JoVE Logo
Faculty Resource Center

Sign In

Summary

Abstract

Introduction

Protocol

Representative Results

Discussion

Acknowledgements

Materials

References

Developmental Biology

Nuclei Isolation from Mouse Cardiac Progenitor Cells for Epigenome and Gene Expression Profiling at Single-Cell Resolution

Published: May 12th, 2023

DOI:

10.3791/65328

1Center for Cardiovascular Disease & Nutrition, U1263, Aix-Marseille University, 2Marseille Medical Genetics, U1251, Aix-Marseille University

Here, we present a protocol describing cell nuclei preparation. After microdissection and enzymatic dissociation of cardiac tissue into single cells, the progenitor cells were frozen, followed by isolation of pure viable cells, which were used for single-nucleus RNA sequencing and the single-nucleus assay for transposase-accessible chromatin with high-throughput sequencing analyses.

The developing heart is a complex structure containing various progenitor cells controlled by complex regulatory mechanisms. The examination of the gene expression and chromatin state of individual cells allows the identification of the cell type and state. Single-cell sequencing approaches have revealed a number of important characteristics of cardiac progenitor cell heterogeneity. However, these methods are generally restricted to fresh tissue, which limits studies with diverse experimental conditions, as the fresh tissue must be processed at once in the same run to reduce the technical variability. Therefore, easy and flexible procedures to produce data from methods such as single-nucleus RNA sequencing (snRNA-seq) and the single-nucleus assay for transposase-accessible chromatin with high-throughput sequencing (snATAC-seq) are needed in this area. Here, we present a protocol to rapidly isolate nuclei for subsequent single-nuclei dual-omics (combined snRNA-seq and snATAC-seq). This method allows the isolation of nuclei from frozen samples of cardiac progenitor cells and can be combined with platforms that use microfluidic chambers.

Among birth defects, congenital heart defects (CHDs) are the most common, occurring in about 1% of live births each year1,2. Genetic mutations are identified in only a minority of cases, implying that other causes, such as abnormalities in gene regulation, are involved in the etiology of CHD2,3. Cardiac development is a complex process of diverse and interacting cell types, making the identification of causal noncoding mutations and their effects on gene regulation challenging. Organogenesis of the heart begins with cellular progenitors that give rise ....

Log in or to access full content. Learn more about your institution’s access to JoVE content here

The animal procedure adopted in this study was approved by the animal ethics committees of the Aix-Marseille University (C2EA-14) and was carried out according to protocols approved by the appointed national ethical committee for animal experimentation (Ministère de l'Education Nationale, de l'Enseignement Supérieur et de la Recherche; Authorization Apafis N°33927-2021111715507212).

1. Setting up the timed mating prior to dissection

  1. To genera.......

Log in or to access full content. Learn more about your institution’s access to JoVE content here

Compared to the preparation of single-cell suspensions for single-cell approaches, the preparation of single-nuclei suspensions is much more challenging and requires a higher degree of resolution and processing. The key factor for successful combined snRNA-seq and snATAC-seq is a clean and intact nuclei suspension. The protocol for efficient nuclei isolation must be adapted to each tissue type and condition (fresh or frozen). Here, an optimized protocol is described for the isolation of nuclei from frozen mouse embryonic.......

Log in or to access full content. Learn more about your institution’s access to JoVE content here

The analysis of the cellular composition of the developing heart by combined snRNA-seq and snATAC-seq studies provides a deeper understanding of the origin of congenital heart disease26. Several research laboratories have studied the effects of cardiac tissue cryopreservation on snRNA-seq27. Conducting snRNA-seq and snATAC-seq using fresh micro-dissected tissue from mouse models of human disease can be logistically challenging when comparing different experimental condition.......

Log in or to access full content. Learn more about your institution’s access to JoVE content here

This research was supported by ERA-CVD-2019 and ANR-JCJC-2020 to SS. We thank the Genomics and Bioinformatics facility (GBiM) from the U 1251/Marseille Medical Genetics lab and the anonymous reviewers for providing valuable comments.

....

