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An integrated pipeline for the multidimensional analysis of branching morphogenesis

Abstract

Developmental branching morphogenesis establishes organ architecture, and it is driven by iterative interactions between epithelial and mesenchymal progenitor cell populations. We describe an approach for analyzing this interaction and how it contributes to organ development. After initial in vivo cell labeling with the nucleoside analog 5-ethynyl-2′-deoxyuridine (EdU) and tissue-specific antibodies, optical projection tomography (OPT) and confocal microscopy are used to image the developing organ. These imaging data then inform a second analysis phase that quantifies (using Imaris and Tree Surveyor software), models and integrates these events at a cell and tissue level in 3D space and across developmental time. The protocol establishes a benchmark for assessing the impact of genetic change or fetal environment on organogenesis that does not rely on ex vivo organ culture or section-based reconstruction. By using this approach, examination of two developmental stages for an organ such as the kidney can be undertaken by a postdoctoral-level researcher in 6 weeks, with a full developmental analysis in mouse achievable in 5 months.

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Figure 1: Flowchart of the protocol.
Figure 2: Correlative microscopy.
Figure 3: Operation of Tree Surveyor.
Figure 4: Activating processes and data management in Tree Surveyor.
Figure 5: Sample processing options in Tree Surveyor.
Figure 6: Tree Surveyor sample display.
Figure 7: Skeleton editing functions in Tree Surveyor.
Figure 8: Analysis of Tree Surveyor data using Microsoft Excel.
Figure 9: Niche counting.
Figure 10: Surface rendering, spot counts and QC.
Figure 11: Assessing the number of nephrons per niche.

References

  1. Herriges, M. & Morrisey, E.E. Lung development: orchestrating the generation and regeneration of a complex organ. Development 141, 502–513 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  2. Costantini, F. & Kopan, R. Patterning a complex organ: branching morphogenesis and nephron segmentation in kidney development. Dev. Cell 18, 698–712 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  3. Huebner, R.J. & Ewald, A.J. Cellular foundations of mammary tubulogenesis. Semin. Cell Dev. Biol. 31, 24–31 (2014).

    Article  CAS  Google Scholar 

  4. Patel, V.N. & Hoffman, M.P. Salivary gland development: a template for regeneration. Semin. Cell Dev. Biol. 25–26C, 52–60 (2014).

    Article  Google Scholar 

  5. Grobstein, C. Inductive epithelio-mesenchymal interaction in cultured organ rudiments of the mouse. Science 118, 52–55 (1953).

    CAS  PubMed  Article  Google Scholar 

  6. Grobstein, C. Inductive interaction in the development of the mouse metanephros. J. Exp. Zool. 130, 319–339 (1955).

    Article  Google Scholar 

  7. Short, K.M., Hodson, M.J. & Smyth, I.M. Tomographic quantification of branching morphogenesis and renal development. Kidney Int. 77, 1132–1139 (2010).

    PubMed  Article  Google Scholar 

  8. al-Awqati, Q. & Goldberg, M.R. Architectural patterns in branching morphogenesis in the kidney. Kidney Int. 54, 1832–1842 (1998).

    CAS  PubMed  Article  Google Scholar 

  9. Cebrian, C., Borodo, K., Charles, N. & Herzlinger, D.A. Morphometric index of the developing murine kidney. Dev. Dyn. 231, 601–608 (2004).

    PubMed  Article  Google Scholar 

  10. Sims-Lucas, S. et al. Three-dimensional imaging reveals ureteric and mesenchymal defects in Fgfr2-mutant kidneys. J. Am. Soc. Nephrol. 20, 2525–2533 (2009).

    PubMed  PubMed Central  Article  Google Scholar 

  11. Hoy, W.E. et al. Nephron number, glomerular volume, renal disease and hypertension. Curr. Opin. Nephrol. Hypertens. 17, 258–265 (2008).

    PubMed  Article  Google Scholar 

  12. Luyckx, V.A. et al. Effect of fetal and child health on kidney development and long-term risk of hypertension and kidney disease. Lancet 382, 273–283 (2013).

