Autonomous patch-clamp robot for functional characterization of neurons in vivo: development and application to mouse visual cortex
Autonomous patch-clamp robot for functional characterization of neurons in vivo: development and application to mouse visual cortex
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DOI：
10.1152/jn.00738.2018
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发表时间：
2019-06-01
影响因子：
2.5
通讯作者：
Forest, Craig R.
中科院分区：
文献类型：
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作者：
Holst, Gregory L.;Stoy, William;Forest, Craig R.
膜片钳是体内细胞类型表征的金标准测量技术，但它具有低通量，难以扩展，并且需要高度熟练的操作。我们开发了一个自主机器人，可以获得多个连续的膜片钳记录在体内。在实践中，将装载到传送带中的40个移液管依次填充并插入脑中，定位到细胞，用于膜片钳，并处理。自动视觉刺激和电生理学软件能够对全细胞补丁细胞进行功能细胞类型分类，正如我们在麻醉小鼠视觉皮层（V1）第5层中显示的37个细胞。我们达到了9%的产率，在数百次试验中每次尝试5.3分钟。体内膜片钳记录的高度可变性和低产量的性质将受益于这样一个标准化的，自动化的，定量的方法，允许开发最佳的算法，并实现大规模研究所需的缩放和与互补技术的集成。新&值得注意的是体内膜片钳是细胞内记录的黄金标准，但它是一个非常手动和高度熟练的技术。这项工作中的机器人展示了迄今为止最自动化的体内膜片钳实验，通过在没有人为干预的情况下产生多个连续的细胞内记录。机器人自动化移液器，线线程。移液器定位、神经元搜寻、插入、传递感觉刺激和记录质量控制，从而实现体内细胞类型表征。
Patch clamping is the gold standard measurement technique for cell-type characterization in vivo, but it has low throughput, is difficult to scale, and requires highly skilled operation. We developed an autonomous robot that can acquire multiple consecutive patch-clamp recordings in vivo. In practice, 40 pipettes loaded into a carousel are sequentially filled and inserted into the brain, localized to a cell, used for patch clamping, and disposed. Automated visual stimulation and electrophysiology software enables functional cell-type classification of whole cell-patched cells, as we show for 37 cells in the anesthetized mouse in visual cortex (V1) layer 5. We achieved 9% yield, with 5.3 min per attempt over hundreds of trials. The highly variable and low-yield nature of in vivo patch-clamp recordings will benefit from such a standardized, automated, quantitative approach, allowing development of optimal algorithms and enabling scaling required for large-scale studies and integration with complementary techniques.NEW & NOTEWORTHY In vivo patch-clamp is the gold standard for intracellular recordings, but it is a very manual and highly skilled technique. The robot in this work demonstrates the most automated in vivo patch-clamp experiment to date, by enabling production of multiple, serial intracellular recordings without human intervention. The robot automates pipette tilling, wire threading. pipette positioning, neuron hunting, break-in, delivering sensory stimulus, and recording quality control, enabling in vivo cell-type characterization.