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Simultaneous Measurement of Surface Proteins and Gene Expression from Single Cells

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T-Cell Receptor Signaling

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2111))

Abstract

Single-cell transcriptomic analysis has become a new and powerful tool to study complex multicellular systems. Single-cell RNA sequencing provides an unbiased classification of heterogeneous cellular states at the transcriptional level, but it does not always correlate to cell-surface protein expression. A recently developed method called cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) simultaneously measures surface proteins and gene expression from single cells. Briefly, based on the existing single-cell sequencing technology, oligonucleotide-labeled antibodies and barcoded primer gel beads are used to bind to corresponding cell-surface proteins and mRNA, respectively. Further, libraries of labeled protein and RNA information are sequenced to integrate cellular protein and transcriptome reads together efficiently. CITE-seq is transforming comprehensive genomic studies into models of causal gene-protein investigation.

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References

  1. Tanay A, Regev A (2017) Scaling single-cell genomics from phenomenology to mechanism. Nature 541(7637):331–338

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Macosko EZ, Basu A, Satija R et al (2015) Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161:1202–1214

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Klein AM, Mazutis L, Akartuna I et al (2015) Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161:1187–1201

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Zheng GX, Terry JM, Belgrader P et al (2017) Massively parallel digital transcriptional profiling of single cells. Nat Commun 8:1–12

    Article  Google Scholar 

  5. Kanter I, Kalisky T (2015) Single cell transcriptomics: methods and applications. Front Oncol 5:53

    Article  PubMed  PubMed Central  Google Scholar 

  6. Liu S, Trapnell C (2016) Single-cell transcriptome sequencing: recent advances and remaining challenges. Version 1. F1000Res 5:F1000 Faculty Rev-182

    PubMed  PubMed Central  Google Scholar 

  7. Jaitin DA, Kenigsberg E, Keren-Shaul H et al (2014) Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Science 343:776–779

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Bendall SC, Davis KL, Amir e-AD et al (2014) Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development. Cell 157:714–725

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Krishnaswamy S, Spitzer MH, Mingueneau M et al (2014) Conditional density-based analysis of T cell signaling in single-cell data. Science 346:1250689

    Article  PubMed  PubMed Central  Google Scholar 

  10. Patel AP, Tirosh I, Trombetta JJ et al (2014) Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science 344:1396–1401

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Grün D, Lyubimova A, Kester L et al (2015) Single-cell messenger RNA sequencing reveals rare intestinal cell types. Nature 525:251–255

    Article  PubMed  Google Scholar 

  12. Pontén F, Gry M, Fagerberg L et al (2009) A global view of protein expression in human cells, tissues, and organs. Mol Syst Biol 5:1–9

    Article  Google Scholar 

  13. Stoeckius M, Hafemeister C, Stephenson W et al (2017) Simultaneous epitope and transcriptome measurement in single cells. Nat Methods 14(9):865–868

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Mimitou E, Cheng A, Montalbano A et al (2019) Expanding the CITE-seq tool-kit: Detection of proteins, transcriptomes, clonotypes and CRISPR perturbations with multiplexing, in a single assay. Nat Methods 16(5):409–412

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgement

This work was supported by NIH grant R01HL137709.

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Correspondence to Kong Chen .

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Luo, J., Erb, C.A., Chen, K. (2020). Simultaneous Measurement of Surface Proteins and Gene Expression from Single Cells. In: Liu, C. (eds) T-Cell Receptor Signaling. Methods in Molecular Biology, vol 2111. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0266-9_3

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  • DOI: https://doi.org/10.1007/978-1-0716-0266-9_3

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-0265-2

  • Online ISBN: 978-1-0716-0266-9

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