IDEAS home Printed from https://ideas.repec.org/a/plo/pcbi00/1006987.html
   My bibliography  Save this article

Interacting cells driving the evolution of multicellular life cycles

Author

Listed:
  • Yuanxiao Gao
  • Arne Traulsen
  • Yuriy Pichugin

Abstract

Evolution of complex multicellular life began from the emergence of a life cycle involving the formation of cell clusters. The opportunity for cells to interact within clusters provided them with an advantage over unicellular life forms. However, what kind of interactions may lead to the evolution of multicellular life cycles? Here, we combine evolutionary game theory with a model for the emergence of multicellular groups to investigate how cell interactions can influence reproduction modes during the early stages of the evolution of multicellularity. In our model, the presence of both cell types is maintained by stochastic phenotype switching during cell division. We identify evolutionary optimal life cycles as those which maximize the population growth rate. Among all interactions captured by two-player games, the vast majority promotes two classes of life cycles: (i) splitting into unicellular propagules or (ii) fragmentation into two offspring clusters of equal (or almost equal) size. Our findings indicate that the three most important characteristics, determining whether multicellular life cycles will evolve, are the average performance of homogeneous groups, heterogeneous groups, and solitary cells.Author summary: Multicellular organisms are ubiquitous. But how did the first multicellular organisms arise? It is typically argued that this occurred due to benefits coming from interactions between cells. One example of such interactions is the division of labour. For instance, colonial cyanobacteria delegate photosynthesis and nitrogen fixation to different cells within the colony. In this way, the colony gains a growth advantage over unicellular cyanobacteria. However, not all cell interactions favour multicellular life. Cheater cells residing in a colony without any contribution will outgrow other cells. Then, the growing burden of cheaters may eventually destroy the colony. Here, we ask what kinds of interactions promote the evolution of multicellularity? We investigated all interactions captured by pairwise games and for each of them, we look for the evolutionarily optimal life cycle: How big should the colony grow and how should it split into offspring cells or colonies? We found that multicellularity can evolve with interactions far beyond cooperation or division of labour scenarios. More surprisingly, most of the life cycles found fall into either of two categories: A parent colony splits into two multicellular parts, or it splits into multiple independent cells.

Suggested Citation

  • Yuanxiao Gao & Arne Traulsen & Yuriy Pichugin, 2019. "Interacting cells driving the evolution of multicellular life cycles," PLOS Computational Biology, Public Library of Science, vol. 15(5), pages 1-16, May.
  • Handle: RePEc:plo:pcbi00:1006987
    DOI: 10.1371/journal.pcbi.1006987
    as

    Download full text from publisher

    File URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1006987
    Download Restriction: no

