Low-input, deterministic profiling of single-cell transcriptomes reveals individual intestinal organoid subtypes comprised of single, dominant cell types
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus Homo sapiens
PROVIDER: GSE148093 | GEO | 2021/11/10
REPOSITORIES: GEO
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Project description:High-throughput single-cell RNA-sequencing (scRNA-seq) has transformed our ability to resolve cellular properties across systems. A key scRNA-seq catalyzer was the introduction of microdroplet-based systems, which vastly improved sample handling and cell throughput. While powerful, the current microfluidic systems are limited to high cell density (>1000 cells) samples. This prevents the efficient processing of individual, small tissues or rare cells, leading to respectively confounded mosaic cell population read-outs or failed capture of diagnostically interesting cells. In this study, we developed a deterministic, mRNA-capture bead and cell co-encapsulation droplet system, DisCo, that overcomes these limitations by enabling precise particle position and droplet sorting control through combined machine-vision and multilayer microfluidics. We demonstrate that DisCo is capable of processing samples containing few cells (< 100 cells) at high efficiencies( >70%). To underscore the unique capabilities of DisCo, we mapped the developmental process of 31 individual intestinal organoids at the single cell level. This uncovered extensive cellular heterogeneity among organoids, revealing two so far uncharacterized organoid subtypes, “gobloids” and spheroids, predominantly consisting of respectively Muc2+ goblet and Ly6a+ stem cells. Further Disco data analysis thereby revealed strongly increased Yap1 target gene expression in these spheroids, suggesting mechano sensing as the underlying mechanism for their spontaneous formation. Together, our novel “no-cell-left-behind” platform enables the deterministic processing of input cells, allowing high-resolution snapshots of cellular heterogeneity among rare cells or individual, small tissues or organoids.Together, our novel “no-cell-left-behind” platform enables the deterministic processing of input cells, allowing high-resolution snapshots of cellular heterogeneity among rare cells or individual, small tissues or organoids.
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Project description:High-throughput single-cell RNA-sequencing (scRNA-seq) has transformed our ability to resolve cellular properties across systems. A key scRNA-seq catalyzer was the introduction of microdroplet-based systems, which vastly improved sample handling and cell throughput. While powerful, the current microfluidic systems are limited to high cell density (>1000 cells) samples. This prevents the efficient processing of individual, small tissues or rare cells, leading to respectively confounded mosaic cell population read-outs or failed capture of diagnostically interesting cells. In this study, we developed a deterministic, mRNA-capture bead and cell co-encapsulation droplet system, DisCo, that overcomes these limitations by enabling precise particle position and droplet sorting control through combined machine-vision and multilayer microfluidics. We demonstrate that DisCo is capable of processing samples containing few cells (< 100 cells) at high efficiencies( >70%). To underscore the unique capabilities of DisCo, we mapped the developmental process of 31 individual intestinal organoids at the single cell level. This uncovered extensive cellular heterogeneity among organoids, revealing two so far uncharacterized organoid subtypes, “gobloids” and spheroids, predominantly consisting of respectively Muc2+ goblet and Ly6a+ stem cells. Further Disco data analysis thereby revealed strongly increased Yap1 target gene expression in these spheroids, suggesting mechano sensing as the underlying mechanism for their spontaneous formation. Together, our novel “no-cell-left-behind” platform enables the deterministic processing of input cells, allowing high-resolution snapshots of cellular heterogeneity among rare cells or individual, small tissues or organoids.Together, our novel “no-cell-left-behind” platform enables the deterministic processing of input cells, allowing high-resolution snapshots of cellular heterogeneity among rare cells or individual, small tissues or organoids.
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Project description:Low-input, deterministic profiling of single-cell transcriptomes reveals individual intestinal organoid subtypes comprised of single, dominant cell types
| PRJNA623190 | ENA
Project description:Low-input, deterministic profiling of single-cell transcriptomes reveals individual intestinal organoid subtypes comprised of single, dominant cell types [SPM]
| PRJNA623192 | ENA
Project description:Low-input, deterministic profiling of single-cell transcriptomes reveals individual intestinal organoid subtypes comprised of single, dominant cell types [Dispencell]
| PRJNA623193 | ENA