• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

使用Patch-seq对单细胞形态、电生理学和基因表达进行多模态分析。

Multimodal profiling of single-cell morphology, electrophysiology, and gene expression using Patch-seq.

作者信息

Cadwell Cathryn R, Scala Federico, Li Shuang, Livrizzi Giulia, Shen Shan, Sandberg Rickard, Jiang Xiaolong, Tolias Andreas S

机构信息

Department of Neuroscience, Baylor College of Medicine, Houston, Texas, USA.

Ludwig Institute for Cancer Research, Stockholm, Sweden.

出版信息

Nat Protoc. 2017 Dec;12(12):2531-2553. doi: 10.1038/nprot.2017.120. Epub 2017 Nov 16.

DOI:10.1038/nprot.2017.120
PMID:29189773
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6422019/
Abstract

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.

摘要

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。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b380/6422019/2d6c9be6dd21/nihms-999727-f0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b380/6422019/45c75640d19d/nihms-999727-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b380/6422019/172d87e41364/nihms-999727-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b380/6422019/39112d9236aa/nihms-999727-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b380/6422019/f22370e8a607/nihms-999727-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b380/6422019/afa22b58a377/nihms-999727-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b380/6422019/f19f341c918c/nihms-999727-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b380/6422019/9c8e11db5f1f/nihms-999727-f0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b380/6422019/2d6c9be6dd21/nihms-999727-f0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b380/6422019/45c75640d19d/nihms-999727-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b380/6422019/172d87e41364/nihms-999727-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b380/6422019/39112d9236aa/nihms-999727-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b380/6422019/f22370e8a607/nihms-999727-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b380/6422019/afa22b58a377/nihms-999727-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b380/6422019/f19f341c918c/nihms-999727-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b380/6422019/9c8e11db5f1f/nihms-999727-f0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b380/6422019/2d6c9be6dd21/nihms-999727-f0008.jpg

相似文献

1
Multimodal profiling of single-cell morphology, electrophysiology, and gene expression using Patch-seq.使用Patch-seq对单细胞形态、电生理学和基因表达进行多模态分析。
Nat Protoc. 2017 Dec;12(12):2531-2553. doi: 10.1038/nprot.2017.120. Epub 2017 Nov 16.
2
Patch-seq: Multimodal Profiling of Single-Cell Morphology, Electrophysiology, and Gene Expression. 切片测序:单细胞形态、电生理学和基因表达的多模态分析。
Methods Mol Biol. 2024;2752:227-243. doi: 10.1007/978-1-0716-3621-3_15.
3
Q&A: using Patch-seq to profile single cells.问答:使用 Patch-seq 技术进行单细胞分析。
BMC Biol. 2017 Jul 6;15(1):58. doi: 10.1186/s12915-017-0396-0.
4
Integration of electrophysiological recordings with single-cell RNA-seq data identifies neuronal subtypes.将电生理记录与单细胞RNA测序数据相结合可识别神经元亚型。
Nat Biotechnol. 2016 Feb;34(2):175-183. doi: 10.1038/nbt.3443. Epub 2015 Dec 21.
5
Electrophysiological, transcriptomic and morphologic profiling of single neurons using Patch-seq.使用Patch-seq对单个神经元进行电生理、转录组和形态学分析。
Nat Biotechnol. 2016 Feb;34(2):199-203. doi: 10.1038/nbt.3445. Epub 2015 Dec 21.
6
Protocol for Patch-Seq of Small Interneurons.小神经元贴壁测序方案。
STAR Protoc. 2020 Oct 22;1(3):100146. doi: 10.1016/j.xpro.2020.100146. eCollection 2020 Dec 18.
7
Gene Expression Analysis by Multiplex Single-Cell RT-PCR.通过多重单细胞逆转录聚合酶链反应进行基因表达分析。
Methods Mol Biol. 2019;1941:139-154. doi: 10.1007/978-1-4939-9077-1_10.
8
Patch-seq: Past, Present, and Future.高通量测序技术:过去、现在和未来。
J Neurosci. 2021 Feb 3;41(5):937-946. doi: 10.1523/JNEUROSCI.1653-20.2020. Epub 2021 Jan 11.
9
Scaled, high fidelity electrophysiological, morphological, and transcriptomic cell characterization.标准化、高保真的电生理、形态学和转录组学细胞特征描述。
Elife. 2021 Aug 13;10:e65482. doi: 10.7554/eLife.65482.
10
Patch-seq: Advances and Biological Applications.基因芯片测序:进展与生物学应用
Cell Mol Neurobiol. 2023 Dec 20;44(1):8. doi: 10.1007/s10571-023-01436-3.

