Beyond Fitness Decoupling: Tradeoff-breaking during Evolutionary Transitions in Individuality

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 anETI, 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. Using a mathematical approach we show this concept to be problematic in that the fitness of particles and collectives can never decouple: calculations of particle and collective fitness performed over appropriate and equivalent time intervals are necessarily the same. By way of solution, we draw attention to the value of mechanistic approaches that emphasise traits as opposed to fitness and tradeoffs among traits. 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 rupture of such tradeoffs. Tradeoff-breaking thus stands as a useful marker for ETIs.

Division of labor and fitness decoupling in evolutionary transitions in individuality

Reproductive division of labor has been proposed to play a key role for evolutionary transitions in individuality (ETIs). This chapter provides a guide to a theoretical model that addresses the role of a tradeoff between life-history traits in selecting for a reproductive division of labor during the transition from unicellular to multicellular organisms. In particular, it focuses on the five keys assumptions of the model, namely (1) fitness is viability times fecundity; (2) collective traits are linear functions of their cellular counterparts; (3) there is a tradeoff between cell viability and fecundity; (4) cell contribution to the collective is optimal; and (5) there is an initial reproductive cost in large collectives. Thereafter the chapter contrasts two interpretations of the model in the context of ETIs. Originally, the model was interpreted as showing that during the transition to multicellularity the fitness of the lower-level (the cells) is “transferred” to the higher level (the collective). Despite its apparent intuitiveness, fitness transfer may obscure actual mechanisms in metaphorical language. Thus, an alternative and more conservative interpretation of the model that focuses on cell traits and the evolutionary constraints that links them is advocated. In addition, it allows for pursuing subsequent questions, such as the evolution of development.

Operationalizing evolutionary transitions in individuality

Evolutionary transitions in individuality (hereafter, ETIs), such as the transition to multi-cellularity and the transition to social colonies, have been at the centre of evolutionary research, but only few attempts were made to systematically operationalize this concept. Here, we devise a set of four indicators intended to assess the change in complexity during ETIs: system size, inseparability, reproductive specialization and non-reproductive specialization. We then conduct a quantitative comparison across multiple taxa and ETIs. Our analysis reveals that inseparability has a crucial role in the process; it seems irreversible and may mark the point where a group of individuals becomes a new individual at a higher hierarchical level. Interestingly, we find that disparate groups demonstrate a similar pattern of progression along ETIs.

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.

The levels of selection and evolution of individuality

In this article I will analyze the transfer of fitness during the major transitions in evolution and its place in the multilevel selection models. The aim of the analysis is to show how social evolution can explain the evolutionary transitions in individuality.

Major evolutionary transitions as Bayesian structure learning

Complexity of life forms on 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 subsolutions 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 mirrors the amount and complexity of data that has been integrated about the environment through the course of evolutionary history.

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’.

Stabilizing multicellularity through ratcheting

The evolutionary transition to multicellularity probably began with the formation of simple undifferentiated cellular groups. Such groups evolve readily in diverse lineages of extant unicellular taxa, suggesting that there are few genetic barriers to this first key step. This may act as a double-edged sword: labile transitions between unicellular and multicellular states may facilitate the evolution of simple multicellularity, but reversion to a unicellular state may inhibit the evolution of increased complexity. In this paper, we examine how multicellular adaptations can act as evolutionary ‘ratchets’, limiting the potential for reversion to unicellularity. We consider a nascent multicellular lineage growing in an environment that varies between favouring multicellularity and favouring unicellularity. The first type of ratcheting mutations increase cell-level fitness in a multicellular context but are costly in a single-celled context, reducing the fitness of revertants. The second type of ratcheting mutations directly decrease the probability that a mutation will result in reversion (either as a pleiotropic consequence or via direct modification of switch rates). We show that both types of ratcheting mutations act to stabilize the multicellular state. We also identify synergistic effects between the two types of ratcheting mutations in which the presence of one creates the selective conditions favouring the other. Ratcheting mutations may play a key role in diverse evolutionary transitions in individuality, sustaining selection on the new higher-level organism by constraining evolutionary reversion. This article is part of the themed issue ‘The major synthetic evolutionary transitions’.

Major evolutionary transitions of life, metabolic scaling and the number and size of mitochondria and chloroplasts

We investigate the effects of trophic lifestyle and two types of major evolutionary transitions in individuality—the endosymbiotic acquisition of organelles and development of multicellularity—on organellar and cellular metabolism and allometry. We develop a quantitative framework linking the size and metabolic scaling of eukaryotic cells to the abundance, size and metabolic scaling of mitochondria and chloroplasts and analyse a newly compiled, unprecedented database representing unicellular and multicellular cells covering diverse phyla and tissues. Irrespective of cellularity, numbers and total volumes of mitochondria scale linearly with cell volume, whereas chloroplasts scale sublinearly and sizes of both organelles remain largely invariant with cell size. Our framework allows us to estimate the metabolic scaling exponents of organelles and cells. Photoautotrophic cells and organelles exhibit photosynthetic scaling exponents always less than one, whereas chemoheterotrophic cells and organelles have steeper respiratory scaling exponents close to one. Multicellularity has no discernible effect on the metabolic scaling of organelles and cells. In contrast, trophic lifestyle has a profound and uniform effect, and our results suggest that endosymbiosis fundamentally altered the metabolic scaling of free-living bacterial ancestors of mitochondria and chloroplasts, from steep ancestral scaling to a shallower scaling in their endosymbiotic descendants.