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Pichugin Y, Traulsen A. Evolution of multicellular life cycles under costly fragmentation. PLoS Comput Biol 2020; 16:e1008406. [PMID: 33211685 PMCID: PMC7714367 DOI: 10.1371/journal.pcbi.1008406] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 12/03/2020] [Accepted: 09/28/2020] [Indexed: 12/18/2022] Open
Abstract
A fascinating wealth of life cycles is observed in biology, from unicellularity to the concerted fragmentation of multicellular units. However, the understanding of factors driving their evolution is still limited. We show that costs of fragmentation have a major impact on the evolution of life cycles due to their influence on the growth rates of the associated populations. We model a group structured population of undifferentiated cells, where cell clusters reproduce by fragmentation. Fragmentation events are associated with a cost expressed by either a fragmentation delay, an additional risk, or a cell loss. The introduction of such fragmentation costs vastly increases the set of possible life cycles. Based on these findings, we suggest that the evolution of life cycles involving splitting into multiple offspring can be directly associated with the fragmentation cost. Moreover, the impact of this cost alone is strong enough to drive the emergence of multicellular units that eventually split into many single cells, even under scenarios that strongly disfavour collectives compared to solitary individuals.
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Affiliation(s)
- Yuriy Pichugin
- Max Planck Institute for Evolutionary Biology, August-Thienemann-Str. 2, 24306 Plön, Germany
- * E-mail:
| | - Arne Traulsen
- Max Planck Institute for Evolutionary Biology, August-Thienemann-Str. 2, 24306 Plön, Germany
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Hodgkinson A, Le Cam L, Trucu D, Radulescu O. Spatio-Genetic and phenotypic modelling elucidates resistance and re-sensitisation to treatment in heterogeneous melanoma. J Theor Biol 2019; 466:84-105. [DOI: 10.1016/j.jtbi.2018.11.037] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Revised: 11/06/2018] [Accepted: 11/29/2018] [Indexed: 12/11/2022]
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Olejarz J, Kaveh K, Veller C, Nowak MA. Selection for synchronized cell division in simple multicellular organisms. J Theor Biol 2018; 457:170-179. [PMID: 30172691 PMCID: PMC6169303 DOI: 10.1016/j.jtbi.2018.08.038] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2018] [Revised: 07/30/2018] [Accepted: 08/29/2018] [Indexed: 02/08/2023]
Abstract
The evolution of multicellularity was a major transition in the history of life on earth. Conditions under which multicellularity is favored have been studied theoretically and experimentally. But since the construction of a multicellular organism requires multiple rounds of cell division, a natural question is whether these cell divisions should be synchronous or not. We study a population model in which there compete simple multicellular organisms that grow by either synchronous or asynchronous cell divisions. We demonstrate that natural selection can act differently on synchronous and asynchronous cell division, and we offer intuition for why these phenotypes are generally not neutral variants of each other.
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Affiliation(s)
- Jason Olejarz
- Program for Evolutionary Dynamics, Harvard University, Cambridge, MA 02138, USA.
| | - Kamran Kaveh
- Program for Evolutionary Dynamics, Harvard University, Cambridge, MA 02138, USA.
| | - Carl Veller
- Program for Evolutionary Dynamics, Harvard University, Cambridge, MA 02138, USA; Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA.
| | - Martin A Nowak
- Program for Evolutionary Dynamics, Harvard University, Cambridge, MA 02138, USA; Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; Department of Mathematics, Harvard University, Cambridge, MA 02138, USA.
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Kaveh K, Veller C, Nowak MA. Games of multicellularity. J Theor Biol 2016; 403:143-158. [PMID: 27179461 DOI: 10.1016/j.jtbi.2016.04.037] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2015] [Revised: 04/21/2016] [Accepted: 04/29/2016] [Indexed: 11/24/2022]
Abstract
Evolutionary game dynamics are often studied in the context of different population structures. Here we propose a new population structure that is inspired by simple multicellular life forms. In our model, cells reproduce but can stay together after reproduction. They reach complexes of a certain size, n, before producing single cells again. The cells within a complex derive payoff from an evolutionary game by interacting with each other. The reproductive rate of cells is proportional to their payoff. We consider all two-strategy games. We study deterministic evolutionary dynamics with mutations, and derive exact conditions for selection to favor one strategy over another. Our main result has the same symmetry as the well-known sigma condition, which has been proven for stochastic game dynamics and weak selection. For a maximum complex size of n=2 our result holds for any intensity of selection. For n≥3 it holds for weak selection. As specific examples we study the prisoner's dilemma and hawk-dove games. Our model advances theoretical work on multicellularity by allowing for frequency-dependent interactions within groups.
