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Physically interacting beta-delta pairs in the regenerating pancreas revealed by single-cell sequencing

ABSTRACT: Physically interacting beta-delta pairs in the regenerating pancreas revealed by single-cell sequencing

PROVIDER: PRJNA762008 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR15831069_1.fastq.gz	Fastqsanger.gz
	SRR15831069_2.fastq.gz	Fastqsanger.gz
	SRR15831070_1.fastq.gz	Fastqsanger.gz
	SRR15831070_2.fastq.gz	Fastqsanger.gz
	SRR15831071_1.fastq.gz	Fastqsanger.gz

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Physically interacting beta-delta pairs in the regenerating pancreas revealed by single-cell sequencing

Project description:We report that delta cells are Sox9 descendants that expand at the periphery of the regenerating islets following partial pancreatectomy. We further characterize regeneration-driven heterogeneity of beta cells at a single-cell resolution, demonstrating sub-populations of ER-stressed, proliferating and highly-functioning beta-cells. We further systematically map sub populations of beta-cells that are paired with other endocrine cell types. Our analysis suggests that the particular cluster of beta-cells that pair with delta-cells benefits from stress protection, implying that the interaction between beta and delta-cells safeguards against regeneration-associated challenges.

2021-09-10 | GSE183788 | GEO

Dissecting cellular crosstalk by sequencing physically interacting cells

Project description:Crosstalk between neighboring cells underlines many biological processes, such as cell activation, differentiation and signaling. Current single-cell genomic technologies lack information of cell-cell interactions, as each cell is profiled separately following tissue dissociation. Here we present Physically Interacting Cells sequencing (PIC-seq), which combines fluorescently activated cell sorting of physically interacting cells along with massively parallel single-cell RNA-sequencing and computational modeling to systematically map in situ cellular interactions and characterize their molecular crosstalk. Focusing on interactions between T cells and dendritic cells (DC) in vitro and in vivo, we map T-DC interaction preferences, and discover regulatory T cells as the major T cell subtype interacting with DC. Analysis of T-DC pairs characterized interaction-specific transcription, including upregulation of a costimulatory program in rare interactions between pathogen-presenting DC and T cells. In summary, PIC-seq provides a new technology to profile cell-cell interactions and characterize interaction-specific pathways and target genes at high resolution.

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Dissecting cellular crosstalk by sequencing physically interacting cells

Project description:Dissecting cellular crosstalk by sequencing physically interacting cells

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Identification of mRNA subsets interacting to RNA binding proteins in regenerating axons

Project description:The goal of this study is to compare the mRNA interactome of different RBPs in regenerating axons utilizing RNA-immunoprecipitation (RIP). Interacting mRNAs to each target RBPs were co-immunoprecipitated from axoplasm of sciatic nerve, injured 7 days ago. Interactome of each RBPs were identified by Next-generation sequencing (NGS).

2018-12-21 | GSE103444 | GEO

Physically interacting cell sequencing of mouse embryonic endoderm at E7.5, E8.5, and E9.5

Project description:Physically interacting cell sequencing of mouse embryonic endoderm at E7.5, E8.5, and E9.5

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Physically interacting cell sequencing of mouse embryonic endoderm at E7.5, E8.5, and E9.5

Project description:Cells continuously communicate with the neighboring cells during development. Direct interaction of different cell types can induce molecular signals dictating lineage specification and cell fate decisions. The current single-cell RNAseq (scRNAseq) technology cannot study cell contact dependent (or niche specific) gene expression due to the loss of spatial information. To overcome this issue and determine cell contact specific gene expression during embryogenesis, we performed RNA sequencing of physically interacting cells (PICseq) and assessed alongside our single cell transcriptomes (scRNAseq) derived from developing mouse embryos between embryonic day (E) 7.5 and E9.5. Analysis of PICseq data identifies an interesting suite of gene expression signatures depending on neighboring cell types. For instance, neural progenitor (NP) cells expressed Nkx2-1 when interacting with definitive endoderm (DE) and DE cells expressed Gsc when interacting with NP. Based on the identified cell contact specific genes, we devised a means to predict the neighboring cell types from individual cell transcriptome. We further developed spatial-tSNE to show the pseudo-spatial distribution of cells in a 2-dimensional space. In sum, we suggest an approach to study niche specific gene regulation during embryogenesis.

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Project description:Our aim was to identify Regenerating islet-derived (REG proteins in dogs. We annotated REG-family members in the canine genome and proteome, and identified one member of the REG3 subfamily, consequently termed REG3E by the Vertebrate Gene Nomenclature Committee. We verified REG3E gene expression using publicly available RNA-seq data (www.barkbase.org). We investigated the presence of REG3E protein in canine pancreatic tissue and plasma with Western blot and immunohistochemistry, using anti-human REG3A antibodies. Protein identity was subsequently confirmed with mass spectrometry on canine pancreas homogenates and plasma.

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