Developmental evolution in social insects: regulatory networks from genes to societies

A Data-Driven Simulation of the Trophallactic Network and Intranidal Food Flow Dissemination in Ants

Food sharing can occur in both social and non-social species, but it is crucial in eusocial species, in which only some group members collect food. This food collection and the intranidal (i.e., inside the nest) food distribution through trophallactic (i.e., mouth-to-mouth) exchanges are fundamental in eusocial insects. However, the behavioural rules underlying the regulation and the dynamics of food intake and the resulting networks of exchange are poorly understood. In this study, we provide new insights into the behavioural rules underlying the structure of trophallactic networks and food dissemination dynamics within the colony. We build a simple data-driven model that implements interindividual variability and the division of labour to investigate the processes of food accumulation/dissemination inside the nest, both at the individual and collective levels. We also test the alternative hypotheses (no variability and no division of labour). The division of labour, combined with inter-individual variability, leads to predictions of the food dynamics and exchange networks that run, contrary to the other models. Our results suggest a link between the interindividual heterogeneity of the trophallactic behaviours, the food flow dynamics and the network of trophallactic events. Our results show that a slight level of heterogeneity in the number of trophallactic events is enough to generate the properties of the experimental networks and seems to be crucial for the creation of efficient trophallactic networks. Despite the relative simplicity of the model rules, efficient trophallactic networks may emerge as the networks observed in ants, leading to a better understanding of the evolution of self-organisation in such societies.

My road to the ants: A model clade for eco-evo-devo

This chapter is the story of how I pioneered ants as a system for studying eco-evo-devo, a field that integrates developmental biology with ecology and evolutionary biology. One aim of eco-evo-devo is to understand how the interactions between genes and their environments during development facilitates the origin and evolution of novel phenotypes. In a series of six parts, I review some of the key discoveries from my lab on how novel worker caste systems in ants--soldiers and supersoldiers--originated and evolved. I also discuss some of the ideas that emerged from these discoveries, including the role that polyphenisms, hidden developmental potentials, and rudimentary organs play in facilitating developmental and evolutionary change. As superorganisms, I argue that ants are uniquely positioned to reveal types of variation that are often difficult to observe in nature. In doing so, they have the potential to transform our view of biology and provide new perspectives in medicine, agriculture, and biodiversity conservation. With my story I hope to inspire the next generation of biologists to continue exploring the unknown regions of phenotypic space to solve some of our most pressing societal challenges.

Hierarchical networks of food exchange in the black garden ant Lasius niger

In most eusocial insects, the division of labor results in relatively few individuals foraging for the entire colony. Thus, the survival of the colony depends on its efficiency in meeting the nutritional needs of all its members. Here, we characterize the network topology of a eusocial insect to understand the role and centrality of each caste in this network during the process of food dissemination. We constructed trophallaxis networks from 34 food-exchange experiments in black garden ants (Lasius niger). We tested the influence of brood and colony size on (i) global indices at the network level (i.e., efficiency, resilience, centralization, and modularity) and (ii) individual values (i.e., degree, strength, betweenness, and the clustering coefficient). Network resilience, the ratio between global efficiency and centralization, was stable with colony size but increased in the presence of broods, presumably in response to the nutritional needs of larvae. Individual metrics highlighted the major role of foragers in food dissemination. In addition, a hierarchical clustering analysis suggested that some domestics acted as intermediaries between foragers and other domestics. Networks appeared to be hierarchical rather than random or centralized exclusively around foragers. Finally, our results suggested that networks emerging from social insect interactions can improve group performance and thus colony fitness.

