Brief Communication | Published:

Multiplexed quantification of proteins and transcripts in single cells

Nature Biotechnology volume 35, pages 936939 (2017) | Download Citation

Abstract

We present a tool to measure gene and protein expression levels in single cells with DNA-labeled antibodies and droplet microfluidics. Using the RNA expression and protein sequencing assay (REAP-seq), we quantified proteins with 82 barcoded antibodies and >20,000 genes in a single workflow. We used REAP-seq to assess the costimulatory effects of a CD27 agonist on human CD8+ lymphocytes and to identify and characterize an unknown cell type.

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Acknowledgements

We acknowledge R. Riener for help with staining and profiling Rhesus blood blocked with aCD27 drug.

Author information

Author notes

    • Vanessa M Peterson
    •  & Kelvin Xi Zhang

    These authors contributed equally to this work.

Affiliations

  1. Genetics & Pharmacogenomics, Department of Translational Medicine, Merck & Co., Inc., Boston, Massachusetts, USA.

    • Vanessa M Peterson
    • , Namit Kumar
    • , Lixia Li
    •  & Joel A Klappenbach
  2. Informatics IT, Merck & Co., Inc., Boston, Massachusetts, USA.

    • Kelvin Xi Zhang
  3. Department of Profiling and Expression, Merck & Co., Inc., Palo Alto, California, USA.

    • Jerelyn Wong
    • , Douglas C Wilson
    • , Terrill K McClanahan
    •  & Svetlana Sadekova
  4. Protein Sciences, Department of Biologics, Merck & Co., Inc., Boston, Massachusetts, USA.

    • Renee Moore

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Contributions

V.M.P. and J.A.K. conceived the method. V.M.P., J.A.K, J.W., T.K.M., and S.S. designed experiments. V.M.P, J.W., N.K., D.C.W., L.L., and R.M. conducted experiments. K.X.Z. wrote analysis software. K.X.Z., V.M.P, N.K., J.A.K., R.M., and S.S. analyzed the data. V.M.P., J.A.K., and K.X.Z. wrote the manuscript with input from all authors.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Vanessa M Peterson.

Integrated supplementary information

Supplementary figures

  1. 1.

    Schematic of REAP-seq

  2. 2.

    Schematic of DNA barcoded antibodies.

  3. 3.

    Overview of REAP-seq protein and mRNA library preparation.

  4. 4.

    Validation of REAP-seq protein assay using Anti-mouse IgG beads labeled with AbBs.

  5. 5.

    Evaluation of blocking buffer on non-specific binding of AbB to cells.

  6. 6.

    Evaluation of specificity and non-specific binding in the REAP-seq protein assay.

  7. 7.

    Benchmarking of REAP-seq on PBMCs.

  8. 8.

    REAP-seq gene expression compared to standard scRNA-seq gene expression

  9. 9.

    Evaluating the effect of different conditions on the transcriptome.

  10. 10.

    REAP-seq characterization of ex vivo activation of naïve CD8+ T cells with aCD27

  11. 11.

    Unsupervised clustering of aCD27 treated and untreated cells based on gene expression

  12. 12.

    Differentially expressed proteins and transcripts in aCD27 treated naïve CD8+ T cells

  13. 13.

    Heatmap showing normalized expression of genes (n=61) that were either upregulated or downregulated in the aCD27 treated and untreated cells for all three donors.

  14. 14.

    REAP-seq differential protein expression in aCD27 stimulated cells

  15. 15.

    Differential protein expression in aCD27 stimulated cells

  16. 16.

    Scatter plots looking at the relationship between the change in protein expression and the change in mRNA expression between aCD27 treated and untreated CD8+ naïve T cells for each of the three donors.

  17. 17.

    Comparative analysis of differentially expressed proteins and genes using Gene Set Enrichment Analysis (GSEA, Broad).

  18. 18.

    REAP-seq comparison of mRNA versus protein expression upon aCD27 stimulation in Donor 2

  19. 19.

    Flow cytometry experiment showing aCD27 drug partially blocks anti-CD27 (clone M-T271) from binding CD27

  20. 20.

    Validation of REAP-seq findings using flow cytometry analysis.

  21. 21.

    mRNA and protein correlations in aCD27 treated and untreated naïve CD8+ T cells

  22. 22.

    Differential expression at both the protein and transcript level in the outlier cluster.

  23. 23.

    MetaCore pathway analysis of the outlier cluster in CD8+ naïve T cells (Fig. 2a).

  24. 24.

    Representative live cell gating strategy for flow cytometry data

Supplementary information

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  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–24, Supplementary Tables 1–8, and Supplementary Discussion

  2. 2.

    Life Sciences Reporting Summary

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DOI

https://doi.org/10.1038/nbt.3973

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