Evolutionary dynamics of altruism and cheating among social amoebas

Minor variations in multicellular life cycles have major effects on adaptation

Multicellularity has evolved several independent times over the past hundreds of millions of years and given rise to a wide diversity of complex life. Recent studies have found that large differences in the fundamental structure of early multicellular life cycles can affect fitness and influence multicellular adaptation. Yet, there is an underlying assumption that at some scale or categorization multicellular life cycles are similar in terms of their adaptive potential. Here, we consider this possibility by exploring adaptation in a class of simple multicellular life cycles of filamentous organisms that only differ in one respect, how many daughter filaments are produced. We use mathematical models and evolutionary simulations to show that despite the similarities, qualitatively different mutations fix. In particular, we find that mutations with a tradeoff between cell growth and group survival, i.e. "selfish" or "altruistic" traits, spread differently. Specifically, altruistic mutations more readily spread in life cycles that produce few daughters while in life cycles producing many daughters either type of mutation can spread depending on the environment. Our results show that subtle changes in multicellular life cycles can fundamentally alter adaptation.

Heterogeneous individual motility biases group composition in a model of aggregating cells

Aggregative life cycles are characterized by alternating phases of unicellular growth and multicellular development. Their multiple, independent evolutionary emergence suggests that they may have coopted pervasive properties of single-celled ancestors. Primitive multicellular aggregates, where coordination mechanisms were less efficient than in extant aggregative microbes, must have faced high levels of conflict between different co-aggregating populations. Such conflicts within a multicellular body manifest in the differential reproductive output of cells of different types. Here, we study how heterogeneity in cell motility affects the aggregation process and creates a mismatch between the composition of the population and that of self-organized groups of active adhesive particles. We model cells as self-propelled particles and describe aggregation in a plane starting from a dispersed configuration. Inspired by the life cycle of aggregative model organisms such as Dictyostelium discoideum or Myxococcus xanthus, whose cells interact for a fixed duration before the onset of chimeric multicellular development, we study finite-time configurations for identical particles and in binary mixes. We show that co-aggregation results in three different types of frequency-dependent biases, one of which is associated to evolutionarily stable coexistence of particles with different motility. We propose a heuristic explanation of such observations, based on the competition between delayed aggregation of slower particles and detachment of faster particles. Unexpectedly, despite the complexity and non-linearity of the system, biases can be largely predicted from the behavior of the two corresponding homogenous populations. This model points to differential motility as a possibly important factor in driving the evolutionary emergence of facultatively multicellular life-cycles.

Enforcing Cooperation in the Social Amoebae

Cooperation has been essential to the evolution of biological complexity, but many societies struggle to overcome internal conflicts and divisions. Dictyostelium discoideum, or the social amoeba, has been a useful model system for exploring these conflicts and how they can be resolved. When starved, these cells communicate, gather into groups, and build themselves into a multicellular fruiting body. Some cells altruistically die to form the rigid stalk, while the remainder sit atop the stalk, become spores, and disperse. Evolutionary theory predicts that conflict will arise over which cells die to form the stalk and which cells become spores and survive. The power of the social amoeba lies in the ability to explore how cooperation and conflict work across multiple levels, ranging from proximate mechanisms (how does it work?) to ultimate evolutionary answers (why does it work?). Recent studies point to solutions to the problem of ensuring fairness, such as the ability to suppress selfishness and to recognize and avoid unrelated individuals. This work confirms a central role for kin selection, but also suggests new explanations for how social amoebae might enforce cooperation. New approaches based on genomics are also enabling researchers to decipher for the first time the evolutionary history of cooperation and conflict and to determine its role in shaping the biology of multicellular organisms.

Cooperation-based branching as a mechanism of evolutionary speciation

When performing complex tasks, coexistence of organisms in a shared environment can be achieved by means of different strategies. For example, individuals can evolve to complete all parts of the complex task, choosing self-sufficiency over cooperation. On the other hand, they may choose to split parts of the task and share the products for mutual benefit, such that distinct groups of the organisms specialize on a subset of elementary tasks. In contrast to the existing theory of specialization and task sharing for cells in multicellular organisms (or colonies of social insects), here we describe a mechanism of evolutionary branching which is based on cooperation and division of labor, and where selection happens at the individual level. Using a class of mathematical models and the methodology of adaptive dynamics, we investigate the conditions for such branching into distinct cooperating subgroups to occur. We show that, as long as performing multiple tasks is associated with additional cost, branching occurs for a wide parameter range, and this scenario is stable against the invasion of cheaters. We hypothesize that over time, this can lead to evolutionary speciation. Examples from bacterial evolution and the connection with the Black Queen Hypothesis are discussed. It is our hope that the theory of diversification rooted in cooperation may inspire further ecological research to identify more evolutionary examples consistent with this speciation mechanism.

