The Mass-Longevity Triangle: Pareto Optimality and the Geometry of Life-History Trait Space

When organisms need to perform multiple tasks they face a fundamental tradeoff: no phenotype can be optimal at all tasks. This situation was recently analyzed using Pareto optimality, showing that tradeoffs between tasks lead to phenotypes distributed on low dimensional polygons in trait space. The vertices of these polygons are archetypes—phenotypes optimal at a single task. This theory was applied to examples from animal morphology and gene expression. Here we ask whether Pareto optimality theory can apply to life history traits, which include longevity, fecundity and mass. To comprehensively explore the geometry of life history trait space, we analyze a dataset of life history traits of 2105 endothermic species. We find that, to a first approximation, life history traits fall on a triangle in log-mass log-longevity space. The vertices of the triangle suggest three archetypal strategies, exemplified by bats, shrews and whales, with specialists near the vertices and generalists in the middle of the triangle. To a second approximation, the data lies in a tetrahedron, whose extra vertex above the mass-longevity triangle suggests a fourth strategy related to carnivory. Each animal species can thus be placed in a coordinate system according to its distance from the archetypes, which may be useful for genome-scale comparative studies of mammalian aging and other biological aspects. We further demonstrate that Pareto optimality can explain a range of previous studies which found animal and plant phenotypes which lie in triangles in trait space. This study demonstrates the applicability of multi-objective optimization principles to understand life history traits and to infer archetypal strategies that suggest why some mammalian species live much longer than others of similar mass.     

Geometry of the Gene Expression Space of Individual Cells

There is a revolution in the ability to analyze gene expression of single cells in a tissue. To understand this data we must comprehend how cells are distributed in a high-dimensional gene expression space. One open question is whether cell types form discrete clusters or whether gene expression forms a continuum of states. If such a continuum exists, what is its geometry? Recent theory on evolutionary trade-offs suggests that cells that need to perform multiple tasks are arranged in a polygon or polyhedron (line, triangle, tetrahedron and so on, generally called polytopes) in gene expression space, whose vertices are the expression profiles optimal for each task. Here, we analyze single-cell data from human and mouse tissues profiled using a variety of single-cell technologies. We fit the data to shapes with different numbers of vertices, compute their statistical significance, and infer their tasks. We find cases in which single cells fill out a continuum of expression states within a polyhedron. This occurs in intestinal progenitor cells, which fill out a tetrahedron in gene expression space. The four vertices of this tetrahedron are each enriched with genes for a specific task related to stemness and early differentiation. A polyhedral continuum of states is also found in spleen dendritic cells, known to perform multiple immune tasks: cells fill out a tetrahedron whose vertices correspond to key tasks related to maturation, pathogen sensing and communication with lymphocytes. A mixture of continuum-like distributions and discrete clusters is found in other cell types, including bone marrow and differentiated intestinal crypt cells. This approach can be used to understand the geometry and biological tasks of a wide range of single-cell datasets. The present results suggest that the concept of cell type may be expanded. In addition to discreet clusters in gene-expression space, we suggest a new possibility: a continuum of states within a polyhedron, in which the vertices represent specialists at key tasks.     

Reproductive physiology, dominance interactions, and division of labour among bumble bee workers

Abstract. Bumble bee workers (Bombus bifarius, Hymenoptera: Apidae) exhibit aggression toward one another after the colony begins producing female reproductive offspring (the competition phase). Workers in competition phase colonies must continue to perform in‐nest tasks, such as nest thermoregulation, and to forage for food, to rear the reproductives to maturity. Therefore, competition phase workers are faced with potentially conflicting pressures to work for their colonies, or to compete for direct reproduction. The effects of reproductive competition on worker task performance were quantified by measuring relationships of worker body size, reproductive physiology, and aggression with their rates of task performance. If worker division of labour was strongly affected by competition, it was predicted that fecund workers would avoid performing nest maintenance and foraging tasks, focusing instead on reproductive behaviour. Furthermore, it was predicted that fecund workers would dominate their nest mates, and that subordinate workers would perform nonreproductive tasks at higher rates. Worker aggression was associated closely with direct reproductive competition. Both aggression and brood interaction rates were related positively with ooctye development. Furthermore, foraging was associated negatively with ovarian development. However, in‐nest and foraging task performance rates were not associated with social aggression. The results support a partial role for reproductive competition in worker polyethism. Although worker aggression did not directly affect polyethism, reproductively competent workers avoided foraging tasks that would remove them from egg‐laying opportunities. Reproductively competent workers did perform in‐nest tasks, suggesting that these tasks entail little cost in terms of reproductive competition.     

