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Abstract

Introduction

Protocol

Representative Results

Discussion

Acknowledgements

Materials

References

Neuroscience

Isolation of Adult Spinal Cord Nuclei for Massively Parallel Single-nucleus RNA Sequencing

Published: October 12th, 2018

DOI:

10.3791/58413

1Spinal Circuits and Plasticity Unit, National Institute of Neurological Disorders and Stroke, 2Bioinformatics Section, Information Technology Program, National Institute of Neurological Disorders and Stroke, 3Laboratory of Cochlear Development, National Institute on Deafness and Other Communication Disorders, 4Single Cell Analysis Facility, Frederick National Laboratory

Here, we present a protocol to rapidly isolate high-quality nuclei from the fresh or frozen tissue for downstream massively parallel RNA sequencing. We include detergent-mechanical and hypotonic-mechanical tissue disruption and cell lysis options, both of which can be used for isolation of nuclei.

Probing an individual cell's gene expression enables the identification of cell type and cell state. Single-cell RNA sequencing has emerged as a powerful tool for studying transcriptional profiles of cells, particularly in heterogeneous tissues such as the central nervous system. However, dissociation methods required for single cell sequencing can lead to experimental changes in the gene expression and cell death. Furthermore, these methods are generally restricted to fresh tissue, thus limiting studies on archival and bio-bank material. Single nucleus RNA sequencing (snRNA-Seq) is an appealing alternative for transcriptional studies, given that it accurately identifies cell types, permits the study of tissue that is frozen or difficult to dissociate, and reduces dissociation-induced transcription. Here, we present a high-throughput protocol for rapid isolation of nuclei for downstream snRNA-Seq. This method enables isolation of nuclei from fresh or frozen spinal cord samples and can be combined with two massively parallel droplet encapsulation platforms.

The nervous system is comprised of heterogenous groups of cells that display a diverse array of morphological, biochemical, and electrophysiological properties. While the bulk RNA sequencing has been useful for determining tissue-wide changes in the gene expression under different conditions, it precludes the detection of transcriptional changes at the single-cell level. Recent advances in the single-cell transcriptional analysis have enabled the classification of heterogenous cells into functional groups based on their molecular repertoire and can even be leveraged to detect sets of neurons that had been recently active.1,

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All animal work was performed in accordance with a protocol approved by the National Institute of Neurological Disorders and Stroke Animal Care and Use Committee. Balanced samples of male and female ICR/CD-1 wild-type mice, between 8 and 12 weeks old, were used for all experiments. Mice should be handled in accordance with local Institutional Animal Care and Use Committee guidelines.

1. Preparation of Materials and Buffers

  1. Prepare all buffers the day of use and pre-chill on ice (se.......

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Here, we performed isolation of nuclei from the adult mouse lumbar spinal cord for downstream massively parallel RNA sequencing. The protocol involved three main components: tissue disruption and cellular lysis, homogenization, and sucrose density centrifugation (Figure 1). Within seconds, the detergent-mechanical lysis yielded a crude nuclei preparation with a large number of nuclei as well as cellular and tissue debris (Figure 2A

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The ultimate goal of this protocol is to isolate nuclei containing high-quality RNA for downstream transcriptional analysis. We adapted snRNA-Seq methods in order to profile all of the cell types in the spinal cord. Initially, we found that typical cell dissociation methods were ineffective for single cell RNA sequencing, as spinal cord neurons are particularly vulnerable to cell death. Furthermore, cell dissociation methods induce expression of various activity- and stress-response genes by up to several hundred-fold.

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This work was supported by the intramural program of NINDS (1 ZIA NS003153 02) and NIDCD (1 ZIA DC000059 18). We thank L. Li and C.I. Dobrott for their technical support and helpful discussions, and C. Kathe for reviewing the manuscript.