    PubMed  Article  Google Scholar 

  13. Boyle, S. et al. Fate mapping using Cited1-CreERT2 mice demonstrates that the cap mesenchyme contains self-renewing progenitor cells and gives rise exclusively to nephronic epithelia. Dev. Biol. 313, 234–245 (2008).

    CAS  PubMed  Article  Google Scholar 

  14. Kobayashi, A. et al. Six2 defines and regulates a multipotent self-renewing nephron progenitor population throughout mammalian kidney development. Cell Stem Cell 3, 169–181 (2008).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  15. El Agha, E. et al. Fgf10-positive cells represent a progenitor cell population during lung development and postnatally. Development 141, 296–306 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  16. Cunha, G.R. et al. Mammary phenotypic expression induced in epidermal cells by embryonic mammary mesenchyme. Acta Anat. (Basel) 152, 195–204 (1995).

    CAS  Article  Google Scholar 

  17. Short, K., Hodson, M. & Smyth, I. Spatial mapping and quantification of developmental branching morphogenesis. Development 140, 471–478 (2013).

    CAS  PubMed  Article  Google Scholar 

  18. Short, K.M. & Smyth, I.M. Analysis of native kidney structures in three dimensions. Methods Mol. Biol. 886, 95–107 (2012).

    CAS  PubMed  Article  Google Scholar 

  19. Lefevre, J. et al. Modelling cell turnover in a complex tissue during development. J. Theor. Biol. 338, 66–79 (2013).

    CAS  PubMed  Article  Google Scholar 

  20. Packard, A. et al. Luminal mitosis drives epithelial cell dispersal within the branching ureteric bud. Dev. Cell 27, 319–330 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  21. Rumballe, B.A. et al. Nephron formation adopts a novel spatial topology at cessation of nephrogenesis. Dev. Biol. 360, 110–122 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  22. Combes, A.N. et al. Three-dimensional visualization of testis cord morphogenesis, a novel tubulogenic mechanism in development. Dev. Dyn. 238, 1033–1041 (2009).

    PubMed  PubMed Central  Article  Google Scholar 

  23. Combes, A.N. et al. Endothelial cell migration directs testis cord formation. Dev. Biol. 326, 112–120 (2009).

    CAS  PubMed  Article  Google Scholar 

  24. Davies, J.A. et al. Access and use of the GUDMAP database of genitourinary development. Methods Mol. Biol. 886, 185–201 (2012).

    CAS  PubMed  Article  Google Scholar 

  25. Georgas, K.M., Chiu, H.S., Lesieur, E., Rumballe, B.A. & Little, M.H. Expression of metanephric nephron-patterning genes in differentiating mesonephric tubules. Dev. Dyn. 240, 1600–1612 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  26. Harding, S.D. et al. The GUDMAP database—an online resource for genitourinary research. Development 138, 2845–2853 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  27. Little, M.H. et al. A high-resolution anatomical ontology of the developing murine genitourinary tract. Gene Expr. Patterns 7, 680–699 (2007).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  28. McMahon, A.P. et al. GUDMAP: the genitourinary developmental molecular anatomy project. J. Am. Soc. Nephrol. 19, 667–671 (2008).

    PubMed  Article  Google Scholar 

  29. Short, K.M. et al. Global quantification of tissue dynamics in the developing mouse kidney. Dev. Cell 29, 188–202 (2014).

    CAS  PubMed  Article  Google Scholar 

  30. Sharpe, J. et al. Optical projection tomography as a tool for 3D microscopy and gene expression studies. Science 296, 541–545 (2002).

    CAS  PubMed  Article  Google Scholar 

  31. Schuchardt, A., D'Agati, V., Pachnis, V. & Costantini, F. Renal agenesis and hypodysplasia in ret-k mutant mice result from defects in ureteric bud development. Development 122, 1919–1929 (1996).

    CAS  PubMed  Article  Google Scholar 

  32. Enomoto, H. et al. RET signaling is essential for migration, axonal growth and axon guidance of developing sympathetic neurons. Development 128, 3963–3974 (2001).

    CAS  PubMed  Article  Google Scholar 

  33. Schuchardt, A., D'Agati, V., Larsson-Blomberg, L., Costantini, F. & Pachnis, V. Defects in the kidney and enteric nervous system of mice lacking the tyrosine kinase receptor Ret. Nature 367, 380–383 (1994).

