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Time-resolved RNA signatures of CD4+ T cells in Parkinson's disease [mRNAarray]

ABSTRACT: We employed time-resolved RNA expression analyses upon the activation of peripheral CD4+ T cells to track and functionally relate changes on cellular signaling in patients at different stages of PD

ORGANISM(S): Homo sapiens

PROVIDER: GSE202665 | GEO | 2023/01/23

REPOSITORIES: GEO

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Time-resolved RNA signatures of CD4+ T cells in Parkinson's disease [microRNAarray]

Project description:We employed time-resolved microRNA expression analyses upon the activation of peripheral CD4+ T cells to track and functionally relate changes on cellular signaling in patients at different stages of PD

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Time-resolved RNA signatures of CD4+ T cells in Parkinson's disease.

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Time-resolved RNA signatures of CD4+ T cells in Parkinson's disease

Project description:This SuperSeries is composed of the SubSeries listed below.

2023-01-23 | GSE202667 | GEO

Time-resolved assessment of single-cell protein secretion by sequencing

Project description:Secreted proteins play critical roles in cellular communication. Methods enabling concurrent measurement of cellular protein secretion, phenotypes and transcriptomes are still unavailable. Here, we describe Time-Resolved Assessment of Protein Secretion from single cells by sequencing (TRAPS-seq). Released proteins are trapped onto cell surface and probed by oligonucleotide-barcoded antibodies before simultaneously sequenced with transcriptomes in single cells. TRAPS-seq unravels the phenotypic and transcriptional determinants of the secretion of pleiotropic Th1 cytokines (IFN-γ, IL-2 and TNF-α) in activated T cells. We further demonstrate the use of TRAPS-seq to track dynamic secretion of multiple cytokines over time, uncovering unique molecular signatures that govern the preservation or transition of single-cell cytokine secretions. Our results revealed that early central memory T cells with CD45RA expression (TCMRA) are important in both the production and maintenance of polyfunctional cytokines. TRAPS-seq presents a unique tool for seamless integration of secretomics measurement with multi-omics profiling in single cells.

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