scFTD-seq: freeze-thaw lysis based, portable approach toward highly distributed single-cell 3′ mRNA profiling

Abstract Cellular barcoding of 3′ mRNAs enabled massively parallel profiling of single-cell gene expression and has been implemented in droplet and microwell based platforms. The latter further adds the value for compatibility with low input samples, optical imaging, scalability, and portability. However, cell lysis in microwells remains challenging despite the recently developed sophisticated solutions. Here, we present scFTD-seq, a microchip platform for performing single-cell freeze-thaw lysis directly toward 3′ mRNA sequencing. It offers format flexibility with a simplified, widely adoptable workflow that reduces the number of preparation steps and hands-on time, with the quality of data and cost per sample matching that of the state-of-the-art scRNA-seq platforms. Freeze-thaw, known as an unfavorable lysis method resulting in possible RNA fragmentation, turns out to be fully compatible with 3′ scRNA-seq. We applied it to the profiling of circulating follicular helper T cells implicated in systemic lupus erythematosus pathogenesis. Our results delineate the heterogeneity in the transcriptional programs and effector functions of these rare pathogenic T cells. As scFTD-seq decouples on-chip cell isolation and library preparation, we envision it to allow sampling at the distributed sites including point-of-care settings and downstream processing at centralized facilities, which should enable wide-spread adoption beyond academic laboratories.

[1]  Jens Hjerling-Leffler,et al.  Oligodendrocyte heterogeneity in the mouse juvenile and adult central nervous system , 2016, Science.

[2]  H. Ueno,et al.  Human blood CXCR5(+)CD4(+) T cells are counterparts of T follicular cells and contain specific subsets that differentially support antibody secretion. , 2011, Immunity.

[3]  K. Blenman,et al.  UV‐induced somatic mutations elicit a functional T cell response in the YUMMER1.7 mouse melanoma model , 2017, Pigment cell & melanoma research.

[4]  Somasekar Seshagiri,et al.  Massively parallel nanowell-based single-cell gene expression profiling , 2017, BMC Genomics.

[5]  G. Tsokos,et al.  Increased Levels of NF-ATc2 Differentially Regulate CD154 and IL-2 Genes in T Cells from Patients with Systemic Lupus Erythematosus1 , 2007, The Journal of Immunology.

[6]  Alice Giustacchini,et al.  Distinct myeloid progenitor differentiation pathways identified through single cell RNA sequencing , 2016, Nature Immunology.

[7]  J. Craft Follicular helper T cells in immunity and systemic autoimmunity , 2012, Nature Reviews Rheumatology.

[8]  F. Tang,et al.  Development and applications of single-cell transcriptome analysis , 2011, Nature Methods.

[9]  C. Mackay,et al.  Circulating precursor CCR7(lo)PD-1(hi) CXCR5⁺ CD4⁺ T cells indicate Tfh cell activity and promote antibody responses upon antigen reexposure. , 2013, Immunity.

[10]  Cole Trapnell,et al.  The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells , 2014, Nature Biotechnology.

[11]  Åsa K. Björklund,et al.  The heterogeneity of human CD127+ innate lymphoid cells revealed by single-cell RNA sequencing , 2016, Nature Immunology.

[12]  Rona S. Gertner,et al.  Single-Cell Genomics Unveils Critical Regulators of Th17 Cell Pathogenicity , 2015, Cell.

[13]  A. Regev,et al.  Spatial reconstruction of single-cell gene expression , 2015, Nature Biotechnology.

[14]  Evan Z. Macosko,et al.  Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets , 2015, Cell.

[15]  I. Amit,et al.  Massively Parallel Single-Cell RNA-Seq for Marker-Free Decomposition of Tissues into Cell Types , 2014, Science.

[16]  H. Ueno,et al.  Phenotype and functions of memory Tfh cells in human blood. , 2014, Trends in immunology.

[17]  J. C. Love,et al.  A microengraving method for rapid selection of single cells producing antigen-specific antibodies , 2006, Nature Biotechnology.

[18]  Allon M. Klein,et al.  Droplet Barcoding for Single-Cell Transcriptomics Applied to Embryonic Stem Cells , 2015, Cell.

[19]  E. Bonfá,et al.  Circulating Follicular Helper–Like T Cells in Systemic Lupus Erythematosus: Association With Disease Activity , 2015, Arthritis & rheumatology.

[20]  Rona S. Gertner,et al.  Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells , 2013, Nature.

[21]  Rebecca Hodge,et al.  STRT-seq-2i: dual-index 5ʹ single cell and nucleus RNA-seq on an addressable microwell array , 2017, bioRxiv.

[22]  J. C. Love,et al.  Seq-Well: A Portable, Low-Cost Platform for High-Throughput Single-Cell RNA-Seq of Low-Input Samples , 2017 .

[23]  Ambrose Carr,et al.  Scalable microfluidics for single-cell RNA printing and sequencing , 2015, Genome Biology.

[24]  D. Pe’er,et al.  Highly multiplexed profiling of single-cell effector functions reveals deep functional heterogeneity in response to pathogenic ligands , 2015, Proceedings of the National Academy of Sciences.

[25]  S. Linnarsson,et al.  Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq , 2015, Science.

[26]  Numrin Thaitrong,et al.  Integrated microfluidic bioprocessor for single-cell gene expression analysis , 2008, Proceedings of the National Academy of Sciences.

[27]  H. Ueno,et al.  Pathophysiology of T follicular helper cells in humans and mice , 2015, Nature Immunology.

[28]  Grace X. Y. Zheng,et al.  Massively parallel digital transcriptional profiling of single cells , 2016, Nature Communications.

[29]  Gioele La Manno,et al.  Quantitative single-cell RNA-seq with unique molecular identifiers , 2013, Nature Methods.

[30]  P. Marrack,et al.  Memory CD4 T Cells That Express CXCR5 Provide Accelerated Help to B Cells , 2011, The Journal of Immunology.

[31]  Sean C. Bendall,et al.  Single-Cell Trajectory Detection Uncovers Progression and Regulatory Coordination in Human B Cell Development , 2014, Cell.

[32]  Junhyong Kim,et al.  The promise of single-cell sequencing , 2013, Nature Methods.

[33]  R. Satija,et al.  Single-cell RNA sequencing to explore immune cell heterogeneity , 2017, Nature Reviews Immunology.

[34]  S. Gendler,et al.  Defective production of interleukin 1 and interleukin 2 in patients with systemic lupus erythematosus (SLE). , 1983, Journal of immunology.

[35]  Paul Hoffman,et al.  Integrating single-cell transcriptomic data across different conditions, technologies, and species , 2018, Nature Biotechnology.

[36]  S. P. Fodor,et al.  Combinatorial labeling of single cells for gene expression cytometry , 2015, Science.

[37]  Michael Poidinger,et al.  Identification of cDC1- and cDC2-committed DC progenitors reveals early lineage priming at the common DC progenitor stage in the bone marrow , 2015, Nature Immunology.

[38]  S. Tangye,et al.  Expansion of circulating T cells resembling follicular helper T cells is a fixed phenotype that identifies a subset of severe systemic lupus erythematosus. , 2010, Arthritis and rheumatism.

[39]  Peter A. Sims,et al.  An Automated Microwell Platform for Large-Scale Single Cell RNA-Seq , 2016, Scientific Reports.

[40]  J. Harley,et al.  Dysregulation of innate and adaptive serum mediators precedes systemic lupus erythematosus classification and improves prognostic accuracy of autoantibodies. , 2016, Journal of autoimmunity.