On the evolution of omnivory in a community context

Omnivory is extremely common in animals, yet theory predicts that when given a choice of resources specialization should be favored over being generalist. The evolution of a feeding phenotype involves complex interactions with many factors other than resource choice alone, including environmental heterogeneity, resource quality, availability, and interactions with other organisms. We applied an evolutionary simulation model to examine how ecological conditions shape evolution of feeding phenotypes (e.g., omnivory), by varying the quality and availability (absolute and relative) of plant and animal (prey) resources. Resulting feeding phenotypes were defined by the relative contribution of plants and prey to diets of individuals. We characterized organisms using seven traits that were allowed to evolve freely in different simulated environments, and we asked which traits are important for different feeding phenotypes to evolve among interacting organisms. Carnivores, herbivores, and omnivores all coexisted without any requirement in the model for a synergistic effect of eating plant and animal prey. Omnivores were most prevalent when ratio of plants and animal prey was low, and to a lesser degree, when habitat productivity was high. A key result of the model is that omnivores evolved through many different combinations of trait values and environmental contexts. Specific combinations of traits tended to form emergent trait complexes, and under certain environmental conditions, are expressed as omnivorous feeding phenotypes. The results indicate that relative availabilities of plants and prey (over the quality of resources) determine an individual's feeding class and that feeding phenotypes are often the product of convergent evolution of emergent trait complexes under specific environmental conditions. Foraging outcomes appear to be consequences of degree and type of phenotypic specialization for plant and animal prey, navigation and exploitation of the habitat, reproduction, and interactions with other individuals in a heterogeneous environment. Omnivory should not be treated as a fixed strategy, but instead a pattern of phenotypic expression, emerging from diverse genetic sources and coevolving across a range of ecological contexts.     

Non‐genetic diversity modulates population performance

Biological functions are typically performed by groups of cells that express predominantly the same genes, yet display a continuum of phenotypes. While it is known how one genotype can generate such non‐genetic diversity, it remains unclear how different phenotypes contribute to the performance of biological function at the population level. We developed a microfluidic device to simultaneously measure the phenotype and chemotactic performance of tens of thousands of individual, freely swimming Escherichia coli as they climbed a gradient of attractant. We discovered that spatial structure spontaneously emerged from initially well‐mixed wild‐type populations due to non‐genetic diversity. By manipulating the expression of key chemotaxis proteins, we established a causal relationship between protein expression, non‐genetic diversity, and performance that was theoretically predicted. This approach generated a complete phenotype‐to‐performance map, in which we found a nonlinear regime. We used this map to demonstrate how changing the shape of a phenotypic distribution can have as large of an effect on collective performance as changing the mean phenotype, suggesting that selection could act on both during the process of adaptation.     

Co‐adaptation impacts the robustness of predator–prey dynamics against perturbations

