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

Nature Protocols volume 12, pages 2531–2553 (2017)Cite this article

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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.

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Figure 1: Schematic of Patch-seq technique.
Figure 2: Ideal patching approach for aspiration of cell contents.
Figure 3: Custom equipment.
Figure 4: cDNA yield using a physiological and a high-osmolarity internal solution.
Figure 5: Quality check of full-length single-cell cDNA libraries.
Figure 6: Bioanalyzer profile of a pooled cDNA library.
Figure 7: Initial Patch-seq data-processing steps.
Figure 8: Direct morphological recovery of Patch-seq cells.

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Acknowledgements

We thank P. Fahey, J. Reimer, Q. Deng, P. Johnsson, and B. Tasic for their helpful discussions and suggestions on improving the protocol and the manuscript. This study was supported by grants R01MH103108, DP1EY023176, P30EY002520, T32EY07001, and DP1OD008301 from the National Institutes of Health (NIH) to A.S.T.; grants from the Swedish Research Council and the Vallee Foundation to R.S.; the McKnight Scholar Award to A.S.T.; and the Arnold and Mabel Beckman Foundation Young Investigator Award to A.S.T. X.J. was supported by the BCM Faculty Start-up Fund. C.R.C. was supported by NIH grants F30MH095440, T32GM007330, and T32EB006350. This work was supported by the Intelligence Advanced Research Projects Activity (IARPA) via Department of Interior/Interior Business Center (DoI/IBC) contract no. D16PC00003. The U.S. government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright annotation thereon. Disclaimer: The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of IARPA, DoI/IBC, or the U.S. government.

Author information

Authors and Affiliations

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

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

  2. Ludwig Institute for Cancer Research, Stockholm, Sweden

    Rickard Sandberg

  3. Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden

    Rickard Sandberg

  4. Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston, Texas, USA

    Xiaolong Jiang

  5. Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, Texas, USA

    Andreas S Tolias

  6. Department of Electrical and Computer Engineering, Rice University, Houston, Texas, USA

    Andreas S Tolias

Authors
  1. Cathryn R Cadwell
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  7. Xiaolong Jiang
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Contributions

F.S., S.L., X.J., G.L., and S.S. performed electrophysiology. F.S., G.L., and X.J. performed immunohistochemistry. C.R.C. assisted with the electrophysiology experiments, generated cDNA libraries, performed the analysis, and drafted the manuscript. A.S.T., X.J., and R.S. supervised all experiments and analyses. All authors contributed to writing the manuscript.

Corresponding authors

Correspondence to Rickard Sandberg, Xiaolong Jiang or Andreas S Tolias.

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The authors declare no competing financial interests.

Supplementary information

Example of Patch-seq sample collection visualized using differential interference contrast (DIC).

The entire sample-collection process, including cell approach, pipette positioning, and aspiration of cell contents into the pipette, is shown under DIC. The simultaneous electrophysiological recording is shown in the bottom left of the screen. (MP4 28115 kb)

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Cadwell, C., Scala, F., Li, S. et al. Multimodal profiling of single-cell morphology, electrophysiology, and gene expression using Patch-seq. Nat Protoc 12, 2531–2553 (2017). https://doi.org/10.1038/nprot.2017.120

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