Insects Provide Unique Systems to Investigate How Early-Life Experience Alters the Brain and Behavior

Early-life experiences have strong and long-lasting consequences for behavior in a surprising diversity of animals. Determining which environmental inputs cause behavioral change, how this information becomes neurobiologically encoded, and the functional consequences of these changes remain fundamental puzzles relevant to diverse fields from evolutionary biology to the health sciences. Here we explore how insects provide unique opportunities for comparative study of developmental behavioral plasticity. Insects have sophisticated behavior and cognitive abilities, and they are frequently studied in their natural environments, which provides an ecological and adaptive perspective that is often more limited in lab-based vertebrate models. A range of cues, from relatively simple cues like temperature to complex social information, influence insect behavior. This variety provides experimentally tractable opportunities to study diverse neural plasticity mechanisms. Insects also have a wide range of neurodevelopmental trajectories while sharing many developmental plasticity mechanisms with vertebrates. In addition, some insects retain only subsets of their juvenile neuronal population in adulthood, narrowing the targets for detailed study of cellular plasticity mechanisms. Insects and vertebrates share many of the same knowledge gaps pertaining to developmental behavioral plasticity. Combined with the extensive study of insect behavior under natural conditions and their experimental tractability, insect systems may be uniquely qualified to address some of the biggest unanswered questions in this field.

Functional genomics of parental care of insects

Parental care was likely the first step most lineages made towards sociality. However, the molecular mechanisms that generate parental care are not broadly characterized. Insects are important as an evolutionary independent group from classic models of parental care, such as, house mice. They provide an opportunity to test the generality of our understanding. With this review, I survey the functional genomics of parental care of insects, summarize several recent advances in the broader framework for studying and understanding parental care, and finish with suggested priorities for further research. Although there are too few studies to draw definitive conclusions, I argue that natural selection appears to be rewiring existing gene networks to produce parental care, that the epigenetic mechanisms influencing parental care are not well understood, and, as an interesting early consensus, that genes strongly associated with carer/offspring interactions appear biased towards proteins that are secreted. I summarize the studies that have functionally validate candidate genes and highlight the increasing need to perform this work. I finish with arguments for both conceptual and practical changes moving forward. I argue that future work can increase the use of predictive frameworks, broaden its definition of conservation of mechanism to gene networks rather than single genes, and increase the use of more established comparative methods. I further highlight the practical considerations of standardizing analyses and reporting, increasing the sampling of both carers and offspring, better characterizing gene regulatory networks, better characterizing taxonomically restricted genes and any consistent role they have underpinning parental care, and using factorial designs to disentangle the influence of multiple variables on the expression of parental care.

Transcriptomic basis and evolution of the ant nurse-larval social interactome

Development is often strongly regulated by interactions among close relatives, but the underlying molecular mechanisms are largely unknown. In eusocial insects, interactions between caregiving worker nurses and larvae regulate larval development and resultant adult phenotypes. Here, we begin to characterize the social interactome regulating ant larval development by collecting and sequencing the transcriptomes of interacting nurses and larvae across time. We find that the majority of nurse and larval transcriptomes exhibit parallel expression dynamics across larval development. We leverage this widespread nurse-larva gene co-expression to infer putative social gene regulatory networks acting between nurses and larvae. Genes with the strongest inferred social effects tend to be peripheral elements of within-tissue regulatory networks and are often known to encode secreted proteins. This includes interesting candidates such as the nurse-expressed giant-lens, which may influence larval epidermal growth factor signaling, a pathway known to influence various aspects of insect development. Finally, we find that genes with the strongest signatures of social regulation tend to experience relaxed selective constraint and are evolutionarily young. Overall, our study provides a first glimpse into the molecular and evolutionary features of the social mechanisms that regulate all aspects of social life.