Global change threatens the maintenance of ecosystem functions that are shaped by the persistence and dynamics of populations. It has been shown that the persistence of species increases if they possess larger trait adaptability. Here, we investigate whether trait adaptability also affects the robustness of population dynamics of interacting species and thereby shapes the reliability of ecosystem functions that are driven by these dynamics. We model co‐adaptation in a predator–prey system as changes to predator offense and prey defense due to evolution or phenotypic plasticity. We investigate how trait adaptation affects the robustness of population dynamics against press perturbations to environmental parameters and against pulse perturbations targeting species abundances and their trait values. Robustness of population dynamics is characterized by resilience, elasticity, and resistance. In addition to employing established measures for resilience and elasticity against pulse perturbations (extinction probability and return time), we propose the warping distance as a new measure for resistance against press perturbations, which compares the shapes and amplitudes of pre‐ and post‐perturbation population dynamics. As expected, we find that the robustness of population dynamics depends on the speed of adaptation, but in nontrivial ways. Elasticity increases with speed of adaptation as the system returns more rapidly to the pre‐perturbation state. Resilience, in turn, is enhanced by intermediate speeds of adaptation, as here trait adaptation dampens biomass oscillations. The resistance of population dynamics strongly depends on the target of the press perturbation, preventing a simple relationship with the adaptation speed. In general, we find that low robustness often coincides with high amplitudes of population dynamics. Hence, amplitudes may indicate the robustness against perturbations also in other natural systems with similar dynamics. Our findings show that besides counteracting extinctions, trait adaptation indeed strongly affects the robustness of population dynamics against press and pulse perturbations.     

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.     

Evolution of specialization in a spatially continuous environment

We study the evolution of specialization in a spatially continuous (one‐dimensional) environment divided into two habitats; we use a general trade‐off function relating fitnesses in the two habitats and illustrate our results with two classical trade‐off functions. We show that the population can either reach an intermediate value of the trait and be moderately adapted to both habitats (1 generalist), or split into two locally adapted subpopulations (2 specialists). We recover the qualitative results obtained with simpler metapopulation models with island migration: the evolutionary outcome depends on the concavity of the trade‐off, on the proportion of each habitat and on migration. Our quantitative prediction on migration, however, depends on isolation by distance. Our spatially explicit model may thus be particularly useful to describe the evolutionary dynamics of specialization in, perhaps, more realistic ecological scenarios.     

ON THE PARADIGM OF ALTRUISTIC SUICIDE IN THE UNICELLULAR WORLD

Altruistic suicide is best known in the context of programmed cell death (PCD) in multicellular individuals, which is understood as an adaptive process that contributes to the development and functionality of the organism. After the realization that PCD‐like processes can also be induced in single‐celled lineages, the paradigm of altruistic cell death has been extended to include these active cell death processes in unicellular organisms. Here, we critically evaluate the current conceptual framework and the experimental data used to support the notion of altruistic suicide in unicellular lineages, and propose new perspectives. We argue that importing the paradigm of altruistic cell death from multicellular organisms to explain active death in unicellular lineages has the potential to limit the types of questions we ask, thus biasing our understanding of the nature, origin, and maintenance of this trait. We also emphasize the need to distinguish between the benefits and the adaptive role of a trait. Lastly, we provide an alternative framework that allows for the possibility that active death in single‐celled organisms is a maladaptive trait maintained as a byproduct of selection on pro‐survival functions, but that could—under conditions in which kin/group selection can act—be co‐opted into an altruistic trait.     

Cross‐sex genetic covariances limit the evolvability of wing‐shape within and among species of Drosophila

The independent evolution of males and females is potentially constrained by both sexes inheriting the same alleles from their parents. This genetic constraint can limit the evolvability of complex traits; however, there are few studies of multivariate evolution that incorporate cross‐sex genetic covariances in their predictions. Drosophila wing‐shape has emerged as a model high‐dimensional phenotype; wing‐shape is highly evolvable in contemporary populations, and yet perplexingly stable across phylogenetic timescales. Here, we show that cross‐sex covariances in Drosophila melanogaster, given by the B ‐matrix, may considerably bias wing‐shape evolution. Using random skewers, we show that B would constrain the response to antagonistic selection by 90%, on average, but would double the response to concordant selection. Both cross‐sex within‐trait and cross‐sex cross‐trait covariances determined the predicted response to antagonistic selection, but only cross‐sex within‐trait covariances facilitated the predicted response to concordant selection. Similar patterns were observed in the direction of extant sexual dimorphism in D. melanogaster, and in directions of most and least dimorphic variation across the Drosophila phylogeny. Our results highlight the importance of considering between‐sex genetic covariances when making predictions about evolution on both macro‐ and microevolutionary timescales, and may provide one more explanatory piece in the puzzle of stasis.     

