Evolutionary construction by staying together and coming together

Evolutionary consequences of nascent multicellular life cycles

A key step in the evolutionary transition to multicellularity is the origin of multicellular groups as biological individuals capable of adaptation. Comparative work, supported by theory, suggests clonal development should facilitate this transition, although this hypothesis has never been tested in a single model system. We evolved 20 replicate populations of otherwise isogenic clonally reproducing 'snowflake' yeast (Δace2/∆ace2) and aggregative 'floc' yeast (GAL1p::FLO1 /GAL1p::FLO1) with daily selection for rapid growth in liquid media, which favors faster cell division, followed by selection for rapid sedimentation, which favors larger multicellular groups. While both genotypes adapted to this regime, growing faster and having higher survival during the group-selection phase, there was a stark difference in evolutionary dynamics. Aggregative floc yeast obtained nearly all their increased fitness from faster growth, not improved group survival; indicating that selection acted primarily at the level of cells. In contrast, clonal snowflake yeast mainly benefited from higher group-dependent fitness, indicating a shift in the level of Darwinian individuality from cells to groups. Through genome sequencing and mathematical modeling, we show that the genetic bottlenecks in a clonal life cycle also drive much higher rates of genetic drift-a result with complex implications for this evolutionary transition. Our results highlight the central role that early multicellular life cycles play in the process of multicellular adaptation.

Multispecies interactions shape the transition to multicellularity

The origin of multicellularity transformed the adaptive landscape on Earth, opening diverse avenues for further innovation. The transition to multicellular life is understood as the evolution of cooperative groups which form a new level of individuality. Despite the potential for community-level interactions, most studies have not addressed the competitive context of this transition, such as competition between species. Here, we explore how interspecific competition shapes the emergence of multicellularity in an experimental system with two yeast species, Saccharomyces cerevisiae and Kluyveromyces lactis, where multicellularity evolves in response to selection for faster settling ability. We find that the multispecies context slows the rate of the transition to multicellularity, and the transition to multicellularity significantly impacts community composition. Multicellular K. lactis emerges first and sweeps through populations in monocultures faster than in cocultures with S. cerevisiae. Following the transition, the between-species competitive dynamics shift, likely in part to intraspecific cooperation in K. lactis. Hence, we document an eco-evolutionary feedback across the transition to multicellularity, underscoring how ecological context is critical for understanding the causes and consequences of innovation. By including two species, we demonstrate that cooperation and competition across several biological scales shapes the origin and persistence of multicellularity.

Spontaneous Emergence of Multicellular Heritability

The major transitions in evolution include events and processes that result in the emergence of new levels of biological individuality. For collectives to undergo Darwinian evolution, their traits must be heritable, but the emergence of higher-level heritability is poorly understood and has long been considered a stumbling block for nascent evolutionary transitions. Using analytical models, synthetic biology, and biologically-informed simulations, we explored the emergence of trait heritability during the evolution of multicellularity. Prior work on the evolution of multicellularity has asserted that substantial collective-level trait heritability either emerges only late in the transition or requires some evolutionary change subsequent to the formation of clonal multicellular groups. In a prior analytical model, we showed that collective-level heritability not only exists but is usually more heritable than the underlying cell-level trait upon which it is based, as soon as multicellular groups form. Here, we show that key assumptions and predictions of that model are borne out in a real engineered biological system, with important implications for the emergence of collective-level heritability.

The scaling of goals from cellular to anatomical homeostasis: an evolutionary simulation, experiment and analysis

Complex living agents consist of cells, which are themselves competent sub-agents navigating physiological and metabolic spaces. Behaviour science, evolutionary developmental biology and the field of machine intelligence all seek to understand the scaling of biological cognition: what enables individual cells to integrate their activities to result in the emergence of a novel, higher-level intelligence with large-scale goals and competencies that belong to it and not to its parts? Here, we report the results of simulations based on the TAME framework, which proposes that evolution pivoted the collective intelligence of cells during morphogenesis of the body into traditional behavioural intelligence by scaling up homeostatic competencies of cells in metabolic space. In this article, we created a minimal in silico system (two-dimensional neural cellular automata) and tested the hypothesis that evolutionary dynamics are sufficient for low-level setpoints of metabolic homeostasis in individual cells to scale up to tissue-level emergent behaviour. Our system showed the evolution of the much more complex setpoints of cell collectives (tissues) that solve a problem in morphospace: the organization of a body-wide positional information axis (the classic French flag problem in developmental biology). We found that these emergent morphogenetic agents exhibit a number of predicted features, including the use of stress propagation dynamics to achieve the target morphology as well as the ability to recover from perturbation (robustness) and long-term stability (even though neither of these was directly selected for). Moreover, we observed an unexpected behaviour of sudden remodelling long after the system stabilizes. We tested this prediction in a biological system-regenerating planaria-and observed a very similar phenomenon. We propose that this system is a first step towards a quantitative understanding of how evolution scales minimal goal-directed behaviour (homeostatic loops) into higher-level problem-solving agents in morphogenetic and other spaces.

Evolutionary dynamics within and among competing groups

Biological and social systems are structured at multiple scales, and the incentives of individuals who interact in a group may diverge from the collective incentive of the group as a whole. Mechanisms to resolve this tension are responsible for profound transitions in evolutionary history, including the origin of cellular life, multicellular life, and even societies. Here, we synthesize a growing literature that extends evolutionary game theory to describe multilevel evolutionary dynamics, using nested birth-death processes and partial differential equations to model natural selection acting on competition within and among groups of individuals. We analyze how mechanisms known to promote cooperation within a single group-including assortment, reciprocity, and population structure-alter evolutionary outcomes in the presence of competition among groups. We find that population structures most conducive to cooperation in multiscale systems can differ from those most conducive within a single group. Likewise, for competitive interactions with a continuous range of strategies we find that among-group selection may fail to produce socially optimal outcomes, but it can nonetheless produce second-best solutions that balance individual incentives to defect with the collective incentives for cooperation. We conclude by describing the broad applicability of multiscale evolutionary models to problems ranging from the production of diffusible metabolites in microbes to the management of common-pool resources in human societies.

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.

