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

2017 ◽  
Author(s):  
William Stephenson ◽  
Laura T. Donlin ◽  
Andrew Butler ◽  
Cristina Rozo ◽  
Ali Rashidfarrokhi ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Single Cell ◽  
Synovial Tissue ◽  
Low Cost ◽  
Single Cells ◽  
Transcriptome Profiling ◽  
Massively Parallel ◽  
Rna Seq ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

AbstractDroplet-based single cell RNA-seq has emerged as a powerful technique for massively parallel cellular profiling. While these approaches offer the exciting promise to deconvolute cellular heterogeneity in diseased tissues, the lack of cost-effective, reliable, and user-friendly instrumentation has hindered widespread adoption of droplet microfluidic techniques. To address this, we have developed a microfluidic control instrument that can be easily assembled from 3D printed parts and commercially available components costing approximately $540. We adapted this instrument for massively parallel scRNA-seq and deployed it in a clinical environment to perform single cell transcriptome profiling of disaggregated synovial tissue from a rheumatoid arthritis patient. We sequenced 8,716 single cells from a synovectomy, revealing 16 transcriptomically distinct clusters. These encompass a comprehensive and unbiased characterization of the autoimmune infiltrate, including inflammatory T and NK subsets that contribute to disease biology. Additionally, we identified fibroblast subpopulations that are demarcated via THY1 (CD90) and CD55 expression. Further experiments confirm that these represent synovial fibroblasts residing within the synovial intimal lining and subintimal lining, respectively, each under the influence of differing microenvironments. We envision that this instrument will have broad utility in basic and clinical settings, enabling low-cost and routine application of microfluidic techniques, and in particular single-cell transcriptome profiling.

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

2018 ◽  
Vol 9 (1) ◽  
Author(s):  
William Stephenson ◽  
Laura T. Donlin ◽  
Andrew Butler ◽  
Cristina Rozo ◽  
Bernadette Bracken ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Single Cell ◽  
Synovial Tissue ◽  
Low Cost ◽  
Rheumatoid Arthritis Synovial Tissue ◽  
Rna Seq

scholarly journals sNucDrop-Seq: Dissecting cell-type composition and neuronal activity state in mammalian brains by massively parallel single-nucleus RNA-Seq

2017 ◽  
Author(s):  
Peng Hu ◽  
Emily Fabyanic ◽  
Zhaolan Zhou ◽  
Hao Wu
Keyword(s):  
Single Cell ◽  
Neuronal Activity ◽  
Low Cost ◽  
Single Cells ◽  
High Sensitivity ◽  
Droplet Microfluidics ◽  
Massively Parallel ◽  
Rna Seq ◽  
Single Nucleus

Massively parallel single-cell RNA sequencing can precisely resolve cellular diversity in a high-throughput manner at low cost, but unbiased isolation of intact single cells from complex tissues, such as adult mammalian brains, is challenging. Here, we integrate sucrose-gradient assisted nuclear purification with droplet microfluidics to develop a highly scalable single-nucleus RNA-Seq approach (sNucDrop-Seq), which is free of enzymatic dissociation and nucleus sorting. By profiling ~11,000 nuclei isolated from adult mouse cerebral cortex, we demonstrate that sNucDrop-Seq not only accurately reveals neuronal and non-neuronal subtype composition with high sensitivity, but also enables analysis of long non-coding RNAs and transient states such as neuronal activity-dependent transcription at single-cell resolution in vivo.

scholarly journals Pooled CRISPR screening with single-cell transcriptome read-out

2016 ◽  
Author(s):  
Paul Datlinger ◽  
Christian Schmidl ◽  
André F Rendeiro ◽  
Peter Traxler ◽  
Johanna Klughammer ◽  
...  
Keyword(s):  
Single Cell ◽  
Selectable Marker ◽  
Single Cells ◽  
Transcriptome Profiling ◽  
Genetic Screens ◽  
Biological Mechanisms ◽  
Guide Rna ◽  
New Gene ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

AbstractCRISPR-based genetic screens have revolutionized the search for new gene functions and biological mechanisms. However, widely used pooled screens are limited to simple read-outs of cell proliferation or the production of a selectable marker protein. Arrayed screens allow for more complex molecular read-outs such as transcriptome profiling, but they provide much lower throughput. Here we demonstrate CRISPR genome editing together with single-cell RNA sequencing as a new screening paradigm that combines key advantages of pooled and arrayed screens. This approach allowed us to link guide-RNA expression to the associated transcriptome responses in thousands of single cells using a straightforward and broadly applicable screening workflow.

