Cadwell Cathryn R, Scala Federico, Li Shuang, Livrizzi Giulia, Shen Shan, Sandberg Rickard, Jiang Xiaolong, Tolias Andreas S
Department of Neuroscience, Baylor College of Medicine, Houston, Texas, USA.
Ludwig Institute for Cancer Research, Stockholm, Sweden.
Nat Protoc. 2017 Dec;12(12):2531-2553. doi: 10.1038/nprot.2017.120. Epub 2017 Nov 16.
Neurons exhibit a rich diversity of morphological phenotypes, electrophysiological properties, and gene-expression patterns. Understanding how these different characteristics are interrelated at the single-cell level has been difficult because of the lack of techniques for multimodal profiling of individual cells. We recently developed Patch-seq, a technique that combines whole-cell patch-clamp recording, immunohistochemistry, and single-cell RNA-sequencing (scRNA-seq) to comprehensively profile single neurons from mouse brain slices. Here, we present a detailed step-by-step protocol, including modifications to the patching mechanics and recording procedure, reagents and recipes, procedures for immunohistochemistry, and other tips to assist researchers in obtaining high-quality morphological, electrophysiological, and transcriptomic data from single neurons. Successful implementation of Patch-seq allows researchers to explore the multidimensional phenotypic variability among neurons and to correlate gene expression with phenotype at the level of single cells. The entire procedure can be completed in ∼2 weeks through the combined efforts of a skilled electrophysiologist, molecular biologist, and biostatistician.
神经元表现出丰富多样的形态学表型、电生理特性和基因表达模式。由于缺乏对单个细胞进行多模态分析的技术,了解这些不同特征在单细胞水平上是如何相互关联的一直很困难。我们最近开发了Patch-seq技术,该技术结合了全细胞膜片钳记录、免疫组织化学和单细胞RNA测序(scRNA-seq),以全面分析来自小鼠脑片的单个神经元。在这里,我们提供了一个详细的分步方案,包括对膜片钳操作力学和记录程序的改进、试剂和配方、免疫组织化学程序以及其他提示,以帮助研究人员从单个神经元获得高质量的形态学、电生理和转录组数据。Patch-seq的成功实施使研究人员能够探索神经元之间的多维表型变异性,并在单细胞水平上关联基因表达与表型。通过熟练的电生理学家、分子生物学家和生物统计学家的共同努力,整个过程大约可以在2周内完成。