among the hallmarks of the eukaryotic cell is its organization into spatially defined subcompartments known as organelles. Organelles provide optimized environments for otherwise incompatible biochemical reactions within the cell. In order to tailor organelle biogenesis to the needs of the cell, the cell can regulate the size and number of many of its organelles. Organelle biogenesis, however, is fundamentally constrained by the limited available pool of resources available to the cell to synthesize its organelles. This begs the question: what principles dictate how much of the cell’s limited resources are devoted to increasing the number versus the size of a given organelle? We find that the solutions to the constrained optimization fall into two regimes separated by a critical point similar to those observed in second order phase transitions in condensed matter physics, suggesting that cells face an unexpectedly sharp tradeoff between organelle number and size in resource-limited contexts. The existence of this critical point is consistent with experimental observations that cells grow larger numbers of small organelles as opposed to simply reducing each organelle’s size when faced with a constraining pool of resources. We find that in organelles that are created via de-novo synthesis, cell size is positively correlated with number of organelles while there is no correlation between size of the cell and average organelle size. We also find that in organelles that undergo fission that cell size is positively correlated with organelle size while there is no correlation between size of the call and number of organelles. Our findings are consistent with our predictions of optimal resource allocation under the limited pool regime.

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