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Abstract
Introduction
Protocol
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Biologie du développement

从小鼠心脏祖细胞中分离细胞核，用于单细胞分辨率的表观基因组和基因表达谱分析

Published: May 12, 2023
doi:
10.3791/65328
, , , , ,
1Center for Cardiovascular Disease & Nutrition, U1263,Aix-Marseille University, 2Marseille Medical Genetics, U1251,Aix-Marseille University

Summary

在这里，我们提出了一个描述细胞核制备的协议。在将心脏组织进行显微切割和酶解离成单细胞后，冷冻祖细胞，然后分离纯活细胞，用于单核RNA测序和单核测定，用于转座酶可接近染色质和高通量测序分析。

Abstract

发育中的心脏是一个复杂的结构，包含由复杂调节机制控制的各种祖细胞。检查单个细胞的基因表达和染色质状态可以识别细胞类型和状态。单细胞测序方法揭示了心脏祖细胞异质性的许多重要特征。然而，这些方法通常仅限于新鲜组织，这限制了具有不同实验条件的研究，因为必须在同一次运行中立即处理新鲜组织以减少技术可变性。因此，该领域需要简单灵活的程序来生成来自单核RNA测序（snRNA-seq）和转座酶可接近染色质的高通量测序（snATAC-seq）等方法的数据。在这里，我们提出了一种快速分离细胞核的协议，用于随后的单核双组学（组合snRNA-seq和snATAC-seq）。该方法允许从心脏祖细胞的冷冻样品中分离细胞核，并且可以与使用微流体室的平台结合使用。

Introduction

在出生缺陷中，先天性心脏缺陷（CHD）是最常见的，每年约有1%的活产婴儿发生1，2。仅在少数病例中发现基因突变，这意味着其他原因，例如基因调节异常，与冠心病2，3的病因有关。心脏发育是多种多样和相互作用的细胞类型的复杂过程，使得鉴定因果非编码突变及其对基因调控的影响具有挑战性。心脏的器官发生始于产生不同亚型心脏细胞的细胞祖细胞，包括心肌细胞、成纤维细胞、心外细胞和心内膜细胞4，5。单细胞基因组学正在成为研究心脏发育和评估细胞异质性对健康和疾病的影响的关键方法6。用于同时测量不同参数的多组学方法的发展和计算管道的扩展促进了正常和患病心脏中细胞类型和亚型的发现6。本文描述了一种可靠的单核分离方案，用于从小鼠胚胎获得的冷冻心脏祖细胞，该方案与下游snRNA-seq和snATAC-seq（以及snRNA-seq和snATAC-seq组合）兼容7，8，9。

ATAC-seq是一种稳健的方法，可以鉴定调节性开放染色质区域和定位核小体10，11。该信息用于得出有关转录因子的位置、身份和活性的结论。因此，可以分析染色质因子（包括重塑剂）的活性以及RNA聚合酶的转录活性，因为该方法对于测量染色质结构1，2的定量变化具有高度敏感性。因此，ATAC-seq提供了一种稳健而公正的方法来揭示控制特定细胞类型中转录调控的机制。ATAC-seq协议也已经过验证，可以测量单细胞中的染色质可及性，揭示细胞群中染色质结构的变异性10，12，13。

尽管近年来在单细胞领域取得了显着进展，但主要困难是处理进行这些实验所需的新鲜样品14。为了规避这一困难，已经进行了各种测试，目的是用冷冻的心脏组织或细胞进行分析，例如snRNA-seq和snATAC-seq15，16。

几个平台已被用于分析单细胞基因组学数据17。广泛使用的单细胞基因表达和ATAC分析平台是用于多个微流体液滴封装的平台17。由于这些平台使用微流体室，碎屑或聚集体会堵塞系统，导致数据不可用。因此，单细胞研究的成功取决于单个细胞/细胞核的准确分离。

这里介绍的方案使用与最近使用snRNA-seq和snATAC-seq的研究类似的方法来了解先天性心脏缺陷18，19，20，21，22，23。该过程利用新鲜显微解剖的心脏组织的酶解离，然后冷冻保存小鼠心脏祖细胞。解冻后，活细胞被纯化并处理以进行核分离。在这项工作中，该协议成功地用于从小鼠心脏祖细胞的相同核制剂中获得snRNA-seq和snATAC-seq数据。

Protocol

本研究中采用的动物程序已获得艾克斯-马赛大学动物伦理委员会（C2EA-14）的批准，并根据指定的国家动物实验伦理委员会（国家教育部，高等和研究部;授权阿帕菲斯号33927-2021111715507212）。 1. 在解剖前设置定时交配 为了产生小鼠胚胎，在心脏区域分离前9.5天在成年小鼠之间进行定时交配。在该过程中，使用2-6个月的野生型C57BL / 6J小鼠，并在夜间进行定?…