Cheating is evolutionarily assimilated with cooperation in the continuous snowdrift game

•

We fully analyze continuous snowdrift games with quadratic payoff functions in diversified populations.

•

It is well known that classical snowdrift games maintain the coexistence of cooperators and cheaters.

•

We clarify that the continuous snowdrift games often lead to assimilation of cooperators and cheaters.

•

Allowing the gradual evolution of cooperative behavior can facilitate social inequity aversion in joint ventures.

It is well known that in contrast to the Prisoner’s Dilemma, the snowdrift game can lead to a stable coexistence of cooperators and cheaters. Recent theoretical evidence on the snowdrift game suggests that gradual evolution for individuals choosing to contribute in continuous degrees can result in the social diversification to a 100% contribution and 0% contribution through so-called evolutionary branching. Until now, however, game-theoretical studies have shed little light on the evolutionary dynamics and consequences of the loss of diversity in strategy. Here, we analyze continuous snowdrift games with quadratic payoff functions in dimorphic populations. Subsequently, conditions are clarified under which gradual evolution can lead a population consisting of those with 100% contribution and those with 0% contribution to merge into one species with an intermediate contribution level. The key finding is that the continuous snowdrift game is more likely to lead to assimilation of different cooperation levels rather than maintenance of diversity. Importantly, this implies that allowing the gradual evolution of cooperative behavior can facilitate social inequity aversion in joint ventures that otherwise could cause conflicts that are based on commonly accepted notions of fairness.

Relationship between aggregation of rewards and the possibility of polymorphism in continuous snowdrift games

The existence of intra-population variations in cooperation level has often been reported by some empirical studies. Evolutionary conditions of polymorphism in cooperation have been investigated by using a framework of the continuous snowdrift game. However, our insights from this framework have been limited because of an assumption that the cooperative reward is a function of total amount of investments within an interacting group. In many cases, payoffs may actually depend on the interactions between the effects of such investments, such as members share the sum of beneficial effects that are individually produced from their own investments. Alternatively, payoffs may depend multiplicatively on investment, such as when investments are complementary. In the present paper, we investigated the influence of such difference on the evolution of cooperation with respect to three aspects of the aggregating process of individuals' contributions for reward, i.e. (i) additive or multiplicative, (ii) aggregation of either investments or effects, and (iii) promotion of advantage or suppression of disadvantage. We analytically show that the possibilities of the emergence of polymorphism are different depending on the type of aggregation process classified from these three aspects. Polymorphism of cooperation level never emerges unless the aggregation process is the aggregation of investment or the multiplicative aggregation of effect with suppression of disadvantage. Our results show the necessary condition for the emergence of polymorphic cooperation levels that are observed in various taxonomic groups.

Individual-based competition between species with spatial correlation and aggregation

In order to clarify the theoretical relationship between individual behavior and population-level competition between two species with spatial correlation, this paper describes how discrete-time competition equations for the two species can be derived from local resource competition among individuals. Competition type of each species is either scramble, contest, or modified contest, and for various combinations of two competition types, different competition models are derived. Simple competition models that can approximate the above models when competition is weak are also derived. Furthermore, the derived models are used to investigate how coexistence conditions and coexistence probability depend on spatial correlation and aggregation of individuals. For the weak competition models, spatial aggregation and non-correlation, in terms of measures adopted here, play exactly symmetric roles in promoting coexistence. In contrast, for the fully developed models, spatial aggregation generally exerts stronger effects than non-correlation on coexistence. Coexistence probability also depends greatly on competition types. For example, two species are generally more likely to coexist when they are of the same competition type than of different competition types. Coexistence probabilities from the mathematical analysis are in good agreement with those from individual-based simulations.

