Abstract
In image-based profiling, software extracts thousands of morphological features of cells from multi-channel fluorescence microscopy images, yielding single-cell profiles that can be used for basic research and drug discovery. Powerful applications have been proven, including clustering chemical and genetic perturbations on the basis of their similar morphological impact, identifying disease phenotypes by observing differences in profiles between healthy and diseased cells and predicting assay outcomes by using machine learning, among many others. Here, we provide an updated protocol for the most popular assay for image-based profiling, Cell Painting. Introduced in 2013, it uses six stains imaged in five channels and labels eight diverse components of the cell: DNA, cytoplasmic RNA, nucleoli, actin, Golgi apparatus, plasma membrane, endoplasmic reticulum and mitochondria. The original protocol was updated in 2016 on the basis of several years’ experience running it at two sites, after optimizing it by visual stain quality. Here, we describe the work of the Joint Undertaking for Morphological Profiling Cell Painting Consortium, to improve upon the assay via quantitative optimization by measuring the assay’s ability to detect morphological phenotypes and group similar perturbations together. The assay gives very robust outputs despite various changes to the protocol, and two vendors’ dyes work equivalently well. We present Cell Painting version 3, in which some steps are simplified and several stain concentrations can be reduced, saving costs. Cell culture and image acquisition take 1–2 weeks for typically sized batches of ≤20 plates; feature extraction and data analysis take an additional 1–2 weeks.
This protocol is an update to Nat. Protoc. 11, 1757–1774 (2016): https://doi.org/10.1038/nprot.2016.105
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Data availability
All images, single-cell profiles and processed profiles are available at the Cell Painting Gallery at https://registry.opendata.aws/cellpainting-gallery/ under accession numbers cpg0000-jump-pilot and cpg0001-cellpainting-protocol. Processed profiles, metadata and a detailed description of all plates are available in the paper’s GitHub repository (https://github.com/carpenterlab/2022_Cimini_NatureProtocols) and the data repositories found therein (https://github.com/jump-cellpainting/pilot-cpjump1-data, https://github.com/jump-cellpainting/pilot-cpjump1-fov-data and https://github.com/jump-cellpainting/pilot-data-public). Source data underlying all figures are provided with this paper.
Code availability
All code necessary to reproduce these analyses is available in the paper’s GitHub repository (https://github.com/carpenter-singh-lab/2023_Cimini_NatureProtocols) and is archived to Zenodo (https://doi.org/10.5281/zenodo.7267354).
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Acknowledgements
The authors gratefully acknowledge a grant from the Massachusetts Life Sciences Center Bits to Bytes Capital Call program for funding the data production. We appreciate funding to support data analysis and interpretation from members of the JUMP Cell Painting Consortium and from the National Institutes of Health (NIH MIRA R35 GM122547 to A.E.C.). We would like to acknowledge the Consortium’s Supporting Partner PerkinElmer for providing an in-kind contribution of the PhenoVue Cell Painting JUMP kit. The authors also gratefully acknowledge the use of the PerkinElmer Opera Phenix high-content/high-throughput imaging system at the Broad Institute, funded by the S10 Grant NIH OD-026839-01. H.S.A. was supported by a postdoctoral scholarship from the Knut and Alice Wallenberg Foundation. This project has been made possible in part by grant number 2020-225720 to B.A.C. from the Chan Zuckerberg Initiative Donor-Advised Fund, an advised fund of the Silicon Valley Community Foundation. The authors thank B. Marion and other members of the automation team in the Broad Institute’s Center for the Development of Therapeutics. The authors appreciate the more than 100 scientists who have contributed to the organization and scientific direction of the JUMP Cell Painting Consortium. The authors also thank the original developers of earlier versions of the protocol, who contributed to prior papers describing the assay3,4; those who are not also authors on this paper are: M. A. Bray, H. Han, C. T. Davis, B. Borgeson, C. Hartland, S. M. Gustafsdottir, C. C. Gibson, V. Ljosa, K. L. Sokolnicki, J. A. Wilson, D. Walpita, M. M. Kemp, K. Petri Seiler, H. A. Carrel, T. R. Golub, S. L. Schreiber, P. A. Clemons and A. F. Shamji.
