Skip to main content

The Cell Painting Assay as a Screening Tool for the Discovery of Bioactivities in New Chemical Matter

  • Protocol
  • First Online:
Systems Chemical Biology

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1888))

Abstract

Multiparametric phenotypic screening based on cellular morphology interrogates many biological pathways simultaneously and is therefore a valuable screening tool for the discovery of new biological activities. The cell painting assay stains various cellular features using six different dyes in one well. By automated image analysis, hundreds of parameters are calculated from the images which deliver a phenotypic profile of the cell. It has been shown that compounds with similar modes of action deliver similar phenotypic profiles. Using a reference set of compounds with known modes of action, it is possible to assign probable modes of action to new compounds and to discover compounds with potentially new modes of action.

Here we describe the cell painting assay as a screening tool using a hit identification workflow which has been implemented using open-source software.

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 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 169.99
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. Vincent F, Loria P, Pregel M, Stanton R, Kitching L, Nocka K, Doyonnas R, Steppan C, Gilbert A, Schroeter T, Peakman MC (2015) Developing predictive assays: the phenotypic screening "rule of 3". Sci Transl Med 7(293):293ps215. https://doi.org/10.1126/scitranslmed.aab1201

    Article  CAS  Google Scholar 

  2. Vendrell-Navarro G, Brockmeyer A, Waldmann H, Janning P, Ziegler S (2015) Identification of the targets of biologically active small molecules using quantitative proteomics. Methods Mol Biol 1263:263–286. https://doi.org/10.1007/978-1-4939-2269-7_21

    Article  CAS  PubMed  Google Scholar 

  3. Singh S, Carpenter AE, Genovesio A (2014) Increasing the content of high-content screening: an overview. J Biomol Screen 19(5):640–650. https://doi.org/10.1177/1087057114528537

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Pennisi E (2016) IMAGING. 'Cell painting' highlights responses to drugs and toxins. Science 352(6288):877–878. https://doi.org/10.1126/science.352.6288.877

    Article  CAS  PubMed  Google Scholar 

  5. Gustafsdottir SM, Ljosa V, Sokolnicki KL, Anthony Wilson J, Walpita D, Kemp MM, Petri Seiler K, Carrel HA, Golub TR, Schreiber SL, Clemons PA, Carpenter AE, Shamji AF (2013) Multiplex cytological profiling assay to measure diverse cellular states. PLoS One 8(12):e80999. https://doi.org/10.1371/journal.pone.0080999

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Reisen F, Sauty de Chalon A, Pfeifer M, Zhang X, Gabriel D, Selzer P (2015) Linking phenotypes and modes of action through high-content screen fingerprints. Assay Drug Dev Technol 13(7):415–427. https://doi.org/10.1089/adt.2015.656

    Article  CAS  PubMed  Google Scholar 

  7. Jones LH, Bunnage ME (2017) Applications of chemogenomic library screening in drug discovery. Nat Rev Drug Discov 16(4):285–296. https://doi.org/10.1038/nrd.2016.244

    Article  CAS  PubMed  Google Scholar 

  8. Boran AD, Iyengar R (2010) Systems approaches to polypharmacology and drug discovery. Curr Opin Drug Discov Devel 13(3):297–309

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Hu Y, Bajorath J (2013) High-resolution view of compound promiscuity. F1000 Res 2:144. https://doi.org/10.12688/f1000research.2-144.v2

    Article  Google Scholar 

  10. Ursu A, Illich DJ, Takemoto Y, Porfetye AT, Zhang M, Brockmeyer A, Janning P, Watanabe N, Osada H, Vetter IR, Ziegler S, Scholer HR, Waldmann H (2016) Epiblastin A induces reprogramming of epiblast stem cells into embryonic stem cells by inhibition of casein kinase 1. Cell Chem Biol 23(4):494–507. https://doi.org/10.1016/j.chembiol.2016.02.015

    Article  CAS  PubMed  Google Scholar 

  11. Perlman ZE, Slack MD, Feng Y, Mitchison TJ, Wu LF, Altschuler SJ (2004) Multidimensional drug profiling by automated microscopy. Science 306(5699):1194–1198. https://doi.org/10.1126/science.1100709

    Article  CAS  PubMed  Google Scholar 

  12. Bray MA, Gustafsdottir SM, Ljosa V, Singh S, Sokolnicki KL, Bittker JA, Bodycombe NE, Dancik V, Hasaka TP, Hon CS, Kemp MM, Li K, Walpita D, Wawer MJ, Golub TR, Schreiber SL, Clemons PA, Shamji AF, Carpenter AE (2017) A dataset of images and morphological profiles of 30,000 small-molecule treatments using the Cell Painting assay. Gigascience 6(12):1–5. https://doi.org/10.1093/gigascience/giw014

    Article  PubMed  PubMed Central  Google Scholar 

  13. Bray MA, Singh S, Han H, Davis CT, Borgeson B, Hartland C, Kost-Alimova M, Gustafsdottir SM, Gibson CC, Carpenter AE (2016) Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes. Nat Protoc 11(9):1757–1774. https://doi.org/10.1038/nprot.2016.105

