Asymmetry, division of labour and the evolution of ageing in multicellular organisms

A dynamic network model predicts the phenotypes of multicellular clusters from cellular properties

Cell division without cell separation produces multicellular clusters in budding yeast. Two fundamental characteristics of these clusters are their size (the number of cells per cluster) and cellular composition: the fractions of cells with different phenotypes. Using cells as nodes and links between mother and daughter cells as edges, we model cluster growth and breakage by varying three parameters: the cell division rate, the rate at which intercellular connections break, and the kissing number (the maximum number of connections to one cell). We find that the kissing number sets the maximum possible cluster size. Below this limit, the ratio of the cell division rate to the connection breaking rate determines the cluster size. If links have a constant probability of breaking per unit time, the probability that a link survives decreases exponentially with its age. Modeling this behavior recapitulates experimental data. We then use this framework to examine synthetic, differentiating clusters with two cell types, faster-growing germ cells and their somatic derivatives. The fraction of clusters that contain both cell types increases as either of two parameters increase: the kissing number and difference between the growth rate of germ and somatic cells. In a population of clusters, the variation in cellular composition is inversely correlated (r2 = 0.87) with the average fraction of somatic cells in clusters. Our results show how a small number of cellular features can control the phenotypes of multicellular clusters that were potentially the ancestors of more complex forms of multicellular development, organization, and reproduction.

Multicellular growth as a dynamic network of cells

Cell division without cell separation produces multicellular clusters in budding yeast. Two fundamental characteristics of these clusters are their size (the number of cells per cluster) and cellular composition: the fractions of cells with different phenotypes. However, we do not understand how different cellular features quantitatively influence these two phenotypes. Using cells as nodes and links between mother and daughter cells as edges, we model cluster growth and breakage by varying three parameters: the cell division rate, the rate at which intercellular connections break, and the kissing number (the maximum number of connections to one cell). We find that the kissing number sets the maximum possible cluster size. Below this limit, the ratio of the cell division rate to the connection breaking rate determines the cluster size. If links have a constant probability of breaking per unit time, the probability that a link survives decreases exponentially with its age. Modeling this behavior recapitulates experimental data. We then use this framework to examine synthetic, differentiating clusters with two cell types, faster-growing germ cells and their somatic derivatives. The fraction of clusters that contain both cell types increases as either of two parameters increase: the kissing number and difference between the growth rate of germ and somatic cells. In a population of clusters, the variation in cellular composition is inversely correlated (r2=0.87) with the average fraction of somatic cells in clusters. Our results show how a small number of cellular features can control the phenotypes of multicellular clusters that were potentially the ancestors of more complex forms of multicellular development, organization, and reproduction.

Metabolic division of labor in social insects

Social insects are known for reproductive and behavioral division of labor, but little attention has been paid to metabolic forms of division of labor. Metabolic division of labor is the partitioning of complementary metabolic tasks between individuals, and it is widespread in social insects. We define two forms of metabolic division of labor, homosynergetic and heterosynergetic, we pinpoint trophallaxis, trophic eggs, and cannibalism as the primary transfers underlying the homosynergetic form and discuss their evolution. We argue that homosynergetic metabolic division of labor underpins fundamental aspects of colony physiology and may be a necessary feature of superorganismal systems, impacting many life history traits. Investigating metabolic division of labor is necessary to understand major evolutionary transition(s) to superorganismality in social insects.

Entropy and Cross-Level Orderliness in Light of the Interconnection between the Neural System and Consciousness

Despite recent advances, the origin and utility of consciousness remains under debate. Using an evolutionary perspective on the origin of consciousness, this review elaborates on the promising theoretical background suggested in the temporospatial theory of consciousness, which outlines world-brain alignment as a critical predisposition for controlling behavior and adaptation. Such a system can be evolutionarily effective only if it can provide instant cohesion between the subsystems, which is possible only if it performs an intrinsic activity modified in light of the incoming stimulation. One can assume that the world-brain interaction results in a particular interference pattern predetermined by connectome complexity. This is what organisms experience as their exclusive subjective state, allowing the anticipation of regularities in the environment. Thus, an anticipative system can emerge only in a regular environment, which guides natural selection by reinforcing corresponding reactions and decreasing the system entropy. Subsequent evolution requires complicated, layered structures and can be traced from simple organisms to human consciousness and society. This allows us to consider the mode of entropy as a subject of natural evolution rather than an individual entity.

