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Single-cell RNA-seq of rheumatoid arthritis synovial tissue using low-cost microfluidic instrumentation

Author

Listed:
  • William Stephenson

    (New York Genome Center)

  • Laura T. Donlin

    (Hospital for Special Surgery
    Weill Cornell Medical College)

  • Andrew Butler

    (New York Genome Center
    Center for Genomics and Systems Biology)

  • Cristina Rozo

    (Hospital for Special Surgery)

  • Bernadette Bracken

    (New York Genome Center
    Center for Genomics and Systems Biology)

  • Ali Rashidfarrokhi

    (New York Genome Center
    New York University School of Medicine)

  • Susan M. Goodman

    (Hospital for Special Surgery
    Weill Cornell Medical College)

  • Lionel B. Ivashkiv

    (Hospital for Special Surgery
    Weill Cornell Medical College)

  • Vivian P. Bykerk

    (Hospital for Special Surgery
    Weill Cornell Medical College)

  • Dana E. Orange

    (Hospital for Special Surgery
    Laboratory of Neuro-Oncology, Rockefeller University)

  • Robert B. Darnell

    (New York Genome Center
    Laboratory of Neuro-Oncology, Rockefeller University
    Howard Hughes Medical Institute, Rockefeller University)

  • Harold P. Swerdlow

    (New York Genome Center)

  • Rahul Satija

    (New York Genome Center
    Center for Genomics and Systems Biology)

Abstract

Droplet-based single-cell RNA-seq has emerged as a powerful technique for massively parallel cellular profiling. While this approach offers the exciting promise to deconvolute cellular heterogeneity in diseased tissues, the lack of cost-effective and user-friendly instrumentation has hindered widespread adoption of droplet microfluidic techniques. To address this, we developed a 3D-printed, low-cost droplet microfluidic control instrument and deploy it in a clinical environment to perform single-cell transcriptome profiling of disaggregated synovial tissue from five rheumatoid arthritis patients. We sequence 20,387 single cells revealing 13 transcriptomically distinct clusters. These encompass an unsupervised draft atlas of the autoimmune infiltrate that contribute to disease biology. Additionally, we identify previously uncharacterized fibroblast subpopulations and discern their spatial location within the synovium. We envision that this instrument will have broad utility in both research and clinical settings, enabling low-cost and routine application of microfluidic techniques.

Suggested Citation

  • William Stephenson & Laura T. Donlin & Andrew Butler & Cristina Rozo & Bernadette Bracken & Ali Rashidfarrokhi & Susan M. Goodman & Lionel B. Ivashkiv & Vivian P. Bykerk & Dana E. Orange & Robert B. D, 2018. "Single-cell RNA-seq of rheumatoid arthritis synovial tissue using low-cost microfluidic instrumentation," Nature Communications, Nature, vol. 9(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-017-02659-x
    DOI: 10.1038/s41467-017-02659-x
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    Cited by:

    1. Zhuohan Yu & Yanchi Su & Yifu Lu & Yuning Yang & Fuzhou Wang & Shixiong Zhang & Yi Chang & Ka-Chun Wong & Xiangtao Li, 2023. "Topological identification and interpretation for single-cell gene regulation elucidation across multiple platforms using scMGCA," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    2. Garrett Dunlap & Aaron Wagner & Nida Meednu & Ruoqiao Wang & Fan Zhang & Jabea Cyril Ekabe & Anna Helena Jonsson & Kevin Wei & Saori Sakaue & Aparna Nathan & Vivian P. Bykerk & Laura T. Donlin & Susan, 2024. "Clonal associations between lymphocyte subsets and functional states in rheumatoid arthritis synovium," Nature Communications, Nature, vol. 15(1), pages 1-21, December.

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