Transcriptomic basis and evolution of the ant nurse-larval social interactome

Development is often strongly regulated by interactions among close relatives, but the underlying molecular mechanisms are largely unknown. In eusocial insects, interactions between caregiving worker nurses and larvae regulate larval development and resultant adult phenotypes. Here, we begin to characterize the social interactome regulating ant larval development by collecting and sequencing the transcriptomes of interacting nurses and larvae across time. We find that the majority of nurse and larval transcriptomes exhibit parallel expression dynamics across larval development. We leverage this widespread nurse-larva gene co-expression to infer putative social gene regulatory networks acting between nurses and larvae. Genes with the strongest inferred social effects tend to be peripheral elements of within-tissue regulatory networks and are often known to encode secreted proteins. This includes interesting candidates such as the nurse-expressed giant-lens, which may influence larval epidermal growth factor signaling, a pathway known to influence various aspects of insect development. Finally, we find that genes with the strongest signatures of social regulation tend to experience relaxed selective constraint and are evolutionarily young. Overall, our study provides a first glimpse into the molecular and evolutionary features of the social mechanisms that regulate all aspects of social life.

Transcriptomic changes during caste development through social interactions in the termite Zootermopsis nevadensis

One of the most striking examples of phenotypic plasticity is the different phenotypes (i.e., castes) within a same nest of social insects. Castes usually derive from a single genotype initially by receiving social cues among individuals during development. Specific gene expression changes may be involved in caste differentiation, and thus, the regulatory mechanism of these changes should be clarified in order to understand social maintenance and evolution. The damp-wood termite Zootermopsis nevadensis is one of the most important model termite species, due to not only the availability of genomic, transcriptomic, and epigenomic information but also evidence that soldier- and worker-destined individuals can be identified in natural conditions. Given that the nutritional intakes via social interactions are crucial for caste differentiation in this species, there is a possibility that transcriptomic changes are influenced by the nutritional difference among these individuals. Here, whole body RNA-seq analysis of 3rd-instar larvae with biological replications and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted. We found the drastic expression differences during caste developments between soldier- and worker-destined individuals. The results indicated that there are several key signaling pathways responsible for caste formations, which are involved in developments and social interactions. Particularly, the nutritional sensitive signaling was upregulated in soldier-destined individuals, while some metabolic pathways were identified in worker-destined individuals. These bioinformatic data obtained should be utilized to examine the molecular mechanisms of caste determination in social insects.

Who needs 'lazy' workers? Inactive workers act as a 'reserve' labor force replacing active workers, but inactive workers are not replaced when they are removed

Social insect colonies are highly successful, self-organized complex systems. Surprisingly however, most social insect colonies contain large numbers of highly inactive workers. Although this may seem inefficient, it may be that inactive workers actually contribute to colony function. Indeed, the most commonly proposed explanation for inactive workers is that they form a 'reserve' labor force that becomes active when needed, thus helping mitigate the effects of colony workload fluctuations or worker loss. Thus, it may be that inactive workers facilitate colony flexibility and resilience. However, this idea has not been empirically confirmed. Here we test whether colonies of Temnothorax rugatulus ants replace highly active (spending large proportions of time on specific tasks) or highly inactive (spending large proportions of time completely immobile) workers when they are experimentally removed. We show that colonies maintained pre-removal activity levels even after active workers were removed, and that previously inactive workers became active subsequent to the removal of active workers. Conversely, when inactive workers were removed, inactivity levels decreased and remained lower post-removal. Thus, colonies seem to have mechanisms for maintaining a certain number of active workers, but not a set number of inactive workers. The rapid replacement (within 1 week) of active workers suggests that the tasks they perform, mainly foraging and brood care, are necessary for colony function on short timescales. Conversely, the lack of replacement of inactive workers even 2 weeks after their removal suggests that any potential functions they have, including being a 'reserve', are less important, or auxiliary, and do not need immediate recovery. Thus, inactive workers act as a reserve labor force and may still play a role as food stores for the colony, but a role in facilitating colony-wide communication is unlikely. Our results are consistent with the often cited, but never yet empirically supported hypothesis that inactive workers act as a pool of 'reserve' labor that may allow colonies to quickly take advantage of novel resources and to mitigate worker loss.

