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Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators

Nature Biotechnology volume 30, pages 858–867 (2012)Cite this article

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Abstract

Mass cytometry facilitates high-dimensional, quantitative analysis of the effects of bioactive molecules on human samples at single-cell resolution, but instruments process only one sample at a time. Here we describe mass-tag cellular barcoding (MCB), which increases mass cytometry throughput by using n metal ion tags to multiplex up to 2n samples. We used seven tags to multiplex an entire 96-well plate, and applied MCB to characterize human peripheral blood mononuclear cell (PBMC) signaling dynamics and cell-to-cell communication, signaling variability between PBMCs from eight human donors, and the effects of 27 inhibitors on this system. For each inhibitor, we measured 14 phosphorylation sites in 14 PBMC types at 96 conditions, resulting in 18,816 quantified phosphorylation levels from each multiplexed sample. This high-dimensional, systems-level inquiry allowed analysis across cell-type and signaling space, reclassified inhibitors and revealed off-target effects. High-content, high-throughput screening with MCB should be useful for drug discovery, preclinical testing and mechanistic investigation of human disease.

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Figure 1: Mass-tag cell barcoding.
Figure 2: PBMC signaling time-course experiment.
Figure 3: Signaling response comparison of PBMCs from eight donors.
Figure 4: Analysis of PBMC response to kinase inhibition.
Figure 5: Overview of inhibitor impact.
Figure 6: Principal component analysis of cell type and drug response.

Change history

  • 23 August 2012

    In the version of this article initially published online, in the legend for Figure 2e, LPS stimulation was said to be by “NFκB, STAT3 and STAT1,” instead of by “NFκB, STAT3 and BTK/ITK.” The error has been corrected for the print, PDF and HTML versions of this article.

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Acknowledgements

We would like to thank A. Trejo, M. Clutter, K. Gibbs and G. Behbahani for their experimental support and discussions, and D. Pe'er and El-ad D. Amir for their feedback on data analysis. B.B. was supported by fellowships of the Swiss National Science Foundation (SNF), the European Molecular Biology Organization (EMBO), and the Marie Curie IOF. E.R.Z. is supported by a fellowship from National Institute of General Medical Sciences (F32GM093508). T.J.C. is supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program, and the Stanford Graduate Fellowship in Science and Engineering. S.C.B. is supported by the Damon Runyon Cancer Research Foundation Fellowship (DRG-2017-09). G.P.N. is supported by the Rachford and Carlota A. Harris Endowed Professorship and grants from U19 AI057229, P01 CA034233, HHSN272200700038C, 1R01CA130826, CIRM DR1-01477 and RB2-01592, NCI RFA CA 09-011, NHLBI-HV-10-05(2), European Commission HEALTH.2010.1.2-1, and the Bill and Melinda Gates Foundation (GF12141-137101).

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Author notes

  1. Bernd Bodenmiller

    Present address: Present address: Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.,

  2. Bernd Bodenmiller, Eli R Zunder and Rachel Finck: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Microbiology and Immunology, Baxter Laboratory in Stem Cell Biology, Stanford University, Stanford, California, USA

    Bernd Bodenmiller, Eli R Zunder, Rachel Finck, Tiffany J Chen, Erica S Savig, Robert V Bruggner, Erin F Simonds, Sean C Bendall, Karen Sachs, Peter O Krutzik & Garry P Nolan

  2. Biomedical Informatics Program, Stanford University, Stanford, California, USA

    Tiffany J Chen & Robert V Bruggner

  3. Department of Computer Science, Stanford University, Stanford, California, USA

    Tiffany J Chen

  4. Cancer Biology Program, Stanford University, Stanford, California, USA

    Erica S Savig

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Contributions

B.B. conceived and designed the experiments, performed all PBMC experiments, MCB multiplexing and mass cytometry analysis, analyzed the data and wrote the manuscript. E.R.Z. conceived and designed the experiments, developed the mDOTA reagents, performed all PBMC experiments, MCB multiplexing and mass cytometry analysis, analyzed the data and wrote the manuscript. R.F. designed and implemented algorithms and software tools for barcode deconvolution, semi-automatic cell-type gating and dose-response analysis. T.J.C. performed PCA and assisted with data analysis. E.S.S. designed and implemented high-density data visualization. R.V.B. designed and implemented scripts for FCS file processing and assisted with SPADE analysis. E.F.S. assisted with SPADE analysis, designed the 96-well barcoding scheme. S.C.B. assisted with antibody labeling and running the mass cytometer, and high-dimensional analysis of human immune cell populations. K.S. helped with bioinformatic data analysis. P.O.K. conceived cell barcoding for mass cytometry. G.P.N. conceived and designed the experiments, wrote the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Garry P Nolan.

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Competing interests

G.P.N. has personal financial interest in the companies Nodality, DVS Sciences and Becton Dickinson, the manufacturers that produce the reagents or instrumentation used in this manuscript.

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Bodenmiller, B., Zunder, E., Finck, R. et al. Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators. Nat Biotechnol 30, 858–867 (2012). https://doi.org/10.1038/nbt.2317

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