Systems Biology of Ageing

The ageing process is highly complex involving multiple processes operating at different biological levels. Systems Biology presents an approach using integrative computational and laboratory study that allows us to address such complexity. The approach relies on the computational analysis of knowledge and data to generate predictive models that may be validated with further laboratory experimentation. Our understanding of ageing is such that translational opportunities are within reach and systems biology offers a means to ensure that optimal decisions are made. We present an overview of the methods employed from bioinformatics and computational modelling and describe some of the insights into ageing that have been gained.

The evolution of ageing in cooperative breeders

Cooperatively breeding animals live longer than their solitary counterparts. This has been suggested for birds, mole rats, and social insects. A common explanation for these long lifespans is that cooperative breeding evolves more readily in long-lived species because lower mortality reduces the rate of territory turnover and thus leads to a limitation of breeding territories. Here, we reverse this argument and show that-rather than being a cause for its evolution-long lifespans are an evolutionary consequence of cooperative breeding. In evolutionary individual-based simulations, we show that natural selection favors a delayed onset of senescence in cooperative breeders, relative to solitary breeders, because cooperative breeders have a delayed age of first reproduction as helpers wait in a reproductive queue to obtain breeder status. Especially long lifespans evolve in cooperative breeders in which queue positions depend on the helpers' age rank among the helpers within the breeding territory. Furthermore, we show that lower genetic relatedness among group members leads to the evolution of longer lifespans. This is because selection against higher mortality is weaker when mortality reduces competition for breeding between relatives. Our results link the evolutionary theory of ageing with kin selection theory, demonstrating that the evolution of ageing in cooperative breeders is driven by the timing of reproduction and kin structure within breeding territories.

The Danaid Theory of Aging

The classical evolutionary theories of aging suggest that aging evolves due to insufficient selective pressure against it. In these theories, declining selection pressure with age leads to aging through genes or resource allocations, implying that aging could potentially be stalled were genes, resource allocation, or selection pressure somewhat different. While these classical evolutionary theories are undeniably part of a description of the evolution of aging, they do not explain the diversity of aging patterns, and they do not constitute the only possible evolutionary explanation. Without denying selection pressure a role in the evolution of aging, we argue that the origin and diversity of aging should also be sought in the nature and evolution of organisms that are, from their very physiological make up, unmaintainable. Drawing on advances in developmental biology, genetics, biochemistry, and complex systems theory since the classical theories emerged, we propose a fresh evolutionary-mechanistic theory of aging, the Danaid theory. We argue that, in complex forms of life like humans, various restrictions on maintenance and repair may be inherent, and we show how such restrictions are laid out during development. We further argue that there is systematic variation in these constraints across taxa, and that this is a crucial factor determining variation in aging and lifespan across the tree of life. Accordingly, the core challenge for the field going forward is to map and understand the mosaic of constraints, trade-offs, chance events, and selective pressures that shape aging in diverse ways across diverse taxa.

Evolutionary origin and the development of consciousness

This review seeks to combine advances in anthropology and neuroscience to investigate the adaptive value of human consciousness. It uses an interdisciplinary perspective on the origin of consciousness to refute the most common fallacies in considering consciousness, particularly, disregarding the evolutionary origin of the subjective reality in looking for the neural correlates of consciousness and divorcing studies in neuroscience and behavioural sciences. Various explanations linked to consciousness in the field of neuroscience, supplemented with the theoretical explanation of an experience as an ongoing process of overlap between intrinsic neural dynamics and stimulation can be summarised as the stochastic dynamics of one's control system experienced by the individual in the form of subjective reality. This framework elaborates on the world-brain research program and lays foundation for the quantitative description of one's qualitative feelings and naturalistic science of consciousness. Furthermore, this study highlights the philosophical perspective of the inseparability between the physical correlates and the subjective reality contributing to the realistic ontology of conscious processes.