CHAOS AND UNPREDICTABILITY IN EVOLUTION

The possibility of complicated dynamic behavior driven by nonlinear feedbacks in dynamical systems has revolutionized science in the latter part of the last century. Yet despite examples of complicated frequency dynamics, the possibility of long‐term evolutionary chaos is rarely considered. The concept of “survival of the fittest” is central to much evolutionary thinking and embodies a perspective of evolution as a directional optimization process exhibiting simple, predictable dynamics. This perspective is adequate for simple scenarios, when frequency‐independent selection acts on scalar phenotypes. However, in most organisms many phenotypic properties combine in complicated ways to determine ecological interactions, and hence frequency‐dependent selection. Therefore, it is natural to consider models for evolutionary dynamics generated by frequency‐dependent selection acting simultaneously on many different phenotypes. Here we show that complicated, chaotic dynamics of long‐term evolutionary trajectories in phenotype space is very common in a large class of such models when the dimension of phenotype space is large, and when there are selective interactions between the phenotypic components. Our results suggest that the perspective of evolution as a process with simple, predictable dynamics covers only a small fragment of long‐term evolution.     

Joint phenotypes,evolutionary conflict and the fundamental theorem of natural selection

Multiple organisms can sometimes affect a common phenotype. For example, the portion of a leaf eaten by an insect is a joint phenotype of the plant and insect and the amount of food obtained by an offspring can be a joint trait with its mother. Here, I describe the evolution of joint phenotypes in quantitative genetic terms. A joint phenotype for multiple species evolves as the sum of additive genetic variances in each species, weighted by the selection on each species. Selective conflict between the interactants occurs when selection takes opposite signs on the joint phenotype. The mean fitness of a population changes not just through its own genetic variance but also through the genetic variance for its fitness that resides in other species, an update of Fisher''s fundamental theorem of natural selection. Some similar results, using inclusive fitness, apply to within-species interactions. The models provide a framework for understanding evolutionary conflicts at all levels.     

Context dependence in complex adaptive landscapes: frequency and trait‐dependent selection surfaces within an adaptive radiation of Caribbean pupfishes

The adaptive landscape provides the foundational bridge between micro‐ and macroevolution. One well‐known caveat to this perspective is that fitness surfaces depend on ecological context, including competitor frequency, traits measured, and resource abundance. However, this view is based largely on intraspecific studies. It is still unknown how context‐dependence affects the larger features of peaks and valleys on the landscape which ultimately drive speciation and adaptive radiation. Here, I explore this question using one of the most complex fitness landscapes measured in the wild in a sympatric pupfish radiation endemic to San Salvador Island, Bahamas by tracking survival and growth of laboratory‐reared F2 hybrids. I present new analyses of the effects of competitor frequency, dietary isotopes, and trait subsets on this fitness landscape. Contrary to expectations, decreasing competitor frequency increased survival only among very common phenotypes, whereas less common phenotypes rarely survived despite few competitors, suggesting that performance, not competitor frequency, shapes large‐scale features of the fitness landscape. Dietary isotopes were weakly correlated with phenotype and growth, but did not explain additional survival variation. Nonlinear fitness surfaces varied substantially among trait subsets, revealing one‐, two‐, and three‐peak landscapes, demonstrating the complexity of selection in the wild, even among similar functional traits.     

Engineering glyceraldehyde-3-phosphate dehydrogenase for switching control of glycolysis in Escherichia coli

Glycolysis has evolved to be a highly robust mechanism for maintaining the cellular metabolism of living organisms. However, relevant modifications of glycolytic activity are required to intentionally modulate cellular phenotypes. Here, we designed a platform that allows switching control of glycolysis in Escherichia coli in response to an environmental signal, in this case, temperature. This system functions by regulating the expression of gapA, which encodes glyceraldehyde‐3‐phosphate dehydrogenase (GAPDH), one of the key glycolytic enzymes. Because a very low level of gapA expression is capable of maintaining cellular physiology, we also modified GAPDH through directed evolution to provide sensitive regulation of glycolytic activity. The switching control of glycolysis was successfully demonstrated by regulating the expression of engineered gapA through changes in temperature. This system offers potential control over the cell's central carbon‐metabolism switch, providing the ability to perform reprogrammed tasks with desired timing depending on environmental signals. Biotechnol. Bioeng. 2012; 109: 2612–2619. © 2012 Wiley Periodicals, Inc.     