引用本文的文献

1
Sensory modality-specific wiring of thalamocortical circuits.丘脑皮质回路的感觉模态特异性布线。
Nat Rev Neurosci. 2025 Jul 30. doi: 10.1038/s41583-025-00945-y.
2
Targeted single cell expression profiling identifies integrators of sleep and metabolic state.靶向单细胞表达谱分析确定睡眠与代谢状态的整合因子。
G3 (Bethesda). 2025 Jun 13. doi: 10.1093/g3journal/jkaf079.
3
Connectomics of predicted Sst transcriptomic types in mouse visual cortex.小鼠视觉皮层中预测的Sst转录组类型的连接组学

本文引用的文献

1
Comprehensive single-cell transcriptional profiling of a multicellular organism.多细胞生物的全面单细胞转录谱分析。
Science. 2017 Aug 18;357(6352):661-667. doi: 10.1126/science.aam8940.
2
Q&A: using Patch-seq to profile single cells.问答:使用 Patch-seq 技术进行单细胞分析。
BMC Biol. 2017 Jul 6;15(1):58. doi: 10.1186/s12915-017-0396-0.
3
Functional identification of islet cell types by electrophysiological fingerprinting.通过电生理指纹识别胰岛细胞类型的功能鉴定
Nature. 2025 Apr;640(8058):497-505. doi: 10.1038/s41586-025-08805-6. Epub 2025 Apr 9.
4
Multimodal single-cell analyses reveal molecular markers of neuronal senescence in human drug-resistant epilepsy.多模态单细胞分析揭示人类耐药性癫痫中神经元衰老的分子标志物。
J Clin Invest. 2025 Mar 3;135(5):e188942. doi: 10.1172/JCI188942.
5
Robotic Fast Patch Clamp in Brain Slices Based on Stepwise Micropipette Navigation and Gigaseal Formation Control.基于逐步微电极导航和千兆封接形成控制的脑片机器人快速膜片钳技术
Sensors (Basel). 2025 Feb 13;25(4):1128. doi: 10.3390/s25041128.
6
Combined statistical-biophysical modeling links ion channel genes to physiology of cortical neuron types.统计-生物物理联合建模将离子通道基因与皮层神经元类型的生理学联系起来。
bioRxiv. 2025 Jan 2:2023.03.02.530774. doi: 10.1101/2023.03.02.530774.
7
Molecular logic for cellular specializations that initiate the auditory parallel processing pathways.启动听觉并行处理通路的细胞特化的分子逻辑。
Nat Commun. 2025 Jan 9;16(1):489. doi: 10.1038/s41467-024-55257-z.
8
Single Cell Deletion of the Transcription Factors Trps1 and Sox9 in Astrocytes Reveals Novel Functions in the Adult Cerebral Cortex.星形胶质细胞中转录因子Trps1和Sox9的单细胞缺失揭示了成年大脑皮质中的新功能。
Glia. 2025 Apr;73(4):737-758. doi: 10.1002/glia.24645. Epub 2024 Nov 28.
9
Targeted single cell expression profiling identifies integrators of sleep and metabolic state.靶向单细胞表达谱分析可识别睡眠与代谢状态的整合因子。
bioRxiv. 2024 Sep 27:2024.09.25.614841. doi: 10.1101/2024.09.25.614841.
10
Integrated electrophysiological and genomic profiles of single cells reveal spiking tumor cells in human glioma.单细胞的综合电生理和基因组图谱揭示了人类神经胶质瘤中的爆发性肿瘤细胞。
Cancer Cell. 2024 Oct 14;42(10):1713-1728.e6. doi: 10.1016/j.ccell.2024.08.009. Epub 2024 Sep 5.
J R Soc Interface. 2017 Mar;14(128). doi: 10.1098/rsif.2016.0999.
4
Molecular interrogation of hypothalamic organization reveals distinct dopamine neuronal subtypes.对下丘脑组织的分子研究揭示了不同的多巴胺神经元亚型。
Nat Neurosci. 2017 Feb;20(2):176-188. doi: 10.1038/nn.4462. Epub 2016 Dec 19.
5
A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor.使用Bioconductor进行单细胞RNA测序数据低级分析的逐步工作流程。
F1000Res. 2016 Aug 31;5:2122. doi: 10.12688/f1000research.9501.2. eCollection 2016.
6
Assessing characteristics of RNA amplification methods for single cell RNA sequencing.评估用于单细胞RNA测序的RNA扩增方法的特性。
BMC Genomics. 2016 Nov 24;17(1):966. doi: 10.1186/s12864-016-3300-3.
7
Molecular Diversity of Midbrain Development in Mouse, Human, and Stem Cells.小鼠、人类及干细胞中脑发育的分子多样性
Cell. 2016 Oct 6;167(2):566-580.e19. doi: 10.1016/j.cell.2016.09.027.
8
Adult mouse cortical cell taxonomy revealed by single cell transcriptomics.单细胞转录组学揭示成年小鼠皮质细胞分类学
Nat Neurosci. 2016 Feb;19(2):335-46. doi: 10.1038/nn.4216. Epub 2016 Jan 4.
9
Integration of electrophysiological recordings with single-cell RNA-seq data identifies neuronal subtypes.将电生理记录与单细胞RNA测序数据相结合可识别神经元亚型。
Nat Biotechnol. 2016 Feb;34(2):175-183. doi: 10.1038/nbt.3443. Epub 2015 Dec 21.
10
Electrophysiological, transcriptomic and morphologic profiling of single neurons using Patch-seq.使用Patch-seq对单个神经元进行电生理、转录组和形态学分析。
Nat Biotechnol. 2016 Feb;34(2):199-203. doi: 10.1038/nbt.3445. Epub 2015 Dec 21.