Boost-DiLeu: Enhanced Isobaric N,N‑Dimethyl Leucine Tagging Strategy for a Comprehensive Quantitative Glycoproteomic Analysis

Intact glycopeptide analysis has been of great interest because it can elucidate glycosylation site information and glycan structural composition at the same time. However, mass spectrometry (MS)-based glycoproteomic analysis is hindered by the low abundance and poor ionization efficiency of glycopeptides. Relatively large amounts of starting materials are needed for the enrichment, which makes the identification and quantification of intact glycopeptides from samples with limited quantity more challenging. To overcome these limitations, we developed an improved isobaric labeling strategy with an additional boosting channel to enhance N,N-dimethyl leucine (DiLeu) tagging-based quantitative glycoproteomic analysis, termed as Boost-DiLeu. With the integration of a one-tube sample processing workflow and high-pH fractionation, 3514 quantifiable N-glycopeptides were identified from 30 μg HeLa cell tryptic digests with reliable quantification performance. Furthermore, this strategy was applied to human cerebrospinal fluid (CSF) samples to differentiate N-glycosylation profiles between Alzheimer’s disease (AD) patients and non-AD donors. The results revealed processes and pathways affected by dysregulated N-glycosylation in AD, including platelet degranulation, cell adhesion, and extracellular matrix, which highlighted the involvement of N-glycosylation aberrations in AD pathogenesis. Moreover, weighted gene coexpression network analysis (WGCNA) showed nine modules of glycopeptides, two of which were associated with the AD phenotype. Our results demonstrated the feasibility of using this strategy for in-depth glycoproteomic analysis of size-limited clinical samples. Taken together, we developed and optimized a strategy for the enhanced comprehensive quantitative intact glycopeptide analysis with DiLeu labeling, showing significant promise for identifying novel therapeutic targets or biomarkers in biological systems with a limited sample quantity.完整糖肽分析一直备受学界关注，因其可同时阐明糖基化位点信息与聚糖结构组成。然而，基于质谱（mass spectrometry, MS）的糖蛋白质组学分析常受限于糖肽丰度较低、电离效率欠佳的问题。富集流程通常需要大量起始样本，这使得从有限量样本中鉴定并定量完整糖肽的难度显著提升。为克服上述局限，本研究开发了一种改进的同量异位素标记策略，引入额外的增强通道以优化基于N,N-二甲基亮氨酸（N,N-dimethyl leucine, DiLeu）标记的定量糖蛋白质组学分析方法，将其命名为Boost-DiLeu。结合单管样品处理流程与高pH分级分离技术，我们从30 μg海拉细胞胰蛋白酶消化物中鉴定出3514种可定量的N-糖肽，且定量性能可靠。此外，该策略被应用于人脑脊液（cerebrospinal fluid, CSF）样本，以区分阿尔茨海默病（Alzheimer’s disease, AD）患者与非AD供体的N-糖基化谱。研究结果揭示了阿尔茨海默病中N-糖基化失调所影响的生物学过程与通路，包括血小板脱颗粒、细胞黏附与细胞外基质相关通路，这凸显了N-糖基化异常在阿尔茨海默病发病机制中的重要作用。进一步的加权基因共表达网络分析（weighted gene coexpression network analysis, WGCNA）显示存在9个糖肽共表达模块，其中2个模块与阿尔茨海默病表型显著相关。本研究结果证实了该策略可用于实现有限量临床样本的深度糖蛋白质组学分析。综上，本研究开发并优化了一种基于DiLeu标记的增强型综合定量完整糖肽分析策略，在样本量有限的生物系统中，该方法在发掘新型治疗靶点或生物标志物方面展现出极具潜力的应用价值。