Senescence: why and where selection gradients might not decline with age

Patterns of ageing across the tree of life are much more diverse than previously thought. Yet, we still do not adequately understand how, why and where across the tree of life a particular pattern of ageing will evolve. An ability to predict ageing patterns requires a firmer understanding of how and why different ecological and evolutionary factors alter the sensitivity of fitness to age-related changes in mortality and reproduction. From this understanding, we can ask why and where selection gradients might not decline with age. Here, we begin by summarizing the recent breadth of literature that is unearthing, empirically and theoretically, the mechanisms that drive variation in patters of senescence. We focus on the relevance of two key parameters, population structure and reproductive value, as key to understanding selection gradients, and therefore senescence. We discuss how growth form, individual trade-offs, stage structure and social interactions may all facilitate differing distributions of these two key parameters than those predicted by classical theory. We argue that these four key aspects can help us understand why patterns of negligible and negative senescence can actually be explained under the same evolutionary framework as classical senescence.

Antagonistic pleiotropy and the evolution of extraordinary lifespans in eusocial organisms

Queens of eusocial species live extraordinarily long compared to their workers. So far, it has been argued that these lifespan divergences are readily explained by the classical evolutionary theory of ageing. As workers predominantly perform risky tasks, such as foraging and nest defense, and queens stay in the well-protected nests, selection against harmful genetic mutations expressed in old age should be weaker in workers than in queens due to caste differences in extrinsic mortality risk, and thus, lead to the evolution of longer queen and shorter worker lifespans. However, these arguments have not been supported by formal models. Here, we present a model for the evolution of caste-specific ageing in social insects, based on Williams' antagonistic pleiotropy theory of ageing. In individual-based simulations, we assume that mutations with antagonistic fitness effects can act within castes, that is, mutations in early life are accompanied by an antagonistic effect acting in later life, or between castes, where antagonistic effects emerge due to caste antagonism or indirect genetic effects between castes. In monogynous social insect species with sterile workers, large lifespan divergences between castes evolved under all different scenarios of antagonistic effects, but regardless of the degree of caste-specific extrinsic mortality. Mutations with antagonistic fitness effects within castes reduced lifespans of both castes, while mutations with between-caste antagonistic effects decreased worker lifespans more than queen lifespans, and consequently increased lifespan divergences. Our results challenge the central explanatory role of extrinsic mortality for caste-specific ageing in eusocial organisms and suggest that antagonistic pleiotropy affects castes differently due to reproductive monopolization by queens, hence, reproductive division of labor. Finally, these findings provide new insights into the evolution of tissue-specific ageing in multicellular organisms in general.

Ageing and sociality: why, when and how does sociality change ageing patterns?

Individual lifespans vary tremendously between and also within species, but the proximate and ultimate causes of different ageing speeds are still not well understood. Sociality appears to be associated with the evolution of greater longevity and probably also with a larger plasticity of the shape and pace of ageing. For example, reproductives of several termites and ants reach lifespans that surpass those of their non-reproductive nestmates by one or two decades. In this issue, 15 papers explore the interrelations between sociality and individual longevity in both, group-living vertebrates and social insects. Here, we briefly give an overview of the contents of the various contributions, including theoretical and comparative studies, and we explore the similarities and dissimilarities in proximate mechanisms underlying ageing among taxa, with particular emphasis on nutrient-sensing pathways and, in insects, juvenile hormone. These studies point to an underestimated role of more downstream processes. We highlight the need for reliable transcriptomic markers of ageing and a comprehensive ageing theory of social animals, which includes the reproductive potential of workers, and considers the fact that social insect queens reach maturity only after a prolonged period of producing non-reproductive workers. This article is part of the theme issue 'Ageing and sociality: why, when and how does sociality change ageing patterns?'