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

William Stephenson(New York Genome Center), Laura T. Donlin(Hospital for Special Surgery), Andrew Butler(New York Genome Center), Cristina Rozo(Hospital for Special Surgery), Bernadette Bracken(New York Genome Center), Ali Rashidfarrokhi(New York Genome Center), Susan M. Goodman(Hospital for Special Surgery), Lionel B. Ivashkiv(Hospital for Special Surgery), Vivian P. Bykerk(Hospital for Special Surgery), Dana E. Orange(Hospital for Special Surgery), Robert B. Darnell(Howard Hughes Medical Institute), Harold Swerdlow(New York Genome Center), Rahul Satija(New York Genome Center)
Nature Communications
February 19, 2018
Cited by 366Open Access
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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.


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