No ecological opportunity signal on a continental scale? Diversification and life‐history evolution of African true toads (Anura: Bufonidae)

The niche‐filling process predicted by the “ecological opportunity” (EO) model is an often‐invoked mechanism for generating exceptional diversity in island colonizers. Whether the same process governs lineage accumulation and trait disparity during continental colonization events is less clear. Here, we test this prediction by investigating the rate dynamics and trait evolution of one of Africa's most widespread amphibian colonizers, the true toads (Bufonidae). By reconstructing the most complete molecular phylogeny of African Bufonidae to date, we find that the diversification of lineages in Africa best conforms to a constant rate model throughout time and across subclades, with little support for EO. Evolutionary rates of life‐history traits have similarly been constant over time. However, an analysis of generalists and specialists showed a shift toward higher speciation rates associated with habitat specialization. The overall lack of EO signal can be interpreted in a number of ways and we propose several explanations. Firstly, methodological issues might preclude the detection of EO. Secondly, colonizers might not experience true EO conditions and due to the size, ecological heterogeneity and age of landmasses, the diversification processes might be more complex. Thirdly, lower speciation rates of habitat generalists may have affected overall proliferation of lineages.     

Gene(s) and individual feeding behavior: Exploring eco‐evolutionary dynamics underlying left‐right asymmetry in the scale‐eating cichlid fish Perissodus microlepis

The scale‐eating cichlid fish Perissodus microlepis is a textbook example of bilateral asymmetry due to its left or right‐bending heads and of negative frequency‐dependent selection, which is proposed to maintain this stable polymorphism. The mechanisms that underlie this asymmetry remain elusive. Several studies had initially postulated a simple genetic basis for this trait, but this explanation has been questioned, particularly by reports observing a unimodal distribution of mouth shapes. We hypothesize that this unimodal distribution might be due to a combination of genetic and phenotypically plastic components. Here, we expanded on previous work by investigating a formerly identified candidate SNP associated to mouth laterality, documenting inter‐individual variation in feeding preference using stable isotope analyses, and testing their association with mouth asymmetry. Our results suggest that this polymorphism is influenced by both a polygenic basis and inter‐individual non‐genetic variation, possibly due to feeding experience, individual specialization, and intraspecific competition. We introduce a hypothesis potentially explaining the simultaneous maintenance of left, right, asymmetric and symmetric mouth phenotypes due to the interaction between diverse eco‐evolutionary dynamics including niche construction and balancing selection. Future studies will have to further tease apart the relative contribution of genetic and environmental factors and their interactions in an integrated fashion.     

Integrating large‐scale geographic patterns in flight morphology,flight characteristics and sexual selection in a range‐expanding damselfly

While geographic trait variation along environmental clines is widespread, associated patterns in sexual selection remain largely unexplored. Geographic patterns in sexual selection may be expected if 1) phenotypes vary geographically and sexual selection is dependent on the local phenotypes in the population, and if 2) sexual selection is influenced by geographically structured environmental conditions. We quantified geographic variation in flight‐related traits and flight performance in mated and unmated males and tested for geographic variation in sexual selection on these traits in the poleward range‐expanding damselfly Coenagrion scitulum across a set of eleven core and edge populations ordered along thermal gradients in the larval and in the adult stage. We found little support for trait differentiation between core and edge populations, instead we found considerable geographic trait variation along the larval and adult thermal gradients. As expected under time constraints, body mass decreased with shorter larval growth seasons. Lower temperatures during the adult flight period were associated with a higher body mass, a higher flight speed and a higher fat content; these traits likely evolved to buffer flight ability at suboptimal temperatures and to optimize starvation resistance. Across the large geographic scale, we found a consistent higher flight duration in mated males. Instead, sexual selection for higher fat content was stronger in populations with lower adult flight temperatures and sexual selection for lower body mass acted only in edge populations. Our results indicate sexual selection on flight performance to be consistent over a large geographic scale and this despite the clear geographic patterns in sexual selection on the underlying morphological traits. Our results highlight that to fully understand the fitness implications of geographically changing trait patterns, researchers should consider the entire phenotype–performance–fitness axis and incorporate effects of geographically structured life‐stage specific environmental conditions on this axis.     