Genetics and Evolution of Social Behavior in Insects

The study of insect social behavior has offered tremendous insight into the molecular mechanisms mediating behavioral and phenotypic plasticity. Genomic applications to the study of eusocial insect species, in particular, have led to several hypotheses for the processes underlying the molecular evolution of behavior. Advances in understanding the genetic control of social organization have also been made, suggesting an important role for supergenes in the evolution of divergent behavioral phenotypes. Intensive study of social phenotypes across species has revealed that behavior and caste are controlled by an interaction between genetic and environmentally mediated effects and, further, that gene expression and regulation mediate plastic responses to environmental signals. However, several key methodological flaws that are hindering progress in the study of insect social behavior remain. After reviewing the current state of knowledge, we outline ongoing challenges in experimental design that remain to be overcome in order to advance the field.

Sequential social experiences interact to modulate aggression but not brain gene expression in the honey bee (Apis mellifera)

BACKGROUND

In highly structured societies, individuals behave flexibly and cooperatively in order to achieve a particular group-level outcome. However, even in social species, environmental inputs can have long lasting effects on individual behavior, and variable experiences can even result in consistent individual differences and constrained behavioral flexibility. Despite the fact that such constraints on behavior could have implications for behavioral optimization at the social group level, few studies have explored how social experiences accumulate over time, and the mechanistic basis of these effects. In the current study, I evaluate how sequential social experiences affect individual and group level aggressive phenotypes, and individual brain gene expression, in the highly social honey bee (Apis mellifera). To do this, I combine a whole colony chronic predator disturbance treatment with a lab-based manipulation of social group composition.

RESULTS

Compared to the undisturbed control, chronically disturbed individuals show lower aggression levels overall, but also enhanced behavioral flexibility in the second, lab-based social context. Disturbed bees display aggression levels that decline with increasing numbers of more aggressive, undisturbed group members. However, group level aggressive phenotypes are similar regardless of the behavioral tendencies of the individuals that make up the group, suggesting a combination of underlying behavioral tendency and negative social feedback influences the aggressive behaviors displayed, particularly in the case of disturbed individuals. An analysis of brain gene expression showed that aggression related biomarker genes reflect an individual's disturbance history, but not subsequent social group experience or behavioral outcomes.

CONCLUSIONS

In highly social animals with collective behavioral phenotypes, social context may mask underlying variation in individual behavioral tendencies. Moreover, gene expression patterns may reflect behavioral tendency, while behavioral outcomes are further regulated by social cues perceived in real-time.

Regulation, development, and evolution of caste ratios in the hyperdiverse ant genus Pheidole

Ant colonies are considered complex biological systems because many individuals are divided into different castes that interact to efficiently perform their tasks. Colonies in the hyperdiverse ant genus Pheidole have evolved a worker caste with at least two subcastes: soldiers and minor workers. The proportion of soldiers and minor workers in a colony has a major impact on the colony's fitness and is tightly regulated. Here, we summarize over 100 years of research on the internal, external, and developmental factors that regulate subcaste production as well as influence subcaste evolution in Pheidole. We hope that summarizing these factors into a network of interactions will provide insight into how complex biological systems regulate, develop, and evolve.

Ant Genetics: Reproductive Physiology, Worker Morphology, and Behavior

Many exciting studies have begun to elucidate the genetics of the morphological and physiological diversity of ants, but as yet few studies have investigated the genetics of ant behavior directly. Ant genomes are marked by extreme rates of gene turnover, especially in gene families related to olfactory communication, such as the synthesis of cuticular hydrocarbons and the perception of environmental semiochemicals. Transcriptomic and epigenetic differences are apparent between reproductive and sterile females, males and females, and workers that differ in body size. Quantitative genetic approaches suggest heritability of task performance, and population genetic studies indicate a genetic association with reproductive status in some species. Gene expression is associated with behavior including foraging, response to queens attempting to join a colony, circadian patterns of task performance, and age-related changes of task. Ant behavioral genetics needs further investigation of the feedback between individual-level physiological changes and socially mediated responses to environmental conditions.