Permissive aggregative group formation favors coexistence between cooperators and defectors in yeast

In Saccharomyces cerevisiae, the FLO1 gene encodes flocculins that lead to formation of multicellular flocs, that offer protection to the constituent cells. Flo1p was found to preferentially bind to fellow cooperators compared to defectors lacking FLO1 expression, enriching cooperators within the flocs. Given this dual function in cooperation and kin recognition, FLO1 has been termed a "green beard gene". Because of the heterophilic nature of the Flo1p bond however, we hypothesize that kin recognition is permissive and depends on the relative stability of the FLO1+/flo1- versus FLO1+/FLO1+ detachment force F. We combine single-cell measurements of adhesion, individual cell-based simulations of cluster formation, and in vitro flocculation to study the impact of relative bond stability on the evolutionary stability of cooperation. We identify a trade-off between both aspects of the green beard mechanism, with reduced relative bond stability leading to increased kin recognition at the expense of cooperative benefits. We show that the fitness of FLO1 cooperators decreases as their frequency in the population increases, arising from the observed permissive character (F+- = 0.5 F++) of the Flo1p bond. Considering the costs associated with FLO1 expression, this asymmetric selection often results in a stable coexistence between cooperators and defectors.

Eco-evolutionary dynamics of clonal multicellular life cycles

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.

Tradeoff breaking as model of evolutionary transitions in individuality and the limits of the fitness-decoupling metaphor

Evolutionary transitions in individuality (ETIs) involve the formation of Darwinian collectives from Darwinian particles. The transition from cells to multicellular life is a prime example. During an ETI, collectives become units of selection in their own right. However, the underlying processes are poorly understood. One observation used to identify the completion of an ETI is an increase in collective-level performance accompanied by a decrease in particle-level performance, for example measured by growth rate. This seemingly counterintuitive dynamic has been referred to as fitness decoupling and has been used to interpret both models and experimental data. Extending and unifying results from the literature, we show that fitness of particles and collectives can never decouple because calculations of fitness performed over appropriate and equivalent time intervals are necessarily the same provided the population reaches a stable collective size distribution. By way of solution, we draw attention to the value of mechanistic approaches that emphasise traits, and tradeoffs among traits, as opposed to fitness. This trait-based approach is sufficient to capture dynamics that underpin evolutionary transitions. In addition, drawing upon both experimental and theoretical studies, we show that while early stages of transitions might often involve tradeoffs among particle traits, later—and critical—stages are likely to involve the rupture of such tradeoffs. Thus, when observed in the context of ETIs, tradeoff-breaking events stand as a useful marker of these transitions.

Long-time behavior of a PDE replicator equation for multilevel selection in group-structured populations

In many biological systems, natural selection acts simultaneously on multiple levels of organization. This scenario typically presents an evolutionary conflict between the incentive of individuals to cheat and the collective incentive to establish cooperation within a group. Generalizing previous work on multilevel selection in evolutionary game theory, we consider a hyperbolic PDE model of a group-structured population, in which members within a single group compete with each other for individual-level replication; while the group also competes against other groups for group-level replication. We derive a threshold level of the relative strength of between-group competition such that defectors take over the population below the threshold while cooperation persists in the long-time population above the threshold. Under stronger assumptions on the initial distribution of group compositions, we further prove that the population converges to a steady state density supporting cooperation for between-group selection strength above the threshold. We further establish long-time bounds on the time-average of the collective payoff of the population, showing that the long-run population cannot outperform the payoff of a full-cooperator group even in the limit of infinitely-strong between-group competition. When the group replication rate is maximized by an intermediate level of within-group cooperation, individual-level selection casts a long shadow on the dynamics of multilevel selection: no level of between-group competition can erase the effects of the individual incentive to defect. We further extend our model to study the case of multiple types of groups, showing how the games that groups play can coevolve with the level of cooperation.

Unicellular-multicellular evolutionary branching driven by resource limitations

Multicellular life forms have evolved many times on our planet, suggesting that this is a common evolutionary innovation. Multiple advantages have been proposed for the emergence of multicellularity (MC). In this paper, we address the problem of how the first precondition for MC, namely 'stay together', might have occurred under spatially limited resources exploited by a population of unicellular agents. Using a minimal model of evolved cell-cell adhesion among growing and dividing cells that exploit a localized resource with a given size, we show that a transition occurs at a critical resource size separating a phase of evolved multicellular aggregates from a phase where unicellularity (UC) is favoured. The two phases are separated by an intermediate domain where both UC and MC can be selected by evolution. This model provides a minimal approach to the early stages that were required to transition from individuality to cohesive groups of cells associated with a physical cooperative effect: when resources are present only in a localized portion of the habitat, MC is a desirable property as it helps cells to keep close to the available local nutrients.

Varied solutions to multicellularity: The biophysical and evolutionary consequences of diverse intercellular bonds

The diversity of multicellular organisms is, in large part, due to the fact that multicellularity has independently evolved many times. Nonetheless, multicellular organisms all share a universal biophysical trait: cells are attached to each other. All mechanisms of cellular attachment belong to one of two broad classes; intercellular bonds are either reformable or they are not. Both classes of multicellular assembly are common in nature, having independently evolved dozens of times. In this review, we detail these varied mechanisms as they exist in multicellular organisms. We also discuss the evolutionary implications of different intercellular attachment mechanisms on nascent multicellular organisms. The type of intercellular bond present during early steps in the transition to multicellularity constrains future evolutionary and biophysical dynamics for the lineage, affecting the origin of multicellular life cycles, cell-cell communication, cellular differentiation, and multicellular morphogenesis. The types of intercellular bonds used by multicellular organisms may thus result in some of the most impactful historical constraints on the evolution of multicellularity.

The possible modes of microbial reproduction are fundamentally restricted by distribution of mass between parent and offspring

Cells and simple cell colonies reproduce by fragmenting their bodies into pieces. Produced newborns need to grow before they can reproduce again. How big a cell or a cell colony should grow? How many offspring should be produced? Should they be of equal size or diverse? We show that the simple fact that the immediate mass of offspring cannot exceed the mass of parents restricts possible answers to these questions. For example, our theory states that, when mass is conserved in the course of fragmentation, the evolutionarily optimal reproduction mode is fragmentation into exactly two, typically equal, parts. Our theory also shows conditions which promote evolution of asymmetric division or fragmentation into multiple pieces.