Evolutionary dynamics in structured populations

Evolutionary dynamics shape the living world around us. At the centre of every evolutionary process is a population of reproducing individuals. The structure of that population affects evolutionary dynamics. The individuals can be molecules, cells, viruses, multicellular organisms or humans. Whenever the fitness of individuals depends on the relative abundance of phenotypes in the population, we are in the realm of evolutionary game theory. Evolutionary game theory is a general approach that can describe the competition of species in an ecosystem, the interaction between hosts and parasites, between viruses and cells, and also the spread of ideas and behaviours in the human population. In this perspective, we review the recent advances in evolutionary game dynamics with a particular emphasis on stochastic approaches in finite sized and structured populations. We give simple, fundamental laws that determine how natural selection chooses between competing strategies. We study the well-mixed population, evolutionary graph theory, games in phenotype space and evolutionary set theory. We apply these results to the evolution of cooperation. The mechanism that leads to the evolution of cooperation in these settings could be called ‘spatial selection’: cooperators prevail against defectors by clustering in physical or other spaces.     

Impaired striatum-dependent behavior in GASP-1-knock-out mice

G protein-coupled receptor (GPCR) associated sorting protein-1 (GASP-1) is suspected to play a key role in recycling and degradation of several GPCRs. In a previous study, we have shown that GASP-1-knock-out (GASP-1-KO) mice displayed deficits in acquiring a cocaine self-administration task, associated with an exacerbated down-regulation of striatal dopaminergic and cholinergic receptors. Among several possibilities, GASP-1 deficiency could have impaired memory processes underlying the acquisition of the operant conditioning task. Therefore, the present study investigated cognitive performances of GASP-1-KO mice and their wild-type littermates (WT) in a broad variety of memory tasks. Consistent with a deficit in procedural memory, GASP-1-KO mice showed delayed acquisition of a food-reinforced bar-press task. During water-maze training in hidden- or visible-platform paradigms, mutant and WT mice acquired the tasks at the same rate. However, GASP-1 mice exhibited persistent thigmotaxic swimming, longer distance to the platform, and reduced swim speed. There was no deficit in several tasks requiring simple behavioral responses (Barnes maze, object recognition and passive avoidance tasks). Thus, the ability to acquire and/or express complex responses seems affected in GASP-1-deficient mice. Hippocampal functions were preserved, as the retention of an acquired memory in spatial tasks remained unaffected. The pattern of behavioral deficits observed in GASP-1-KO mice is coherent with current knowledge on the role of striatal GPCRs in acquisition/expression of skilled behavior and in motivation. Together with the previous findings, the so far established phenotype of GASP-1-KO mice makes them a potentially exciting tool to study striatal functions.     

Fluidic and microfluidic tools for quantitative systems biology

Understanding genes and their functions is a daunting task due to the level of complexity in biological organisms. For discovering how genotype and phenotype are linked to each other, it is essential to carry out systematic studies with maximum sensitivity and high-throughput. Recent developments in fluid-handling technologies, both at the macro and micro scale, are now allowing us to apply engineering approaches to achieve this goal. With these newly developed tools, it is now possible to identify genetic factors that are responsible for particular phenotypes, perturb and monitor cells at the single-cell level, evaluate cell-to-cell variability, detect very rare phenotypes, and construct faithful in vitro disease models.