Skip to main content

Segmentation and Quantitative Analysis of Individual Cells in Developmental Tissues

  • Protocol
  • First Online:
Mouse Molecular Embryology

Abstract

Image analysis is vital for extracting quantitative information from biological images and is used extensively, including investigations in developmental biology. The technique commences with the segmentation (delineation) of objects of interest from 2D images or 3D image stacks and is usually followed by the measurement and classification of the segmented objects. This chapter focuses on the segmentation task and here we explain the use of ImageJ, MIPAV (Medical Image Processing, Analysis, and Visualization), and VisSeg, three freely available software packages for this purpose. ImageJ and MIPAV are extremely versatile and can be used in diverse applications. VisSeg is a specialized tool for performing highly accurate and reliable 2D and 3D segmentation of objects such as cells and cell nuclei in images and stacks.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Pawley J (2006) Handbook of biological confocal microscopy, 3rd edn. Springer, New York

    Book  Google Scholar 

  2. Russ JC (2002) The image processing handbook, 4th edn. CRC, Boca Raton, FL

    Google Scholar 

  3. Castleman KR (1995) Digital image processing. Prentice Hall, Englewood Cliffs, NJ

    Google Scholar 

  4. Delft University of Technology, Quantitative Imaging Group interactive image processing course. http://www.tnw.tudelft.nl/fileadmin/Faculteit/TNW/Over_de_faculteit/Afdelingen/Imaging_Science_and_Technology/Research/Research_Groups/Quantitative_Imaging/Education/doc/FIP2_3.pdf

  5. Merks RMH, Brodsky SV, Goligorksy MS, Newman SA, Glazier JA (2006) Cell elongation is key to in silico replication of in vitro vasculogenesis and subsequent remodeling. Dev Biol 289:44–54

    Article  PubMed  CAS  Google Scholar 

  6. Heid PJ, Voss E, Soll DR (2002) 3D-DIASemb: a computer-assisted system for reconstructing and motion analyzing in 4D every cell and nucleus in a developing embryo. Dev Biol 245:329–347

    Article  PubMed  CAS  Google Scholar 

  7. Blacher S, Devy L, Burbridge MF, Roland G, Tucker G, Noël A, Foidart J-M (2001) Improved quantification of angiogenesis in the rat aortic ring assay. Angiogenesis 4:133–142

    Article  PubMed  CAS  Google Scholar 

  8. Peng H, Long F, Zhou J, Leung G, Eisen MB, Myers EW (2007) Automatic image analysis for gene expression patterns of fly embryos. BMC Cell Biol 8(Suppl 1):S7

    Article  PubMed  Google Scholar 

  9. ImageJ website http://rsb.info.nih.gov/ij/

  10. MIPAV website http://mipav.cit.nih.gov/index.php

  11. Kass M, Witkin A, Terzopoulos D (1988) Snakes: active contour models. Int J Comput Vision 1:321–331

    Article  Google Scholar 

  12. Blake A, Isard M (1998) Active contours. Cambridge University Press, New York, NY

    Book  Google Scholar 

  13. McAuliffe MJ, Lalonde FM, McGarry D, Gandler W, Csaky K, Trus BL (2001) Medical image processing, analysis and visualization in clinical research. Proceedings 14th IEEE symposium on computer-based medical systems, pp 381–386

    Google Scholar 

  14. Baggett D, Nakaya M, McAuliffe M, Yamaguchi TP, Lockett S (2005) Whole cell segmentation in solid tissue sections. Cytometry A 67A:137–143

    Article  Google Scholar 

  15. McCullough DP, Gudla PR, Harris BS, Collins JA, Meaburn KJ, Nakaya M, Yamaguchi TP, Misteli T, Lockett SJ (2008) Segmentation of whole cells and cell nuclei from 3D optical microscope images using dynamic programming. IEEE Trans Med Imaging 27:723–734

    Article  PubMed  CAS  Google Scholar 

  16. Dean P, Mascio L, Ow D, Sudar D, Mullikin J (1990) Proposed standard for image cytometry data files. Cytometry 11:561–569

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

Fluorescence imaging of the MCF-10A sample was performed at the National Cancer Institute Fluorescent Imaging Facility. The cell line was a gift from Dr S. Muthuswamy (Cold Spring Harbor Laboratory). This project was funded in whole or in part with federal funds from the National Cancer Institute (NCI), National Institutes of Health under contract N01-CO-12400. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services and nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government. NCI-Frederick is accredited by AAALAC International and follows the Public Health Service Policy for the Care and Use of Laboratory Animals. Animal care was provided in accordance with the procedures outlined in the “Guide for Care and Use of Laboratory Animals” (National Research Council; 1996; National Academy Press, Washington, D.C.). This research was supported [in part] by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research. We would like to thank Dr. Tom Mistelli for his continuous support and feedback.