Multiple modes of asexual reproduction are observed among microbial organisms in natural populations. These modes are not only subject to evolution, but may drive evolutionary competition directly through their impact on population growth rates. The most prominent transition between two such modes is the one from unicellularity to multicellularity. We present a model of the evolution of reproduction modes, where a parent organism fragments into smaller parts. While the size of an organism at fragmentation, the number of offspring, and their sizes may vary a lot, the combined mass of fragments is limited by the mass of the parent organism. We found that mass conservation can fundamentally limit the number of possible reproduction modes. This has important direct implications for microbial life: For unicellular species, the interplay between cell shape and kinetics of the cell growth implies that the largest and the smallest possible cells should be rod shaped rather than spherical. For primitive multicellular species, these considerations can explain why rosette cell colonies evolved a mechanistically complex binary split reproduction. Finally, we show that the loss of organism mass during sporulation can explain the macroscopic sizes of the formally unicellular microorganism Myxomycetes plasmodium. Our findings demonstrate that a number of seemingly unconnected phenomena observed in unrelated species may be different manifestations of the same underlying process.

Evolution of reproductive strategies in incipient multicellularity

Multicellular organisms potentially show a large degree of diversity in reproductive strategies, producing offspring with varying sizes and compositions compared to their unicellular ancestors. In reality, only a few of these reproductive strategies are prevalent. To understand why this could be the case, we develop a stage-structured population model to probe the evolutionary growth advantages of reproductive strategies in incipient multicellular organisms. The performance of reproductive strategies is evaluated by the growth rates of the corresponding populations. We identify the optimal reproductive strategy, leading to the largest growth rate for a population. Considering the effects of organism size and cellular interaction, we found that distinct reproductive strategies could perform uniquely or equally well under different conditions. If a single reproductive strategy is optimal, it is binary splitting, dividing into two parts. Our results show that organism size and cellular interaction can play crucial roles in shaping reproductive strategies in nascent multicellularity. Our model sheds light on understanding the mechanism driving the evolution of reproductive strategies in incipient multicellularity. Beyond multicellularity, our results imply that a crucial factor in the evolution of unicellular species’ reproductive strategies is organism size.

Regulation of sedimentation rate shapes the evolution of multicellularity in a close unicellular relative of animals

Significant increases in sedimentation rate accompany the evolution of multicellularity. These increases should lead to rapid changes in ecological distribution, thereby affecting the costs and benefits of multicellularity and its likelihood to evolve. However, how genetic and cellular traits control this process, their likelihood of emergence over evolutionary timescales, and the variation in these traits as multicellularity evolves are still poorly understood. Here, using isolates of the ichthyosporean genus Sphaeroforma-close unicellular relatives of animals with brief transient multicellular life stages-we demonstrate that sedimentation rate is a highly variable and evolvable trait affected by at least 2 distinct physical mechanisms. First, we find extensive (>300×) variation in sedimentation rates for different Sphaeroforma species, mainly driven by size and density during the unicellular-to-multicellular life cycle transition. Second, using experimental evolution with sedimentation rate as a focal trait, we readily obtained, for the first time, fast settling and multicellular Sphaeroforma arctica isolates. Quantitative microscopy showed that increased sedimentation rates most often arose by incomplete cellular separation after cell division, leading to clonal "clumping" multicellular variants with increased size and density. Strikingly, density increases also arose by an acceleration of the nuclear doubling time relative to cell size. Similar size- and density-affecting phenotypes were observed in 4 additional species from the Sphaeroforma genus, suggesting that variation in these traits might be widespread in the marine habitat. By resequencing evolved isolates to high genomic coverage, we identified mutations in regulators of cytokinesis, plasma membrane remodeling, and chromatin condensation that may contribute to both clump formation and the increase in the nuclear number-to-volume ratio. Taken together, this study illustrates how extensive cellular control of density and size drive sedimentation rate variation, likely shaping the onset and further evolution of multicellularity.

A scaling law of multilevel evolution: how the balance between within- and among-collective evolution is determined

Numerous living systems are hierarchically organised, whereby replicating components are grouped into reproducing collectives-e.g., organelles are grouped into cells, and cells are grouped into multicellular organisms. In such systems, evolution can operate at two levels: evolution among collectives, which tends to promote selfless cooperation among components within collectives (called altruism), and evolution within collectives, which tends to promote cheating among components within collectives. The balance between within- and among-collective evolution thus exerts profound impacts on the fitness of these systems. Here, we investigate how this balance depends on the size of a collective (denoted by N) and the mutation rate of components (m) through mathematical analyses and computer simulations of multiple population genetics models. We first confirm a previous result that increasing N or m accelerates within-collective evolution relative to among-collective evolution, thus promoting the evolution of cheating. Moreover, we show that when within- and among-collective evolution exactly balance each other out, the following scaling relation generally holds: Nmα is a constant, where scaling exponent α depends on multiple parameters, such as the strength of selection and whether altruism is a binary or quantitative trait. This relation indicates that although N and m have quantitatively distinct impacts on the balance between within- and among-collective evolution, their impacts become identical if m is scaled with a proper exponent. Our results thus provide a novel insight into conditions under which cheating or altruism evolves in hierarchically-organised replicating systems.

Adaptation to a Viscous Snowball Earth Ocean as a Path to Complex Multicellularity

AbstractAnimals, fungi, and algae with complex multicellular bodies all evolved independently from unicellular ancestors. The early history of these major eukaryotic multicellular clades, if not their origins, co-occur with an extreme phase of global glaciations known as the Snowball Earth. Here, I propose that the long-term loss of low-viscosity environments due to several rounds global glaciation drove the multiple origins of complex multicellularity in eukaryotes and the subsequent radiation of complex multicellular groups into previously unoccupied niches. In this scenario, life adapts to Snowball Earth oceans by evolving large size and faster speeds through multicellularity, which acts to compensate for high-viscosity seawater and achieve fluid flow at sufficient levels to satisfy metabolic needs. Warm, low-viscosity seawater returned with the melting of the Snowball glaciers, and with it, by virtue of large and fast multicellular bodies, new ways of life were unveiled.

