Multidimensional Optimization of Voltage Indicators for In Vivo Neural Activity Imaging

近年来，关于神经基因编码的荧光指示物的研究非常令人兴奋。 活性，新分子，如基因编码的钙指示剂GCaMP6被用来成像 活着的大脑中许多神经元同时的活动。然而，这些指标是缓慢的，这引发了一个问题： 电压指示器是否会变得足够有用，从而在神经科学中得到广泛应用。此外，成像 轴突和树突的定位仍然很困难，尤其是在表达密集的组织中。例如，当神经元 密集地表达这样的记者，轴突和树突在光的衍射极限内就会有它们的信号 混合，使得单个神经过程的信号不能被解析。我们如何才能推动 神经活动成像的时空性能符合神经科学家的要求--细至 毫秒级的时间尺度，直到神经元的亚微米尺度的轴突和树突部分？我们在这里 建议在体内成像限制的指导下，通过分子工程来解决这个问题。至 解决空间维度：如果神经活动指标可以安全地聚集成离散的、明亮的点状 即使在神经回路的所有细胞中表达，也是彼此相隔一段距离的 大于成像系统的衍射极限，那么这些点就可以清晰地成像，并用来 样本活动沿轴突和树突的神经元在电路中。在这笔赠款中，我们将(目标1)创建和 验证这一策略，我们称之为簇中试剂随机排列(STARC)。通过这种方式，我们 将有效地为全电路神经活动成像指明方向，从而允许研究轴突 信号和树突处理，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的产生 指标，但它们在大脑中使用时往往表现不佳，因为糟糕的贩运和 在体内表现的膜定位，因为体内神经元与过去培养的细胞不同 电压传感器的屏幕。我们将进行现场筛查，直接识别荧光电压指示器 通过病毒表达突变体库的成员，在完整的小鼠大脑回路中的神经元中工作良好 电压指示器直接在小鼠大脑中，在小鼠大脑中以单细胞分辨率成像响应 切片，然后直接读出产生实际表现最好的电压指示器的突变 大脑回路，验证小鼠大脑中的结果指示器。我们还将创建(目标3)STARC表单 电压传感器，因为目标1中讨论的接近问题在神经活动时更加严重 记者在一个神经膜上，它与其他膜非常接近。我们将通过测试来关闭环路 所有这些指标在活体内，然后在分子工程上迭代，传递给神经科学 社区功能强大、简单易用的工具箱，可在两个空间中快速部署以实现超精密 (通过STARE)和时间(通过现场优化的电压指示器)--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.