Effects of microRNA-305 knockdown on brain gene expression associated with division of labor in honey bee colonies (Apis mellifera).

Division of labor in honey bee colonies is based on the behavioral maturation of adult workers that involves a transition from working in the hive to foraging. This behavioral maturation is associated with distinct task-related transcriptomic profiles in the brain and abdominal fat body that are related to multiple regulatory factors including juvenile hormone (JH) and queen mandibular pheromone (QMP). A prominent physiological feature associated with behavioral maturation is a loss of abdominal lipid mass as bees transition to foraging. We used transcriptomic and physiological analyses to study whether microRNAs (miRNAs) are involved in the regulation of division of labor. We first identified two miRNAs that showed patterns of expression associated with behavioral maturation, ame-miR-305-5p and ame-miR-375-3p. We then downregulated the expression of these two miRNAs with sequence-specific antagomirs. Neither ame-miR-305-5p nor ame-miR-375-3p knockdown in the abdomen affected abdominal lipid mass on their own. Similarly, knockdown of ame-miR-305-5p in combination with JH or QMP also did not affect lipid mass. By contrast, ame-miR-305-5p knockdown in the abdomen caused substantial changes in gene expression in the brain. Brain gene expression changes included genes encoding transcription factors previously implicated in behavioral maturation. The results of these functional genomic experiments extend previous correlative associations of microRNAs with honey bee division of labor and point to specific roles for ame-miR-305-5p.

Gut microbiota contribute to variations in honey bee foraging intensity.

Gut microbiomes are increasingly recognized for mediating diverse biological aspects of their hosts, including complex behavioral phenotypes. Although many studies have reported that experimental disruptions to the gut microbial community result in atypical host behavior, studies that address how gut microbes contribute to adaptive behavioral trait variation are rare. Eusocial insects represent a powerful model to test this, because of their simple gut microbiota and complex division of labor characterized by colony-level variation in behavioral phenotypes. Although previous studies report correlational differences in gut microbial community associated with division of labor, here, we provide evidence that gut microbes play a causal role in defining differences in foraging behavior between European honey bees (Apis mellifera). We found that gut microbial community structure differed between hive-based nurse bees and bees that leave the hive to forage for floral resources. These differences were associated with variation in the abundance of individual microbes, including Bifidobacterium asteroides, Bombilactobacillus mellis, and Lactobacillus melliventris. Manipulations of colony demography and individual foraging experience suggested that differences in gut microbial community composition were associated with task experience. Moreover, single-microbe inoculations with B. asteroides, B. mellis, and L. melliventris caused effects on foraging intensity. These results demonstrate that gut microbes contribute to division of labor in a social insect, and support a role of gut microbes in modulating host behavioral trait variation.

The genomic case against genetic determinism.

Animal studies reveal that the molecular wiring of the brain can be altered by heredity, the environment, and their interaction. A deeper molecular understanding of these interactions could be a potent antidote to societal concerns of genetic determinism for human behavior, but this requires a paradigm that extends beyond traditional genome-wide association study (GWAS).

Single-cell dissection of aggression in honeybee colonies.

Understanding how genotypic variation results in phenotypic variation is especially difficult for collective behaviour because group phenotypes arise from complex interactions among group members. A genome-wide association study identified hundreds of genes associated with colony-level variation in honeybee aggression, many of which also showed strong signals of positive selection, but the influence of these 'colony aggression genes' on brain function was unknown. Here we use single-cell (sc) transcriptomics and gene regulatory network (GRN) analyses to test the hypothesis that genetic variation for colony aggression influences individual differences in brain gene expression and/or gene regulation. We compared soldiers, which respond to territorial intrusion with stinging attacks, and foragers, which do not. Colony environment showed stronger influences on soldier-forager differences in brain gene regulation compared with brain gene expression. GRN plasticity was strongly associated with colony aggression, with larger differences in GRN dynamics detected between soldiers and foragers from more aggressive relative to less aggressive colonies. The regulatory dynamics of subnetworks composed of genes associated with colony aggression genes were more strongly correlated with each other across different cell types and brain regions relative to other genes, especially in brain regions involved with olfaction and vision and multimodal sensory integration, which are known to mediate bee aggression. These results show how group genetics can shape a collective phenotype by modulating individual brain gene regulatory network architecture.