    CAS  PubMed  Article  Google Scholar 

  34. Metzger, R.J., Klein, O.D., Martin, G.R. & Krasnow, M.A. The branching programme of mouse lung development. Nature 453, 745–750 (2008).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  35. Hockendorf, B., Thumberger, T. & Wittbrodt, J. Quantitative analysis of embryogenesis: a perspective for light sheet microscopy. Dev. Cell 23, 1111–1120 (2012).

    PubMed  Article  CAS  Google Scholar 

  36. Francois, M. et al. Segmental territories along the cardinal veins generate lymph sacs via a ballooning mechanism during embryonic lymphangiogenesis in mice. Dev. Biol. 364, 89–98 (2012).

    CAS  PubMed  Article  Google Scholar 

  37. Livet, J. et al. Transgenic strategies for combinatorial expression of fluorescent proteins in the nervous system. Nature 450, 56–62 (2007).

    CAS  PubMed  Article  Google Scholar 

  38. Chung, K. & Deisseroth, K. CLARITY for mapping the nervous system. Nat. Methods 10, 508–513 (2013).

    CAS  PubMed  Article  Google Scholar 

  39. Becker, K., Jahrling, N., Saghafi, S., Weiler, R. & Dodt, H.U. Chemical clearing and dehydration of GFP expressing mouse brains. PLoS ONE 7, e33916 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  40. Kuwajima, T. et al. ClearT: a detergent- and solvent-free clearing method for neuronal and non-neuronal tissue. Development 140, 1364–1368 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  41. Hornblad, A., Cheddad, A. & Ahlgren, U. An improved protocol for optical projection tomography imaging reveals lobular heterogeneities in pancreatic islet and beta cell mass distribution. Islets 3, 204–208 (2011).

    PubMed  PubMed Central  Article  Google Scholar 

  42. Theiler, K. The House Mouse: Atlas of Embryonic Development 2nd edn. (Springer-Verlag, 1989).

  43. Wanek, N., Muneoka, K., Holler-Dinsmore, G., Burton, R. & Bryant, S.V. A staging system for mouse limb development. J. Exp. Zool. 249, 41–49 (1989).

    CAS  PubMed  Article  Google Scholar 

  44. Nagy, A., Gertsenstein, M., Vintersten, K. & Behringer, R. Alcian blue staining of the mouse fetal cartilaginous skeleton. Cold Spring Harbor Protoc. 2009 10.1101/pdb.prot5169 (2009).

  45. McDonald, J.H. Handbook of Biological Statistics 161–168 (Sparky House Publishing, 2009).

  46. Welch, B.L. The generalization of 'Student's' problem when several different population variances are involved. Biometrika 34, 28–35 (1947).

    CAS  PubMed  Google Scholar 

  47. Buck, S.B. et al. Detection of S-phase cell cycle progression using 5-ethynyl-2′-deoxyuridine incorporation with click chemistry, an alternative to using 5-bromo-2′-deoxyuridine antibodies. BioTechniques 44, 927–929 (2008).

    CAS  PubMed  Article  Google Scholar 

  48. Salic, A. & Mitchison, T.J. A chemical method for fast and sensitive detection of DNA synthesis in vivo. Proc. Natl. Acad. Sci. USA 105, 2415–2420 (2008).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  49. Zeng, C. et al. Evaluation of 5-ethynyl-2′-deoxyuridine staining as a sensitive and reliable method for studying cell proliferation in the adult nervous system. Brain Res. 1319, 21–32 (2010).

    CAS  PubMed  Article  Google Scholar 

  50. Farah, M.H. Cumulative labeling of embryonic mouse neural retina with bromodeoxyuridine supplied by an osmotic minipump. J. Neurosci. Methods 134, 169–178 (2004).

    PubMed  Article  Google Scholar 

  51. Alanentalo, T. et al. High-resolution three-dimensional imaging of islet-infiltrate interactions based on optical projection tomography assessments of the intact adult mouse pancreas. J. Biomed. Optics 13, 054070 (2008).

    Article  Google Scholar 

  52. Walls, J.R., Coultas, L., Rossant, J. & Henkelman, R.M. Three-dimensional analysis of vascular development in the mouse embryo. PLoS ONE 3, e2853 (2008).

