SUGAR-Seq enables simultaneous detection of glycans, epitopes and the transcriptome in single cells [TIL scRNA-seq]. SUGAR-Seq enables simultaneous detection of glycans, epitopes and the transcriptome in single cells [TIL scRNA-seq]

Multi-modal single cell RNA sequencing enables the precise mapping of transcriptional and phenotypic features of cellular differentiation states, but does not allow for simultaneous integration of critical post-translational modification data. Here, we describe SUrface-protein Glycan And RNA-seq (SUGAR-seq); a method that enables detection and analysis of N-linked glycosylation, extracellular epitopes and the transcriptome at the single cell level. Integrated SUGAR-seq and glycoproteome analysis identified tumor infiltrating T cells with unique surface glycan properties that report their epigenetic and functional state. Overall design: Single cell sequencing analysis (Including detection of L-Pha lectin) of pooled TILs from B16-Ova and MC38-Ova tumor infiltrating lymphocytes (TILs). The experiment comprises of a single 10x Genomics capture reaction with hashtag 1 marking B16_Ova TILs and hashtag 2 marking MC38-Ova TILs

多模态单细胞RNA测序可精准绘制细胞分化状态的转录组与表型特征图谱，但无法同时整合关键的翻译后修饰数据。本文介绍了表面蛋白聚糖与RNA测序（Surface-protein Glycan And RNA-seq，简称SUGAR-seq）技术，该方法可实现在单细胞层面检测并分析N-连接糖基化、细胞外表位及转录组。通过整合SUGAR-seq与糖蛋白组学分析，可识别出具有独特表面聚糖特征的肿瘤浸润T细胞，此类特征可反映其表观遗传与功能状态。
整体实验设计：对来自B16-Ova与MC38-Ova肿瘤的混合肿瘤浸润淋巴细胞（tumor infiltrating lymphocytes，TILs）开展单细胞测序分析（包含L-Pha凝集素（L-Pha lectin）检测）。本实验仅包含一次10x Genomics捕获反应，其中标签1标记B16_Ova TILs，标签2标记MC38-Ova TILs