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Knapp S, Arruda P, Blagg J, Burley S, Drewry DH, Edwards A, Fabbro D, Gillespie P, Gray NS, Kuster B, Lackey KE, Mazzafera P, Tomkinson NC, Willson TM, Workman P, Zuercher WJ (2013) A public-private partnership to unlock the untargeted kinome. Nat Chem Biol 9(1):3–6. https://doi.org/10.1038/nchembio.1113

    Article  CAS  PubMed  Google Scholar 

  15. Carpenter AE, Jones TR, Lamprecht MR, Clarke C, Kang IH, Friman O, Guertin DA, Chang JH, Lindquist RA, Moffat J, Golland P, Sabatini DM (2006) CellProfiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biol 7(10):R100. https://doi.org/10.1186/gb-2006-7-10-r100

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Rogers DJ, Tanimoto TT (1960) A Computer program for classifying plants. Science 132(3434):1115–1118. https://doi.org/10.1126/science.132.3434.1115

    Article  CAS  PubMed  Google Scholar 

  17. Lundholt BK, Scudder KM, Pagliaro L (2003) A simple technique for reducing edge effect in cell-based assays. J Biomol Screen 8(5):566–570. https://doi.org/10.1177/1087057103256465

    Article  CAS  PubMed  Google Scholar 

  18. Ljosa V, Caie PD, Ter Horst R, Sokolnicki KL, Jenkins EL, Daya S, Roberts ME, Jones TR, Singh S, Genovesio A, Clemons PA, Carragher NO, Carpenter AE (2013) Comparison of methods for image-based profiling of cellular morphological responses to small-molecule treatment. J Biomol Screen 18(10):1321–1329. https://doi.org/10.1177/1087057113503553

    Article  CAS  PubMed  Google Scholar 

  19. Kummel A, Selzer P, Beibel M, Gubler H, Parker CN, Gabriel D (2011) Comparison of multivariate data analysis strategies for high-content screening. J Biomol Screen 16(3):338–347. https://doi.org/10.1177/1087057110395390

    Article  CAS  PubMed  Google Scholar 

  20. Twarog NR, Low JA, Currier DG, Miller G, Chen T, Shelat AA (2016) Robust classification of small-molecule mechanism of action using a minimalist high-content microscopy screen and multidimensional phenotypic trajectory analysis. PLoS One 11(2):e0149439. https://doi.org/10.1371/journal.pone.0149439

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Young DW, Bender A, Hoyt J, McWhinnie E, Chirn GW, Tao CY, Tallarico JA, Labow M, Jenkins JL, Mitchison TJ, Feng Y (2008) Integrating high-content screening and ligand-target prediction to identify mechanism of action. Nat Chem Biol 4(1):59–68. https://doi.org/10.1038/nchembio.2007.53

    Article  CAS  PubMed  Google Scholar 

  22. Gerry CJ, Hua BK, Wawer MJ, Knowles JP, Nelson SD Jr, Verho O, Dandapani S, Wagner BK, Clemons PA, Booker-Milburn KI, Boskovic ZV, Schreiber SL (2016) Real-time biological annotation of synthetic compounds. J Am Chem Soc 138(28):8920–8927. https://doi.org/10.1021/jacs.6b04614

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Reisen F, Zhang X, Gabriel D, Selzer P (2013) Benchmarking of multivariate similarity measures for high-content screening fingerprints in phenotypic drug discovery. J Biomol Screen 18(10):1284–1297. https://doi.org/10.1177/1087057113501390

    Article  CAS  PubMed  Google Scholar 

  24. Hutz JE, Nelson T, Wu H, McAllister G, Moutsatsos I, Jaeger SA, Bandyopadhyay S, Nigsch F, Cornett B, Jenkins JL, Selinger DW (2013) The multidimensional perturbation value: a single metric to measure similarity and activity of treatments in high-throughput multidimensional screens. J Biomol Screen 18(4):367–377. https://doi.org/10.1177/1087057112469257

    Article  PubMed  Google Scholar 

  25. Wawer MJ, Li K, Gustafsdottir SM, Ljosa V, Bodycombe NE, Marton MA, Sokolnicki KL, Bray MA, Kemp MM, Winchester E, Taylor B, Grant GB, Hon CS, Duvall JR, Wilson JA, Bittker JA, Dancik V, Narayan R, Subramanian A, Winckler W, Golub TR, Carpenter AE, Shamji AF, Schreiber SL, Clemons PA (2014) Toward performance-diverse small-molecule libraries for cell-based phenotypic screening using multiplexed high-dimensional profiling. Proc Natl Acad Sci U S A 111(30):10911–10916. https://doi.org/10.1073/pnas.1410933111

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sonja Sievers .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Pahl, A., Sievers, S. (2019). The Cell Painting Assay as a Screening Tool for the Discovery of Bioactivities in New Chemical Matter. In: Ziegler, S., Waldmann, H. (eds) Systems Chemical Biology. Methods in Molecular Biology, vol 1888. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8891-4_6

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-8891-4_6

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-8890-7

  • Online ISBN: 978-1-4939-8891-4

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics