Multidimensional Optimization of Voltage Indicators for In Vivo Neural Activity Imaging

近年来，关于遗传编码的神经细胞荧光指示剂已经引起了很大的兴趣。 活性，新的分子，如遗传编码的钙指标GCaMP 6被用来成像 在活体大脑中许多神经元同时活动。然而，这些指标进展缓慢，提出了一个问题， 电压指示器是否会变得足够有用，在神经科学中广泛使用。此外，成像 轴突和树突的分离仍然是困难的，特别是在密集表达的组织中。例如，当神经元 密集地表达这种报告分子，在光的衍射极限内的轴突和树突将具有它们的信号 混合，因此单个神经过程的信号不能被解析。我们如何推动 神经活动成像的时空性能达到神经科学家所需的规格-低至 从毫秒级的时间尺度，到亚微米级的神经元轴突和树突部分？我们这里 建议通过分子工程，在体内成像约束的指导下解决这个问题。到 解决空间维度：如果神经活动指标可以安全地聚集到离散的，明亮的点 即使在神经回路的所有细胞中表达， 大于成像系统的衍射极限，则这些斑点可以被干净地成像，并用于 沿着回路中神经元的轴突和树突的沿着活动的样本。在这一点上，我们将（目标1）创造和 验证这种策略，我们称之为随机安排的试剂在集群（STARC）。这样我们 将有效地指向回路范围的神经活动成像，允许轴突的调查， 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）。开创性的努力导致了荧光电压 指标，但在大脑中使用时，其性能往往很差，因为贩运和 在体内表现的膜定位，因为体内的神经元不同于用于 电压传感器的屏幕。我们将进行现场筛选，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，在小鼠大脑中以单细胞分辨率成像响应 切片，然后直接阅读产生在实际中表现最佳的电压指示器的突变。 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表单 的电压传感器，因为在目标1中讨论的接近性问题，甚至更严重时，神经活动 报告基因位于神经膜上，与其他膜非常接近。我们将通过测试来关闭循环 所有这些指标都在体内，然后在分子工程上迭代， 社区是一个功能强大、易于使用的工具箱，可以快速部署，以实现超精密-跨越两个领域 (via STARC）和时间（通过原位优化的电压指示器）-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.