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B.A.C., S.N.C., M.K.-A., L.M., A.G., B.F., S.G., J.B.C., C.-H.L., E.M., S.S., J.D.B., T.G., D.G., T.M., J.E.P., A.S., S.E.S., A.V., G.W., S.Y., B.Z. and A.E.C. contributed to experimental design. M.K.-A., L.M., A.G., B.F., P.B., J.B.C., E.M., P.A.Jr, J.D.B., T.G., D.H., G.H., K.J., M.M., T.M., J.E.P., A.S., A.V., G.W. and S.Y. conducted laboratory experiments. B.A.C., S.N.C., D.J.L., N.J., H.S.A., S.H., L.H.M., G.W. and B.Z. performed image and/or data analysis. B.A.C., S.N.C., M.K.-A., L.M., P.B., S.G., J.B.C., C.-H.L., E.M., S.S., J.D.B., G.H., M.M., L.H.M., T.M., A.S., S.E.S., G.W., B.Z. and A.E.C. contributed to data interpretation. B.A.C., D.J.L., J.B.C., P.A.Jr, S.H., E.W. and A.E.C. contributed to protocol development. B.A.C., S.N.C., M.K.-A., L.M., A.G., B.F., S.G., J.B.C., S.S., P.A.Jr, D.G., E.W. and A.E.C. wrote the manuscript, with all authors contributing to editing and giving manuscript approval. Supervision and administration were carried out by B.A.C., S.S. and A.E.C.
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Competing interests
S.S. and A.E.C. serve as scientific advisors for companies that use image-based profiling and Cell Painting (A.E.C.: Recursion; S.S.: Waypoint Bio and Dewpoint Therapeutics) and receive honoraria for occasional talks at pharmaceutical and biotechnology companies. D.G. is an employee of Bayer, AG, Pharmaceuticals. S.G., B.Z. and G.H. are employees of Merck Healthcare KGaA, Darmstadt, Germany. J.D.B. and T.G. were employed at Pfizer for the duration of this work. S.Y. was employed at Takeda for the duration of this work. S.E.S. was employed at Biogen for the duration of her contributions to this work. C.-H.L. was employed at Janssen Pharmaceutica at the time of writing. J.B.C. and P.A.Jr are employees of the Novartis Institutes for Biomedical Research, Cambridge, MA, USA and declare no competing interests. E.M., G.W., T.M, L.M. and J.E.P. are employees of AstraZeneca, Cambridge, UK. K.J. was employed at AstraZeneca for the duration of this work. D.J.L. and S.H. are employees of Pfizer, Inc.
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Nature Protocols thanks Marc Bickle, Joshua Harrill and Sonja Sievers for their contribution to the peer review of this work.
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Key references using this protocol
Nyffeler, J. et al. Toxicol. Appl. Pharmacol. 389, 114876 (2020): https://doi.org/10.1016/j.taap.2019.114876
Rohban, M. H. et al. Cell Syst. 13, 724–736.e9 (2022): https://doi.org/10.1016/j.cels.2022.08.003
Caicedo, J. C. et al. Mol. Biol. Cell 33, ar49 (2022): https://doi.org/10.1091/mbc.E21-11-0538
Key data used in this protocol
JUMP Cell Painting Consortium. Datasets (2023): https://doi.org/10.5281/zenodo.7628768
Extended data
Extended Data Fig. 1 The JUMP-MOA plate map labeled by compound.
The JUMP-MOA compound plate map: unlabeled wells are DMSO only; all other wells are labeled to show the distribution of compound replicates across the entire plate. A version of this figure grouped by MOA rather than compound is available as Fig. 2a.
Extended Data Fig. 2 Further assessment of cell type suitability for Cell Painting.
a, Percent replicating of each cell line and time point tested when selecting the cell type and treatement time points to be used by the consortium. A549 (red dots) has better replication at both time points of compound treatment than U2OS (blue dots) but worse performance at all time points of genetic perturbation experiments. b, Assessment of decreasing or increasing the number of cells plated by 20% on the ability to perform percent matching. Few consistent effects are seen when comparing across the columns present in each panel. c, Assessment of using parental cell lines or Cas9-expressing polyclonal lines for compound treatments. Few consistent effects are seen; the top right panel represents the desired task, the ability to match compounds added to either parental or Cas9 cells to CRISPR (which must be performed in Cas9 cells). The results in that panel do not seem extremely different either for matching 48-h compound treatment to 96 h of CRISPR treatment (compare the orange dots) or for matching 48-h compound treatment to 144 h of CRISPR treatment (compare the yellow dots). For more information including the plate(s) represented by each data point, see the Source Data file for this figure; expanded experimental details for each plate may be found in Supplementary Data File 1.
Extended Data Fig. 3 Assessment of the effect of gene-treatment-related compounds on Cell Painting performance.
a, Addition of blasticidin to ORF plates or puromycin to CRISPR plates does not appear to improve cross-modailty matching across modalities versus unselected plates; compare the second and third columns to the first column in the top center, top-left and bottom-middle panels. b, Addition of selection compounds may have a deleterious effect on percent replicating versus unselected plates, although we cannot rule out that this is due to fewer replicates for the selected plates than the unselected ones. c, Addition of 4 µg/ml polybrene for 24 h may produce a phenotypic effect; polybrene addition displays decreased inter-treatment cross-plate percent replicating versus intra-treatment cross-plate-percent replicating (compare the center column to the outside columns), even though both sets of plates were stained and imaged as part of the same batch. d, Addition of polybrene to Target2-treated cells does not improve percent matching between Target2-treated plates and ORF-treated plates; note that the Target-ORF plates came from a previous batch and were not stained and imaged in parallel to the Target2 compound plates. For more information including the plate(s) represented by each data point, see the Source Data file for this figure; expanded experimental details for each plate may be found in Supplementary Data File 1.