scholarly journals Targeting individual cells by barcode in pooled sequence libraries

2017 ◽  
Author(s):  
Navpreet Ranu ◽  
Alexandra-Chloé Villani ◽  
Nir Hacohen ◽  
Paul C. Blainey
Keyword(s):  
Single Cell ◽  
Mononuclear Cells ◽  
Single Cells ◽  
Dna Barcodes ◽  
Rna Seq ◽  
Enrichment Method ◽  
Peripheral Blood Mononuclear ◽  
Efficient Sampling ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

There is rising interest in applying single-cell transcriptome analysis and other single-cell sequencing methods to resolve differences between cells. Pooled processing of thousands of single cells is now routinely practiced by introducing cell-specific DNA barcodes early in cell processing protocols1-5. However, researchers must sequence a large number of cells to sample rare subpopulations6-8, even when fluorescence-activated cell sorting (FACS) is used to pre-enrich rare cell populations. Here, a new molecular enrichment method is used in conjunction with FACS enrichment to enable efficient sampling of rare dendritic cell (DC) populations, including the recently identified AXL+SIGLEC6+ (AS DCs) subset7, within a 10X Genomics single-cell RNA-Seq library. DC populations collectively represent 1-2% of total peripheral blood mononuclear cells (PBMC), with AS DC representing only 1-3% of human blood DCs and 0.01-0.06% of total PBMCs.

scholarly journals Single-cell transcriptome profiling of the Ciona larval brain

2018 ◽  
Author(s):  
Sarthak Sharma ◽  
Wei Wang ◽  
Alberto Stolfi
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Expression Patterns ◽  
Transcriptome Profiling ◽  
Specific Gene ◽  
Larval Brain ◽  
Rnaseq Data ◽  
Cell Type Specific ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

AbstractThe tadpole-type larva of Ciona has emerged as an intriguing model system for the study of neurodevelopment. The Ciona intestinalis connectome has been recently mapped, revealing the smallest central nervous system (CNS) known in any chordate, with only 177 neurons. This minimal CNS is highly reminiscent of larger CNS of vertebrates, sharing many conserved developmental processes, anatomical compartments, neuron subtypes, and even specific neural circuits. Thus, the Ciona tadpole offers a unique opportunity to understand the development and wiring of a chordate CNS at single-cell resolution. Here we report the use of single-cell RNAseq to profile the transcriptomes of single cells isolated by fluorescence-activated cell sorting (FACS) from the whole brain of Ciona robusta (formerly intestinalis Type A) larvae. We have also compared these profiles to bulk RNAseq data from specific subsets of brain cells isolated by FACS using cell type-specific reporter plasmid expression. Taken together, these datasets have begun to reveal the compartment- and cell-specific gene expression patterns that define the organization of the Ciona larval brain.

scholarly journals A flexible microfluidic system for single-cell transcriptome profiling elucidates phased transcriptional regulators of cell cycle

2020 ◽  
Author(s):  
Karen Davey ◽  
Daniel Wong ◽  
Filip Konopacki ◽  
Eugene Kwa ◽  
Heike Fiegler ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Single Cell ◽  
Regulatory Networks ◽  
Single Cells ◽  
Transcriptome Profiling ◽  
Cost Effective ◽  
Microfluidic System ◽  
Cellular Systems ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

SummarySingle cell transcriptome profiling has emerged as a breakthrough technology for the high-resolution understanding of complex cellular systems. Here we report a flexible, cost-effective and user-friendly droplet-based microfluidics system, called the Nadia Instrument, that can allow 3’ mRNA capture of ∼50,000 single cells or individual nuclei in a single run. The precise pressure-based system demonstrates highly reproducible droplet size, low doublet rates and high mRNA capture efficiencies that compare favorably in the field. Moreover, when combined with the Nadia Innovate, the system can be transformed into an adaptable setup that enables use of different buffers and barcoded bead configurations to facilitate diverse applications. Finally, by 3’ mRNA profiling asynchronous human and mouse cells at different phases of the cell cycle, we demonstrate the system’s ability to readily distinguish distinct cell populations and infer underlying transcriptional regulatory networks. Notably this identified multiple transcription factors that had little or no known link to the cell cycle (e.g. DRAP1, ZKSCAN1 and CEBPZ). In summary, the Nadia platform represents a promising and flexible technology for future transcriptomic studies, and other related applications, at cell resolution.

scholarly journals Single cell transcriptome profiling of mouse and hESC-derived pancreatic progenitors