Representative Results

与用于单细胞方法的单细胞悬液制备相比，单核悬浮液的制备更具挑战性，并且需要更高的分辨率和处理。成功结合snRNA-seq和snATAC-seq的关键因素是干净且完整的细胞核悬浮液。高效细胞核分离的方案必须适应每种组织类型和条件（新鲜或冷冻）。在这里，描述了一种优化的方案，用于从冷冻小鼠胚胎心脏细胞中分离细胞核。从胚胎心脏区域解剖和心脏细胞解离到细胞核分离的所有步骤总结在 <stro…

Discussion

通过结合snRNA-seq和snATAC-seq研究对发育中心脏的细胞组成的分析，可以更深入地了解先天性心脏病的起源26。一些研究实验室研究了心脏组织冷冻保存对snRNA-seq27的影响。在比较不同的实验条件时，使用来自人类疾病小鼠模型的新鲜微解剖组织进行snRNA-seq和snATAC-seq在逻辑上可能具有挑战性。对于给定的开发阶段，一个困难是必须在同一次运行中处理对照组和实验?…

Divulgations

The authors have nothing to disclose.

Acknowledgements

这项研究得到了 ERA-CVD-2019 和 ANR-JCJC-2020 对 SS 的支持。我们感谢U 1251/马赛医学遗传学实验室的基因组学和生物信息学设施（GBiM）以及匿名审稿人提供的宝贵意见。

Materials

2100 Bioanalyzer Instrument Agilent No catalog number
5M Sodium chloride (NaCl) Sigma 59222C-500ML 
BSA 10%  Sigma A1595-50ML
Chromium Next GEM Chip J Single Cell Kit, 16 rxns 10X Genomics 1000230
Chromium Next GEM Single Cell Multiome ATAC + Gene Expression Reagent Bundle, 4 rxns (including Nuclei Buffer 20X) 10X Genomics 1000285
Countess cell counting chamber slides Invitrogen C10283
Countess III FL Thermofisher No catalog number
Digitonin (5%) Thermofisher BN2006
DMSO Sigma D2650-5x5ML
DNA LoBind Tubes  Eppendorf 22431021
D-PBS Thermofisher 14190094 Sterile and RNase-free
Dual Index Kit TT Set A 96 rxns 10X Genomics 1000215
Falcon 15 mL Conical Centrifuge Tubes  Fisher Scientific  352096
Falcon 50 mL Conical Centrifuge Tubes  Fisher Scientific  10788561
HI-FBS Thermofisher A3840001 Heat inactivated
High sensitivity DNA kit Agilent 5067-4626
Igepal CA-630 Sigma I8896-50ML
LIVE/DEAD Viability/Cytotoxicity Kit Thermofisher L3224
MACS Dead Cell Removal kit: Dead Cell Romoval MicroBeads, Binding Buffer 20X Miltenyi Biotec 130-090-101
MACS SmartStrainers (30 µm) Miltenyi Biotec 130-098-458
Magnesium chloride (MgCl2) Sigma M1028-100ML
Milieu McCoy 5A  Thermofisher 16600082
MS Columns Miltenyi Biotec 130-042-201
NovaSeq 6000 S2 Illumina No catalog number
Penicillin Streptomycin (Pen/Strep) Thermofisher 15070063
PluriStrainer Mini 40µm PluriSelect V-PM15-2021-12
Rock inhibitor Enzo Life Sciences ALX-270-333-M005
Single Index Kit N Set A, 96 rxn 10X Genomics 1000212
Standard 90mm Petri dish Sterilin Thermofisher 101R20
Sterile double-distilled water Thermofisher R0582
Trizma Hydrochloride solution (HCl) Sigma T2194-100ML 
Trypan Blue stain (0.4%) Invitrogen T10282
Trypsin 0.05% – EDTA 1X Thermofisher 25300054
Tween20 Sigma P9416-50ML 
Wide orifice filtered pipette tips 200 μl Labcon 1152-965-008-9
ZEISS SteREO Discovery.V8 ZEISS No catalog number
DOWNLOAD MATERIALS LIST

References

  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).

Tags

Keywords: Nuclei IsolationMouse Cardiac Progenitor CellsEpigenome ProfilingGene Expression ProfilingSingle-cell ResolutionSingle Nuclei RNA-seqSingle Nuclei ATAC-seqCellular HeterogeneityCongenital Heart DefectsHeart DevelopmentFrozen SamplesMolecular Mechanisms
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Ibrahim, S., Robert, C., Humbert, C., Ferreira, C., Collod, G., Stefanovic, S. Nuclei Isolation from Mouse Cardiac Progenitor Cells for Epigenome and Gene Expression Profiling at Single-Cell Resolution. J. Vis. Exp. (195), e65328, doi:10.3791/65328 (2023).
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