Engineering designer probes for imaging membrane potential: novel parts, architectures, and platforms

工程设计师探索膜电位成像：新颖的部件、架构和平台

• 批准号: 10112904
• 负责人: Francois St-Pierre
• 金额: $ 53.37万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-06-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10112904
• 关键词: Action Potentials; Address; Architecture; Axon; Behavior; Brain; Brain imaging; Calcium; Cells; Characteristics; Computers; Data; Dendrites; Detection; Disease; Electrodes; Electrophysiology (science); Engineering; Family; Fluorescence; Fluorescent Probes; Genetic Engineering; Genomics; Goals; Health; Image; Imaging Device; Imaging Techniques; Impairment; In Vitro; Individual; Infrastructure; Kinetics; Laboratories; Lead; Libraries; Light; Membrane; Membrane Potentials; Methodology; Methods; Mining; Molecular; Monitor; Morphology; Neuroglia; Neurons; Neuropil; Optics; Orthologous Gene; Outcome; Performance; Phylogenetic Analysis; Population; Property; Protein Engineering; Proteins; Rapid screening; Reporting; Resolution; Rest; Rodent; Role; Signal Transduction; Slice; Synapses; Training; Transistors; Variant; absorption; base; brain cell; cell type; experience; experimental study; high throughput screening; imaging probe; improved; in vivo; in vivo imaging; information processing; innovation; molecular marker; novel; promoter; relating to nervous system; response; screening; sensor; tool; two-photon; voltage

Project Summary/Abstract The mammalian brain is composed of a diverse array of neuronal and glial cell types that differ in their morphology, electrical characteristics, and molecular markers. Understanding the neural basis of behavior in health and disease will, therefore, require elucidation of the respective roles of these cell types in representing and processing information. However, traditional electrophysiological (electrode-based) methods for monitoring neural activity cannot be restricted to specific cell types. The solution suggested in this proposal is to develop improved Genetically Encoded Voltage Indicators (GEVIs), which are fluorescent proteins whose brightness is modulated by electrical activity (voltage). GEVIs are promising tools as their expression can be restricted to genetically-defined cell populations. Moreover, by directly reporting voltage rather than a surrogate parameter (e.g. calcium), they can monitor a richer repertoire of neuronal electrical signals, including inhibitory signals (hyperpolarizations), subthreshold depolarizations, and rapid trains of action potentials. While GEVIs have shown early promise for optical detection of voltage transients, their performance is currently insufficient for single-trial imaging of voltage in populations of individual neurons in vivo. This proposal aims to address this performance gap using a multipronged approach. First, the authors propose to optimize a new GEVI architecture optimized for long-term in vivo imaging. Second, natural diversity will be mined to uncover novel voltage-sensing proteins that enable detection of voltage dynamics with more sensitivity or temporal precision. Finally, a new high-throughput screening platform optimized for engineering GEVIs will be deployed for rapidly screening large libraries of indicators. To facilitate deployment in downstream applications, GEVIs with improved properties will be comprehensively evaluated across all key performance metrics in neurons, in brain slices, and in vivo. Overall, the experiments are anticipated to lead to designer GEVIs of broad utility and impact for understanding how the various cell types in the brain cooperate to enable behavior.

项目概要/摘要 哺乳动物的大脑由多种神经元和神经胶质细胞类型组成，它们的功能不同 形态、电特性和分子标记。了解行为的神经基础 因此，需要阐明这些细胞类型在健康和疾病中各自的作用 表示和处理信息。然而，传统的电生理学（基于电极） 监测神经活动的方法不能仅限于特定的细胞类型。中建议的解决方案 该提案旨在开发改进的基因编码电压指示器（GEVI）， 其亮度受电活动（电压）调节的荧光蛋白。 GEVI 前景广阔 工具，因为它们的表达可以仅限于基因定义的细胞群。此外，通过直接 报告电压而不是替代参数（例如钙），他们可以监测更丰富的内容 神经元电信号，包括抑制信号（超极化）、阈下去极化、 和快速的动作电位序列。 虽然 GEVI 在电压瞬变光学检测方面已显示出早期前景，但它们的 目前的性能不足以对单个神经元群体进行电压的单次试验成像 体内。该提案旨在采用多管齐下的方法来解决这一绩效差距。首先， 作者建议优化一种新的 GEVI 架构，该架构针对长期体内成像进行了优化。第二， 将挖掘自然多样性来发现能够检测电压的新型电压传感蛋白 具有更高灵敏度或时间精度的动力学。最后，一个新的高通量筛选平台 将部署针对工程优化的 GEVI，以快速筛选大型指标库。到 促进下游应用的部署，具有改进性能的GEVI将 对神经元、大脑切片和体内的所有关键性能指标进行全面评估。 总体而言，这些实验预计将产生具有广泛实用性和影响力的 GEVI 设计者 了解大脑中的各种细胞类型如何合作以实现行为。