Modeling the Molecular Networks that Underlie the Formation and Consolidation of Memory
模拟记忆形成和巩固的分子网络
基本信息
- 批准号:10083237
- 负责人:
- 金额:$ 33.45万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2018
- 资助国家:美国
- 起止时间:2018-02-15 至 2022-12-31
- 项目状态:已结题
- 来源:
- 关键词:ATF2 geneAffectAnimal ModelAplysiaBiologicalBrain-Derived Neurotrophic FactorCCAAT-Enhancer-Binding ProteinsCREB1 geneCREBBP geneCell modelChemosensitizationCluster AnalysisCoffin-Lowry syndromeCognition DisordersComputer ModelsCyclic AMP-Dependent Protein KinasesDataDevelopmentFeedbackGene MutationGenetic TranscriptionGrantGrowth FactorHippocampus (Brain)Histone AcetylationImpaired cognitionImpairmentInterventionIntuitionLaboratoriesLeadLearningLesionLong-Term PotentiationMAP Kinase GeneMapsMemoryMemory impairmentMethodologyMethodsMethyl-CpG-Binding Protein 2ModelingMolecularMutationPathway interactionsPharmaceutical PreparationsPharmacological TreatmentPharmacologyPharmacotherapyPhosphorylationPhosphotransferasesPlayProcessProtocols documentationRegulationRett SyndromeRibosomal Protein S6 KinaseRibosomesRoleRubinstein-Taybi SyndromeSerotoninSignal PathwayStimulusSynapsesSynaptic plasticitySystemTestingTrainingTranscriptional RegulationTransforming Growth Factor betaUnited States National Institutes of HealthUp-RegulationWood materialconditioningdesignenhancing factorextracellularinnovationinsightlong term memorymemory consolidationmolecular modelingmolecular sitemouse modelnovelp38 Mitogen Activated Protein Kinasepredictive modelingresearch studysimulationtranscription factortreatment strategy
项目摘要
Molecular processes that underlie the induction and consolidation of long-term memory (LTM) are the subjects
of intensive research, and studies are providing a wealth of empirical data that relate aspects of memory to
specific intracellular signaling pathways. For example, empirical studies are elucidating the roles played by
extracellular factors (e.g. growth factors), kinase activity, and transcriptional regulation in induction and
consolidation of memory. Due in part to the complexity and nonlinear features of these molecular pathways, it
is difficult to develop an intuitive understanding of the ways in which these pathways respond to stimulus
protocols or pharmacological manipulations or are affected by single-site molecular lesions. To provide a better
understanding of the processes underlying LTM, the present proposal will develop quantitative models of the
molecular pathways that underlie two well-characterized models of LTM: i) long-term synaptic facilitation (LTF)
and ii) long-term synaptic potentiation (LTP). Parameters will be constrained by empirical data. Parameter
sensitivity analysis and a novel cluster analysis will assess model robustness. Aim 1 will extend our model for
LTF, which describes the regulation of transcription by PKA and ERK via phosphorylation of the transcription
factors CREB1 and CREB2. The extended model will include components of additional intra- and extracellular
feedback loops (e.g., TGFβ, and ApNT), an additional transcription factor (C/EBP), ribosomal s6 kinase (RSK)
and p38 MAP kinase. In Aim 2, this model will be used to predict stimulus protocols, as well as pharmacological
treatments, that enhance LTF and that rescue impaired LTF. Aim 3 will extend our current model of LTP, which
describes roles of several kinase pathways (e.g., MAPK, PKA, PKC, and CAMKII) and histone acetylation. The
model will incorporate a recently delineated BDNF positive-feedback loop, which leads to activation of ERK,
phosphorylation of CREB1, and induction of transcription necessary for the consolidation of LTP. We will
simulate stimulus protocols and drug effects to predict treatments that could rescue impaired memory
mechanisms in Rett syndrome, which is caused by mutations that alter the activity of the transcription factor
MeCP2, and that can rescue impaired mechanisms in Rubinstein-Taybi syndrome, which is caused by mutations
in CREB binding protein. This proposed approach of using models to predict novel learning paradigms and/or
drug treatments that restore normal plasticity, is an innovative methodology that could ultimately lead to the
development of new strategies for the treatment of cognitive disorders.