Log in or to access full content. Learn more about your institution’s access to JoVE content here

NameCompanyCatalog NumberComments
2100 Bioanalyzer InstrumentAgilentNo catalog number
5M Sodium chloride (NaCl)Sigma59222C-500ML 
BSA 10% SigmaA1595-50ML
Chromium Next GEM Chip J Single Cell Kit, 16 rxns10X Genomics1000230
Chromium Next GEM Single Cell Multiome ATAC + Gene Expression Reagent Bundle, 4 rxns (including Nuclei Buffer 20X)10X Genomics1000285
Countess cell counting chamber slidesInvitrogenC10283
Countess III FLThermofisherNo catalog number
Digitonin (5%)ThermofisherBN2006
DMSOSigmaD2650-5x5ML
DNA LoBind Tubes Eppendorf22431021
D-PBSThermofisher14190094Sterile and RNase-free
Dual Index Kit TT Set A 96 rxns10X Genomics1000215
Falcon 15 mL Conical Centrifuge Tubes Fisher Scientific 352096
Falcon 50 mL Conical Centrifuge Tubes Fisher Scientific 10788561
HI-FBSThermofisherA3840001Heat inactivated
High sensitivity DNA kitAgilent5067-4626
Igepal CA-630SigmaI8896-50ML
LIVE/DEAD Viability/Cytotoxicity KitThermofisherL3224
MACS Dead Cell Removal kit: Dead Cell Romoval MicroBeads, Binding Buffer 20XMiltenyi Biotec130-090-101
MACS SmartStrainers (30 µm)Miltenyi Biotec130-098-458
Magnesium chloride (MgCl2)SigmaM1028-100ML
Milieu McCoy 5A Thermofisher16600082
MS ColumnsMiltenyi Biotec130-042-201
NovaSeq 6000 S2IlluminaNo catalog number
Penicillin Streptomycin (Pen/Strep)Thermofisher15070063
PluriStrainer Mini 40µmPluriSelectV-PM15-2021-12
Rock inhibitorEnzo Life SciencesALX-270-333-M005
Single Index Kit N Set A, 96 rxn10X Genomics1000212
Standard 90mm Petri dish SterilinThermofisher101R20
Sterile double-distilled waterThermofisherR0582
Trizma Hydrochloride solution (HCl)SigmaT2194-100ML 
Trypan Blue stain (0.4%)InvitrogenT10282
Trypsin 0.05% - EDTA 1XThermofisher25300054
Tween20SigmaP9416-50ML 
Wide orifice filtered pipette tips 200 μlLabcon1152-965-008-9
ZEISS SteREO Discovery.V8ZEISSNo catalog number