The transcriptomic and evolutionary signature of social interactions regulating honey bee caste development

The caste fate of developing female honey bee larvae is strictly socially regulated by adult nurse workers. As a result of this social regulation, nurse-expressed genes as well as larval-expressed genes may affect caste expression and evolution. We used a novel transcriptomic approach to identify genes with putative direct and indirect effects on honey bee caste development, and we subsequently studied the relative rates of molecular evolution at these caste-associated genes. We experimentally induced the production of new queens by removing the current colony queen, and we used RNA sequencing to study the gene expression profiles of both developing larvae and their caregiving nurses before and after queen removal. By comparing the gene expression profiles of queen-destined versus worker-destined larvae as well as nurses observed feeding these two types of larvae, we identified larval and nurse genes associated with caste development. Of 950 differentially expressed genes associated with caste, 82% were expressed in larvae with putative direct effects on larval caste, and 18% were expressed in nurses with putative indirect effects on caste. Estimated selection coefficients suggest that both nurse and larval genes putatively associated with caste are rapidly evolving, especially those genes associated with worker development. Altogether, our results suggest that indirect effect genes play important roles in both the expression and evolution of socially influenced traits such as caste.

Extended evolution: A conceptual framework for integrating regulatory networks and niche construction

This paper introduces a conceptual framework for the evolution of complex systems based on the integration of regulatory network and niche construction theories. It is designed to apply equally to cases of biological, social and cultural evolution. Within the conceptual framework we focus especially on the transformation of complex networks through the linked processes of externalization and internalization of causal factors between regulatory networks and their corresponding niches and argue that these are an important part of evolutionary explanations. This conceptual framework extends previous evolutionary models and focuses on several challenges, such as the path‐dependent nature of evolutionary change, the dynamics of evolutionary innovation and the expansion of inheritance systems. J. Exp. Zool. (Mol. Dev. Evol.) 324B: 565–577, 2015. © 2015 The Authors. Journal of Experimental Zoology Part B: Molecular and Developmental Evolution published by Wiley Periodicals, Inc.

The Comet Cometh: Evolving Developmental Systems

In a recent opinion piece, Denis Duboule has claimed that the increasing shift towards systems biology is driving evolutionary and developmental biology apart, and that a true reunification of these two disciplines within the framework of evolutionary developmental biology (EvoDevo) may easily take another 100 years. He identifies methodological, epistemological, and social differences as causes for this supposed separation. Our article provides a contrasting view. We argue that Duboule’s prediction is based on a one-sided understanding of systems biology as a science that is only interested in functional, not evolutionary, aspects of biological processes. Instead, we propose a research program for an evolutionary systems biology, which is based on local exploration of the configuration space in evolving developmental systems. We call this approach—which is based on reverse engineering, simulation, and mathematical analysis—the natural history of configuration space. We discuss a number of illustrative examples that demonstrate the past success of local exploration, as opposed to global mapping, in different biological contexts. We argue that this pragmatic mode of inquiry can be extended and applied to the mathematical analysis of the developmental repertoire and evolutionary potential of evolving developmental mechanisms and that evolutionary systems biology so conceived provides a pragmatic epistemological framework for the EvoDevo synthesis.

Inference of the oxidative stress network in Anopheles stephensi upon Plasmodium infection

Ookinete invasion of Anopheles midgut is a critical step for malaria transmission; the parasite numbers drop drastically and practically reach a minimum during the parasite's whole life cycle. At this stage, the parasite as well as the vector undergoes immense oxidative stress. Thereafter, the vector undergoes oxidative stress at different time points as the parasite invades its tissues during the parasite development. The present study was undertaken to reconstruct the network of differentially expressed genes involved in oxidative stress in Anopheles stephensi during Plasmodium development and maturation in the midgut. Using high throughput next generation sequencing methods, we generated the transcriptome of the An. stephensi midgut during Plasmodium vinckei petteri oocyst invasion of the midgut epithelium. Further, we utilized large datasets available on public domain on Anopheles during Plasmodium ookinete invasion and Drosophila datasets and arrived upon clusters of genes that may play a role in oxidative stress. Finally, we used support vector machines for the functional prediction of the un-annotated genes of An. stephensi. Integrating the results from all the different data analyses, we identified a total of 516 genes that were involved in oxidative stress in An. stephensi during Plasmodium development. The significantly regulated genes were further extracted from this gene cluster and used to infer an oxidative stress network of An. stephensi. Using system biology approaches, we have been able to ascertain the role of several putative genes in An. stephensi with respect to oxidative stress. Further experimental validations of these genes are underway.

Development and evolution of insect polyphenisms: novel insights through the study of sex determination mechanisms

Polyphenism is defined as a single individual's ability to develop into two or more alternative phenotypes. Polyphenic development is taxonomically widespread among insects, cued by diverse environmental factors, and enables single genotypes to accommodate breathtaking phenotypic diversity. Most research on the developmental regulation and evolution of insect polyphenisms has focused on endocrine control mechanisms, in particular the role of the sesquiterpenoid juvenile hormone. Here we review recent finding that suggest additional and previously overlooked mechanisms that underlie the developmental regulation and rapid evolution of polyphenic development. Specifically, we focus on the role of somatic sex determination mechanisms, which mediate body-region and tissue-specific differentiation as a function of sex across insects. Recent work on Onthophagus horned beetles suggest that the same mechanisms have been co-opted to regulate the development of nutritionally cued, alternative male morphs, and that rapid changes in these mechanisms underlie rapid evolutionary changes in patterns of phenotype expression across Onthophagus species, including the loss of old and gain of novel locations for horn development, the evolution of reversed sexual dimorphisms, and the secondary loss of male polyphenism. We discuss how these findings expand the way we think about the origins and diversification of polyphenisms, and close by briefly highlighting potentially fruitful avenues for future research.

Genomics: moving behavioural ecology beyond the phenotypic gambit

Researchers studying the adaptive significance of behaviour typically assume that genetic mechanisms will not inhibit evolutionary trajectories, an assumption commonly known as the 'phenotypic gambit'. Although the phenotypic gambit continues to be a useful heuristic for behavioural ecology, here we discuss how genomic methods provide new tools and conceptual approaches that are relevant to behavioural ecology. We first describe how the concept of a genetic toolkit for behaviour can allow behavioural ecologists to synthesize both genomic and ecological information when assessing behavioural adaptation. Then we show how gene expression profiles can be viewed as complex phenotypic measurements, used to (1) predict behaviour, (2) evaluate phenotypic plasticity and (3) devise methods to manipulate behaviour in order to test adaptive hypotheses. We propose that advances in genomics and bioinformatics may allow researchers to overcome some of the logistical obstacles that motivated the inception of the phenotypic gambit. Behavioural ecology and genomics are mutually informative, providing potential synergy that could lead to powerful advances in the field of animal behaviour.

Improving the adaptability of simulated evolutionary swarm robots in dynamically changing environments

One of the important challenges in the field of evolutionary robotics is the development of systems that can adapt to a changing environment. However, the ability to adapt to unknown and fluctuating environments is not straightforward. Here, we explore the adaptive potential of simulated swarm robots that contain a genomic encoding of a bio-inspired gene regulatory network (GRN). An artificial genome is combined with a flexible agent-based system, representing the activated part of the regulatory network that transduces environmental cues into phenotypic behaviour. Using an artificial life simulation framework that mimics a dynamically changing environment, we show that separating the static from the conditionally active part of the network contributes to a better adaptive behaviour. Furthermore, in contrast with most hitherto developed ANN-based systems that need to re-optimize their complete controller network from scratch each time they are subjected to novel conditions, our system uses its genome to store GRNs whose performance was optimized under a particular environmental condition for a sufficiently long time. When subjected to a new environment, the previous condition-specific GRN might become inactivated, but remains present. This ability to store 'good behaviour' and to disconnect it from the novel rewiring that is essential under a new condition allows faster re-adaptation if any of the previously observed environmental conditions is reencountered. As we show here, applying these evolutionary-based principles leads to accelerated and improved adaptive evolution in a non-stable environment.