Multilevel selection analysis of a microbial social trait

The study of microbial communities often leads to arguments for the evolution of cooperation due to group benefits. However, multilevel selection models caution against the uncritical assumption that group benefits will lead to the evolution of cooperation. We analyze a microbial social trait to precisely define the conditions favoring cooperation. We combine the multilevel partition of the Price equation with a laboratory model system: swarming in Pseudomonas aeruginosa. We parameterize a population dynamics model using competition experiments where we manipulate expression, and therefore the cost-to-benefit ratio of swarming cooperation. Our analysis shows that multilevel selection can favor costly swarming cooperation because it causes population expansion. However, due to high costs and diminishing returns constitutive cooperation can only be favored by natural selection when relatedness is high. Regulated expression of cooperative genes is a more robust strategy because it provides the benefits of swarming expansion without the high cost or the diminishing returns. Our analysis supports the key prediction that strong group selection does not necessarily mean that microbial cooperation will always emerge.

Synergy and group size in microbial cooperation

Microbes produce many molecules that are important for their growth and development, and the exploitation of these secretions by nonproducers has recently become an important paradigm in microbial social evolution. Although the production of these public-goods molecules has been studied intensely, little is known of how the benefits accrued and the costs incurred depend on the quantity of public-goods molecules produced. We focus here on the relationship between the shape of the benefit curve and cellular density, using a model assuming three types of benefit functions: diminishing, accelerating, and sigmoidal (accelerating and then diminishing). We classify the latter two as being synergistic and argue that sigmoidal curves are common in microbial systems. Synergistic benefit curves interact with group sizes to give very different expected evolutionary dynamics. In particular, we show that whether and to what extent microbes evolve to produce public goods depends strongly on group size. We show that synergy can create an "evolutionary trap" that can stymie the establishment and maintenance of cooperation. By allowing density-dependent regulation of production (quorum sensing), we show how this trap may be avoided. We discuss the implications of our results on experimental design.

Understanding microbial cooperation

The field of microbial cooperation has grown enormously over the last decade, leading to improved experimental techniques and a growing awareness of collective behavior in microbes. Unfortunately, many of our theoretical tools and concepts for understanding cooperation fail to take into account the peculiarities of the microbial world, namely strong selection strengths, unique population structure, and non-linear dynamics. Worse yet, common verbal arguments are often far removed from the math involved, leading to confusion and mistakes. Here, we review the general mathematical forms of Price's equation, Hamilton's rule, and multilevel selection as they are applied to microbes and provide some intuition on these otherwise abstract formulas. However, these sometimes overly general equations can lack specificity and predictive power, ultimately forcing us to advocate for more direct modeling techniques.

Adaptive dynamics of altruistic cooperation in a metapopulation: evolutionary emergence of cooperators and defectors or evolutionary suicide?

We investigate the evolution of public goods cooperation in a metapopulation model with small local populations, where altruistic cooperation can evolve due to assortment and kin selection, and the evolutionary emergence of cooperators and defectors via evolutionary branching is possible. Although evolutionary branching of cooperation has recently been demonstrated in the continuous snowdrift game and in another model of public goods cooperation, the required conditions on the cost and benefit functions are rather restrictive, e.g., altruistic cooperation cannot evolve in a defector population. We also observe selection for too low cooperation, such that the whole metapopulation goes extinct and evolutionary suicide occurs. We observed intuitive effects of various parameters on the numerical value of the monomorphic singular strategy. Their effect on the final coexisting cooperator-defector pair is more complex: changes expected to increase cooperation decrease the strategy value of the cooperator. However, at the same time the population size of the cooperator increases enough such that the average strategy does increase. We also extend the theory of structured metapopulation models by presenting a method to calculate the fitness gradient in a general class of metapopulation models, and try to make a connection with the kin selection approach.

Dynamics in the mixed microbial concourse

Isolated, clonal populations of cells are rarely found in nature. The emergent properties of microbial consortia present a challenge for the systems approach to biology, as chances for competition, communication, or collaboration multiply with the number of interacting agents. This review focuses on recent work on intercourse within biofilms, among quorum-sensing populations, and between cross-feeding metabolic cooperators. New tools from synthetic biology allow microbial interactions to be designed and tightly controlled, creating valuable model systems. We address both natural and synthetic partnerships, with an emphasis on how system behaviors derive from the properties of their components. Essential features of microbial biology arose in the context of a very mixed culture and cannot be understood without unscrambling it.