  1. vander Bom, T., et al. The changing epidemiology of congenital heart disease. Nature Reviews. Cardiology. 8 (1), 50-60 (2011).
  2. Bouma, B. J., Mulder, B. J. Changing landscape of congenital heart disease. Circulation Research. 120 (6), 908-922 (2017).
  3. Postma, A. V., Bezzina, C. R., Christoffels, V. M. Genetics of congenital heart disease: The contribution of the noncoding regulatory genome. Journal of Human Genetics. 61 (1), 13-19 (2016).
  4. Buijtendijk, M. F. J., Barnett, P., vanden Hoff, M. J. B. Development of the human heart. American Journal of Medical Genetics. Part C, Seminars in Medical Genetics. 184 (1), 7-22 (2020).
  5. Sylva, M., vanden Hoff, M. J., Moorman, A. F. Development of the human heart. American Journal of Medical Genetics. Part A. 164 (6), 1347-1371 (2014).
  6. Gromova, T., Gehred, N. D., Vondriska, T. M. Single-cell transcriptomes in the heart: When every epigenome counts. Cardiovascular Research. 119 (1), 64-78 (2022).
  7. Tanay, A., Regev, A. Scaling single-cell genomics from phenomenology to mechanism. Nature. 541 (7637), 331-338 (2017).
  8. Schwartzman, O., Tanay, A. Single-cell epigenomics: Techniques and emerging applications. Nature Reviews. Genetics. 16 (12), 716-726 (2015).
  9. Macaulay, I. C., Ponting, C. P., Voet, T. Single-cell multiomics: Multiple measurements from single cells. Trends in Genetics. 33 (2), 155-168 (2017).
  10. Buenrostro, J. D., Wu, B., Chang, H. Y., Greenleaf, W. J. ATAC-seq: A method for assaying chromatin accessibility genome-wide. Current Protocols in Molecular Biology. 109, 1-9 (2015).
  11. Stefanovic, S., et al. Hox-dependent coordination of mouse cardiac progenitor cell patterning and differentiation. Elife. 9, e55124 (2020).
  12. Xu, W., et al. A plate-based single-cell ATAC-seq workflow for fast and robust profiling of chromatin accessibility. Nature Protocols. 16 (8), 4084-4107 (2021).
  13. Buenrostro, J. D., et al. Single-cell chromatin accessibility reveals principles of regulatory variation. Nature. 523 (7561), 486-490 (2015).
  14. Denisenko, E., et al. Systematic assessment of tissue dissociation and storage biases in single-cell and single-nucleus RNA-seq workflows. Genome Biology. 21 (1), 130 (2020).
  15. Safabakhsh, S., et al. Isolating nuclei from frozen human heart tissue for single-nucleus RNA sequencing. Current Protocols. 2 (7), e480 (2022).
  16. Pimpalwar, N., et al. Methods for isolation and transcriptional profiling of individual cells from the human heart. Heliyon. 6 (12), 05810 (2020).
  17. 10x Genomics. Chromium Next GEM Single Cell Multiome ATAC + Gene Expression Reagent Kits User Guide. 10x Genomics. , (2022).
  18. Jia, G., et al. Single cell RNA-seq and ATAC-seq analysis of cardiac progenitor cell transition states and lineage settlement. Nature Communications. 9 (1), 4877 (2018).
  19. Wang, L., et al. Single-cell dual-omics reveals the transcriptomic and epigenomic diversity of cardiac non-myocytes. Cardiovascular Research. 118 (6), 1548-1563 (2022).
  20. Wang, Z., et al. Cell-type-specific gene regulatory networks underlying murine neonatal heart regeneration at single-cell resolution. Cell Reports. 35 (8), 109211 (2021).
  21. Ameen, M., et al. Integrative single-cell analysis of cardiogenesis identifies developmental trajectories and non-coding mutations in congenital heart disease. Cell. 185 (26), 4937-4953 (2022).
  22. Gao, R., et al. Pioneering function of Isl1 in the epigenetic control of cardiomyocyte cell fate. Cell Research. 29 (6), 486-501 (2019).
  23. Manivannan, S., et al. Single-cell transcriptomic profiling unveils dysregulation of cardiac progenitor cells and cardiomyocytes in a mouse model of maternal hyperglycemia. Communications Biology. 5 (1), 820 (2022).
  24. Cao, Y., et al. Integrated analysis of multimodal single-cell data with structural similarity. Nucleic Acids Research. 50 (21), e121 (2022).
  25. What is CellRanger. 10x Genomics Available from: https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/what-is-cell-ranger (2023)
  26. Hill, M. C. Integrated multi-omic characterization of congenital heart disease. Nature. 608 (7921), 181-191 (2022).
  27. Chen, Z., Wei, L., Duru, F., Chen, L. Single-cell RNA sequencing: In-depth decoding of heart biology and cardiovascular diseases. Current Genomics. 21 (8), 585-601 (2020).
  28. Machado, L., Relaix, F., Mourikis, P. Stress relief: Emerging methods to mitigate dissociation-induced artefacts. Trends in Cell Biology. 31 (11), 888-897 (2021).
  29. Tabula Muris, C., et al. Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris. Nature. 562 (7727), 367-372 (2018).
  30. Machado, L., et al. Tissue damage induces a conserved stress response that initiates quiescent muscle stem cell activation. Cell Stem Cell. 28 (6), 1125-1135 (2021).
  31. Haghverdi, L., Lun, A. T. L., Morgan, M. D., Marioni, J. C. Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors. Nature Biotechnology. 36 (5), 421-427 (2018).
  32. Yang, Y., et al. SMNN: Batch effect correction for single-cell RNA-seq data via supervised mutual nearest neighbor detection. Briefings in Bioinformatics. 22 (3), 097 (2021).
  33. Stefanovic, S., Christoffels, V. M. GATA-dependent transcriptional and epigenetic control of cardiac lineage specification and differentiation. Cellular and Molecular Life Sciences. 72 (20), 3871-3881 (2015).
  34. Gunthel, M., Barnett, P., Christoffels, V. M. Development, proliferation, and growth of the mammalian heart. Molecular Therapy. 26 (7), 1599-1609 (2018).
  35. Stefanovic, S., Etchevers, H. C., Zaffran, S. Outflow tract formation-embryonic origins of conotruncal congenital heart disease. Journal of Cardiovascular Development and Disease. 8 (4), 42 (2021).
  36. Hao, Y., et al. Integrated analysis of multimodal single-cell data. Cell. 184 (13), 3573-3587 (2021).
  37. Bai, H., Lin, M., Meng, Y., Bai, H., Cai, S. An improved CUT&RUN method for regulation network reconstruction of low abundance transcription factor. Cellular Signalling. 96, 110361 (2022).

This article has been published

Video Coming Soon

JoVE Logo

Privacy

Terms of Use

Policies

Research

Education

ABOUT JoVE

Copyright © 2024 MyJoVE Corporation. All rights reserved