Genomic mechanisms of firing rate homeostasis

放电率稳态的基因组机制

• 批准号: 10094256
• 负责人: Susan M. Dymecki
• 金额: $ 57.68万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-03-01 至 2023-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10094256
• 关键词: Address; Back; Biological Assay; Brain; Buffers; CaM kinase I activator; Calcium; Cells; Chemicals; Coupled; Coupling; Data; Detection; Dominant-Negative Mutation; Electrodes; Event; Feedback; Functional disorder; Gene Expression; Genes; Genetic Transcription; Genomics; High-Throughput Nucleotide Sequencing; Homeostasis; Hour; Individual; Investigation; Kinetics; Knock-out; Knowledge; Lead; Learning; MAP Kinase Gene; Maps; Measurement; Measures; Mediating; Memory; Mental Health; Mental disorders; Messenger RNA; Mission; Molecular; Neurons; Pattern; Pharmacology; Phase; Public Health; Recording of previous events; Recovery; Research; Runaway; Seizures; Serum Response Factor; Signal Transduction; Specific qualifier value; Synapses; Synaptic Receptors; System; Technology; Temperature; Testing; Therapeutic Intervention; Time; Transcription Factor AP-1; Translating; United States National Institutes of Health; Work; base; conditional knockout; design; experimental study; gene induction; genome-wide; high throughput screening; improved; innovation; multi-electrode arrays; optogenetics; prevent; programs; receptor density; sensor; therapeutic development; tool; transcriptome sequencing

PROJECT SUMMARY/ABSTRACT Neuronal Firing Rate Homeostasis (FRH) describes the ability of neurons to maintain their average firing rates at precise set points in the long-term, even in the face of changing synaptic inputs. The stability provided by FRH enables learning and memory. Achieving FRH requires an FRH control circuit that is akin to a thermostat that compares desired to actual room temperatures or an autopilot that compares desired to actual trajectories. Identifying this control circuit will require direct measurement of FRH by perturbing firing rates and observing homeostatic recovery, which has rarely been done. A promising candidate FRH control circuit is the neuronal Activity-Regulated Gene (ARG) program, in which activity-dependent increases in calcium lead to transcription of genes whose mRNA levels remain elevated for many hours. The ARG program is a promising candidate because individual activity-regulated genes protect against seizures, and they also regulate homeostatic effector mechanisms like synaptic scaling that may mediate FRH. However, the molecules that comprise the FRH control circuit are unknown. We hypothesize that the ARG program is the core control mechanism of FRH. Our extensive preliminary data reinforce the importance of testing this hypothesis at genome-scale. The genome-scale approach is important not only because of the sheer number of ARGs but also because different ARGs appear to “interpret” firing rate error in very different -- but as yet undefined -- ways. Relying on our extensive knowledge of the ARG program, we will evaluate its contribution to FRH. For ARG induction to be a core mechanism of FRH, it must be specified quantitatively by firing rates. We will therefore map the coupling of firing rates to ARG expression levels, by controlling firing rates optogenetically and detecting gene expression with RNA-Seq. We will also directly assess the functional contribution of ARG induction to FRH by perturbing firing rates pharmacologically in cortical neurons and observing homeostatic recovery using multi- electrode arrays, with or without perturbation of ARGs. Our approach is innovative because it is a genome- wide investigation of the activity-sensing control system for homeostasis rather than the far better-studied homeostatic effector mechanisms. Our work is significant because it will advance basic knowledge of the control circuit mediating FRH and produce tools for manipulating FRH that will help connect this control circuit to candidate homeostatic mechanisms.

项目摘要/摘要 神经元放电率稳态（FRH）描述了神经元维持其平均放电率的能力 即使面对不断变化的突触输入，提供的稳定性 FRH使学习和记忆。实现FRH需要一个类似于恒温器的FRH控制电路 将期望温度与实际室温进行比较，或者将期望轨迹与实际轨迹进行比较的自动驾驶仪。 识别这种控制回路需要通过扰动点火率和观察来直接测量FRH。 体内平衡恢复，这是很少做的。一个有前途的候选FRH控制电路是神经元 活动调节基因（ARG）程序，其中钙的活动依赖性增加导致转录 mRNA水平持续升高数小时的基因。ARG计划是一个很有前途的候选者 因为个体活动调节基因可以防止癫痫发作， 效应器机制，如突触缩放，可能介导FRH。然而，组成这些分子的分子 FRH控制电路未知。我们假设，ARG程序是核心控制机制， FRH。我们广泛的初步数据加强了在基因组规模上检验这一假设的重要性。的 基因组规模的方法很重要，不仅因为ARG的绝对数量，还因为不同的基因组之间的差异。 ARG似乎以非常不同但尚未定义的方式“解释”发射率误差。依靠我们 我们对ARG计划有着广泛的了解，我们将评估它对FRH的贡献。对于ARG诱导， FRH的核心机制，它必须定量规定的射击率。因此，我们将映射耦合 通过光遗传学控制放电率和检测基因， 用RNA-Seq.我们还将通过以下方法直接评估ARG诱导对FRH的功能贡献： 扰动皮层神经元的放电率，并使用多个 电极阵列，具有或不具有ARG的扰动。我们的方法是创新的，因为它是一个基因组- 广泛调查的活动感应控制系统的稳态，而不是更好的研究 稳态效应器机制我们的工作是重要的，因为它将促进基本的知识， 调节FRH的控制电路，并产生用于操纵FRH的工具，该工具将帮助连接该控制电路 候选的自我平衡机制