    File URL: https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1006987&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pcbi.1006987?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. William C. Ratcliff & Matthew D. Herron & Kathryn Howell & Jennifer T. Pentz & Frank Rosenzweig & Michael Travisano, 2013. "Experimental evolution of an alternating uni- and multicellular life cycle in Chlamydomonas reinhardtii," Nature Communications, Nature, vol. 4(1), pages 1-7, December.
    2. Jorgen W. Weibull, 1997. "Evolutionary Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262731215, April.
    3. Katrin Hammerschmidt & Caroline J. Rose & Benjamin Kerr & Paul B. Rainey, 2014. "Life cycles, fitness decoupling and the evolution of multicellularity," Nature, Nature, vol. 515(7525), pages 75-79, November.
    4. Paul B. Rainey & Katrina Rainey, 2003. "Evolution of cooperation and conflict in experimental bacterial populations," Nature, Nature, vol. 425(6953), pages 72-74, September.
    5. repec:hhs:iuiwop:487 is not listed on IDEAS
    6. Rashidi, Armin & Shelton, Deborah E. & Michod, Richard E., 2015. "A Darwinian approach to the origin of life cycles with group properties," Theoretical Population Biology, Elsevier, vol. 102(C), pages 76-84.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cao, Lixuan & Wu, Bin, 2021. "Eco-evolutionary dynamics with payoff-dependent environmental feedback," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    2. Dufwenberg, Martin, 1997. "Some relationships between evolutionary stability criteria in games," Economics Letters, Elsevier, vol. 57(1), pages 45-50, November.
    3. Lichi Zhang & Yanyan Jiang & Junmin Wu, 2022. "Evolutionary Game Analysis of Government and Residents’ Participation in Waste Separation Based on Cumulative Prospect Theory," IJERPH, MDPI, vol. 19(21), pages 1-16, November.
    4. Tom Johnston & Michael Savery & Alex Scott & Bassel Tarbush, 2023. "Game Connectivity and Adaptive Dynamics," Papers 2309.10609, arXiv.org, revised Oct 2024.
    5. Gu, Tianqi & Xu, Weiping & Liang, Hua & He, Qing & Zheng, Nan, 2024. "School bus transport service strategies’ policy-making mechanism – An evolutionary game approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 182(C).
    6. Petrohilos-Andrianos, Yannis & Xepapadeas, Anastasios, 2017. "Resource harvesting regulation and enforcement: An evolutionary approach," Research in Economics, Elsevier, vol. 71(2), pages 236-253.
    7. Philippe Jehiel, 2022. "Analogy-Based Expectation Equilibrium and Related Concepts:Theory, Applications, and Beyond," Working Papers halshs-03735680, HAL.
    8. Waters, George A., 2009. "Chaos in the cobweb model with a new learning dynamic," Journal of Economic Dynamics and Control, Elsevier, vol. 33(6), pages 1201-1216, June.
    9. Meng Ding & Hui Zeng, 2022. "Multi-Agent Evolutionary Game in the Recycling Utilization of Sulfate-Rich Wastewater," IJERPH, MDPI, vol. 19(14), pages 1-20, July.
    10. Stojkoski, Viktor & Karbevski, Marko & Utkovski, Zoran & Basnarkov, Lasko & Kocarev, Ljupco, 2021. "Evolution of cooperation in networked heterogeneous fluctuating environments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    11. Kulsum, Umma & Alam, Muntasir & Kamrujjaman, Md., 2024. "Modeling and investigating the dilemma of early and delayed vaccination driven by the dynamics of imitation and aspiration," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    12. Guohui Song & Yongbin Wang, 2021. "Mainstream Value Information Push Strategy on Chinese Aggregation News Platform: Evolution, Modelling and Analysis," Sustainability, MDPI, vol. 13(19), pages 1-17, October.
    13. Gaudeul, Alexia & Keser, Claudia & Müller, Stephan, 2021. "The evolution of morals under indirect reciprocity," Games and Economic Behavior, Elsevier, vol. 126(C), pages 251-277.
    14. Sandholm,W.H., 2003. "Excess payoff dynamics, potential dynamics, and stable games," Working papers 5, Wisconsin Madison - Social Systems.
    15. Angelo Antoci & Simone Borghesi & Marcello Galeotti, 2013. "Environmental options and technological innovation: an evolutionary game model," Journal of Evolutionary Economics, Springer, vol. 23(2), pages 247-269, April.
    16. Alexander Isakov & David Rand, 2012. "The Evolution of Coercive Institutional Punishment," Dynamic Games and Applications, Springer, vol. 2(1), pages 97-109, March.
    17. Hui Yu & Wei Wang & Baohua Yang & Cunfang Li, 2019. "Evolutionary Game Analysis of the Stress Effect of Cross-Regional Transfer of Resource-Exhausted Enterprises," Complexity, Hindawi, vol. 2019, pages 1-16, November.
    18. Galor, Oded & Klemp, Marc, 2014. "The Biocultural Origins of Human Capital Formation," IZA Discussion Papers 8433, Institute of Labor Economics (IZA).
    19. Moreira, Helmar Nunes & Araujo, Ricardo Azevedo, 2011. "On the existence and the number of limit cycles in evolutionary games," MPRA Paper 33895, University Library of Munich, Germany.
    20. Xie, Yunya & Zhang, Shuhua & Zhang, Zhipeng & Bu, Hongyu, 2020. "Impact of binary social status with hierarchical punishment on the evolution of cooperation in the spatial prisoner’s dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 130(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pcbi00:1006987. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ploscompbiol (email available below). General contact details of provider: https://journals.plos.org/ploscompbiol/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.