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Simultaneous Quantification of Single-Cell Proteomes and Transcriptomes in Integrated Fluidic Circuits.

Mandi Wong1, Carol Kosman2, Liane Takahashi2

  • 1Fluidigm Corporation, South San Francisco, CA, USA. mandi.wong@fluidigm.com.

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|November 12, 2021
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Summary

Researchers can now simultaneously measure RNA and protein levels in single cells using the RNA expression and protein sequencing assay (REAP-seq). This method uses DNA-tagged antibodies for high-plex protein analysis, integrated with the Fluidigm C1 system.

Keywords:
Gene expressionGenomicsImmunologyLymphocytesMethodsMulti-omicsProtein expressionREAP-seqRNASequencingSingle cell analysis

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Area of Science:

  • Single-cell biology
  • Molecular biology
  • Genomics

Background:

  • Gene regulation studies require integrating multiple data types at single-cell resolution.
  • Single-cell multi-omic technologies are advancing, enabling combined measurements.
  • Existing methods have limitations in multiplexing protein targets.

Purpose of the Study:

  • To describe the implementation of the RNA expression and protein sequencing assay (REAP-seq).
  • To enable simultaneous measurement of protein and gene expression in single cells.
  • To integrate REAP-seq with the Fluidigm C1 mRNA Seq HT system.

Main Methods:

  • RNA expression and protein sequencing assay (REAP-seq) utilizing DNA-barcoded antibodies.
  • Antibodies conjugated to unique DNA sequences for protein detection.
  • Implementation on the Fluidigm C1 mRNA Seq HT (high-throughput) v2 system.

Main Results:

  • Simultaneous analysis of protein and gene expression within individual cells is achievable.
  • REAP-seq allows for high-plex protein quantification (up to 65,536 unique barcodes).
  • Successful integration of REAP-seq with a high-throughput single-cell RNA sequencing platform.

Conclusions:

  • REAP-seq offers a powerful approach for single-cell multi-omic analysis.
  • This method overcomes limitations of traditional protein detection techniques like fluorescence.
  • The described implementation facilitates deeper understanding of gene regulation at the single-cell level.