The quantitative genetics of indirect genetic effects: a selective review of modelling issues

Indirect genetic effects (IGE) occur when the genotype of an individual affects the phenotypic trait value of another conspecific individual. IGEs can have profound effects on both the magnitude and the direction of response to selection. Models of inheritance and response to selection in traits subject to IGEs have been developed within two frameworks; a trait-based framework in which IGEs are specified as a direct consequence of individual trait values, and a variance-component framework in which phenotypic variance is decomposed into a direct and an indirect additive genetic component. This work is a selective review of the quantitative genetics of traits affected by IGEs, with a focus on modelling, estimation and interpretation issues. It includes a discussion on variance-component vs trait-based models of IGEs, a review of issues related to the estimation of IGEs from field data, including the estimation of the interaction coefficient Ψ (psi), and a discussion on the relevance of IGEs for response to selection in cases where the strength of interaction varies among pairs of individuals. An investigation of the trait-based model shows that the interaction coefficient Ψ may deviate considerably from the corresponding regression coefficient when feedback occurs. The increasing research effort devoted to IGEs suggests that they are a widespread phenomenon, probably particularly in natural populations and plants. Further work in this field should considerably broaden our understanding of the quantitative genetics of inheritance and response to selection in relation to the social organisation of populations.

Systems biology and the integration of mechanistic explanation and mathematical explanation

The paper discusses how systems biology is working toward complex accounts that integrate explanation in terms of mechanisms and explanation by mathematical models-which some philosophers have viewed as rival models of explanation. Systems biology is an integrative approach, and it strongly relies on mathematical modeling. Philosophical accounts of mechanisms capture integrative in the sense of multilevel and multifield explanations, yet accounts of mechanistic explanation (as the analysis of a whole in terms of its structural parts and their qualitative interactions) have failed to address how a mathematical model could contribute to such explanations. I discuss how mathematical equations can be explanatorily relevant. Several cases from systems biology are discussed to illustrate the interplay between mechanistic research and mathematical modeling, and I point to questions about qualitative phenomena (rather than the explanation of quantitative details), where quantitative models are still indispensable to the explanation. Systems biology shows that a broader philosophical conception of mechanisms is needed, which takes into account functional-dynamical aspects, interaction in complex networks with feedback loops, system-wide functional properties such as distributed functionality and robustness, and a mechanism's ability to respond to perturbations (beyond its actual operation). I offer general conclusions for philosophical accounts of explanation.

Development and evolution of caste dimorphism in honeybees - a modeling approach

The difference in phenotypes of queens and workers is a hallmark of the highly eusocial insects. The caste dimorphism is often described as a switch-controlled polyphenism, in which environmental conditions decide an individual's caste. Using theoretical modeling and empirical data from honeybees, we show that there is no discrete larval developmental switch. Instead, a combination of larval developmental plasticity and nurse worker feeding behavior make up a colony-level social and physiological system that regulates development and produces the caste dimorphism. Discrete queen and worker phenotypes are the result of discrete feeding regimes imposed by nurses, whereas a range of experimental feeding regimes produces a continuous range of phenotypes. Worker ovariole numbers are reduced through feeding-regime-mediated reduction in juvenile hormone titers, involving reduced sugar in the larval food. Based on the mechanisms identified in our analysis, we propose a scenario of the evolutionary history of honeybee development and feeding regimes.