Glyco Atlas Supplemental Tables (Leo Alexander Dworkin) PhD Thesis

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 testing usage of single cell transcriptomics to break this barrier. We investigated how single cell RNA-seq data can be used to characterise the state of the glycosylation machinery and metabolic network in single cell. The metabolic network involves 214 glycosylation and modification enzymes with their contributions to the glycome 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.糖基化（glycosylation）的复杂多步骤过程可在单个细胞内完成，但当前分析技术普遍无法检测单个细胞的糖基化产物——糖组（glycome）。本研究针对这一技术与现实的矛盾，探索利用单细胞转录组学（single cell transcriptomics）突破该瓶颈。我们探究了单细胞RNA测序（single cell RNA-seq）数据如何用于表征单细胞内糖基化相关机制与代谢网络的状态。本次研究涉及的代谢网络包含214种糖基化与修饰酶，相关酶类对糖组的贡献已在我们此前构建的细胞糖基化通路图谱中得到明确阐明。我们在器官与单细胞层面研究了酶类的mRNA差异调控规律，发现绝大多数通用蛋白质与脂质寡糖骨架的合成，由细胞间转录调控程度有限的酶类所介导。我们预测，不同糖基化通路中的关键酶类会受到高度转录调控，成为细胞糖组的可调控热点。我们开发了Glycopacity软件，可帮助研究人员从转录组数据中提取并解析糖基化相关信息，并定位调控热点。