Comparative genomics and the roots of human behavior.

Advances in genomics provide tools to test whether similar behaviors in distinct species have statistically similar brain transcriptomic signatures. Here, we (a genomicist and a cognitive neuroscientist) suggest that these techniques can help cognitive scientists tackle some of the most pressing questions about the roots of human behavior.

Automated monitoring of honey bees with barcodes and artificial intelligence reveals two distinct social networks from a single affiliative behavior.

Barcode-based tracking of individuals is revolutionizing animal behavior studies, but further progress hinges on whether in addition to determining an individual's location, specific behaviors can be identified and monitored. We achieve this goal using information from the barcodes to identify tightly bounded image regions that potentially show the behavior of interest. These image regions are then analyzed with convolutional neural networks to verify that the behavior occurred. When applied to a challenging test case, detecting social liquid transfer (trophallaxis) in the honey bee hive, this approach yielded a 67% higher sensitivity and an 11% lower error rate than the best detector for honey bee trophallaxis so far. We were furthermore able to automatically detect whether a bee donates or receives liquid, which previously required manual observations. By applying our trophallaxis detector to recordings from three honey bee colonies and performing simulations, we discovered that liquid exchanges among bees generate two distinct social networks with different transmission capabilities. Finally, we demonstrate that our approach generalizes to detecting other specific behaviors. We envision that its broad application will enable automatic, high-resolution behavioral studies that address a broad range of previously intractable questions in evolutionary biology, ethology, neuroscience, and molecular biology.

The Influences of Illumination Regime on Egg-laying Rhythms of Honey Bee Queens.

Honey bee queens show extreme fecundity, commonly laying more than a thousand eggs in a single day. It has proven challenging to study the temporal organization of egg-laying behavior because queens are typically active around the clock in the dark cavity of a densely populated nest. To contend with this challenge, we developed two novel methods allowing detailed monitoring of queen activity and egg laying. We first adapted a high-resolution, continuous, tracking system allowing to track the position of barcode-tagged queens in observation hives with colonies foraging outside. We found that the queen is active ~96% of the day with typically no diurnal rhythm. Next, we developed a new laboratory procedure to monitor egg laying at single egg resolution under different light regimes. We found that under constant darkness (DD) and temperature conditions, queens laid eggs with no circadian rhythms. Queen fecundity was severely reduced under constant light (LL). Under a 12:12 illumination regime, queen fecundity was comparable to under constant darkness, with a higher number of eggs during the light phase. These daily rhythms in egg laying continued when these queens were released to DD conditions, suggesting that egg-laying rhythms are influenced by endogenous circadian clocks. These results suggest that honey bee queens are active and lay eggs around the clock with no diurnal rhythms. Light has complex influences on these behaviors, but more studies are needed to determine whether these effects reflect the influence of light directly on the queen or indirectly by affecting workers that interact with the queen.

Behavioral genetics and genomics: Mendel's peas, mice, and bees.

The question of the heritability of behavior has been of long fascination to scientists and the broader public. It is now widely accepted that most behavioral variation has a genetic component, although the degree of genetic influence differs widely across behaviors. Starting with Mendel's remarkable discovery of "inheritance factors," it has become increasingly clear that specific genetic variants that influence behavior can be identified. This goal is not without its challenges: Unlike pea morphology, most natural behavioral variation has a complex genetic architecture. However, we can now apply powerful genome-wide approaches to connect variation in DNA to variation in behavior as well as analyses of behaviorally related variation in brain gene expression, which together have provided insights into both the genetic mechanisms underlying behavior and the dynamic relationship between genes and behavior, respectively, in a wide range of species and for a diversity of behaviors. Here, we focus on two systems to illustrate both of these approaches: the genetic basis of burrowing in deer mice and transcriptomic analyses of division of labor in honey bees. Finally, we discuss the troubled relationship between the field of behavioral genetics and eugenics, which reminds us that we must be cautious about how we discuss and contextualize the connections between genes and behavior, especially in humans.

