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.

项目摘要/摘要 哺乳动物大脑由各种各样的神经元和神经胶质细胞类型组成，它们的不同 形态，电特性和分子标记物。了解行为的神经基础 因此，在健康和疾病中，将需要阐明这些细胞类型在 表示和处理信息。但是，传统电生理（基于电极） 监测神经活动的方法不仅限于特定的细胞类型。建议的解决方案 该建议是开发改进的遗传编码电压指标（GEVI），这是 荧光蛋白的亮度是由电活动（电压）调节的。 Gevis很有希望 工具作为表达，可以局限于遗传定义的细胞群。而且，直接 报告电压而不是替代参数（例如钙），它们可以监视更丰富的曲目 神经元电信号，包括抑制信号（超极化），亚阈值去极化， 和快速的行动潜力。 虽然Gevis已经表现出对电压瞬变光学检测的早期希望 目前，性能不足以在单个神经元种群中的电压单次试验成像 体内。该建议旨在使用多收益的方法来解决此绩效差距。首先， 作者建议优化用于长期体内成像的新的GEVI架构。第二， 自然多样性将被开采以发现新型的电压感应蛋白，以检测电压 具有更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 针对工程GEVI的优化将被部署，以快速筛选大量指标库。到 促进在下游应用程序中的部署，具有改进属性的GEVIS将是 在神经元，大脑切片和体内的所有关键性能指标中进行了全面评估。 总体而言，预计实验会导致广泛实用性的设计师Gevis，并影响 了解大脑中的各种细胞类型如何配合以实现行为。