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Name Company Catalog Number Comments
Sucrose Invitrogen 15503-022
1 M HEPES (pH = 8.0) Gibco 15630-080
CaCl2 Sigma Aldrich C1016-100G
MgAc Sigma Aldrich M1028-10X1ML
0.5 M EDTA (pH = 8.0) Corning MT-46034CI
Dithiothreitol (DTT) Sigma Aldrich 10197777001 Add DTT just prior to use
Triton-X Sigma Aldrich T8787
Nuclease-free water Crystalgen 221-238-10
1 M Tris-HCl (pH = 7.4) Sigma Aldrich T2194
5 M NaCl Sigma Aldrich 59222C
1 M MgCl2 Sigma Aldrich M1028
Nonidet P40 Sigma Aldrich 74385
Hibernate-A Gibco A12475-01
Glutamax (100X) Gibco 35050-061
B27 (50X) Gibco 17504-044
1X PBS Crystalgen 221-133-10
0.04% BSA New England Biolabs B9000S
0.2 U/μL RNAse Inhibitor Lucigen 30281-1
Oak Ridge Centrifuge Tube Thermo Scientific 3118-0050
Disposable Cotton-Plugged Borosilicate-Glass Pasteur Pipets Fisher Scientific 13-678-8B
Glass Tissue Dounce (2 ml) Kimble 885303-002
Glass large clearance pestle Kimble 885301-0002
Glass small clearance pestle Kimble 885302-002
T 10 Basic Ultra Turrax Homogenizer IKA 3737001
Dispersing tool (S 10 N – 5G) IKA 3304000
Trypan Blue Stain (0.4%) Thermo Fisher Scientific T10282
40 μm cell strainer Falcon 352340
MACS SmartStrainers, 30 μm Miltenyi Biotec 130-098-458
Conical tubes Denville Scientific 1000799
Sorvall Legend XTR Centrifuge Thermo Fisher Scientific 75004505
Fiberlite F15-6 x 100y Fixed-Angle Rotor Thermo Fisher Scientific 75003698
Sterological Pipettes: 5 ml, 10 ml Denville Scientific P7127
Hemocytometer Daigger Scientific EF16034F
Chemgenes Barcoding Beads Chemgenes Macosko-2011-10
RNaseZap RNase Decontamination Solution Invitrogen AM9780
Falcon Test Tube with Cell Strainer Cap (35 μm) Corning 352235
MoFlo Astrios Cell Sorter Beckman Coulter B25982
Chromium i7 Multiplex Kit, 96 rxns 10X Genomics 120262
Chromium Single Cell 3’ Library and Gel Bead Kit v2, 4 rxns 10X Genomics 120267
Chromium Single Cell A Chip Kit, 16 rxns 10X Genomics
Tissue Culture Dish (60 x 15 mm) Corning 353002