Bend or break: how biochemically versatile molecules enable metabolic division of labor in clonal microbial communities

In fluctuating nutrient environments, isogenic microbial cells transition into "multicellular" communities composed of phenotypically heterogeneous cells, showing functional specialization. In fungi (such as budding yeast), phenotypic heterogeneity is often described in the context of cells switching between different morphotypes (e.g., yeast to hyphae/pseudohyphae or white/opaque transitions in Candida albicans). However, more fundamental forms of metabolic heterogeneity are seen in clonal Saccharomyces cerevisiae communities growing in nutrient-limited conditions. Cells within such communities exhibit contrasting, specialized metabolic states, and are arranged in distinct, spatially organized groups. In this study, we explain how such an organization can stem from self-organizing biochemical reactions that depend on special metabolites. These metabolites exhibit plasticity in function, wherein the same metabolites are metabolized and utilized for distinct purposes by different cells. This in turn allows cell groups to function as specialized, interdependent cross-feeding systems which support distinct metabolic processes. Exemplifying a system where cells exhibit either gluconeogenic or glycolytic states, we highlight how available metabolites can drive favored biochemical pathways to produce new, limiting resources. These new resources can themselves be consumed or utilized distinctly by cells in different metabolic states. This thereby enables cell groups to sustain contrasting, even apparently impossible metabolic states with stable transcriptional and metabolic signatures for a given environment, and divide labor in order to increase community fitness or survival. We speculate on possible evolutionary implications of such metabolic specialization and division of labor in isogenic microbial communities.

The Consequences of Budding versus Binary Fission on Adaptation and Aging in Primitive Multicellularity

Early multicellular organisms must gain adaptations to outcompete their unicellular ancestors, as well as other multicellular lineages. The tempo and mode of multicellular adaptation is influenced by many factors including the traits of individual cells. We consider how a fundamental aspect of cells, whether they reproduce via binary fission or budding, can affect the rate of adaptation in primitive multicellularity. We use mathematical models to study the spread of beneficial, growth rate mutations in unicellular populations and populations of multicellular filaments reproducing via binary fission or budding. Comparing populations once they reach carrying capacity, we find that the spread of mutations in multicellular budding populations is qualitatively distinct from the other populations and in general slower. Since budding and binary fission distribute age-accumulated damage differently, we consider the effects of cellular senescence. When growth rate decreases with cell age, we find that beneficial mutations can spread significantly faster in a multicellular budding population than its corresponding unicellular population or a population reproducing via binary fission. Our results demonstrate that basic aspects of the cell cycle can give rise to different rates of adaptation in multicellular organisms.

Evolution of Cellular Differentiation: From Hypotheses to Models

Cellular differentiation is one of the hallmarks of complex multicellularity, allowing individual organisms to capitalize on among-cell functional diversity. The evolution of multicellularity is a major evolutionary transition that allowed for the increase of organismal complexity in multiple lineages, a process that relies on the functional integration of cell-types within an individual. Multiple hypotheses have been proposed to explain the origins of cellular differentiation, but we lack a general understanding of what makes one cell-type distinct from others, and how such differentiation arises. Here, we describe how the use of Boolean networks (BNs) can aid in placing empirical findings into a coherent conceptual framework, and we emphasize some of the standing problems when interpreting data and model behaviors.

The Order of Trait Emergence in the Evolution of Cyanobacterial Multicellularity

The transition from unicellular to multicellular organisms is one of the most significant events in the history of life. Key to this process is the emergence of Darwinian individuality at the higher level: Groups must become single entities capable of reproduction for selection to shape their evolution. Evolutionary transitions in individuality are characterized by cooperation between the lower level entities and by division of labor. Theory suggests that division of labor may drive the transition to multicellularity by eliminating the trade off between two incompatible processes that cannot be performed simultaneously in one cell. Here, we examine the evolution of the most ancient multicellular transition known today, that of cyanobacteria, where we reconstruct the sequence of ecological and phenotypic trait evolution. Our results show that the prime driver of multicellularity in cyanobacteria was the expansion in metabolic capacity offered by nitrogen fixation, which was accompanied by the emergence of the filamentous morphology and succeeded by a reproductive life cycle. This was followed by the progression of multicellularity into higher complexity in the form of differentiated cells and patterned multicellularity.

Evolution of multicellular life cycles under costly fragmentation

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.

Evolution of Multicellularity: One from Many or Many from One?

Multicellularity has evolved many times. A new study explores why some forms of multicellularity may be better than others.

Ecological Advantages and Evolutionary Limitations of Aggregative Multicellular Development

All multicellular organisms develop through one of two basic routes: they either aggregate from free-living cells, creating potentially chimeric multicellular collectives, or they develop clonally via mother-daughter cellular adhesion. Although evolutionary theory makes clear predictions about trade-offs between these developmental modes, these have never been experimentally tested in otherwise genetically identical organisms. We engineered unicellular baker's yeast (Saccharomyces cerevisiae) to develop either clonally ("snowflake"; Δace2) or aggregatively ("floc"; GAL1p::FLO1) and examined their fitness in a fluctuating environment characterized by periods of growth and selection for rapid sedimentation. When cultured independently, aggregation was far superior to clonal development, providing a 35% advantage during growth and a 2.5-fold advantage during settling selection. Yet when competed directly, clonally developing snowflake yeast rapidly displaced aggregative floc. This was due to unexpected social exploitation: snowflake yeast, which do not produce adhesive FLO1, nonetheless become incorporated into flocs at a higher frequency than floc cells themselves. Populations of chimeric clusters settle much faster than floc alone, providing snowflake yeast with a fitness advantage during competition. Mathematical modeling suggests that such developmental cheating may be difficult to circumvent; hypothetical "choosy floc" that avoid exploitation by maintaining clonality pay an ecological cost when rare, often leading to their extinction. Our results highlight the conflict at the heart of aggregative development: non-specific cellular binding provides a strong ecological advantage-the ability to quickly form groups-but this very feature leads to its exploitation.

