Summary

Clonal Analysis of the Neonatal Mouse Heart using Nearest Neighbor Modeling

Published: August 22, 2020
doi:

Summary

Presented here is a protocol for using multicolor lineage tracing and nearest-neighbor modeling to identify clonally derived cardiomyocytes during growth and regeneration in mice. This approach is objective, works across different labeling conditions, and can be adapted to incorporate a variety of image analysis pipelines.

Abstract

By replacing lost or dysfunctional myocardium, tissue regeneration is a promising approach to treat heart failure. However, the challenge of detecting bona fide heart regeneration limits the validation of potential regenerative factors. One method to detect new cardiomyocytes is multicolor lineage tracing with clonal analysis. Clonal analysis experiments can be difficult to undertake, because labeling conditions that are too sparse lack sensitivity for rare events such as cardiomyocyte proliferation, and diffuse labeling limits the ability to resolve clones. Presented here is a protocol to undertake clonal analysis of the neonatal mouse heart by using statistical modeling of nearest neighbor distributions to resolve cardiomyocyte clones. This approach enables resolution of clones over a range of labeling conditions and provides a robust analytical approach for quantifying cardiomyocyte proliferation and regeneration. This protocol can be adapted to other tissues and can be broadly used to study tissue regeneration.

Introduction

A histologic hallmark of heart failure is the loss of cardiomyocytes (CMs), either following injury, senescence, or apoptosis1. Replenishing lost or dysfunctional myocardium through tissue regeneration represents a potential therapeutic strategy for curing patients with heart failure. Over the past several decades, seminal advances in developmental and regenerative biology have unearthed a limited ability for the mammalian heart to replenish lost CMs2,3,4,5. This exciting work has raised the possibility that innate growth mechanisms can be deployed for regeneration. Because innate regenerative responses are functionally absent in the adult mammalian heart, methods to improve the robustness of endogenous repair are needed for therapeutic heart regeneration to be realized.

The mechanisms for innate heart regeneration appear to be conserved across species. Following injury, pre-existing CMs proliferate to generate new CMs in zebrafish6,7, newts8,9, mice4,10, rats11, and pigs12,13. Accordingly, many groups are seeking to identify mitogens capable of promoting cardiomyogenesis. However, such work is challenging. Not only is the task of getting adult mammalian CMs to proliferate daunting but being able to identify rare proliferative events is difficult1,14. The challenge of identifying rare cycling CMs is compounded by the tendency of adult mammalian CMs to preferentially undergo endomitosis. For example, after injury to the mouse heart, almost 25% of CMs in the border zone re-enter the cell cycle, but only 3.2% of CMs divide4. Because most cycling CMs duplicate their genome but fail to undergo cytokinesis, simply assaying for an increase in the numbers of cycling CMs is ambiguous to bona fide cardiomyogenesis. Thus, assays for nucleoside incorporation by CMs or for the presence of proliferative markers on CMs may not entirely indicate regeneration. As more candidate factors for heart regeneration emerge, assays to better identify CM hyperplasia are needed.

Clonal analysis by lineage tracing is a valuable approach to assay for cardiomyogenesis because it allows for the direct visualization of cells and their progeny. Traditional approaches for clonal analysis involve rare labeling of single cells with a reporter gene. However, single-color lineage tracing of rare cells may be of limited value for infrequent events such as CM proliferation because the chances of labeling a proliferating CM are low15. Alternatively, multicolor lineage tracing can increase the sensitivity for clonal analysis16. Briefly, individual cells are genetically labeled with one of several fluorescent proteins at random, such that proliferating cells will generate homogeneously colored clusters of cells that can be resolved from neighboring fluorescent cells. This method has been used to trace growth across a variety of organs, and has been more recently applied to studies of mammalian heart regeneration17,18. While multicolor lineage tracing can detect clonal expansion of CMs in embryonic and neonatal stages, innate regenerative responses are not easily detected in the adult mouse heart after cardiac injury17,19. One approach to enhance the sensitivity of multicolor lineage tracing would be to increase the level of labeling and increase the probability for visualizing rare events. However, wider labeling comes at the cost of not being able to distinguish similarly labeled cells as rising from a common ancestor versus cells that were independently labeled with the same fluorophore. Presented here is a protocol that uses nearest-neighbor modeling to identify clonally related CMs in the neonatal mouse heart. This method is unbiased, quantitative, and works over a range of labeling conditions.

