Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94305, USA.
Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94305, USA.
J Neurosci Methods. 2021 Feb 1;349:109041. doi: 10.1016/j.jneumeth.2020.109041. Epub 2020 Dec 17.
Ca-imaging is a powerful tool to measure neuronal dynamics and network activity. To monitor network-level changes in cultured neurons, neuronal activity is often evoked by electrical or optogenetic stimulation and assessed using multi-electrode arrays or sophisticated imaging. Although such approaches allow detailed network analyses, multi-electrode arrays lack single-cell precision, whereas optical physiology generally requires advanced instrumentation that may not be universally available.
Here we developed a simple, stimulation-free protocol with associated Matlab algorithms that enables scalable analyses of spontaneous network activity in cultured human and mouse neurons. The approach allows analysis of the overall network activity and of single-neuron dynamics, and is amenable to screening purposes.
We validated the new protocol by assessing human neurons with a heterozygous conditional deletion of Munc18-1, and mouse neurons with a homozygous conditional deletion of neurexins. The approach described enabled identification of differential changes in these mutant neurons, allowing quantifications of the synchronous firing rate at the network level and of the amplitude and frequency of Ca-spikes at the single-neuron level. These results demonstrate the utility of the approach.
Compared with current imaging platforms, our method is simple, scalable, accessible, and easy to implement. It enables quantification of more detailed parameters than multi-electrode arrays, but does not have the resolution and depth of more sophisticated yet labour-intensive methods, such as patch-clamp electrophysiology.
The method reported here is scalable for a rapid direct assessment of neuronal function in culture, and can be applied to both human and mouse neurons. Thus, the method can serve as a basis for phenotypical analysis of mutations and for drug discovery efforts.
钙成像技术是测量神经元动力学和网络活动的强大工具。为了监测培养神经元中的网络级变化，通常通过电或光遗传学刺激来激发神经元活性，并使用多电极阵列或复杂的成像技术进行评估。虽然这些方法允许进行详细的网络分析，但多电极阵列缺乏单细胞精度，而光学生理学通常需要先进的仪器，这可能不是普遍可用的。
在这里，我们开发了一种简单的、无需刺激的方案，并提供了相关的 Matlab 算法，使对培养的人类和小鼠神经元中的自发性网络活动进行可扩展分析成为可能。该方法允许对整体网络活动和单个神经元动力学进行分析，并且适用于筛选目的。
我们通过评估具有 Munc18-1 杂合条件缺失的人类神经元和具有神经连接蛋白 1 同源条件缺失的小鼠神经元，验证了新方案。该方法能够识别这些突变神经元的差异变化，从而能够在网络水平上量化同步发射率，并在单个神经元水平上量化钙峰的幅度和频率。这些结果证明了该方法的实用性。
与当前的成像平台相比，我们的方法简单、可扩展、易于获取且易于实现。它能够量化比多电极阵列更详细的参数，但没有更复杂但劳动密集型的方法（如膜片钳电生理学）的分辨率和深度。
本文报道的方法可用于快速直接评估培养中的神经元功能，并且可适用于人类和小鼠神经元。因此，该方法可以作为突变表型分析和药物发现工作的基础。