Interplay of mesoscale physics and agent-like behaviors in the parallel evolution of aggregative multicellularity

Myxobacteria and dictyostelids are prokaryotic and eukaryotic multicellular lineages, respectively, that after nutrient depletion aggregate and develop into structures called fruiting bodies. The developmental processes and resulting morphological outcomes resemble one another to a remarkable extent despite their independent origins, the evolutionary distance between them and the lack of traceable homology in molecular mechanisms. We hypothesize that the morphological parallelism between the two lineages arises as the consequence of the interplay within multicellular aggregates between generic processes, physical and physicochemical processes operating similarly in living and non-living matter at the mesoscale (~10^-3-10^-1 m) and agent-like behaviors, unique to living systems and characteristic of the constituent cells, considered as autonomous entities acting according to internal rules in a shared environment. Here, we analyze the contributions of generic and agent-like determinants in myxobacteria and dictyostelid development and their roles in the generation of their common traits. Consequent to aggregation, collective cell-cell contacts mediate the emergence of liquid-like properties, making nascent multicellular masses subject to novel patterning and morphogenetic processes. In both lineages, this leads to behaviors such as streaming, rippling, and rounding-up, as seen in non-living fluids. Later the aggregates solidify, leading them to exhibit additional generic properties and motifs. Computational models suggest that the morphological phenotypes of the multicellular masses deviate from the predictions of generic physics due to the contribution of agent-like behaviors of cells such as directed migration, quiescence, and oscillatory signal transduction mediated by responses to external cues. These employ signaling mechanisms that reflect the evolutionary histories of the respective organisms. We propose that the similar developmental trajectories of myxobacteria and dictyostelids are more due to shared generic physical processes in coordination with analogous agent-type behaviors than to convergent evolution under parallel selection regimes. Insights from the biology of these aggregative forms may enable a unified understanding of developmental evolution, including that of animals and plants.

Resource plasticity-driven carbon-nitrogen budgeting enables specialization and division of labor in a clonal community

Previously, we found that in glucose-limited Saccharomyces cerevisiae colonies, metabolic constraints drive cells into groups exhibiting gluconeogenic or glycolytic states. In that study, threshold amounts of trehalose - a limiting, produced carbon-resource, controls the emergence and self-organization of cells exhibiting the glycolytic state, serving as a carbon source that fuels glycolysis (Varahan et al., 2019). We now discover that the plasticity of use of a non-limiting resource, aspartate, controls both resource production and the emergence of heterogeneous cell states, based on differential metabolic budgeting. In gluconeogenic cells, aspartate is a carbon source for trehalose production, while in glycolytic cells using trehalose for carbon, aspartate is predominantly a nitrogen source for nucleotide synthesis. This metabolic plasticity of aspartate enables carbon-nitrogen budgeting, thereby driving the biochemical self-organization of distinct cell states. Through this organization, cells in each state exhibit true division of labor, providing growth/survival advantages for the whole community.

Evolution of simple multicellular life cycles in dynamic environments

The mode of reproduction is a critical characteristic of any species, as it has a strong effect on its evolution. As any other trait, the reproduction mode is subject to natural selection and may adapt to the environment. When the environment varies over time, different reproduction modes could be optimal at different times. The natural response to a dynamic environment seems to be bet hedging, where multiple reproductive strategies are stochastically executed. Here, we develop a framework for the evolution of simple multicellular life cycles in a dynamic environment. We use a matrix population model of undifferentiated multicellular groups undergoing fragmentation and ask which mode maximizes the population growth rate. Counterintuitively, we find that natural selection in dynamic environments generally tends to promote deterministic, not stochastic, reproduction modes.

Turbulent coherent structures and early life below the Kolmogorov scale

Major evolutionary transitions, including the emergence of life, likely occurred in aqueous environments. While the role of water’s chemistry in early life is well studied, the effects of water’s ability to manipulate population structure are less clear. Population structure is known to be critical, as effective replicators must be insulated from parasites. Here, we propose that turbulent coherent structures, long-lasting flow patterns which trap particles, may serve many of the properties associated with compartments — collocalization, division, and merging — which are commonly thought to play a key role in the origins of life and other evolutionary transitions. We substantiate this idea by simulating multiple proposed metabolisms for early life in a simple model of a turbulent flow, and find that balancing the turnover times of biological particles and coherent structures can indeed enhance the likelihood of these metabolisms overcoming extinction either via parasitism or via a lack of metabolic support. Our results suggest that group selection models may be applicable with fewer physical and chemical constraints than previously thought, and apply much more widely in aqueous environments.

Models of the origin of life generally require a mechanism to structure emerging populations. Here, Krieger et al. develop spatial models showing that coherent structures arising in turbulent flows in aquatic environments could have provided compartments that facilitated the origin of life.

Coexistence and cooperation in structured habitats

Background

Natural habitats are typically structured, imposing constraints on inhabiting populations and their interactions. Which conditions are important for coexistence of diverse communities, and how cooperative interaction stabilizes in such populations, have been important ecological and evolutionary questions.

Results

We investigate a minimal ecological framework of microbial population dynamics that exhibits crucial features to show coexistence: Populations repeatedly undergo cycles of separation into compartmentalized habitats and mixing with new resources. The characteristic time-scale is longer than that typical of individual growth. Using analytic approximations, averaging techniques and phase-plane methods of dynamical systems, we provide a framework for analyzing various types of microbial interactions. Population composition and population size are both dynamic variables of the model; they are found to be decoupled both in terms of time-scale and parameter dependence. We present specific results for two examples of cooperative interaction by public goods: collective antibiotics resistance, and enhanced iron-availability by pyoverdine. We find stable coexistence to be a likely outcome.

Conclusions

The two simple features of a long mixing time-scale and spatial compartmentalization are enough to enable coexisting strains. In particular, costly social traits are often stabilized in such an environment—and thus cooperation established.

The Computational Boundary of a "Self": Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition

