Nagai-Okatani Chiaki, Tomioka Azusa, Tominaga Daisuke, Sakaue Hiroaki, Kuno Atsushi, Kaji Hiroyuki
Molecular and Cellular Glycoproteomics Research Group, Cellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, 305-8565, Japan.
Institute for Glyco-core Research (iGCORE), Nagoya University, Furo-Cho, Chikusa, Nagoya, Aichi, 464-8601, Japan.
Anal Bioanal Chem. 2025 Feb;417(5):973-988. doi: 10.1007/s00216-024-05686-y. Epub 2024 Dec 16.
To understand the biological and pathological functions of protein glycosylation, the glycan heterogeneities for each glycosite in a single glycoprotein need to be elucidated depending on the type and status of cells. For this aim, a reliable strategy is needed to compare site-specific glycoforms of multiple glycoprotein samples in a comprehensive manner. To analyze this "inter-heterogeneity" of samples, we previously introduced an MS1-based glycopeptide detection method, "Glyco-RIDGE." Here, to elucidate inter-tissue glycan heterogeneities, this estimation method was applied to site-specific N-glycoforms of glycoproteins from six normal mouse tissues (liver, kidney, spleen, pancreas, stomach, and testis). The analyses of desialylated glycopeptides estimated 11,325 site-specific N-glycoforms with 239 glycan compositions at 1260 sites (1122 non-redundant core peptides) in 800 glycoproteins, revealing inter-tissue differences in macro-, micro-, and meta-glycan heterogeneities. To obtain detailed information on their glycan features and tissue distribution, the Glyco-RIDGE results were compared with laser microdissection-assisted lectin microarray (LMD-LMA)-based mouse tissue glycome mapping data deposited on LM-GlycomeAtlas, as well as MS-based mouse tissue glycome data deposited on GlycomeAtlas. This integrated approach supported the certainty of Glyco-RIDGE results and suggested that inter-tissue differences exist in glycan motifs, such as alpha-galactose and bisecting N-acetylglucosamine, in both whole tissue glycomes and specific glycoproteins, Anpep and Lamc1. In addition, the comparison with LMD-LMA-based tissue glycome mapping data suggested the possibility of estimating the tissue distribution of the assigned glycans and glycopeptides. Taken together, these findings demonstrate the utility of an integrated approach using MS assisted by LMA for large-scale analyses.
为了解蛋白质糖基化的生物学和病理学功能，需要根据细胞类型和状态阐明单个糖蛋白中每个糖基化位点的聚糖异质性。为此，需要一种可靠的策略来全面比较多个糖蛋白样品的位点特异性糖型。为了分析样品的这种“相互异质性”，我们之前引入了一种基于MS1的糖肽检测方法“Glyco-RIDGE”。在此，为了阐明组织间聚糖异质性，将这种估算方法应用于来自六种正常小鼠组织（肝脏、肾脏、脾脏、胰腺、胃和睾丸）的糖蛋白的位点特异性N-糖型。对去唾液酸化糖肽的分析估计了800种糖蛋白中1260个位点（1122个非冗余核心肽）的11325种位点特异性N-糖型，其具有239种聚糖组成，揭示了组织间在宏观、微观和元聚糖异质性方面的差异。为了获得关于其聚糖特征和组织分布的详细信息，将Glyco-RIDGE结果与沉积在LM-GlycomeAtlas上的基于激光显微切割辅助凝集素微阵列（LMD-LMA）的小鼠组织糖组图谱数据以及沉积在GlycomeAtlas上的基于质谱的小鼠组织糖组数据进行了比较。这种综合方法支持了Glyco-RIDGE结果的确定性，并表明在整个组织糖组和特定糖蛋白Anpep和Lamac1中，聚糖基序（如α-半乳糖和平分型N-乙酰葡糖胺）存在组织间差异。此外，与基于LMD-LMA的组织糖组图谱数据的比较表明，有可能估算指定聚糖和糖肽的组织分布。综上所述，这些发现证明了使用LMA辅助的质谱进行大规模分析的综合方法的实用性。
