Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Protocol
  • Published:

Arrayed cellular microenvironments for identifying culture and differentiation conditions for stem, primary and rare cell populations

Nature Protocols volume 7, pages 703–717 (2012)Cite this article

Subjects

Abstract

During the development of an organism, cells are exposed to a myriad of signals, structural components and scaffolds, which collectively make up the cellular microenvironment. The majority of current developmental biology studies examine the effect of individual or small subsets of molecules and parameters on cellular behavior, and they consequently fail to explore the complexity of factors to which cells are exposed. Here we describe a technology, referred to as arrayed cellular microenvironments (ACMEs), that allows for a high-throughput examination of the effects of multiple extracellular components in a combinatorial manner on any cell type of interest. We will specifically focus on the application of this technology to human pluripotent stem cells (hPSCs), a population of cells with tremendous therapeutic potential, and one for which growth and differentiation conditions are poorly characterized and far from defined and optimized. A standard ACME screen uses the technologies previously applied to the manufacture and analysis of DNA microarrays, requires standard cell-culture facilities and can be performed from beginning to end within 5–10 days.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Flowchart outlining the protocol.
Figure 2
Figure 3: Example of a live-analysis experiment to identify conditions that promote hPSC attachment and growth.
Figure 4: Characterization of printed ACME slides.
Figure 5: Example of an endpoint analysis experiment.

Similar content being viewed by others

References

  1. Chen, Y., Yu, P., Luo, J. & Jiang, Y. Secreted protein prediction system combining CJ-SPHMM, TMHMM, and PSORT. Mamm. Genome 14, 859–865 (2003).

    Article  CAS  Google Scholar 

  2. Grimmond, S.M. et al. The mouse secretome: functional classification of the proteins secreted into the extracellular environment. Genome Res. 13, 1350–1359 (2003).

    Article  CAS  Google Scholar 

  3. Brafman, D.A., Shah, K.D., Fellner, T., Chien, S. & Willert, K. Defining long-term maintenance conditions of human embryonic stem cells with arrayed cellular microenvironment technology. Stem Cells Dev. 18, 1141–1154 (2009).

    Article  Google Scholar 

  4. Brafman, D.A. et al. Investigating the role of the extracellular environment in modulating hepatic stellate cell biology with arrayed combinatorial microenvironments. Integr. Biol. (Camb) 1, 513–524 (2009).

    Article  CAS  Google Scholar 

  5. Flaim, C.J., Chien, S. & Bhatia, S.N. An extracellular matrix microarray for probing cellular differentiation. Nat. Methods 2, 119–125 (2005).

    Article  CAS  Google Scholar 

  6. Flaim, C.J., Teng, D., Chien, S. & Bhatia, S.N. Combinatorial signaling microenvironments for studying stem cell fate. Stem Cells Dev. 17, 29–39 (2008).

    Article  CAS  Google Scholar 

  7. Soen, Y., Mori, A., Palmer, T.D. & Brown, P.O. Exploring the regulation of human neural precursor cell differentiation using arrays of signaling microenvironments. Mol. Syst. Biol. 2, 37 (2006).

    Article  Google Scholar 

  8. La Barge, M.A. et al. Human mammary progenitor cell fate decisions are products of interactions with combinatorial microenvironments. Integr. Biol. (Camb) 1, 70–79 (2009).

    Article  CAS  Google Scholar 

  9. Brafman, D.A. et al. Long-term human pluripotent stem cell self-renewal on synthetic polymer surfaces. Biomaterials 31, 9135–9144 (2010).

    Article  CAS  Google Scholar 

  10. Anderson, D.G., Putnam, D., Lavik, E.B., Mahmood, T.A. & Langer, R. Biomaterial microarrays: rapid, microscale screening of polymer-cell interaction. Biomaterials 26, 4892–4897 (2005).

    Article  CAS  Google Scholar 

  11. Damoiseaux, R., Sherman, S.P., Alva, J.A., Peterson, C. & Pyle, A.D. Integrated chemical genomics reveals modifiers of survival in human embryonic stem cells. Stem Cells 27, 533–542 (2009).

    Article  CAS  Google Scholar 

  12. Watanabe, K. et al. A ROCK inhibitor permits survival of dissociated human embryonic stem cells. Nat. Biotechnol. 25, 681–686 (2007).

    Article  CAS  Google Scholar 

  13. Jones, C.N. et al. Multifunctional protein microarrays for cultivation of cells and immunodetection of secreted cellular products. Anal. Chem. 80, 6351–6357 (2008).

