Summary

小鼠卵巢表观基因组和转录组的细胞特异性配对询问

Published: February 24, 2023
doi:

Summary

在该协议中,翻译核糖体亲和纯化(TRAP)方法和特定细胞类型(INTACT)方法中标记的细胞核的分离针对使用NuTRAP小鼠模型交叉到Cyp17a1-Cre小鼠系的细胞特异性卵巢转录组和表观基因组的配对询问进行了优化。

Abstract

评估细胞类型特异性表观基因组和转录组变化是了解卵巢衰老的关键。为此,使用新型转基因NuTRAP小鼠模型对翻译核糖体亲和纯化(TRAP)方法进行了优化,并分离了特定细胞类型中标记的细胞核(INTACT)方法,以便随后对细胞特异性卵巢转录组和表观基因组进行配对询问。NuTRAP等位基因的表达在絮状STOP盒的控制下,可以使用启动子特异性Cre系靶向特定的卵巢细胞类型。由于最近的研究表明卵巢基质细胞驱动过早衰老表型,NuTRAP表达系统使用Cyp17a1-Cre驱动程序靶向基质细胞。NuTRAP构建体的诱导对卵巢间质成纤维细胞具有特异性,并且从单个卵巢中获得足够的DNA和RNA进行测序研究。这里介绍的NuTRAP模型和方法可用于研究具有可用Cre系的任何卵巢细胞类型。

Introduction

卵巢是体细胞衰老的主要参与者1,具有来自特定细胞群的不同贡献。卵巢的细胞异质性使得难以解释来自大块全卵巢测定的分子结果。了解特定细胞群在卵巢衰老中的作用是确定导致老年妇女生育和健康下降的分子驱动因素的关键。传统上,特定卵巢细胞类型的多组学评估是通过激光显微切割2,单细胞方法3或细胞分选4等技术实现的。然而,显微切割可能昂贵且难以执行,细胞分选可以改变细胞表型谱5

一种评估卵巢细胞类型特异性表观基因组和转录组谱的新方法使用核标记和翻译核糖体亲和纯化(NuTRAP)小鼠模型。NuTRAP模型允许使用亲和纯化方法分离细胞类型特异性核酸,而无需进行细胞分选:翻译核糖体亲和纯化(TRAP)和分离特定细胞类型中标记的细胞核(INTACT)6。NuTRAP等位基因的表达在絮状STOP盒的控制下,可以使用启动子特异性Cre系靶向特定的卵巢细胞类型。通过用细胞类型特异性Cre系交叉NuTRAP小鼠,去除STOP盒导致核糖体复合物的eGFP标记和细胞核的生物素/mCherry标记以Cre依赖性方式6。然后可以使用TRAP和INTACT技术从感兴趣的细胞类型中分离mRNA和核DNA,并进行转录组学和表观基因组学分析。

NuTRAP模型已用于不同的组织,例如脂肪组织6组织7,8,9和视网膜10,以揭示细胞类型特异性表观基因组和转录组学变化这些变化可能无法在全组织匀浆中检测到。与传统的细胞分选技术相比,NuTRAP方法的优势包括:1)防止离体活化伪影8,2)对专用设备(即细胞分选仪)的需求最小化,以及3)细胞类型特异性分析的通量增加和成本降低。此外,从单个小鼠中分离细胞类型特异性DNA和RNA的能力允许配对分析,从而提高统计能力。由于最近的研究表明卵巢基质细胞与驱动过早衰老表型111213有关,我们使用Cyp17a1-Cre驱动程序将NuTRAP表达系统靶向基质细胞和膜细胞。在这里,我们证明了NuTRAP构建体的诱导对卵巢基质和膜细胞具有特异性,并且从单个卵巢中获得足够的DNA和RNA进行测序研究。这里介绍的NuTRAP模型和方法可用于研究具有任何可用Cre系的任何卵巢细胞类型。

为了生成细胞类型特异性卵巢NuTRAP小鼠系,核标记和翻译核糖体亲和纯化(NuTRAP)等位基因具有控制BirA,生物素连接酶识别肽(BLRP)标记的mCherry/mRANGAP1和eGFP/L10a表达的絮状STOP密码子。当与细胞类型特异性Cre系交叉时,NuTRAP盒的表达以Cre依赖性方式用生物素/mCherry和核糖体蛋白L10a与eGFP标记核蛋白mRANGAP1。这允许从特定细胞类型中分离细胞核和mRNA,而无需细胞分选。NuTRAP flox/flox 可以与与卵巢细胞类型相关的细胞类型特异性Cre配对以评估这一点。

Protocol

所有动物程序均由俄克拉荷马州医学研究基金会(OMRF)的机构动物护理和使用委员会批准。亲本小鼠从杰克逊实验室(缅因州巴尔港)购买,并在 HEPA 屏障环境中的 SPF 条件下在 OMRF 的 14 小时/10 小时光照/黑暗循环(上午 6:00 开灯)下繁殖和饲养。 注意:在本演示中,我们使用Cyp17iCre+/−(菌株#028547,杰克逊实验室)雄性与NuTRAP雌性(菌株#029899,杰克逊实验室)配…

Representative Results

TRAP和INTACT协议的原理图如图1所示。在这里,Cyp17-NuTRAP小鼠模型对卵巢基质/膜细胞的特异性通过免疫荧光成像和来自TRAP分离RNA的RNA-Seq得到证明。首先,对卵巢中的eGFP信号进行免疫荧光成像,并将eGFP信号定位到膜细胞和基质细胞。简而言之,用二甲苯和乙醇梯度对5μm切片进行脱蜡。为了获得更好的eGFP信号传导,使用山羊抗GFP一抗和Alexa 488驴抗山羊二抗对eGFP蛋白进行染色,…

Discussion

NuTRAP小鼠模型6是一种强大的转基因标记方法,用于配对询问来自特定细胞类型的转录组和表观基因组,这些细胞类型可以通过可用的Cre驱动程序适应任何细胞类型。在这里,我们证明了Cyp17-NuTRAP小鼠模型在靶向卵巢膜和基质细胞方面的特异性。Cyp17-NuTRAP模型可用于进一步阐明参与卵巢衰老,癌症和疾病的膜和基质细胞特异性表观遗传机制。

选择Cre驱动程序?…

Disclosures

The authors have nothing to disclose.

Acknowledgements

这项工作得到了美国国立卫生研究院(NIH)(R01AG070035,R01AG069742,T32AG052363),BrightFocus基金会(M2020207)和长老会健康基金会的资助。这项工作也得到了美国 (U.S) 的 MERIT 奖 I01BX003906 和共享设备评估计划 (ShEEP) 奖 ISIBX004797 的部分支持。退伍军人事务部,生物医学实验室研究与发展处。作者还要感谢临床基因组学中心(OMRF)和成像核心设施(OMRF)的帮助和仪器使用。

Materials

0.1 M Spermidine Sigma-Aldrich 05292-1ML-F
1 M MgCl2 Thermo Scientific AM9530G
10% NP-40 Thermo Scientific 85124
100 mg/mL Cycloheximide Sigma-Aldrich C4859-1ML
2-mercaptoethanol Sigma-Aldrich M3148
30 µm cell strainer  Miltenyi Biotec 130-098-458
All Prep DNA/RNA Mini Kit Qiagen 80204
anti-GFP antibody Abcam Ab290 For TRAP and IHC (Rabbit polyclonal to GFP)
Buffer RLT Qiagen 79216 RNA Lysis Buffer in protocol
cOmplete, mini, EDTA-free protease inhibitor tablet Roche 11836170001 For TRAP Homogenization Buffer
Cyp17iCre mouse model The Jackson Laboratory 28547 B6;SJL-Tg(Cyp17a1-icre)AJako/J
DynaMag-2 magnet Invitrogen 12321D
Genotyping Primers IDT Custom Generic Cre – Jackson Laboratory protocol 22392, Primers: oIMR1084, oIMR1085, oIMR7338, oIMR7339
         Cyp17iCre – Jackson Laboratory protocol 30847, Primers: 21218, 31704, 31705, 35663
         NuTRAP – Jackson Laboratory protocol 21509, Primers: 21306, 24493, 32625, 32626
Halt Protease Inhibitor cocktail (100X) Thermo Scientific 1861278 For NPB Buffer
M-280 Streptavidin Dynabeads  Invitrogen 11205D 2.8 µm bead diameter
MixMate Eppendorf 5353000529
Nuclei Isolation Kit: Nuclei EZ Prep Sigma-Aldrich Nuc101 Contains Nuclei Lysis Buffer and Nuclei Storage Buffer
1 M HEPES Gibco 15630-080
5 M NaCl Thermo Scientific AM9760G
2M KCl Thermo Scientific AM9640G
0.5 M EDTA Thermo Scientific AM9260G
0.5 M EGTA Fisher Scientific 50-255-956
NuTRAP mouse model The Jackson Laboratory 29899 B6;129S6-Gt(ROSA)26Sortm2(CAG-NuTRAP)Evdr/J
Pierce DTT No-Weigh Format Thermo Scientific A39255
Protein G Dynabeads ThermoFisher 10004D For TRAP
RNaseOUT Invitrogen 10777019
Sodium Heparin Fisher Scientific BP2425
Ultrapure 1M Tris-HCl, pH 7.5 Invitrogen 15567-027
VWR Tube Rotator Fisher Scientific NC9854190