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Affiliation(s)
- Kamran Kaveh
- Program for Evolutionary Dynamics, Harvard University, Cambridge, MA 02138, USA.
| | - Carl Veller
- Program for Evolutionary Dynamics, Harvard University, Cambridge, MA 02138, USA; Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; Department of Mathematics, Harvard University, Cambridge, MA 02138, USA
| | - Martin A Nowak
- Program for Evolutionary Dynamics, Harvard University, Cambridge, MA 02138, USA; Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; Department of Mathematics, Harvard University, Cambridge, MA 02138, USA
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Watson RA, Mills R, Buckley CL, Kouvaris K, Jackson A, Powers ST, Cox C, Tudge S, Davies A, Kounios L, Power D. Evolutionary Connectionism: Algorithmic Principles Underlying the Evolution of Biological Organisation in Evo-Devo, Evo-Eco and Evolutionary Transitions. Evol Biol 2015; 43:553-581. [PMID: 27932852 PMCID: PMC5119841 DOI: 10.1007/s11692-015-9358-z] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2015] [Accepted: 10/31/2015] [Indexed: 12/16/2022]
Abstract
The mechanisms of variation, selection and inheritance, on which evolution by natural selection depends, are not fixed over evolutionary time. Current evolutionary biology is increasingly focussed on understanding how the evolution of developmental organisations modifies the distribution of phenotypic variation, the evolution of ecological relationships modifies the selective environment, and the evolution of reproductive relationships modifies the heritability of the evolutionary unit. The major transitions in evolution, in particular, involve radical changes in developmental, ecological and reproductive organisations that instantiate variation, selection and inheritance at a higher level of biological organisation. However, current evolutionary theory is poorly equipped to describe how these organisations change over evolutionary time and especially how that results in adaptive complexes at successive scales of organisation (the key problem is that evolution is self-referential, i.e. the products of evolution change the parameters of the evolutionary process). Here we first reinterpret the central open questions in these domains from a perspective that emphasises the common underlying themes. We then synthesise the findings from a developing body of work that is building a new theoretical approach to these questions by converting well-understood theory and results from models of cognitive learning. Specifically, connectionist models of memory and learning demonstrate how simple incremental mechanisms, adjusting the relationships between individually-simple components, can produce organisations that exhibit complex system-level behaviours and improve the adaptive capabilities of the system. We use the term "evolutionary connectionism" to recognise that, by functionally equivalent processes, natural selection acting on the relationships within and between evolutionary entities can result in organisations that produce complex system-level behaviours in evolutionary systems and modify the adaptive capabilities of natural selection over time. We review the evidence supporting the functional equivalences between the domains of learning and of evolution, and discuss the potential for this to resolve conceptual problems in our understanding of the evolution of developmental, ecological and reproductive organisations and, in particular, the major evolutionary transitions.
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Affiliation(s)
- Richard A. Watson
- Agents, Interactions and Complexity, ECS, University of Southampton, Southampton, UK
- Institute for Life Sciences, University of Southampton, Southampton, UK
| | - Rob Mills
- Biosystems & Integrative Sciences Institute (BioISI), Faculty of Sciences, University of Lisbon, Lisbon, Portugal
| | - C. L. Buckley
- School of Engineering and Informatics, University of Sussex, Falmer, UK
| | - Kostas Kouvaris
- Agents, Interactions and Complexity, ECS, University of Southampton, Southampton, UK
| | - Adam Jackson
- Agents, Interactions and Complexity, ECS, University of Southampton, Southampton, UK
| | | | - Chris Cox
- Agents, Interactions and Complexity, ECS, University of Southampton, Southampton, UK
| | - Simon Tudge
- Agents, Interactions and Complexity, ECS, University of Southampton, Southampton, UK
| | - Adam Davies
- Agents, Interactions and Complexity, ECS, University of Southampton, Southampton, UK
| | - Loizos Kounios
- Agents, Interactions and Complexity, ECS, University of Southampton, Southampton, UK
| | - Daniel Power
- Agents, Interactions and Complexity, ECS, University of Southampton, Southampton, UK
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