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  • Modeling the impact of single-cell stochasticity and size control on the population growth rate in asymmetrically dividing cells
Title: Modeling the impact of single-cell stochasticity and size control on the population growth rate in asymmetrically dividing cells
Microbial populations show striking diversity in cell growth morphology and lifecycle; however, our understanding of how these factors influence the growth rate of cell populations remains limited. We use theory and simulations to predict the impact of asymmetric cell division, cell size regulation and single-cell stochasticity on the population growth rate. Our model predicts that coarse-grained noise in the single-cell growth rate λ decreases the population growth rate, as previously seen for symmetrically dividing cells. However, for a given noise in λ we find that dividing asymmetrically can enhance the population growth rate for cells with strong size control (between a “sizer” and an “adder”). To reconcile this finding with the abundance of symmetrically dividing organisms in nature, we propose that additional constraints on cell growth and division must be present which are not included in our model, and we explore the effects of selected extensions thereof. Further, we find that within our model, epigenetically inherited generation times may arise due to size control in asymmetrically dividing cells, providing a possible explanation for recent experimental observations in budding yeast. Taken together, our findings provide insight into the complex effects generated by non-canonical growth morphologies.  more » « less
Award ID(s):
1752024
PAR ID:
10342560
Author(s) / Creator(s):
; ; ;
Editor(s):
Csikász-Nagy, Attila
Date Published:
Journal Name:
PLOS Computational Biology
Volume:
17
Issue:
6
ISSN:
1553-7358
Page Range / eLocation ID:
e1009080
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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