Epigenetic MRI: Noninvasive imaging of DNA methylation in the brain.

Both neuronal and genetic mechanisms regulate brain function. While there are excellent methods to study neuronal activity in vivo, there are no nondestructive methods to measure global gene expression in living brains. Here, we present a method, epigenetic MRI (eMRI), that overcomes this limitation via direct imaging of DNA methylation, a major gene-expression regulator. eMRI exploits the methionine metabolic pathways for DNA methylation to label genomic DNA through 13C-enriched diets. A 13C magnetic resonance spectroscopic imaging method then maps the spatial distribution of labeled DNA. We validated eMRI using pigs, whose brains have stronger similarity to humans in volume and anatomy than rodents, and confirmed efficient 13C-labeling of brain DNA. We also discovered strong regional differences in global DNA methylation. Just as functional MRI measurements of regional neuronal activity have had a transformational effect on neuroscience, we expect that the eMRI signal, both as a measure of regional epigenetic activity and as a possible surrogate for regional gene expression, will enable many new investigations of human brain function, behavior, and disease.

Context-dependent influence of threat on honey bee social network dynamics and brain gene expression.

Adverse social experience affects social structure by modifying the behavior of individuals, but the relationship between an individual's behavioral state and its response to adversity is poorly understood. We leveraged naturally occurring division of labor in honey bees and studied the biological embedding of environmental threat using laboratory assays and automated behavioral tracking of whole colonies. Guard bees showed low intrinsic levels of sociability compared with foragers and nurse bees, but large increases in sociability following exposure to a threat. Threat experience also modified the expression of caregiving-related genes in a brain region called the mushroom bodies. These results demonstrate that the biological embedding of environmental experience depends on an individual's societal role and, in turn, affects its future sociability.

Why sequence all eukaryotes?

Life on Earth has evolved from initial simplicity to the astounding complexity we experience today. Bacteria and archaea have largely excelled in metabolic diversification, but eukaryotes additionally display abundant morphological innovation. How have these innovations come about and what constraints are there on the origins of novelty and the continuing maintenance of biodiversity on Earth? The history of life and the code for the working parts of cells and systems are written in the genome. The Earth BioGenome Project has proposed that the genomes of all extant, named eukaryotes-about 2 million species-should be sequenced to high quality to produce a digital library of life on Earth, beginning with strategic phylogenetic, ecological, and high-impact priorities. Here we discuss why we should sequence all eukaryotic species, not just a representative few scattered across the many branches of the tree of life. We suggest that many questions of evolutionary and ecological significance will only be addressable when whole-genome data representing divergences at all of the branchings in the tree of life or all species in natural ecosystems are available. We envisage that a genomic tree of life will foster understanding of the ongoing processes of speciation, adaptation, and organismal dependencies within entire ecosystems. These explorations will resolve long-standing problems in phylogenetics, evolution, ecology, conservation, agriculture, bioindustry, and medicine.

Neural and Molecular Mechanisms of Biological Embedding of Social Interactions.

Animals operate in complex environments, and salient social information is encoded in the nervous system and then processed to initiate adaptive behavior. This encoding involves biological embedding, the process by which social experience affects the brain to influence future behavior. Biological embedding is an important conceptual framework for understanding social decision-making in the brain, as it encompasses multiple levels of organization that regulate how information is encoded and used to modify behavior. The framework we emphasize here is that social stimuli provoke short-term changes in neural activity that lead to changes in gene expression on longer timescales. This process, simplified-neurons are for today and genes are for tomorrow-enables the assessment of the valence of a social interaction, an appropriate and rapid response, and subsequent modification of neural circuitry to change future behavioral inclinations in anticipation of environmental changes. We review recent research on the neural and molecular basis of biological embedding in the context of social interactions, with a special focus on the honeybee.

The genomic basis of evolutionary differentiation among honey bees.