长期记忆(LTM)诱导和巩固的分子过程是主题
深入的研究,并且研究提供了大量的经验数据,将记忆的各个方面与
特定的细胞内信号传导途径。例如,实证研究正在阐明
细胞外因子(例如生长因子)、激酶活性以及诱导和转录调控
巩固记忆。部分由于这些分子途径的复杂性和非线性特征,
很难对这些途径对刺激的反应方式产生直观的理解
方案或药理学操作或受到单位点分子损伤的影响。为了提供更好的
为了理解 LTM 的基本过程,本提案将开发 LTM 的定量模型
两种充分表征的 LTM 模型的分子途径: i) 长期突触促进 (LTF)
ii) 长时程突触增强(LTP)。参数将受到经验数据的约束。范围
敏感性分析和新颖的聚类分析将评估模型的稳健性。目标 1 将我们的模型扩展为
LTF,描述了 PKA 和 ERK 通过转录磷酸化对转录的调节
因子 CREB1 和 CREB2。扩展模型将包括额外的细胞内和细胞外组件
反馈环(例如 TGFβ 和 ApNT)、附加转录因子 (C/EBP)、核糖体 s6 激酶 (RSK)
和 p38 MAP 激酶。在目标 2 中,该模型将用于预测刺激方案以及药理学
治疗,增强 LTF 并挽救受损的 LTF。目标 3 将扩展我们当前的 LTP 模型,即
描述了多种激酶途径(例如 MAPK、PKA、PKC 和 CAMKII)和组蛋白乙酰化的作用。这
模型将包含最近描述的 BDNF 正反馈回路,这会导致 ERK 的激活,
CREB1 的磷酸化,以及 LTP 巩固所必需的转录诱导。我们将
模拟刺激方案和药物效果来预测可以挽救受损记忆的治疗方法
雷特综合征的机制,该综合征是由改变转录因子活性的突变引起的
MeCP2,可以挽救由突变引起的 Rubinstein-Taybi 综合征的受损机制
在CREB结合蛋白中。这种使用模型来预测新的学习范式和/或
恢复正常可塑性的药物治疗是一种创新方法,最终可能导致
开发治疗认知障碍的新策略。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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John H Byrne其他文献
John H Byrne的其他文献
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{{ truncateString('John H Byrne', 18)}}的其他基金
A novel approach to analyzing functional connectomics and combinatorial control in a tractable small-brain closed-loop system
一种在易处理的小脑闭环系统中分析功能连接组学和组合控制的新方法
- 批准号:
10700737 - 财政年份:2020
- 资助金额:
$ 33.45万 - 项目类别:
A novel approach to analyzing functional connectomics and combinatorial control in a tractable small-brain closed-loop system
一种在易处理的小脑闭环系统中分析功能连接组学和组合控制的新方法
- 批准号:
10058915 - 财政年份:2020
- 资助金额:
$ 33.45万 - 项目类别:
Modeling the Molecular Networks that Underlie the Formation and Consolidation of Memory
模拟记忆形成和巩固的分子网络
- 批准号:
10607560 - 财政年份:2018
- 资助金额:
$ 33.45万 - 项目类别:
Analyses of the Distributed Representation of Associative-Learning in an Identified Circuit Using a Combination of Single-Cell Electrophysiology and Multicellular Voltage-Sensitive Dye Recordings
结合单细胞电生理学和多细胞电压敏感染料记录分析已识别电路中联想学习的分布式表示
- 批准号:
10083235 - 财政年份:2018
- 资助金额:
$ 33.45万 - 项目类别:
Modeling the Molecular Networks that Underlie the Formation and Consolidation of Memory
模拟记忆形成和巩固的分子网络
- 批准号:
10317000 - 财政年份:2018
- 资助金额:
$ 33.45万 - 项目类别:
Analyses of the Distributed Representation of Associative-Learning in an Identified Circuit Using a Combination of Single-Cell Electrophysiology and Multicellular Voltage-Sensitive Dye Recordings
结合单细胞电生理学和多细胞电压敏感染料记录分析已识别电路中联想学习的分布式表示
- 批准号:
10317049 - 财政年份:2018
- 资助金额:
$ 33.45万 - 项目类别:
Analyses of the Distributed Representation of Associative-Learning in an Identified Circuit Using a Combination of Single-Cell Electrophysiology and Multicellular Voltage-Sensitive Dye Recordings
结合单细胞电生理学和多细胞电压敏感染料记录分析已识别电路中联想学习的分布式表示
- 批准号:
10539225 - 财政年份:2018
- 资助金额:
$ 33.45万 - 项目类别:
Modeling Gene Regulation Essential for Long-Term Plasticity
对长期可塑性至关重要的基因调控建模
- 批准号:
8652842 - 财政年份:2011
- 资助金额:
$ 33.45万 - 项目类别:
Modeling Gene Regulation Essential for Long-Term Plasticity
对长期可塑性至关重要的基因调控建模
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- 资助金额:
$ 33.45万 - 项目类别:
Modeling Gene Regulation Essential for Long-Term Plasticity
对长期可塑性至关重要的基因调控建模
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8464817 - 财政年份:2011
- 资助金额:
$ 33.45万 - 项目类别:
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