  1. Hrvatin, S., et al. Single-cell analysis of experience-dependent transcriptomic states in the mouse visual cortex. Nature Neuroscience. 21 (1), 120-129 (2018).
  2. Hu, P., et al. Dissecting Cell-Type Composition and Activity-Dependent Transcriptional State in Mammalian Brains by Massively Parallel Single-Nucleus RNA-Seq. Molecular Cell. 68 (5), 1006-1015 (2017).
  3. Wu, Y. E., Pan, L., Zuo, Y., Li, X., Hong, W. Detecting Activated Cell Populations Using Single-Cell RNA-Seq. Neuron. 96 (2), 313-329 (2017).
  4. Sathyamurthy, A., et al. Massively Parallel Single Nucleus Transcriptional Profiling Defines Spinal Cord Neurons and Their Activity during Behavior. Cell Reports. 22 (8), 2216-2225 (2018).
  5. Tang, F., et al. mRNA-Seq whole-transcriptome analysis of a single cell. Nature Methods. 6 (5), 377-382 (2009).
  6. Campbell, J. N., et al. A molecular census of arcuate hypothalamus and median eminence cell types. Nature Neuroscience. 20 (3), 484-496 (2017).
  7. Macosko, E. Z., et al. Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets. Cell. 161 (5), 1202-1214 (2015).
  8. Chen, R., Wu, X., Jiang, L., Zhang, Y. Single-Cell RNA-Seq Reveals Hypothalamic Cell Diversity. Cell Reports. 18 (13), 3227-3241 (2017).
  9. Jaitin, D. A., et al. Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Science. 343 (6172), 776-779 (2014).
  10. Li, C. L., et al. Somatosensory neuron types identified by high-coverage single-cell RNA-sequencing and functional heterogeneity. Cell Research. 26 (8), 967 (2016).
  11. Shin, J., et al. Single-Cell RNA-Seq with Waterfall Reveals Molecular Cascades underlying Adult Neurogenesis. Cell Stem Cell. 17 (3), 360-372 (2015).
  12. Tasic, B., et al. Adult mouse cortical cell taxonomy revealed by single cell transcriptomics. Nature Neuroscience. 19 (2), 335-346 (2016).
  13. Usoskin, D., et al. Unbiased classification of sensory neuron types by large-scale single-cell RNA sequencing. Nature Neuroscience. 18 (1), 145-153 (2015).
  14. Villani, A. C., et al. Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors. Science. 356 (6335), (2017).
  15. Zeisel, A., et al. Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science. 347 (6226), 1138-1142 (2015).
  16. Lacar, B., et al. Nuclear RNA-seq of single neurons reveals molecular signatures of activation. Nature Communications. 7, 11022 (2016).
  17. Lake, B. B., et al. Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain. Science. 352 (6293), 1586-1590 (2016).
  18. Grindberg, R. V., et al. RNA-sequencing from single nuclei. Proceedings of the National Academy of Sciences of the United States of America. 110 (49), 19802-19807 (2013).
  19. Krishnaswami, S. R., et al. Using single nuclei for RNA-seq to capture the transcriptome of postmortem neurons. Nature Protocols. 11 (3), 499-524 (2016).
  20. Matevossian, A., Akbarian, S. Neuronal nuclei isolation from human postmortem brain tissue. Journal of Visualized Experiments. (20), (2008).
  21. Bergmann, O., Jovinge, S. Isolation of cardiomyocyte nuclei from post-mortem tissue. Journal of Visualized Experiments. (65), (2012).
  22. Nohara, K., Chen, Z., Yoo, S. H. A Filtration-based Method of Preparing High-quality Nuclei from Cross-linked Skeletal Muscle for Chromatin Immunoprecipitation. Journal of Visualized Experiments. (125), (2017).
  23. Halder, R., et al. DNA methylation changes in plasticity genes accompany the formation and maintenance of memory. Nature Neuroscience. 19 (1), 102-110 (2016).
  24. Habib, N., et al. Massively parallel single-nucleus RNA-seq with DroNc-seq. Nature Methods. 14 (10), 955-958 (2017).
  25. . Sample Preparation Demonstrated Protocols: Isolation of Nuclei for Single Cell RNA Sequencing Available from: https://support.10xgenomics.com/single-cell-gene-expression/sample-prep/doc/demonstrated-protocol-isolation-of-nuclei-for-single-cell-rna-sequencing (2018)
  26. 10X Genomics. . Single Cell 3' Reagent Kits v2 User Guide. , (2018).
  27. Fu, Y., Rusznak, Z., Herculano-Houzel, S., Watson, C., Paxinos, G. Cellular composition characterizing postnatal development and maturation of the mouse brain and spinal cord. Brain Structure and Function. 218 (5), 1337-1354 (2013).
  28. Lake, B. B., et al. A comparative strategy for single-nucleus and single-cell transcriptomes confirms accuracy in predicted cell-type expression from nuclear RNA. Scientific Reports. 7 (1), 6031 (2017).
  29. Bakken, T. E. Equivalent high-resolution identification of neuronal cell types with single-nucleus and single-cell RNA-sequencing. bioRxiv. , (2018).
  30. Habib, N., et al. Div-Seq: Single-nucleus RNA-Seq reveals dynamics of rare adult newborn neurons. Science. 353 (6302), 925-928 (2016).

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