Protocol

All procedures for handling mice, performing survival surgeries, and for harvesting hearts require approval by a local institutional animal use committee. 1. Mice for clonal analysis of CMs Cross Myh6-MerCreMer mice20 with Gt(ROSA)26Sortm1(CAG-EGFP,-mCerulean,-mOrange,-mCherry)Ilw mice21 to generate Myh6-MerCreMer; R26R-Rainbow bitransgenic mic…

Representative Results

Following the protocol for neonatal cryoinjury should yield P21 hearts with and without injury. Cryoinjured hearts have a well-circumscribed injury while the surface of sham hearts is smooth and homogeneous. In cryoinjured hearts, the area of injury should be consistent from heart to heart. After microscopy, images similar to Figure 1 should be obtained. Note that the image resolution allows for identification of individual CMs and imaging conditions allow for each fluorophore to be resolved…

Discussion

Multicolor lineage tracing is a powerful approach to identify patterns of organ growth with single cell resolution. However, a major limitation to multicolor lineage tracing is the need for sparse labeling of cells, which can reduce the sensitivity for identifying rare events. For organs like the heart with notoriously low levels of parenchymal cell turnover, this can lead to underestimates of growth responses. Presented here is a step-by-step protocol for performing clonal analysis of CM expansion during growth and rege…

Divulgations

The authors have nothing to disclose.

Acknowledgements

This work was funded by an R03 HL144812 (RK), a Duke University Strong Start Physician Scientist Award (RK), a Mandel Foundation Seed Grant (RK), and a T32 HL007101 Training grant (DCC). We would additionally like to acknowledge Evelyn McCullough for assistance with mouse husbandry and Dr. Douglas Marchuk and Matthew Detter for helpful comments and discussion. Finally, we would like to thank Purushothama Rao Tata for kindly providing R26R-Rainbow mice.

Materials

#1.5 glass coverslip FisherScientific 12-544E
6-O prolene Ethicon 8706H
Anti-fade mounting medium FisherScientific 00-4958-02
CO2 inhalational chamber
Cold pack
Cryomolds VWR 15160-215
Cryoprobe World Precision Instruments 501313
Filter cubes
Gt(ROSA)26Sortm1(CAG-EGFP,-mCerulean,-mOrange,-mCherry)Ilw mice
ImageJ software https://imagej.net
KCl 1M FisherScientific LC187951
Leica CM3050 cryostat
Liquid Nitrogen
Microscissors, 6mm World Precision Instruments 14003
Myh6-CreERT2 mice The Jackson Laboratory 005657
Needler holder World Precision Instruments 14109
Paraformaldehyde 4% FisherScientific AC416785000
Phosphate buffered saline
Python https://www.python.org/
R https://cran.r-project.org/
Rotating Shaker
Stereoscope
Sucrose 30% (wt/vol) FisherScientific BP220
Surgical dissecting scissors World Precision Instruments 14393
Syringe for tamoxifen VWR BD328438
Tamoxifen, 20 μg Sigma T5648
Tissue Freezing Media VWR 15148-031
White Frosted/Plus slides Globe Scientific 1358W
Zeiss Axio Imager M1 upright widefield fluorescence system
Zen 2.5 Blue software