All epistemic agents physically consist of parts that must somehow comprise an integrated cognitive self. Biological individuals consist of subunits (organs, cells, and molecular networks) that are themselves complex and competent in their own native contexts. How do coherent biological Individuals result from the activity of smaller sub-agents? To understand the evolution and function of metazoan creatures' bodies and minds, it is essential to conceptually explore the origin of multicellularity and the scaling of the basal cognition of individual cells into a coherent larger organism. In this article, I synthesize ideas in cognitive science, evolutionary biology, and developmental physiology toward a hypothesis about the origin of Individuality: "Scale-Free Cognition." I propose a fundamental definition of an Individual based on the ability to pursue goals at an appropriate level of scale and organization and suggest a formalism for defining and comparing the cognitive capacities of highly diverse types of agents. Any Self is demarcated by a computational surface - the spatio-temporal boundary of events that it can measure, model, and try to affect. This surface sets a functional boundary - a cognitive "light cone" which defines the scale and limits of its cognition. I hypothesize that higher level goal-directed activity and agency, resulting in larger cognitive boundaries, evolve from the primal homeostatic drive of living things to reduce stress - the difference between current conditions and life-optimal conditions. The mechanisms of developmental bioelectricity - the ability of all cells to form electrical networks that process information - suggest a plausible set of gradual evolutionary steps that naturally lead from physiological homeostasis in single cells to memory, prediction, and ultimately complex cognitive agents, via scale-up of the basic drive of infotaxis. Recent data on the molecular mechanisms of pre-neural bioelectricity suggest a model of how increasingly sophisticated cognitive functions emerge smoothly from cell-cell communication used to guide embryogenesis and regeneration. This set of hypotheses provides a novel perspective on numerous phenomena, such as cancer, and makes several unique, testable predictions for interdisciplinary research that have implications not only for evolutionary developmental biology but also for biomedicine and perhaps artificial intelligence and exobiology.

Social genes are selection hotspots in kin groups of a soil microbe

The composition of cooperative systems, including animal societies, organismal bodies, and microbial groups, reflects their past and shapes their future evolution. However, genomic diversity within many multiunit systems remains uncharacterized, limiting our ability to understand and compare their evolutionary character. We have analyzed genomic and social-phenotype variation among 120 natural isolates of the cooperative bacterium Myxococcus xanthus derived from six multicellular fruiting bodies. Each fruiting body was composed of multiple lineages radiating from a unique recent ancestor. Genomic evolution was concentrated in selection hotspots associated with evolutionary change in social phenotypes. Synonymous mutations indicated that kin lineages within the same fruiting body often first diverged from a common ancestor more than 100 generations ago. Thus, selection appears to promote endemic diversification of kin lineages that remain together over long histories of local interaction, thereby potentiating social coevolution.

Multilevel selection as Bayesian inference, major transitions in individuality as structure learning

Complexity of life forms on the Earth has increased tremendously, primarily driven by subsequent evolutionary transitions in individuality, a mechanism in which units formerly being capable of independent replication combine to form higher-level evolutionary units. Although this process has been likened to the recursive combination of pre-adapted sub-solutions in the framework of learning theory, no general mathematical formalization of this analogy has been provided yet. Here we show, building on former results connecting replicator dynamics and Bayesian update, that (i) evolution of a hierarchical population under multilevel selection is equivalent to Bayesian inference in hierarchical Bayesian models and (ii) evolutionary transitions in individuality, driven by synergistic fitness interactions, is equivalent to learning the structure of hierarchical models via Bayesian model comparison. These correspondences support a learning theory-oriented narrative of evolutionary complexification: the complexity and depth of the hierarchical structure of individuality mirror the amount and complexity of data that have been integrated about the environment through the course of evolutionary history.

Emergence of diverse life cycles and life histories at the origin of multicellularity

The evolution of multicellularity has given rise to a remarkable diversity of multicellular life cycles and life histories. Whereas some multicellular organisms are long-lived, grow through cell division, and repeatedly release single-celled propagules (for example, animals), others are short-lived, form by aggregation, and propagate only once, by generating large numbers of solitary cells (for example, cellular slime moulds). There are no systematic studies that explore how diverse multicellular life cycles can come about. Here, we focus on the origin of multicellularity and develop a mechanistic model to examine the primitive life cycles that emerge from a unicellular ancestor when an ancestral gene is co-opted for cell adhesion. Diverse life cycles readily emerge, depending on ecological conditions, group-forming mechanism, and ancestral constraints. Among these life cycles, we recapitulate both extremes of long-lived groups that propagate continuously and short-lived groups that propagate only once, with the latter type of life cycle being particularly favoured when groups can form by aggregation. Our results show how diverse life cycles and life histories can easily emerge at the origin of multicellularity, shaped by ancestral constraints and ecological conditions. Beyond multicellularity, this finding has similar implications for other major transitions, such as the evolution of sociality.

Defining Division of Labor in Microbial Communities

In order to survive and reproduce, organisms must perform a multitude of tasks. However, trade-offs limit their ability to allocate energy and resources to all of these different processes. One strategy to solve this problem is to specialize in some traits and team up with other organisms that can help by providing additional, complementary functions. By reciprocally exchanging metabolites and/or services in this way, both parties benefit from the interaction. This phenomenon, which has been termed functional specialization or division of labor, is very common in nature and exists on all levels of biological organization. Also, microorganisms have evolved different types of synergistic interactions. However, very often, it remains unclear whether or not a given example represents a true case of division of labor. Here we aim at filling this gap by providing a list of criteria that clearly define division of labor in microbial communities. Furthermore, we propose a set of diagnostic experiments to verify whether a given interaction fulfills these conditions. In contrast to the common use of the term, our analysis reveals that both intraspecific and interspecific interactions meet the criteria defining division of labor. Moreover, our analysis identified non-cooperators of intraspecific public goods interactions as growth specialists that divide labor with conspecific producers, rather than being social parasites. By providing a conceptual toolkit, our work will help to unambiguously identify cases of division of labor and stimulate more detailed investigations of this important and widespread type of inter-microbial interaction.

Interacting cells driving the evolution of multicellular life cycles

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.

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.

The replicator dynamics for multilevel selection in evolutionary games

We consider a stochastic model for evolution of group-structured populations in which interactions between group members correspond to the Prisoner's Dilemma or the Hawk-Dove game. Selection operates at two organization levels: individuals compete with peer group members based on individual payoff, while groups also compete with other groups based on average payoff of group members. In the Prisoner's Dilemma, this creates a tension between the two levels of selection, as defectors are favored at the individual level, whereas groups with at least some cooperators outperform groups of defectors at the between-group level. In the limit of infinite group size and infinite number of groups, we derive a non-local PDE that describes the probability distribution of group compositions in the population. For special families of payoff matrices, we characterize the long-time behavior of solutions of our equation, finding a threshold intensity of between-group selection required to sustain density steady states and the survival of cooperation. When all-cooperator groups are most fit, the average and most abundant group compositions at steady state range from featuring all-defector groups when individual-level selection dominates to featuring all-cooperator groups when group-level selection dominates. When the most fit groups have a mix of cooperators and defectors, then the average and most abundant group compositions always feature a smaller fraction of cooperators than required for the optimal mix, even in the limit where group-level selection is infinitely stronger than individual-level selection. In such cases, the conflict between the two levels of selection cannot be decoupled, and cooperation cannot be sustained at all in the case where between-group competition favors an even mix of cooperators and defectors.