Extended Data Fig. 4 Assessment of permeabilization timing and plate type on Cell Painting performance.
a, Performing permeabilization at the same time as staining produces comparable percent replicating and percent matching results. b, PhenoPlates without barrier wells and Aurora plates with barrier wells produce comparable percent replicating and percent matching results. For more information including the plate(s) represented by each data point, see the Source Data file for this figure; expanded experimental details for each plate may be found in Supplementary Data File 1.
Extended Data Fig. 5 Expanded assessment of dye concentration effects on Cell Painting performance.
a, Within batches, reducing all dyes by two- or fourfold produces comparable percent replicating and comparable but perhaps slightly decreased percent matching results. b, All quantitatively tested stain concentration changes, broken out by the dye(s) perturbed. For more information including the plate(s) represented by each data point, see the Source Data file for this figure; expanded experimental details for each plate may be found in Supplementary Data File 1.
Extended Data Fig. 6 Further assessment of imaging conditions on Cell Painting performance.
a, Imaging of the same plates on a wide-field microscope with 2 × 2 binning versus a different manufacturer’s microscope in confocal mode with 1 × 1 binning. No major differences are observed. b, Acquisition of multiple Z planes slightly improves percent replicating but not percent matching in two batches. For more information including the plate(s) represented by each data point, see the Source Data file for this figure; expanded experimental details for each plate may be found in Supplementary Data File 1.
Extended Data Fig. 7 Assesment of Cell Painting performance when using various combinations of channel features.
Mean percent replicating of eight JUMP-MOA plates stained with the final staining conditions after dropping out all feature names containing individual channel names before performing feature selection and calculation of percent replicating. ‘None’ means that only AreaShape features are present. To create a sufficiently compact data representation, the eight channels present were split four each onto the X (AGP, DNA, ER and Mito) and Y (RNA, Brightfield, BFHigh and BFLow) axes; this allows visualization of the 256 possible unique combinations. Note that these results are not the same as truly having the stains not present, because (i) a channel still may have been used in creating the initial segmentation results, and (ii) it does not account for cross-talk between stains. An alternate representation of these data is presented in Extended Data Fig. 8. For more information including the plates represented in this figure, see the Source Data file for this figure; expanded experimental details for each plate may be found in Supplementary Data File 1. AGP, actin golgi plasma membrane; BF, brightfield; Mito, mitochondria.
Extended Data Fig. 8 Change in Cell Painting performance when adding individual channel features.
Change in mean percent replicating of eight JUMP-MOA plates stained with the final staining conditions when an individual stain is present versus not; each chart shows for a particular stain when added to the non-channel-specific features plus zero or more other stains (x axis) the change in the mean percent replicating (y axis) when those features are included. The color(s) of each marker indicate which channel(s) are already present. Note that these results are not the same as truly having the stains not present, because (i) a channel still may have been used in creating the initial segmentation results, and (ii) it does not account for cross-talk between stains. The absolute percent replicating numbers are available in Extended Data Fig. 7. For more information including the plates represented in this figure, see the Source Data file for this figure; expanded experimental details for each plate may be found in Supplementary Data File 1.
Extended Data Fig. 9 Assessment of Cell Painting performance for individual channels and feature categories.
Stain-by-stain breakdown of mean percent replicating of eight JUMP-MOA plates stained with the final staining conditions after dropping out all possible combinations of features from the five stain-specific feature categories before performing feature selection and calculation of percent replicating. Unlike the analyses in Extended Data Fig. 7 and Extended Data Fig. 8, non-channel-specific feature categories (AreaShape and Neighbors) are not included here, because the goal is to assess the information contribution of each feature category in each stain. To create sufficiently compact data representation, the five categories present were split three each onto the X (Correlation, Granularity and Intensity) and two onto the Y (RadialDistribution and Texture) axes; this allows visualization of the 31 possible unique combinations. For more information including the plates represented in this figure, see the Source Data file for this figure; expanded experimental details for each plate may be found in Supplementary Data 1.
Supplementary information
Supplementary Information
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Supplementary Data 1
Treatment, staining and microscopy conditions of all plates included in this work
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Cimini, B.A., Chandrasekaran, S.N., Kost-Alimova, M. et al. Optimizing the Cell Painting assay for image-based profiling. Nat Protoc 18, 1981–2013 (2023). https://doi.org/10.1038/s41596-023-00840-9
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DOI: https://doi.org/10.1038/s41596-023-00840-9
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