References

  1. Karra, R., Poss, K. D. Redirecting cardiac growth mechanisms for therapeutic regeneration. Journal of Clinical Investigation. 127 (2), 427-436 (2017).
  2. Bergmann, O., et al. Dynamics of Cell Generation and Turnover in the Human Heart. Cell. 161 (7), 1566-1575 (2015).
  3. Bergmann, O., et al. Evidence for cardiomyocyte renewal in humans. Science. 324 (5923), 98-102 (2009).
  4. Senyo, S. E., et al. Mammalian heart renewal by pre-existing cardiomyocytes. Nature. 493 (7432), 433-436 (2013).
  5. Mollova, M., et al. Cardiomyocyte proliferation contributes to heart growth in young humans. Proceedings of the National Academy of Sciences U.S.A. 110 (4), 1446-1451 (2013).
  6. Kikuchi, K., et al. Primary contribution to zebrafish heart regeneration by gata4(+) cardiomyocytes. Nature. 464 (7288), 601-605 (2010).
  7. Jopling, C., et al. Zebrafish heart regeneration occurs by cardiomyocyte dedifferentiation and proliferation. Nature. 464 (7288), 606-609 (2010).
  8. Oberpriller, J. O., Oberpriller, J. C. Response of the adult newt ventricle to injury. Journal of Experimental Zoology. 187 (2), 249-253 (1974).
  9. Oberpriller, J., Oberpriller, J. C. Mitosis in adult newt ventricle. Journal of Cell Biology. 49 (2), 560-563 (1971).
  10. Porrello, E. R., et al. Transient regenerative potential of the neonatal mouse heart. Science. 331 (6020), 1078-1080 (2011).
  11. Wang, H., et al. Natural Heart Regeneration in a Neonatal Rat Myocardial Infarction Model. Cells. 9 (1), (2020).
  12. Ye, L., et al. Early Regenerative Capacity in the Porcine Heart. Circulation. 138 (24), 2798-2808 (2018).
  13. Zhu, W., et al. Regenerative Potential of Neonatal Porcine Hearts. Circulation. 138 (24), 2809-2816 (2018).
  14. Kadow, Z. A., Martin, J. F. Distinguishing Cardiomyocyte Division From Binucleation. Circulation Research. 123 (9), 1012-1014 (2018).
  15. Roy, E., Neufeld, Z., Livet, J., Khosrotehrani, K. Concise review: understanding clonal dynamics in homeostasis and injury through multicolor lineage tracing. Stem Cells. 32 (12), 3046-3054 (2014).
  16. Livet, J., et al. Transgenic strategies for combinatorial expression of fluorescent proteins in the nervous system. Nature. 450 (7166), 56-62 (2007).
  17. Sereti, K. I., et al. Analysis of cardiomyocyte clonal expansion during mouse heart development and injury. Nature Communications. 9 (1), 1-13 (2018).
  18. Xiao, Q., et al. A p53-based genetic tracing system to follow postnatal cardiomyocyte expansion in heart regeneration. Development. 144 (4), 580-589 (2017).
  19. Ali, S. R., et al. Existing cardiomyocytes generate cardiomyocytes at a low rate after birth in mice. Proceedings of the National Academy of Sciences U.S.A. 111 (24), 8850-8855 (2014).
  20. Sohal, D. S., et al. Temporally regulated and tissue-specific gene manipulations in the adult and embryonic heart using a tamoxifen-inducible Cre protein. Circulation Research. 89 (1), 20-25 (2001).
  21. Red-Horse, K., Ueno, H., Weissman, I. L., Krasnow, M. A. Coronary arteries form by developmental reprogramming of venous cells. Nature. 464 (7288), 549-553 (2010).
  22. Polizzotti, B. D., et al. Neuregulin stimulation of cardiomyocyte regeneration in mice and human myocardium reveals a therapeutic window. Science Translational Medicine. 7 (281), 245 (2015).
  23. Polizzotti, B. D., Ganapathy, B., Haubner, B. J., Penninger, J. M., Kuhn, B. A cryoinjury model in neonatal mice for cardiac translational and regeneration research. Nature Protocols. 11 (3), 542-552 (2016).
  24. Schindelin, J., et al. Fiji: an open-source platform for biological-image analysis. Nature Methods. 9 (7), 676-682 (2012).
  25. van Rossum, G. Python tutorial, Technical Report CS-R9526. Centrum voor Wiskunde en Informatica (CWI). , (1995).
  26. Team, R. C. . R: A language and environment for statistical computing. , (2013).
  27. Denwood, M. J. runjags: An R package providing interface utilities, model templates, parallel computing methods and additional distributions for MCMC models in JAGS. Journal of Statistical Software. 71 (9), 1-25 (2016).
  28. Plummer, M., Best, N., Cowles, K., Vines, K. CODA: convergence diagnosis and output analysis for MCMC. R News. 6 (1), 7-11 (2006).
  29. Plummer, M. . Proceedings of the 3rd international workshop on distributed statistical computing. , 1-10 (2003).
  30. Kruschke, J. . Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan. , (2014).
  31. Darehzereshki, A., et al. Differential regenerative capacity of neonatal mouse hearts after cryoinjury. Biologie du développement. 399 (1), 91-99 (2015).
  32. Kimura, W., et al. Hypoxia fate mapping identifies cycling cardiomyocytes in the adult heart. Nature. 523 (7559), 226-230 (2015).
This article has been published
Video Coming Soon
Keep me updated:

.

Citer Cet Article
Bakovic, M., Thakkar, D., DeBenedittis, P., Chong, D. C., Thomas, M. C., Iversen, E. S., Karra, R. Clonal Analysis of the Neonatal Mouse Heart using Nearest Neighbor Modeling. J. Vis. Exp. (162), e61656, doi:10.3791/61656 (2020).

View Video