{"title":"Single-cell glycome and transcriptome profiling uncovers the glycan signature of each cell subpopulation of human iPSC-derived neurons.","authors":"Haruki Odaka, Hiroaki Tateno","doi":"10.1016/j.stemcr.2025.102631","DOIUrl":null,"url":null,"abstract":"<p><p>Human induced pluripotent stem cell (iPSC)-derived neurons are often heterogeneous, posing challenges for disease modeling and cell therapy. We previously developed single-cell glycan and RNA sequencing (scGR-seq) to analyze the glycome and transcriptome simultaneously. Here, we applied scGR-seq to examine heterogeneous populations of human iPSC-derived neurons. We identified four subpopulations: mature neurons, immature neurons, undifferentiated neural progenitor cells (undiffNPCs), and mesenchymal cells (MCs). Lectin-binding patterns indicated high α1,3-fucose expression in undiffNPCs. MCs exhibited strong binding of a poly-LacNAc-recognizing lectin (rLSLN) and high expression of B3GNT2, a poly-LacNAc synthetic enzyme. Pseudotime analysis revealed that a subpopulation of NPCs acquired mesenchymal features and differentiated into MCs. Immunocytochemistry confirmed the specific detection of undiffNPCs and MCs using anti-Lewis X (α1,3-fucosylated glycan) antibodies and rLSLN. Beyond identifying cell heterogeneity, scGR-seq enables the discovery of glycan markers and detection probes for iPSC-derived cells, aiding in their further cell processing and manipulation.</p>","PeriodicalId":21885,"journal":{"name":"Stem Cell Reports","volume":" ","pages":"102631"},"PeriodicalIF":5.1000,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Stem Cell Reports","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.stemcr.2025.102631","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CELL & TISSUE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
Human induced pluripotent stem cell (iPSC)-derived neurons are often heterogeneous, posing challenges for disease modeling and cell therapy. We previously developed single-cell glycan and RNA sequencing (scGR-seq) to analyze the glycome and transcriptome simultaneously. Here, we applied scGR-seq to examine heterogeneous populations of human iPSC-derived neurons. We identified four subpopulations: mature neurons, immature neurons, undifferentiated neural progenitor cells (undiffNPCs), and mesenchymal cells (MCs). Lectin-binding patterns indicated high α1,3-fucose expression in undiffNPCs. MCs exhibited strong binding of a poly-LacNAc-recognizing lectin (rLSLN) and high expression of B3GNT2, a poly-LacNAc synthetic enzyme. Pseudotime analysis revealed that a subpopulation of NPCs acquired mesenchymal features and differentiated into MCs. Immunocytochemistry confirmed the specific detection of undiffNPCs and MCs using anti-Lewis X (α1,3-fucosylated glycan) antibodies and rLSLN. Beyond identifying cell heterogeneity, scGR-seq enables the discovery of glycan markers and detection probes for iPSC-derived cells, aiding in their further cell processing and manipulation.
人类诱导多能干细胞(iPSC)衍生的神经元通常是异质的,这给疾病建模和细胞治疗带来了挑战。我们之前开发了单细胞聚糖和RNA测序(scGR-seq)来同时分析糖和转录组。在这里,我们应用scGR-seq来检测人类ipsc衍生的神经元的异质群体。我们确定了四个亚群:成熟神经元、未成熟神经元、未分化神经祖细胞(undiffNPCs)和间充质细胞(MCs)。凝集素结合模式显示α1,3在不同npc中高表达。MCs表现出与多聚lacnac识别凝集素(rLSLN)的强结合和多聚lacnac合成酶B3GNT2的高表达。伪时间分析显示,NPCs的一个亚群获得了间充质特征并分化为MCs。免疫细胞化学证实了抗lewis X (α1,3- focusylated glycan)抗体和rLSLN对无差异npc和MCs的特异性检测。除了识别细胞异质性外,scGR-seq还可以为ipsc衍生细胞发现聚糖标记物和检测探针,帮助其进一步进行细胞加工和操作。
期刊介绍:
Stem Cell Reports publishes high-quality, peer-reviewed research presenting conceptual or practical advances across the breadth of stem cell research and its applications to medicine. Our particular focus on shorter, single-point articles, timely publication, strong editorial decision-making and scientific input by leaders in the field and a "scoop protection" mechanism are reasons to submit your best papers.