Consequences of fluctuating group size for the evolution of cooperation

Studies of cooperation have traditionally focused on discrete games such as the well-known prisoner's dilemma, in which players choose between two pure strategies: cooperation and defection. Increasingly, however, cooperation is being studied in continuous games that feature a continuum of strategies determining the level of cooperative investment. For the continuous snowdrift game, it has been shown that a gradually evolving monomorphic population may undergo evolutionary branching, resulting in the emergence of a defector strategy that coexists with a cooperator strategy. This phenomenon has been dubbed the 'tragedy of the commune'. Here we study the effects of fluctuating group size on the tragedy of the commune and derive analytical conditions for evolutionary branching. Our results show that the effects of fluctuating group size on evolutionary dynamics critically depend on the structure of payoff functions. For games with additively separable benefits and costs, fluctuations in group size make evolutionary branching less likely, and sufficiently large fluctuations in group size can always turn an evolutionary branching point into a locally evolutionarily stable strategy. For games with multiplicatively separable benefits and costs, fluctuations in group size can either prevent or induce the tragedy of the commune. For games with general interactions between benefits and costs, we derive a general classification scheme based on second derivatives of the payoff function, to elucidate when fluctuations in group size help or hinder cooperation.

Adaptive dynamics of cooperation may prevent the coexistence of defectors and cooperators and even cause extinction

It has recently been demonstrated that ecological feedback mechanisms can facilitate the emergence and maintenance of cooperation in public goods interactions: the replicator dynamics of defectors and cooperators can result, for example, in the ecological coexistence of cooperators and defectors. Here we show that these results change dramatically if cooperation strategy is not fixed but instead is a continuously varying trait under natural selection. For low values of the factor with which the value of resources is multiplied before they are shared among all participants, evolution will always favour lower cooperation strategies until the population falls below an Allee threshold and goes extinct, thus evolutionary suicide occurs. For higher values of the factor, there exists a unique evolutionarily singular strategy, which is convergence stable. Because the fitness function is linear with respect to the strategy of the mutant, this singular strategy is neutral against mutant invasions. This neutrality disappears if a nonlinear functional response in receiving benefits is assumed. For strictly concave functional responses, singular strategies become uninvadable. Evolutionary branching, which could result in the evolutionary emergence of cooperators and defectors, can occur only with locally convex functional responses, but we illustrate that it can also result in coevolutionary extinction.

Cooperation is less likely to evolve in a finite population with a highly skewed distribution of family size

In the context of the finitely repeated Prisoner's Dilemma with the possibility of cooperating or defecting each time, the strategy tit-for-tat (TFT) consists in cooperating the first time and copying the strategy previously used by the opponent the next times. Assuming random pairwise interactions in a finite population of always defecting individuals, TFT can be favoured by selection to go to fixation following its introduction as a mutant strategy. We deduce the condition for this to be the case under weak selection in the framework of a general reproduction scheme in discrete time. In fact, we show when and why the one-third rule for the evolution of cooperation holds, and how it extends to a more general rule. The condition turns out to be more stringent when the numbers of descendants left by the individuals from one time-step to the next may substantially differ. This suggests that the evolution of cooperation is made more difficult in populations with a highly skewed distribution of family size. This is illustrated by two examples.

High relatedness maintains multicellular cooperation in a social amoeba by controlling cheater mutants

The control of cheating is important for understanding major transitions in evolution, from the simplest genes to the most complex societies. Cooperative systems can be ruined if cheaters that lower group productivity are able to spread. Kin-selection theory predicts that high genetic relatedness can limit cheating, because separation of cheaters and cooperators limits opportunities to cheat and promotes selection against low-fitness groups of cheaters. Here, we confirm this prediction for the social amoeba Dictyostelium discoideum; relatedness in natural wild groups is so high that socially destructive cheaters should not spread. We illustrate in the laboratory how high relatedness can control a mutant that would destroy cooperation at low relatedness. Finally, we demonstrate that, as predicted, mutant cheaters do not normally harm cooperation in a natural population. Our findings show how altruism is preserved from the disruptive effects of such mutant cheaters and how exceptionally high relatedness among cells is important in promoting the cooperation that underlies multicellular development.

Functional information and the emergence of biocomplexity

Complex emergent systems of many interacting components, including complex biological systems, have the potential to perform quantifiable functions. Accordingly, we define "functional information," I(E(x)), as a measure of system complexity. For a given system and function, x (e.g., a folded RNA sequence that binds to GTP), and degree of function, E(x) (e.g., the RNA-GTP binding energy), I(E(x)) = -log(2)[F(E(x))], where F(E(x)) is the fraction of all possible configurations of the system that possess a degree of function > or = E(x). Functional information, which we illustrate with letter sequences, artificial life, and biopolymers, thus represents the probability that an arbitrary configuration of a system will achieve a specific function to a specified degree. In each case we observe evidence for several distinct solutions with different maximum degrees of function, features that lead to steps in plots of information versus degree of function.