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Appendix

Appendix

Sample preparation and image acquisition. Two biological samples were used in this study. One was an early somite stage (E8.0–8.5) mouse embryo obtained from an NIH Swiss female mouse. The embryo was fixed with 2 % paraformaldehyde/phosphate buffered saline (PBS) for 30 min at room temperature and stained with Oregon Green 488 Phalloidin (O-7466, Molecular Probes, Eugene, OR, USA) after treatment with 0.1 M glycine/0.2 % Triton X-100/PBS for 10 min. Phalloidin predominantly labels filamentous actin found abundantly at the cell surface underlying the cell membrane. The embryo was counter stained with the DNA dye 4′,6-diamidino-2–phenylindole (DAPI). The posterior primitive streak region of the embryos was manually dissected and mounted with SlowFade Light Antifade kit (S-7461, Molecular Probes) on a glass slide. Images were acquired using a 40×, 1.3 numerical aperture oil objective lens, and pinhole of one airy unit on an LSM 510 confocal microscope (Carl Zeiss Inc., Thornwood, NY, USA). Excitation was with a 488-nm laser light and emitted light between 500 and 550 nm was acquired. Thus, the effective thickness of the optical sections was 425 nm at the coverslip but increased further away from the coverslip. Pixel size was 0.14 μm in the x and y dimensions. DAPI was excited with two photon excitation at 780 nm and emitted light between 420 and 480 nm was collected.

The other biological sample used in this chapter was a 3D cell culture model of early breast tumorigenesis. MCF-10A.B2 a human mammary epithelial cell line was grown on basement membrane extract (Trevigen Inc., Gaithersburg, MD) for 20 days. MCF-10A.B2 cells express a synthetic ligand-inducible active ErbB2 variant. To induce tumorigenesis the synthetic ligand (AP1510; ARIAD Pharmaceuticals Inc)) was added for the final 10 days of culture. The acini structures formed by growth in 3D culture were fixed in 2 % paraformaldehyde/PBS for 20 min at room temperature and permeabilized by a 10 min incubation in 0.5 % Triton X-100 at 4 °C. Following three 15 min rinses in 100 mM glycine/PBS, the acini were blocked in IF buffer (0.1 % bovine serum albumin/0.2 % Triton X-100/0.05 % Tween-20/PBS) containing 10 % fetal bovine serum (Invitrogen) for 1 h. The cells were then incubated overnight in anti-integrin alpha 6 antibody (Chemicon International). Integrin alpha 6 stains for basolateral polarity, it stains the cell surface membrane with strong basal and weaker lateral staining. After three 20 min washes in IF buffer the cells were incubated in Alexa Fluor 488 donkey anti-rat (Invitrogen). Samples were mounted in DAPI containing VECTASHIELD mounting media (Vector Laboratories Ltd.) after three further 20 min washes in IF buffer. Images were acquired using a 63× 1.4-NA oil objective lens on an LSM 510 confocal microscope.

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media, New York

About this protocol

Cite this protocol

Nandy, K. et al. (2014). Segmentation and Quantitative Analysis of Individual Cells in Developmental Tissues. In: Lewandoski, M. (eds) Mouse Molecular Embryology. Methods in Molecular Biology, vol 1092. Humana Press, Boston, MA. https://doi.org/10.1007/978-1-60327-292-6_16

Download citation

  • DOI: https://doi.org/10.1007/978-1-60327-292-6_16

  • Published:

  • Publisher Name: Humana Press, Boston, MA

  • Print ISBN: 978-1-60327-290-2

  • Online ISBN: 978-1-60327-292-6

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics