Social experiences impact nearly every facet of human behavior, and social adversity can have devastating and long-lasting health effects on mental and emotional health. A comprehensive framework of how social interactions are processed at the molecular, individual behavioral and societal levels is thus essential to fully understand both healthy and impaired social behavior. Plasticity in transcriptional regulatory networks plays a crucial and deeply conserved role in body plan development, and we hypothesize that it also underlies social behavior (another highly plastic property of an organism's biology). To test this hypothesis, we will use an established model of social behavior (the honey bee) to explore the bidirectional flow of information between three levels of biological organization: 1) brain neurogenomic state, 2) individual behavior, and 3) emergent properties of the society.
Aim 1 will examine reciprocal feedback between behavioral state and the regulatory functions of two transcription factors (TFs) predicted in previous systems biology studies to play prominent roles in brain gene expression networks regulating social behavior. RNA interference will be used to knock down expression of these TFs and neuroendocrine-mediated manipulation of behavioral state, and to thereby test the hypothesis that social behavior is controlled by context-dependent rewiring of brain transcriptional regulatory networks.
Aim 2 will use a novel technology to automatically monitor the social interactions of every bee in the colony, in order to characterize how alterations in the neurogenomic and behavioral state of a set of focal bees (as done in Aim 1) influence the social interactions and brain gene expression of untreated individuals.
Aim 3 will then generate novel algorithms to describe the emergent properties of the social network as a whole, and use them to construct a simulation of how the proportion of individuals in a particular behavioral or neurogenomic state influences the global properties of the social network. These analyses will allow us to identify mechanisms of information flow from the transcriptome to the social network, as well as determine how a social network responds to changes in social group composition. The outcome of this research will be a multi-level model of the reciprocal relationships between brain transcriptional regulatory networks, individual behavior, and societal function. This model will provide new insights into how genes influence social behavior and how an individual's neurogenomic and behavioral states influence social groups, with important implications for our understanding of how healthy and pathological behavior influence societal function.

Public Health Relevance

Social pathologies ranging from social anxiety to autism have a molecular basis and affect not only individuals suffering from these conditions, but their family, friends and all of society as well. Understanding how social interactions are processed at the molecular, behavioral and societal levels is therefore essential to assess the full impact of socia disease and provide proper interventions to ameliorate its impact. This project will use the honey bee to investigate how behaviorally relevant gene expression in the brain of the individual affects the behavior and gene expression of other society members, and in the process will provide a holistic, multi-level theoretical model of network dynamics that span brain transcriptome, individual social behavior, and whole society.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM117467-02
Application #
9148238
Study Section
Special Emphasis Panel (ZRG1-HDM-Y (55))
Program Officer
Marcus, Stephen
Project Start
2015-09-24
Project End
2018-08-31
Budget Start
2016-09-01
Budget End
2017-08-31
Support Year
2
Fiscal Year
2016
Total Cost
$402,784
Indirect Cost
$139,768
Name
University of Illinois Urbana-Champaign
Department
Genetics
Type
Organized Research Units
DUNS #
041544081
City
Champaign
State
IL
Country
United States
Zip Code
61820
Gernat, Tim; Rao, Vikyath D; Middendorf, Martin et al. (2018) Automated monitoring of behavior reveals bursty interaction patterns and rapid spreading dynamics in honeybee social networks. Proc Natl Acad Sci U S A 115:1433-1438
Li, Mingwu; Rao, Vikyath D; Gernat, Tim et al. (2018) Lifetime-preserving reference models for characterizing spreading dynamics on temporal networks. Sci Rep 8:709