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.

项目概要/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 从长远来看，即使面对不断变化的突触输入，也能保持精确的设定点。 FRH 支持学习和记忆 实现 FRH 需要类似于恒温器的 FRH 控制电路。 它将期望与实际室温进行比较，或者自动驾驶仪将期望与实际轨迹进行比较。 识别该控制电路需要通过扰动发射率并观察来直接测量 FRH 神经元是一种很有前途的候选 FRH 控制电路，但这种情况很少进行。 活性调节基因 (ARG) 程序，其中钙的活性依赖性增加导致转录 ARG 程序是一个很有前途的候选基因。 因为个体活动调节基因可以防止癫痫发作，并且它们还可以调节体内平衡 然而，突触缩放等效应机制可能介导 FRH。 FRH控制电路未知。我们了解到ARG程序是其核心控制机制。 FRH。我们广泛的初步数据强化了在基因组规模上测试这一假设的重要性。 基因组规模的方法很重要，不仅因为 ARG 的数量庞大，还因为不同的 ARG 似乎以非常不同但尚未定义的方式“解释”发射率误差，具体取决于我们。 对 ARG 计划的广泛了解，我们将评估其对 FRH 的贡献，以使其成为 ARG 诱导计划的一部分。 FRH 的核心机制，必须通过发射率来定量指定，因此我们将绘制耦合图。 通过光遗传学控制放电率并检测基因，将放电率与 ARG 表达水平相关 我们还将通过 RNA-Seq 直接评估 ARG 诱导对 FRH 的功能贡献。 扰乱皮层神经元的药理学放电率并使用多种方法观察稳态恢复 电极阵列，有或没有 ARG 扰动，我们的方法是创新的，因为它是基因组。 对稳态活动传感控制系统的广泛研究，而不是更好的研究 我们的工作意义重大，因为它将增进有关稳态效应机制的基础知识。 调节 FRH 的控制电路并生产用于操纵 FRH 的工具，以帮助连接该控制电路 候选稳态机制。