In contrast to the western honey bee, Apis mellifera, other honey bee species have been largely neglected despite their importance and diversity. The genetic basis of the evolutionary diversification of honey bees remains largely unknown. Here, we provide a genome-wide comparison of three honey bee species, each representing one of the three subgenera of honey bees, namely the dwarf (Apis florea), giant (A. dorsata), and cavity-nesting (A. mellifera) honey bees with bumblebees as an outgroup. Our analyses resolve the phylogeny of honey bees with the dwarf honey bees diverging first. We find that evolution of increased eusocial complexity in Apis proceeds via increases in the complexity of gene regulation, which is in agreement with previous studies. However, this process seems to be related to pathways other than transcriptional control. Positive selection patterns across Apis reveal a trade-off between maintaining genome stability and generating genetic diversity, with a rapidly evolving piRNA pathway leading to genomes depleted of transposable elements, and a rapidly evolving DNA repair pathway associated with high recombination rates in all Apis species. Diversification within Apis is accompanied by positive selection in several genes whose putative functions present candidate mechanisms for lineage-specific adaptations, such as migration, immunity, and nesting behavior.

Neurodevelopmental and transcriptomic effects of CRISPR/Cas9-induced somatic orco mutation in honey bees.

In insects, odorant receptors facilitate olfactory communication and require the functionality of the highly conserved co-receptor gene orco. Genome editing studies in a few species of ants and moths have revealed that orco can also have a neurodevelopmental function, in addition to its canonical role in adult olfaction, discovered first in Drosophila melanogaster. To extend this analysis, we determined whether orco mutations also affect the development of the adult brain of the honey bee Apis mellifera, an important model system for social behavior and chemical communication. We used CRISPR/Cas9 to knock out orco and examined anatomical and molecular consequences. To increase efficiency, we coupled embryo microinjection with a laboratory egg collection and in vitro rearing system. This new workflow advances genomic engineering technologies in honey bees by overcoming restrictions associated with field studies. We used Sanger sequencing to quickly select individuals with complete orco knockout for neuroanatomical analyses and later validated and described the mutations with amplicon sequencing. Mutant bees had significantly fewer glomeruli, smaller total volume of all the glomeruli, and higher mean individual glomerulus volume in the antennal lobe compared to wild-type controls. RNA-Sequencing revealed that orco knockout also caused differential expression of hundreds of genes in the antenna, including genes related to neural development and genes encoding odorant receptors. The expression of other types of chemoreceptor genes was generally unaffected, reflecting specificity of CRISPR activity in this study. These results suggest that neurodevelopmental effects of orco are related to specific insect life histories.

Transcriptomic analyses of black women in neighborhoods with high levels of violence.

Chronic stress threatens an individual's capacity to maintain psychological and physiological homeostasis, but the molecular processes underlying the biological embedding of these experiences are not well understood. This is particularly true for marginalized groups, presenting a fundamental challenge to decreasing racial, economic, and gender-based health disparities. Physical and social environments influence genome function, including the transcriptional activity of core stress responsive genes. We studied the relationship between social experiences that are associated with systemic inequality (e.g., racial segregation, poverty, and neighborhood violence) and blood cell (leukocytes) gene expression, focusing on the activation of transcription factors (TF) critical to stress response pathways. The study used data from 68 women collected from a convenience sample in 2013 from the Southside of Chicago. Comparing single, low-income Black mothers living in neighborhoods with high levels of violence (self-reported and assessed using administrative police records) to those with low levels of violence we found no significant differences in expression of 51 genes associated with the Conserved Transcriptional Response to Adversity (CTRA). Using TELiS analysis of promoter TF-binding motif prevalence we found that mothers who self-reported higher levels of neighborhood stress showed greater expression of genes regulated by the glucocorticoid receptor (GR). These findings may reflect increased cortisol output from the hypothalamic-pituitary-adrenal (HPA) axis, or increased GR transcriptional sensitivity. Transcript origin analyses identified monocytes and dendritic cells as the primary cellular sources of gene transcripts up-regulated in association with neighborhood stress. The prominence of GR-related transcripts and the absence of sympathetic nervous system-related CTRA transcripts suggest that a subjective perception of elevated chronic neighborhood stress may be associated with an HPA-related defeat-withdrawal phenotype rather than a fight-or-flight phenotype. The defeat-withdrawal phenotype has been previously observed in animal models of severe, overwhelming threat. These results demonstrate the importance of studying biological embedding in diverse environments and communities, specifically marginalized populations such as low-income Black women.