Does resource availability help determine the evolutionary route to multicellularity?

Genetic heterogeneity and homogeneity are associated with distinct sets of adaptive advantages and bottlenecks, both in developmental biology and population genetics. Whereas populations of individuals are usually genetically heterogeneous, most multicellular metazoans are genetically homogeneous. Observing that resource scarcity fuels genetic heterogeneity in populations, we propose that monoclonal development is compatible with the resource‐rich and stable internal environments that complex multicellular bodies offer. In turn, polyclonal development persists in tumors and in certain metazoans, both exhibiting a closer dependence on external resources. This eco‐evo‐devo approach also suggests that multicellularity may originally have emerged through polyclonal development in early metazoans, because of their reduced shielding from environmental fluctuations.

Aggregate Filamentous Growth Responses in Yeast

Filamentous growth is a fungal morphogenetic response that is critical for virulence in some fungal species. Many aspects of filamentous growth remain poorly understood. We have identified an aspect of filamentous growth in the budding yeast Saccharomyces cerevisiae and the human pathogen Candida albicans where cells behave collectively to invade surfaces in aggregates. These responses may reflect an extension of normal filamentous growth, as they share the same signaling pathways and effector processes. Aggregate responses may involve cooperation among individual cells, because aggregation was stimulated by cell adhesion molecules, secreted enzymes, and diffusible molecules that promote quorum sensing. Our study may provide insights into the genetic basis of collective cellular responses in fungi. The study may have ramifications in fungal pathogenesis, in situations where collective responses occur to promote virulence.

Many fungal species, including pathogens, undergo a morphogenetic response called filamentous growth, where cells differentiate into a specialized cell type to promote nutrient foraging and surface colonization. Despite the fact that filamentous growth is required for virulence in some plant and animal pathogens, certain aspects of this behavior remain poorly understood. By examining filamentous growth in the budding yeast Saccharomyces cerevisiae and the opportunistic pathogen Candida albicans, we identify responses where cells undergo filamentous growth in groups of cells or aggregates. In S. cerevisiae, aggregate invasive growth was regulated by signaling pathways that control normal filamentous growth. These pathways promoted aggregation in part by fostering aspects of microbial cooperation. For example, aggregate invasive growth required cellular contacts mediated by the flocculin Flo11p, which was produced at higher levels in aggregates than cells undergoing regular invasive growth. Aggregate invasive growth was also stimulated by secreted enzymes, like invertase, which produce metabolites that are shared among cells. Aggregate invasive growth was also induced by alcohols that promote density-dependent filamentous growth in yeast. Aggregate invasive growth also required highly polarized cell morphologies, which may affect the packing or organization of cells. A directed selection experiment for aggregating phenotypes uncovered roles for the fMAPK and RAS pathways, which indicates that these pathways play a general role in regulating aggregate-based responses in yeast. Our study extends the range of responses controlled by filamentation regulatory pathways and has implications in understanding aspects of fungal biology that may be relevant to fungal pathogenesis.

IMPORTANCE Filamentous growth is a fungal morphogenetic response that is critical for virulence in some fungal species. Many aspects of filamentous growth remain poorly understood. We have identified an aspect of filamentous growth in the budding yeast Saccharomyces cerevisiae and the human pathogen Candida albicans where cells behave collectively to invade surfaces in aggregates. These responses may reflect an extension of normal filamentous growth, as they share the same signaling pathways and effector processes. Aggregate responses may involve cooperation among individual cells, because aggregation was stimulated by cell adhesion molecules, secreted enzymes, and diffusible molecules that promote quorum sensing. Our study may provide insights into the genetic basis of collective cellular responses in fungi. The study may have ramifications in fungal pathogenesis, in situations where collective responses occur to promote virulence.

Selection for synchronized cell division in simple multicellular organisms

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.

The Cost of Being Big: Local Competition, Importance of Dispersal, and Experimental Evolution of Reversal to Unicellularity

Multicellularity provides multiple benefits. Nonetheless, unicellularity is ubiquitous, and there have been multiple cases of evolutionary reversal to a unicellular organization. In this article, we explore some of the costs of multicellularity as well as the possibility and dynamics of evolutionary reversals to unicellularity. We hypothesize that recently evolved multicellular organisms would face a high cost of increased competition for local resources in spatially structured environments because of larger size and increased cell densities. To test this hypothesis we conducted competition assays, computer simulations, and selection experiments using isolates of Saccharomyces cerevisiae that recently evolved multicellularity. In well-mixed environments, multicellular isolates had lower growth rates relative to their unicellular ancestor because of limitations of space and resource acquisition. In structured environments with localized resources, cells in both multicellular and unicellular isolates grew at a similar rate. Despite similar growth, higher local density of cells in multicellular groups led to increased competition and higher fitness costs in spatially structured environments. In structured environments all of the multicellular isolates rapidly evolved a predominantly unicellular life cycle, while in well-mixed environments reversal was more gradual. Taken together, these results suggest that a lack of dispersal, leading to higher local competition, might have been one of the main constraints in the evolution of early multicellular forms.

Nascent life cycles and the emergence of higher-level individuality

Evolutionary transitions in individuality (ETIs) occur when formerly autonomous organisms evolve to become parts of a new, 'higher-level' organism. One of the first major hurdles that must be overcome during an ETI is the emergence of Darwinian evolvability in the higher-level entity (e.g. a multicellular group), and the loss of Darwinian autonomy in the lower-level units (e.g. individual cells). Here, we examine how simple higher-level life cycles are a key innovation during an ETI, allowing this transfer of fitness to occur 'for free'. Specifically, we show how novel life cycles can arise and lead to the origin of higher-level individuals by (i) mitigating conflicts between levels of selection, (ii) engendering the expression of heritable higher-level traits and (iii) allowing selection to efficiently act on these emergent higher-level traits. Further, we compute how canonical early life cycles vary in their ability to fix beneficial mutations via mathematical modelling. Life cycles that lack a persistent lower-level stage and develop clonally are far more likely to fix 'ratcheting' mutations that limit evolutionary reversion to the pre-ETI state. By stabilizing the fragile first steps of an evolutionary transition in individuality, nascent higher-level life cycles may play a crucial role in the origin of complex life.This article is part of the themed issue 'Process and pattern in innovations from cells to societies'.

