Multidimensional Optimization of Voltage Indicators for In Vivo Neural Activity Imaging

近年来，神经编码的基因编码荧光指标引起了人们的极大兴趣。 活性，使用新分子（例如基因编码的钙指示剂 GCaMP6）来成像 活体大脑中许多神经元同时活动。然而，这些指标进展缓慢，引发了一个问题： 电压指示器是否会变得足够有用并在神经科学中广泛应用。此外，成像 轴突和树突的分析仍然很困难，特别是在密集表达的组织中。例如，当神经元 密集地表达这样的记者，在光的衍射极限内的轴突和树突都会有它们的信号 混合在一起，从而无法解析各个神经过程的信号。我们怎样才能推动 神经活动成像的时空性能符合神经科学家所需的规格 - 低至 毫秒时间尺度，直至神经元的亚微米级轴突和树突部分？我们在这里 建议在体内成像限制的指导下通过分子工程解决这个问题。至 解决空间维度问题：神经活动指标是否可以安全地聚集成离散的、明亮的点 即使在神经回路的所有细胞中表达时，它们之间也有一定的距离 大于成像系统的衍射极限，那么这些斑点就可以清晰地成像，并用于 沿回路中神经元的轴突和树突采样活动。在这笔赠款中，我们将（目标 1）创建并 验证这一策略，我们称之为簇中试剂的随机排列（STARC）。这样，我们 将有效地为全电路神经活动成像指明道路，从而可以研究轴突 信号传导和树突处理，而不仅仅是细胞体成像。为了解决时间维度：我们将 创建优化的荧光电压指示器（目标 2）。开创性的努力已经产生了荧光电压 指标，但由于贩运不畅和在大脑中使用时它们的表现往往很差 膜定位在体内表现出来，因为体内的神经元与用于培养的细胞不同 电压传感器屏幕。我们将进行原位筛选，直接识别荧光电压指标 通过病毒表达突变体库的成员，在完整小鼠大脑回路的神经元中发挥良好作用 电压指示器直接在小鼠大脑中，以单细胞分辨率对小鼠大脑中的反应进行成像 切片，然后直接读出产生在实际中表现最佳的电压指标的突变 大脑回路，验证小鼠大脑中的结果指标。我们还将创建（目标 3）STARC 表格 电压传感器，因为当神经活动发生时，目标 1 中讨论的邻近问题甚至更加严重 记者位于与其他膜非常接近的神经膜上。我们将通过测试来关闭循环 所有这些体内指标，然后迭代分子工程，交付给神经科学 社区是一个功能强大、易于使用的工具箱，可以跨两个空间快速部署以实现超精确 （通过 STARC）和时间（通过原位优化电压指示器）——神经活动成像。

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.