Live-seq for live cell transcriptome profiling
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA591913 | ENA |
REPOSITORIES: ENA
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Project description:Single-cell RNA-seq (scRNA-seq) has greatly advanced the characterization of cellular heterogeneity in physiological and pathological conditions. However, since cells are lysed and can thus only be profiled once, it is currently impossible to perform downstream functional assays on the same cells and to obtain a direct scRNA-seq-based read-out of transcriptional dynamics. Here, we present Live-seq, a novel single cell transcriptomic biopsy approach based on fluidic force microscopy that differs from other scRNA-seq methods because the cells can be kept alive for further analysis. We demonstrate that live-seq allows the identification of both cell types and states. In addition, when coupled to an inverted optical microscope, it uniquely enables linking single cell transcriptomes to downstream functional properties through real-time imaging.
2022-05-01 | GSE141064 | GEO
Project description:Erythroblasts cultured from mobilized CD34+ cells from six healthy adult human donors were used to generate an erythroblast transcriptome. Cellular maturation was maintained including enucleation. On culture day 14 total RNA was isolated (see PMID: 23798711 for details). These RNA-Seq profiles were generated after flow cytometric sorting (live cell gating of culture Day 14 erythroblasts according to forward and side scatter).
2017-02-01 | GSE93814 | GEO
Project description:Erythroblasts cultured from six healthy commercial available cord blood CD34+ cells were used to generate an cord blood erythroblast transcriptome. Cellular maturation was maintained including enucleation. On culture day 14 total RNA was isolated (see PMID: 23798711 for details). These RNA-Seq profiles were generated after flow cytometric sorting (live cell gating of culture Day 14 erythroblasts according to forward and side scatter).
2017-02-01 | GSE93960 | GEO
Project description:Transcriptome profiling is an indispensable tool in advancing the understanding of single cell biology, but depends upon methods capable of isolating mRNA at the spatial resolution of a single cell. Current capture methods lack sufficient spatial resolution to isolate mRNA from individual in vivo resident cells without damaging adjacent tissue. Because of this limitation, it has been difficult to assess the influence of the microenvironment on the transcriptome of individual neurons. Here, we engineered a Transcriptome In Vivo Analysis (TIVA)-tag, which upon photoactivation enables mRNA capture from single cells in live tissue. Using the TIVA-tag in combination with RNA-seq to analyze transcriptome variance among single dispersed cells and in vivo resident mouse and human neurons, we show that the tissue microenvironment shapes the transcriptomic landscape of individual cells. The TIVA methodology provides the first noninvasive approach for capturing mRNA from single cells in their natural microenvironment. Samples represent cortex and hippocampus neuron cells collected by pipette and TIVA captured.
2014-01-12 | E-GEOD-52525 | biostudies-arrayexpress
Project description:<p>Droplet-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 $575. 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 5 rheumatoid arthritis patients. We sequenced 20,387 single cells from synovectomies, revealing 13 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.</p> <p>Reprinted from [Stephenson et al., Nature Communications, 2018], with permission from the Nature Publishing Group.</p>
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Project description: Not available
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Project description:Transcriptome profiling of Mantle Cell Lymphoma and healthy controls using RNA-seq
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