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Survival in branching cellular populations

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  • Bryant, Adam S.
  • Lavrentovich, Maxim O.

Abstract

We analyze evolutionary dynamics in a confluent, branching cellular population, such as in a growing duct, vasculature, or in a branching microbial colony. We focus on the coarse-grained features of the evolution and build a statistical model that captures the essential features of the dynamics. Using simulations and analytic approaches, we show that the survival probability of strains within the growing population is sensitive to the branching geometry: Branch bifurcations enhance survival probability due to an overall population growth (i.e., “inflation†), while branch termination and the small effective population size at the growing branch tips increase the probability of strain extinction. We show that the evolutionary dynamics may be captured on a wide range of branch geometries parameterized just by the branch diameter N0 and branching rate b. We find that the survival probability of neutral cell strains is largest at an “optimal†branching rate, which balances the effects of inflation and branch termination. We find that increasing the selective advantage s of the cell strain mitigates the inflationary effect by decreasing the average time at which the mutant cell fate is determined. For sufficiently large selective advantages, the survival probability of the advantageous mutant decreases monotonically with the branching rate.

Suggested Citation

  • Bryant, Adam S. & Lavrentovich, Maxim O., 2022. "Survival in branching cellular populations," Theoretical Population Biology, Elsevier, vol. 144(C), pages 13-23.
  • Handle: RePEc:eee:thpobi:v:144:y:2022:i:c:p:13-23
    DOI: 10.1016/j.tpb.2022.01.005
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    References listed on IDEAS

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    1. Jeffrey West & Ryan O. Schenck & Chandler Gatenbee & Mark Robertson-Tessi & Alexander R. A. Anderson, 2021. "Normal tissue architecture determines the evolutionary course of cancer," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    2. Ingrid Paine & Arnaud Chauviere & John Landua & Amulya Sreekumar & Vittorio Cristini & Jeffrey Rosen & Michael T Lewis, 2016. "A Geometrically-Constrained Mathematical Model of Mammary Gland Ductal Elongation Reveals Novel Cellular Dynamics within the Terminal End Bud," PLOS Computational Biology, Public Library of Science, vol. 12(4), pages 1-23, April.
    3. Erez Lieberman & Christoph Hauert & Martin A. Nowak, 2005. "Evolutionary dynamics on graphs," Nature, Nature, vol. 433(7023), pages 312-316, January.
    4. Lavrentovich, Maxim O. & Nelson, David R., 2015. "Survival probabilities at spherical frontiers," Theoretical Population Biology, Elsevier, vol. 102(C), pages 26-39.
    5. Doering, Charles R. & Mueller, Carl & Smereka, Peter, 2003. "Interacting particles, the stochastic Fisher–Kolmogorov–Petrovsky–Piscounov equation, and duality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 325(1), pages 243-259.
    6. Colinda L. G. J. Scheele & Edouard Hannezo & Mauro J. Muraro & Anoek Zomer & Nathalia S. M. Langedijk & Alexander van Oudenaarden & Benjamin D. Simons & Jacco van Rheenen, 2017. "Identity and dynamics of mammary stem cells during branching morphogenesis," Nature, Nature, vol. 542(7641), pages 313-317, February.
    7. Pigolotti, S. & Benzi, R. & Perlekar, P. & Jensen, M.H. & Toschi, F. & Nelson, D.R., 2013. "Growth, competition and cooperation in spatial population genetics," Theoretical Population Biology, Elsevier, vol. 84(C), pages 72-86.
    8. Adnan Ali & Stefan Grosskinsky, 2010. "Pattern Formation Through Genetic Drift At Expanding Population Fronts," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 13(03), pages 349-366.
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