    PubMed  PubMed Central  Article  Google Scholar 

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Acknowledgements

This work was supported by the National Health and Medical Research Council of Australia (APP1002748, APP1022239 and APP1063989), the Australian Research Council (DP10310086) and the Human Frontiers in Science Program (RGP0039/2011). Microscopy was performed at the Australian Cancer Research Foundation (ARCF)/Institute for Molecular Bioscience Cancer Biology Imaging Facility, which was established with the support of the ARCF. I.M.S. holds a Future Fellowship from the Australian Research Council. M.H.L. is a Senior Principal Research Fellow of the Australian National Health and Medical Research Council.

Author information

Authors and Affiliations

Authors

Contributions

A.N.C. and J.L. developed the methodologies used in analyzing confocal data, cell cycle length and population modeling. K.M.S. developed the Tree Surveyor protocol and tools to examine tree morphometrics. I.M.S. undertook the correlative microscopy experiments. N.A.H. oversaw and contributed to the development of approaches to mathematical analyses. I.M.S. and M.H.L. were responsible for the initial conception of the project, directed the collaboration and were involved in the design of experiments, ongoing planning, and analysis and interpretation of the data. K.M.S., A.N.C., J.L. and I.M.S. wrote the manuscript with substantive input from M.H.L. and N.A.H.

Corresponding authors

Correspondence to Melissa H Little or Ian M Smyth.

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Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Whole Organ Confocal Z-stack.

Confocal imaging data from a whole 14.5 dpc kidney demonstrate that the quality of imaging can be maintained throughout the sample. Panels show every 10th optical slice throughout the Z-stack (depth from the fist slice is indicated in each panel). The whole file is composed of 101 Z-slices that encompass a total thickness of 352 microns. Scale bar = 100 μm.

Supplementary information

Supplementary Figure 1 and Supplementary Manual

(PDF 213 kb)

Introduction to the Tree Surveyor application.

The movie explains the interface, project setup, loading data, and an explanation of the algorithms used and the sliders and buttons which control them. (MOV 6995 kb)

A guide to running a Tree Surveyor process.

Discussed are the processing algorithms, the assessment of the first stage of skeletonization, editing of the tree and placement of root. (MOV 6082 kb)

Completion of processing and export of data from Tree Surveyor.

Visualisation modes, explanation of segment/branch naming conventions and introduction to data export and analysis. (MOV 7006 kb)

Supplementary Data 1: Cell Modeling.

This zip file contains an excel spreadsheet (Supp Data 1 worksheet.xl) and a Word document with instructions for its use (Supp Data 1 instructions.doc). The excel spreadsheet contains the formulas required to determine whole organ estimates and to model population growth and exit from cell niches. (ZIP 33 kb)

Supplementary Data 2: An example OPT z-stack.

This data is from a normal E14.5 C57BL/6 embryonic kidney with ureteric tree detected with Trop-2 antibody. The stack can be used as a guide to test Tree Surveyor usage and analysis. On analysis, this sample should have approximately 327 tips, total length of 44 μm, a convex hull volume of 0.56 mm3, and tips with an approximate mean length of 56 μm. (ZIP 8367 kb)

Supplementary Data 3: Example confocal dataset.

An example of a high resolution 40× confocal z-stack of a normal E15.5 kidney (Zeiss LSM format, compatible with Imaris). The stack contains data from four channels marking nuclei (blue), cap mesenchyme (red), Cytokeratin (white), GFP (green). This can be used as a guide to test the included protocols in Imaris. (ZIP 51871 kb)

Supplementary Software: R Studio Script to model EdU incorporation.

This file provides code and demonstration data for EdU incorporation curve modelling. An R Studio script (curvefitting.R) calculates cell cycle length estimates and standard errors, and plots modelled curves. The script has example data embedded which can be replaced. Instructions for use are embedded in the script. (ZIP 5 kb)

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Combes, A., Short, K., Lefevre, J. et al. An integrated pipeline for the multidimensional analysis of branching morphogenesis. Nat Protoc 9, 2859–2879 (2014). https://doi.org/10.1038/nprot.2014.193

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