Assessing Agrochemical Risk to Mated Honey Bee Queens.

Current risk assessment strategies for honey bees rely heavily upon laboratory tests performed on adult or immature worker bees, but these methods may not accurately capture the effects of agrochemical exposure on honey bee queens. As the sole producer of fertilized eggs inside a honeybee colony, the queen is arguably the most important single member of a functioning colony unit. Therefore, understanding how agrochemicals affect queen health and productivity should be considered a critical aspect of pesticide risk assessment. Here, an adapted method is presented to expose honey bee queens and worker queen attendants to agrochemical stressors administered through a worker diet, followed by tracking egg production in the laboratory and assessing first instar eclosion using a specialized cage, referred to as a Queen Monitoring Cage. To illustrate the method's intended use, results of an experiment in which worker queen attendants were fed diet containing sublethal doses of imidacloprid and effects on queens were monitored are described.

Individual differences in honey bee behavior enabled by plasticity in brain gene regulatory networks.

Understanding the regulatory architecture of phenotypic variation is a fundamental goal in biology, but connections between gene regulatory network (GRN) activity and individual differences in behavior are poorly understood. We characterized the molecular basis of behavioral plasticity in queenless honey bee (Apis mellifera) colonies, where individuals engage in both reproductive and non-reproductive behaviors. Using high-throughput behavioral tracking, we discovered these colonies contain a continuum of phenotypes, with some individuals specialized for either egg-laying or foraging and 'generalists' that perform both. Brain gene expression and chromatin accessibility profiles were correlated with behavioral variation, with generalists intermediate in behavior and molecular profiles. Models of brain GRNs constructed for individuals revealed that transcription factor (TF) activity was highly predictive of behavior, and behavior-associated regulatory regions had more TF motifs. These results provide new insights into the important role played by brain GRN plasticity in the regulation of behavior, with implications for social evolution.

Individual variations lead to universal and cross-species patterns of social behavior.

The duration of interaction events in a society is a fundamental measure of its collective nature and potentially reflects variability in individual behavior. Here we performed a high-throughput measurement of trophallaxis and face-to-face event durations experienced by a colony of honeybees over their entire lifetimes. The interaction time distribution is heavy-tailed, as previously reported for human face-to-face interactions. We developed a theory of pair interactions that takes into account individual variability and predicts the scaling behavior for both bee and extant human datasets. The individual variability of worker honeybees was nonzero but less than that of humans, possibly reflecting their greater genetic relatedness. Our work shows how individual differences can lead to universal patterns of behavior that transcend species and specific mechanisms for social interactions.

Genes and environments, development and time.

A now substantial body of science implicates a dynamic interplay between genetic and environmental variation in the development of individual differences in behavior and health. Such outcomes are affected by molecular, often epigenetic, processes involving gene-environment (G-E) interplay that can influence gene expression. Early environments with exposures to poverty, chronic adversities, and acutely stressful events have been linked to maladaptive development and compromised health and behavior. Genetic differences can impart either enhanced or blunted susceptibility to the effects of such pathogenic environments. However, largely missing from present discourse regarding G-E interplay is the role of time, a "third factor" guiding the emergence of complex developmental endpoints across different scales of time. Trajectories of development increasingly appear best accounted for by a complex, dynamic interchange among the highly linked elements of genes, contexts, and time at multiple scales, including neurobiological (minutes to milliseconds), genomic (hours to minutes), developmental (years and months), and evolutionary (centuries and millennia) time. This special issue of PNAS thus explores time and timing among G-E transactions: The importance of timing and timescales in plasticity and critical periods of brain development; epigenetics and the molecular underpinnings of biologically embedded experience; the encoding of experience across time and biological levels of organization; and gene-regulatory networks in behavior and development and their linkages to neuronal networks. Taken together, the collection of papers offers perspectives on how G-E interplay operates contingently within and against a backdrop of time and timescales.