2018 ◽  
Author(s):  
Nicole A. J. Krentz ◽  
Michelle Lee ◽  
Eric E. Xu ◽  
Shugo Sasaki ◽  
Francis C. Lynn
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Differential Expression Analysis ◽  
Embryonic Stem ◽  
Transcriptome Profiling ◽  
Β Cells ◽  
Pancreatic Progenitors ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome ◽  
Endocrine Progenitors

SummaryHuman embryonic stem cells (hESCs) are a potential unlimited source of insulin-producing β-cells for diabetes treatment. A greater understanding of how β-cells form during embryonic development will improve current hESC differentiation protocols. As β-cells are formed from NEUROG3-expressing endocrine progenitors, this study focused on characterizing the single-cell transcriptomes of mouse and hESC-derived endocrine progenitors. To do this, 7,223 E15.5 and 6,852 E18.5 single cells were isolated from Neurog3-Cre; Rosa26mT/mG embryos, allowing for enrichment of endocrine progenitors (yellow; tdTomato + EGFP) and endocrine cells (green; EGFP). From a NEUROG3-2A-eGFP CyT49 hESC reporter line (N5-5), 4,497 hESC-derived endocrine progenitor cells were sequenced. Differential expression analysis reveals enrichment of markers that are consistent with progenitor, endocrine, or novel cell-state populations. This study characterizes the single-cell transcriptomes of mouse and hESC-derived endocrine progenitors and serves as a resource (https://lynnlab.shinyapps.io/embryonic_pancreas/) for improving the formation of functional β-like cells from hESCs.

scholarly journals Single-cell proteomics reveals changes in expression during hair-cell development

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Ying Zhu ◽  
Mirko Scheibinger ◽  
Daniel Christian Ellwanger ◽  
Jocelyn F Krey ◽  
Dongseok Choi ◽  
...  
Keyword(s):  
Single Cell ◽  
Hair Cells ◽  
De Novo ◽  
Single Cells ◽  
Transcriptome Profiling ◽  
Developmental Trajectory ◽  
Proteomics Data ◽  
Sensory Hair Cells ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

Hearing and balance rely on small sensory hair cells that reside in the inner ear. To explore dynamic changes in the abundant proteins present in differentiating hair cells, we used nanoliter-scale shotgun mass spectrometry of single cells, each ~1 picoliter, from utricles of embryonic day 15 chickens. We identified unique constellations of proteins or protein groups from presumptive hair cells and from progenitor cells. The single-cell proteomes enabled the de novo reconstruction of a developmental trajectory using protein expression levels, revealing proteins that greatly increased in expression during differentiation of hair cells (e.g., OCM, CRABP1, GPX2, AK1, GSTO1) and those that decreased during differentiation (e.g., TMSB4X, AGR3). Complementary single-cell transcriptome profiling showed corresponding changes in mRNA during maturation of hair cells. Single-cell proteomics data thus can be mined to reveal features of cellular development that may be missed with transcriptomics.

scholarly journals A flexible microfluidic system for single-cell transcriptome profiling elucidates phased transcriptional regulators of cell cycle

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Karen Davey ◽  
Daniel Wong ◽  
Filip Konopacki ◽  
Eugene Kwa ◽  
Tony Ly ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Single Cell ◽  
Regulatory Networks ◽  
Single Cells ◽  
Transcriptome Profiling ◽  
Cost Effective ◽  
Microfluidic System ◽  
Cellular Systems ◽  
Cell Transcriptome ◽  
Single Cell Transcriptome

AbstractSingle cell transcriptome profiling has emerged as a breakthrough technology for the high-resolution understanding of complex cellular systems. Here we report a flexible, cost-effective and user-friendly droplet-based microfluidics system, called the Nadia Instrument, that can allow 3′ mRNA capture of ~ 50,000 single cells or individual nuclei in a single run. The precise pressure-based system demonstrates highly reproducible droplet size, low doublet rates and high mRNA capture efficiencies that compare favorably in the field. Moreover, when combined with the Nadia Innovate, the system can be transformed into an adaptable setup that enables use of different buffers and barcoded bead configurations to facilitate diverse applications. Finally, by 3′ mRNA profiling asynchronous human and mouse cells at different phases of the cell cycle, we demonstrate the system's ability to readily distinguish distinct cell populations and infer underlying transcriptional regulatory networks. Notably this provided supportive evidence for multiple transcription factors that had little or no known link to the cell cycle (e.g. DRAP1, ZKSCAN1 and CEBPZ). In summary, the Nadia platform represents a promising and flexible technology for future transcriptomic studies, and other related applications, at cell resolution.

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