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.

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.

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.

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 () 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.

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.

Honey bee virus causes context-dependent changes in host social behavior.

Anthropogenic changes create evolutionarily novel environments that present opportunities for emerging diseases, potentially changing the balance between host and pathogen. Honey bees provide essential pollination services, but intensification and globalization of honey bee management has coincided with increased pathogen pressure, primarily due to a parasitic mite/virus complex. Here, we investigated how honey bee individual and group phenotypes are altered by a virus of concern, Israeli acute paralysis virus (IAPV).

Automated monitoring of behavior reveals bursty interaction patterns and rapid spreading dynamics in honeybee social networks.

Social networks mediate the spread of information and disease. The dynamics of spreading depends, among other factors, on the distribution of times between successive contacts in the network. Heavy-tailed (bursty) time distributions are characteristic of human communication networks, including face-to-face contacts and electronic communication via mobile phone calls, email, and internet communities.

Lifetime-preserving reference models for characterizing spreading dynamics on temporal networks.

To study how a certain network feature affects processes occurring on a temporal network, one often compares properties of the original network against those of a randomized reference model that lacks the feature in question. The randomly permuted times (PT) reference model is widely used to probe how temporal features affect spreading dynamics on temporal networks. However, PT implicitly assumes that edges and nodes are continuously active during the network sampling period - an assumption that does not always hold in real networks.

Gain, loss and divergence in primate zinc-finger genes: a rich resource for evolution of gene regulatory differences between species.

The molecular changes underlying major phenotypic differences between humans and other primates are not well understood, but alterations in gene regulation are likely to play a major role. Here we performed a thorough evolutionary analysis of the largest family of primate transcription factors, the Krüppel-type zinc finger (KZNF) gene family. We identified and curated gene and pseudogene models for KZNFs in three primate species, chimpanzee, orangutan and rhesus macaque, to allow for a comparison with the curated set of human KZNFs.

Differences in human and chimpanzee gene expression patterns define an evolving network of transcription factors in brain.

Humans differ from other primates by marked differences in cognitive abilities and a significantly larger brain. These differences correlate with metabolic changes, as evidenced by the relative up-regulation of energy-related genes and metabolites in human brain. While the mechanisms underlying these evolutionary changes have not been elucidated, altered activities of key transcription factors (TFs) could play a pivotal role.