    Article  CAS  Google Scholar 

  14. Fernandes, T.G. et al. On-chip, cell-based microarray immunofluorescence assay for high-throughput analysis of target proteins. Anal. Chem. 80, 6633–6639 (2008).

    Article  CAS  Google Scholar 

  15. Hariharan, R. The analysis of microarray data. Pharmacogenomics 4, 477–497 (2003).

    Article  CAS  Google Scholar 

  16. Svrakic, N.M., Nesic, O., Dasu, M.R., Herndon, D. & Perez-Polo, J.R. Statistical approach to DNA chip analysis. Recent Prog. Horm. Res. 58, 75–93 (2003).

    Article  CAS  Google Scholar 

  17. Shannon, W., Culverhouse, R. & Duncan, J. Analyzing microarray data using cluster analysis. Pharmacogenomics 4, 41–52 (2003).

    Article  CAS  Google Scholar 

  18. Malo, N., Hanley, J.A., Cerquozzi, S., Pelletier, J. & Nadon, R. Statistical practice in high-throughput screening data analysis. Nat. Biotechnol. 24, 167–175 (2006).

    Article  CAS  Google Scholar 

  19. Makarenkov, V. et al. HTS-Corrector: software for the statistical analysis and correction of experimental high-throughput screening data. Bioinformatics 22, 1408–1409 (2006).

    Article  CAS  Google Scholar 

  20. Box, G., Hunter, W.G., Hunter, J.S. & Hunter, W. Statistics for Experimenters (Wiley, 1978).

  21. Eisen, M.B., Spellman, P.T., Brown, P.O. & Botstein, D. Cluster analysis and display of genome-wide expression patterns. Proc. Natl Acad. Sci. USA 95, 14863–14868 (1998).

    Article  CAS  Google Scholar 

  22. Xu, C. et al. Feeder-free growth of undifferentiated human embryonic stem cells. Nat. Biotechnol. 19, 971–974 (2001).

    Article  CAS  Google Scholar 

  23. Nandivada, H. et al. Fabrication of synthetic polymer coatings and their use in feeder-free culture of human embryonic stem cells. Nat. Protoc. 6, 1037–1043 (2011).

    Article  CAS  Google Scholar 

  24. Ware, C.B., Nelson, A.M. & Blau, C.A. A comparison of NIH-approved human ESC lines. Stem Cells 24, 2677–2684 (2006).

    Article  CAS  Google Scholar 

  25. Willert, K.H. Isolation and application of bioactive Wnt proteins. Methods Mol. Biol. 468, 17–29 (2008).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

D.A.B. was supported by funding from the University of California San Diego Stem Cell Program and by a gift from Michael and Nancy Kaehr. This research was supported in part by the California Institute of Regenerative Medicine (RS1-00172-1) to S.C. and (RB1-01406) to K.W.

Author information

Authors and Affiliations

  1. Cellular and Molecular Medicine, Stem Cell Program, University of California, San Diego, California, USA

    David A Brafman & Karl Willert

  2. Department of Bioengineering, University of California, San Diego, California, USA

    Shu Chien

Authors
  1. David A Brafman
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shu Chien
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Karl Willert
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

D.A.B., S.C. and K.W. developed the protocol. D.A.B. and K.W. designed and performed the experiments. D.A.B., S.C. and K.W. analyzed the results. D.A.B., S.C. and K.W. wrote the manuscript.

Corresponding authors

Correspondence to David A Brafman or Karl Willert.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Fig 1

Schematic representation of ACME format. (a) Schematic of a 10x10 subarray that contains 20 different conditions spotted in replicates of five. Spot diameter (closed circles) is 150 μm and the center to center distance between neighboring spots is 450 μm. These subarrays can be arranged to generate several different designs including (b) a 8x2, 1600 spot/320 condition, (c) a 16x4, 6400 spot/1280 condition, or (d) a 16x5, 8000 spot/1600 condition array. (PPT 415 kb)

Supplementary Table 1

Example of analysis of raw data generated from the array in Figure 5e. (DOC 1214 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Brafman, D., Chien, S. & Willert, K. Arrayed cellular microenvironments for identifying culture and differentiation conditions for stem, primary and rare cell populations. Nat Protoc 7, 703–717 (2012). https://doi.org/10.1038/nprot.2012.017

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nprot.2012.017

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing