Emergence of collective multi-level network dynamics in a model society: From brain transcriptome to social behavior

 描述(由申请人提供)：社会经历几乎影响到人类行为的方方面面，社会逆境可能对心理和情绪健康产生毁灭性和持久的健康影响。因此，在分子、个人行为和社会层面上如何处理社会互动的全面框架对于充分理解健康和受损的社会行为是至关重要的。转录调控网络中的可塑性在身体计划的发展中起着至关重要且极其保守的作用，我们假设它也是社会行为(有机体生物学的另一个高度可塑性属性)的基础。为了验证这一假设，我们将使用一个已建立的社会行为模型(蜜蜂)来探索生物的三个层次之间的双向信息流动 组织：1)脑神经基因组状态，2)个人行为，3)社会的突发性。目的1研究行为状态与先前系统生物学研究中预测的两种转录因子(TF)的调节功能之间的相互反馈，这两种转录因子在调节社会行为的脑基因表达网络中发挥重要作用。RNA干扰将被用来抑制这些转录因子的表达和神经内分泌介导的行为状态的操纵，从而检验社会行为是由大脑转录调控网络的上下文相关重连控制的假设。目标2将使用一种新技术来自动监控蜂群中每一只蜜蜂的社会互动，以便 描述一组焦点蜜蜂的神经基因组和行为状态的变化(如在目标1中所做的)如何影响未经治疗的个体的社会互动和脑基因表达。然后，AIM 3将生成新的算法来描述社交网络作为一个整体的紧急属性，并使用它们来构建一个模拟，说明处于特定行为或神经基因组状态的个人比例如何影响社交网络的全局属性。这些分析将使我们能够确定信息流从转录组到社会网络的机制，以及确定社会网络如何对社会群体构成的变化做出反应。这项研究的结果将是大脑转录调控网络、个人行为和社会功能之间相互关系的多层次模型。这一模型将为基因如何影响社会行为以及个体的神经基因组和行为状态如何影响社会群体提供新的见解，对于我们理解健康和病理性行为如何影响社会功能具有重要意义。

 DESCRIPTION (provided by applicant): 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.