Multidimensional Optimization of Voltage Indicators for In Vivo Neural Activity Imaging

体内神经活动成像电压指示器的多维优化

• 批准号: 10553676
• 负责人: Xue Han
• 金额: $ 67.77万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-01 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10553676
• 关键词: 3-Dimensional; Address; Assessment tool; Axon; Behavioral; Brain; Cell Fraction; Cell membrane; Cells; Clinical; Code; Communities; Corpus striatum structure; Cultured Cells; Dendrites; Development; Dimensions; Disease; Educational process of instructing; Engineering; Exhibits; Fluorescence; Future; Grant; Hippocampus; Image; In Situ; Individual; Investigation; Kinetics; Label; Libraries; Light; Location; Maps; Membrane; Microscopy; Molecular; Mus; Mutation; Nature; Neurons; Neuropil; Neurosciences; Noise; Performance; Philosophy; Population; Population Analysis; Process; Property; Public Health; Reading; Reagent; Reporter; Research; Resolution; Safety; Sampling; Sea; Signal Transduction; Slice; Specific qualifier value; Speed; System; Technology; Testing; Time; Tissues; Validation; Variant; Viral; Work; anatomical tracing; calcium indicator; design; experience; image guided; imaging modality; imaging system; in vivo; in vivo imaging; interest; member; millisecond; mutant; neural; neural circuit; neural network; neuroregulation; neurotransmission; optogenetics; preservation; response; scale up; sensor; side effect; spatiotemporal; submicron; superresolution imaging; tool; trafficking; ultra high resolution; voltage

In recent years there has been much excitement about genetically encoded fluorescent indicators of neural activity, with new molecules such as the genetically encoded calcium indicator GCaMP6 being used to image the activity of many neurons at once in living brains. However, such indicators are slow, raising the question of whether voltage indicators will become useful enough to be widespread in neuroscience. Furthermore, imaging of axons and dendrites remains difficult, especially in densely expressing tissues. For example, when neurons express such reporters densely, axons and dendrites within the diffraction limit of light will have their signals mixed, so that the signals of individual neural processes cannot be resolved. How can we push the spatiotemporal performance of neural activity imaging to the specifications desired by neuroscientists – down to the millisecond timescale, and down to the sub-micron scale axonal and dendritic parts of neurons? We here propose to address this problem through molecular engineering, guided by in vivo imaging constraints. To address the spatial dimension: if neural activity indicators could be safely clustered into discrete, bright puncta that, even when expressed in all the cells of a neural circuit, are separated from one another by a distance greater than the diffraction limit of the imaging system, then these puncta could cleanly be imaged, and used to sample activity along axons and dendrites of the neurons in a circuit. In this grant, we will (Aim 1) create and validate this strategy, which we call stochastic arrangement of reagents in clusters (STARC). In this way, we will effectively point the way towards circuit-wide neural activity imaging that allows for the investigation of axonal signaling and dendritic processing, and not only cell body imaging. To address the temporal dimension: we will create optimized fluorescent voltage indicators (Aim 2). Pioneering efforts have resulted in fluorescent voltage indicators, but their performance is often poor when utilized in the brain, because of poor trafficking and membrane localization that manifests in vivo, since neurons in vivo are different from the cultured cells used to screen for the voltage sensors. We will conduct an in situ screen to directly identify fluorescent voltage indicators that work well in neurons in intact mouse brain circuits, by virally expressing members of a library of mutant voltage indicators directly in the mouse brain, imaging the responses with single cell resolution in mouse brain slices, and then directly reading out the mutations that yielded the voltage indicators that best perform in actual brain circuits, validating the resultant indicators in the mouse brain. We will also create (Aim 3) STARC forms of voltage sensors, since the proximity issues discussed in Aim 1 are even more severe when a neural activity reporter is on a neural membrane that is in close proximity to other membranes. We will close the loop by testing all such indicators in vivo and then iterating on the molecular engineering, delivering to the neuroscience community a powerful, simple-to-use toolbox that can be rapidly deployed for ultraprecise – across both space (via STARC) and time (via in situ optimized voltage indicators) -- neural activity imaging.

近年来，神经元的遗传编码荧光指标引起了很多兴奋 活性，新分子（例如用于图像的一般编码的钙指示剂GCAMP6） 许多神经元在活脑中的活动。但是，这样的指标很慢，提出了 电压指示器是否会变得足够有用，可以在神经科学中广泛。此外，成像 轴突和树突仍然很困难，尤其是在静脉内表达的组织中。例如，当神经元 在光线衍射极限内，轴突和树枝状的敏锐地表达这些记者的信号 混合，使得单个神经过程的信号无法解决。我们如何推动 神经元活动成像对神经科学家所需的规范的时空性能 - 毫秒的时间尺度，直到神经元的轴突和树突状部分？我们在这里 通过分子工程来解决此问题的建议，并在体内成像限制的指导下。到 解决空间维度：如果可以将神经元活动指标安全地聚集到离散的，明亮的点 即使在神经元电路的所有细胞中表达，也会相互分离 大于成像系统的衍射极限，然后可以清洁成像，并习惯 电路中神经元的轴突和树突的样品活性。在这笔赠款中，我们将（目标1）创建和 验证该策略，我们称之为簇中的试剂随机排列（Starc）。这样，我们 将有效地指向通道范围范围的神经活动成像的道路，该成像允许研究轴突 信号传导和树突处理，不仅是细胞体成像。解决临时维度：我们将 创建优化的荧光电压指示器（AIM 2）。开创性的工作导致荧光电压 指标，但是由于贩运较差和 由于体内神经元与曾经的培养细胞不同，因此在体内表现出来的膜定位 屏幕电压传感器。我们将进行原位屏幕以直接识别荧光电压指示器 通过病毒表达突变体库的成员 直接在小鼠大脑中的电压指示器，以小鼠脑中的单细胞分辨率成像响应 切片，然后直接读取产生最佳性能的电压指示器的突变 脑电路，验证小鼠大脑中的结果指标。我们还将创建（AIM 3）Starc形式 电压传感器的电压传感器，因为AIM 1中讨论的接近性问题在神经活动时更加严重 记者处于与其他膜相近的神经元膜上。我们将通过测试结束循环 所有此类指标在体内，然后在分子工程上迭代，以传递到神经科学 社区一个功能强大，易于使用的工具箱，可以迅速部署以进行超脑 - 遍及两个空间 （通过Starc）和时间（通过原位优化电压指示器） - 神经活动成像。