Eco-evolutionary dynamics of clonal multicellular life cycles

Abstract

The evolution of multicellular life cycles is a central process in the course of the emergence of multicellularity. The simplest multicellular life cycle is comprised of the growth of the propagule into a colony and its fragmentation to give rise to new propagules. The majority of theoretical models assume selection among life cycles to be driven by internal properties of multicellular groups, resulting in growth competition. At the same time, the influence of interactions between groups on the evolution of life cycles is rarely even considered. Here, we present a model of colonial life cycle evolution taking into account group interactions. Our work shows that the outcome of evolution could be coexistence between multiple life cycles or that the outcome may depend on the initial state of the population – scenarios impossible without group interactions. At the same time, we found that some results of these simpler models remain relevant: evolutionary stable strategies in our model are restricted to binary fragmentation – the same class of life cycles that contains all evolutionarily optimal life cycles in the model without interactions. Our results demonstrate that while models neglecting interactions can capture short-term dynamics, they fall short in predicting the population-scale picture of evolution.

The role of the unicellular bottleneck and organism size in mediating cooperation and conflict among cells at the onset of multicellularity

“…Here, under spatially-explicit size-independent competition, there is an advantage to fragmenting into more than two offspring. We believe the advantage of having multiple offspring arises from the fact that competition affects dispersing offspring and resident groups differently, which is not the case in Ress et al (2022). The probability that a dispersing offspring gets a spot on the lattice is the probability it lands on an empty spot, 1 − N / M 9 , where N is the number of individuals on the lattice, plus the probability it lands on an occupied spot but wins, N /(2 M 9 ), which together give p = 1 − N /(2 M 9 ).…”

“…One of our key new results is the dominance of life cycles other than binary fragmentation. Previous models have found binary fragmentation to dominate whether considering discrete or continuous time (Pichugin and Traulsen, 2022), exponential or frequency-dependent growth (Pichugin et al 2017, Ress et al 2022), or even when considering bidirectional switching between two cell types (Gao et al 2019). Here, however, we find modes that produce multiple offspring to dominate under a wide range of conditions.…”

“…Rather, it may simply maximize population growth rate (see also Ratcliff et al 2013). Adding frequency-dependent competition between organisms (Ress et al 2022) does not affect the fact that all optimal modes have two offspring, but does allow for complications such as coexistence and bistability. Phenotypic switching between two cell types was added to the fragmentation framework by Gao et al (2019), who used a payoff matrix to describe the interactions between the cells.…”

Minor variations in multicellular life cycles have major effects on adaptation

“…Studies of multicellular adaptation that do compare different multicellular life cycles often impose some selective environment and determine which life cycle is fittest under these conditions. For example, a series of papers by Y. Pichugin and A. Traulsen [ 18 , 59 , 80 , 81 ] compute the fittest way for clonal multicellular groups to fragment given various selective conditions, e.g. the rate between specific cell divisions in a group or the payoff matrix in an evolutionary game.…”

Group-selection via aggregative propagule-formation enables cooperative multicellularity in an individual based, spatial model

“…While the authors have explicitly modelled regulatory gene networks linking these traits and the status of the environment, their model ignored spatiality (for the parameters and results of their model, see Table A in the S1 Text). Dynamical models of aggregative slime moulds were focused on the effect of variable starvation time on the ecology of strategies [32], selection between different life cycles [58], or on the origin of the aggregative strategy as a first step towards multicellularity [59,60].…”