References

  1. Broekmans, F. J., Soules, M. R., Fauser, B. C. Ovarian aging: Mechanisms and clinical consequences. Endocrine Reviews. 30 (5), 465-493 (2009).
  2. Cheng, L., et al. Laser-assisted microdissection in translational research: Theory, technical considerations, and future applications. Applied Immunohistochemistry & Molecular Morphology. 21 (1), 31-47 (2013).
  3. Morris, M. E., et al. A single-cell atlas of the cycling murine ovary. eLife. 11, 77239 (2022).
  4. Kendrick, H., et al. Transcriptome analysis of mammary epithelial subpopulations identifies novel determinants of lineage commitment and cell fate. BMC Genomics. 9, 591 (2008).
  5. Richardson, G. M., Lannigan, J., Macara, I. G. Does FACS perturb gene expression. Cytometry A. 87 (2), 166-175 (2015).
  6. Roh, H. C., et al. Simultaneous transcriptional and epigenomic profiling from specific cell types within heterogeneous tissues in vivo. Cell Reports. 18 (4), 1048-1061 (2017).
  7. Chucair-Elliott, A. J., et al. Inducible cell-specific mouse models for paired epigenetic and transcriptomic studies of microglia and astroglia. Communications Biology. 3 (1), 693 (2020).
  8. Ocanas, S. R., et al. Minimizing the ex vivo confounds of cell-isolation techniques on transcriptomic and translatomic profiles of purified microglia. eNeuro. 9 (2), (2022).
  9. Raus, A. M., Nelson, N. E., Fuller, T. D., Ivy, A. S. 34;SIT" with Emx1-NuTRAP mice: Simultaneous INTACT and TRAP for paired transcriptomic and epigenetic sequencing. Current Protocols. 2 (10), 570 (2022).
  10. Chucair-Elliott, A. J., et al. Translatomic response of retinal Muller glia to acute and chronic stress. Neurobiology Disease. 175, 105931 (2022).
  11. Amargant, F., et al. Ovarian stiffness increases with age in the mammalian ovary and depends on collagen and hyaluronan matrices. Aging Cell. 19 (11), 13259 (2020).
  12. Briley, S. M., et al. Reproductive age-associated fibrosis in the stroma of the mammalian ovary. Reproduction. 152 (3), 245-260 (2016).
  13. Umehara, T., et al. Female reproductive life span is extended by targeted removal of fibrotic collagen from the mouse ovary. Science Advances. 8 (24), (2022).
  14. Lopez-Sanchez, N., Frade, J. M. Cell cycle analysis in the vertebrate brain using immunolabeled fresh cell nuclei. Bio-Protocol. 3 (22), 973 (2013).
  15. Saccon, T. D., et al. Primordial follicle reserve, DNA damage and macrophage infiltration in the ovaries of the long-living Ames dwarf mice. Experimental Gerontology. 132, 110851 (2020).
  16. Kinnear, H. M., et al. The ovarian stroma as a new frontier. Reproduction. 160 (3), 25-39 (2020).
  17. Ajayi, A. F., Akhigbe, R. E. Staging of the estrous cycle and induction of estrus in experimental rodents: an update. Fertility Research and Practice. 6, 5 (2020).
  18. Tighe, R. M., et al. Improving the quality and reproducibility of flow cytometry in the lung. An official American Thoracic Society workshop report. American Journal of Respiratory Cell and Molecular Biology. 61 (2), 150-161 (2019).
  19. Zhang, X., et al. Comparative analysis of droplet-based ultra-high-throughput single-cell RNA-Seq systems. Molecular Cell. 73 (1), 130-142 (2019).
  20. Zheng, G. X., et al. Massively parallel digital transcriptional profiling of single cells. Nature Communications. 8, 14049 (2017).
  21. Klein, A. M., et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell. 161 (5), 1187-1201 (2015).
  22. Macosko, E. Z., et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell. 161 (5), 1202-1214 (2015).
  23. Prakadan, S. M., Shalek, A. K., Weitz, D. A. Scaling by shrinking: Empowering single-cell ‘omics’ with microfluidic devices. Nature Reviews Genetics. 18 (6), 345-361 (2017).
  24. Wang, Q., et al. CoBATCH for high-throughput single-cell epigenomic profiling. Molecular Cell. 76 (1), 206-216 (2019).
  25. Luo, C., et al. Robust single-cell DNA methylome profiling with snmC-seq2. Nature Communications. 9, 3824 (2018).
  26. Liu, H., et al. DNA methylation atlas of the mouse brain at single-cell resolution. Nature. 598 (7879), 120-128 (2021).
  27. Yamawaki, T. M., et al. Systematic comparison of high-throughput single-cell RNA-seq methods for immune cell profiling. BMC Genomics. 22 (1), 66 (2021).
  28. Hashimshony, T., et al. CEL-Seq2: Sensitive highly-multiplexed single-cell RNA-Seq. Genome Biology. 17, 77 (2016).
  29. Natarajan, K. N. Single-cell tagged reverse transcription (STRT-Seq). Methods in Molecular Biology. 1979, 133-153 (2019).
  30. 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).
  31. Aldridge, S., Teichmann, S. A. Single cell transcriptomics comes of age. Nature Communications. 11, 4307 (2020).
  32. Clark, S. J., Lee, H. J., Smallwood, S. A., Kelsey, G., Reik, W. Single-cell epigenomics: Powerful new methods for understanding gene regulation and cell identity. Genome Biology. 17, 72 (2016).
  33. Christensson, E., Lewan, L. The use of spermidine for the isolation of nuclei from mouse liver. Studies of purity and yield during different physiological conditions. Zeitschrift für Naturforschung. Section C, Biosciences. 29 (5-6), 267-271 (1974).
  34. Levine, M. E., et al. Menopause accelerates biological aging. Proceedings of the National Academy of Sciences of the United States of America. 113 (33), 9327-9332 (2016).
  35. Ossewaarde, M. E., et al. Age at menopause, cause-specific mortality and total life expectancy. Epidemiology. 16 (4), 556-562 (2005).
  36. Wellons, M., Ouyang, P., Schreiner, P. J., Herrington, D. M., Vaidya, D. Early menopause predicts future coronary heart disease and stroke: the Multi-Ethnic Study of Atherosclerosis. Menopause. 19 (10), 1081-1087 (2012).
  37. Camaioni, A., et al. The process of ovarian aging: It is not just about oocytes and granulosa cells. Journal of Assisted Reproduction and Genetics. 39 (4), 783-792 (2022).
check_url/cn/64765?article_type=t

Play Video

Cite This Article
Ocañas, S. R., Isola, J. V. V., Saccon, T. D., Pham, K. D., Chucair-Elliott, A. J., Schneider, A., Freeman, W. M., Stout, M. B. Cell-Specific Paired Interrogation of the Mouse Ovarian Epigenome and Transcriptome. J. Vis. Exp. (192), e64765, doi:10.3791/64765 (2023).

View Video