A theoretical approach to the size-complexity rule

The so-called size-complexity rule claims the existence of a positive correlation between organism size and number of cell types. In this spirit, here we address the relationship between organism size and number of potential tasks that can be performed. The modeling relies on the assumption that the states of the cells within the aggregates are such that the maximum fitness is realized, but also relies on the existence of tradeoffs among the distinct functions. For group sizes larger than the number of potential tasks, fitness maximization is attained when all cells in group specialize in a given task. Under this scenario, the number of potential tasks equals the number of cell types. We have found that the morphology and the topology of aggregates, as well as the developmental mode, strongly influence the dynamics of body formation. Particularly, it has been observed that more compact structures, such as sphere-like structures, are more likely to follow the claim of the size-complexity rule, whereas more fragile structures such as linear chains, which are more vulnerable to drastic changes due to division mechanisms, can, in a broad scenario, violate the size-complexity rule.

Fragmentation modes and the evolution of life cycles

Reproduction is a defining feature of living systems. To reproduce, aggregates of biological units (e.g., multicellular organisms or colonial bacteria) must fragment into smaller parts. Fragmentation modes in nature range from binary fission in bacteria to collective-level fragmentation and the production of unicellular propagules in multicellular organisms. Despite this apparent ubiquity, the adaptive significance of fragmentation modes has received little attention. Here, we develop a model in which groups arise from the division of single cells that do not separate but stay together until the moment of group fragmentation. We allow for all possible fragmentation patterns and calculate the population growth rate of each associated life cycle. Fragmentation modes that maximise growth rate comprise a restrictive set of patterns that include production of unicellular propagules and division into two similar size groups. Life cycles marked by single-cell bottlenecks maximise population growth rate under a wide range of conditions. This surprising result offers a new evolutionary explanation for the widespread occurrence of this mode of reproduction. All in all, our model provides a framework for exploring the adaptive significance of fragmentation modes and their associated life cycles.

Mode of reproduction is a defining trait of all organisms, including colonial bacteria and multicellular organisms. To produce offspring, aggregates must fragment by splitting into two or more groups. The particular way that a given group fragments defines the life cycle of the organism. For instance, insect colonies can reproduce by splitting or by producing individuals that found new colonies. Similarly, some colonial bacteria propagate by fission or by releasing single cells, while others split in highly sophisticated ways; in multicellular organisms reproduction typically proceeds via a single-cell bottleneck phase. The space of possibilities for fragmentation is so vast that an exhaustive analysis seems daunting. Focusing on fragmentation modes of a simple kind we parametrise all possible modes of group fragmentation and identify those modes leading to the fastest population growth rate. Two kinds of life cycle dominate: one involving division into two equal size groups, and the other involving production of a unicellular propagule. The prevalence of these life cycles in nature is consistent with our null model and suggests that benefits accruing from population growth rate alone may have shaped the evolution of fragmentation mode.

On the origin of biological construction, with a focus on multicellularity

Biology is marked by a hierarchical organization: all life consists of cells; in some cases, these cells assemble into groups, such as endosymbionts or multicellular organisms; in turn, multicellular organisms sometimes assemble into yet other groups, such as primate societies or ant colonies. The construction of new organizational layers results from hierarchical evolutionary transitions, in which biological units (e.g., cells) form groups that evolve into new units of biological organization (e.g., multicellular organisms). Despite considerable advances, there is no bottom-up, dynamical account of how, starting from the solitary ancestor, the first groups originate and subsequently evolve the organizing principles that qualify them as new units. Guided by six central questions, we propose an integrative bottom-up approach for studying the dynamics underlying hierarchical evolutionary transitions, which builds on and synthesizes existing knowledge. This approach highlights the crucial role of the ecology and development of the solitary ancestor in the emergence and subsequent evolution of groups, and it stresses the paramount importance of the life cycle: only by evaluating groups in the context of their life cycle can we unravel the evolutionary trajectory of hierarchical transitions. These insights also provide a starting point for understanding the types of subsequent organizational complexity. The central research questions outlined here naturally link existing research programs on biological construction (e.g., on cooperation, multilevel selection, self-organization, and development) and thereby help integrate knowledge stemming from diverse fields of biology.

Synergistic cooperation promotes multicellular performance and unicellular free-rider persistence

The evolution of multicellular life requires cooperation among cells, which can be undermined by intra-group selection for selfishness. Theory predicts that selection to avoid non-cooperators limits social interactions among non-relatives, yet previous evolution experiments suggest that intra-group conflict is an outcome, rather than a driver, of incipient multicellular life cycles. Here we report the evolution of multicellularity via two distinct mechanisms of group formation in the unicellular budding yeast Kluyveromyces lactis. Cells remain permanently attached following mitosis, giving rise to clonal clusters (staying together); clusters then reversibly assemble into social groups (coming together). Coming together amplifies the benefits of multicellularity and allows social clusters to collectively outperform solitary clusters. However, cooperation among non-relatives also permits fast-growing unicellular lineages to 'free-ride' during selection for increased size. Cooperation and competition for the benefits of multicellularity promote the stable coexistence of unicellular and multicellular genotypes, underscoring the importance of social and ecological context during the transition to multicellularity.

The ecology and evolution of social behavior in microbes

Cooperation has been studied extensively across the tree of life, from eusociality in insects to social behavior in humans, but it is only recently that a social dimension has been recognized and extensively explored for microbes. Research into microbial cooperation has accelerated dramatically and microbes have become a favorite system because of their fast evolution, their convenience as lab study systems and the opportunity for molecular investigations. However, the study of microbes also poses significant challenges, such as a lack of knowledge and an inaccessibility of the ecological context (used here to include both the abiotic and the biotic environment) under which the trait deemed cooperative has evolved and is maintained. I review the experimental and theoretical evidence in support of the limitations of the study of social behavior in microbes in the absence of an ecological context. I discuss both the need and the opportunities for experimental investigations that can inform a theoretical framework able to reframe the general questions of social behavior in a clear ecological context and to account for eco-evolutionary feedback.