Applying transcriptomics to studyglycosylation at the cell type level
Summary: The complex multi-step process of glycosylation occurs in a single cell, yet current analytics generally cannot measure the output (the glycome) of a single cell. Here, we addressed this discordance by investigating how single cell RNA-seq data can be used to characterize the state of the g...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-06-01
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| Series: | iScience |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004222006903 |
| Summary: | Summary: The complex multi-step process of glycosylation occurs in a single cell, yet current analytics generally cannot measure the output (the glycome) of a single cell. Here, we addressed this discordance by investigating how single cell RNA-seq data can be used to characterize the state of the glycosylation machinery and metabolic network in a single cell. The metabolic network involves 214 glycosylation and modification enzymes outlined in our previously built atlas of cellular glycosylation pathways. We studied differential mRNA regulation of enzymes at the organ and single cell level, finding that most of the general protein and lipid oligosaccharide scaffolds are produced by enzymes exhibiting limited transcriptional regulation among cells. We predict key enzymes within different glycosylation pathways to be highly transcriptionally regulated as regulatable hotspots of the cellular glycome. We designed the Glycopacity software that enables investigators to extract and interpret glycosylation information from transcriptome data and define hotspots of regulation. |
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| ISSN: | 2589-0042 |