Glycan Sequencing Based on Glycosidase-Assisted Nanopore Sensing

作者：Guangda Yao, Bingqing Xia, Fangyu Wei, Jiahong Wang, Yuting Yang, Shengzhou Ma, Wenjun Ke, Tiehai Li, Xi Cheng, Liuqing Wen, Yi‐Tao Long, Zhaobing Gao · 发表于：Journal of the American Chemical Society · 年份：2025 · DOI：10.1021/jacs.4c12940 · 被引用次数：27 · 研究领域：Nanopore and Nanochannel Transport Studies、Microfluidic and Capillary Electrophoresis Applications、Genomics and Phylogenetic Studies

Nanopores are promising sensors for glycan analysis with the accurate identification of complex glycans laying the foundation for nanopore-based sequencing. However, their applicability toward continuous glycan sequencing has not yet been demonstrated. Here, we present a proof-of-concept of glycan sequencing by combining nanopore technology with glycosidase-hydrolyzing reactions. By continuously monitoring the changes in the characteristic current generated by the translocation of glycan hydrolysis products through a nanopore, the glycan sequence can be accurately identified based on the specificity of glycosidases. With machine learning, we improved the sequencing accuracy to over 98%, allowing for the reliable determination of consecutive building blocks and glycosidic linkages of glycan chains while reducing the need for operator expertise. This approach was validated on real glycan samples, with accuracy calibrated using hydrophilic interaction chromatography-high-performance liquid chromatography (HILIC-HPLC) and mass spectrometry (MS). We achieved the sequencing of ten consecutive units in natural glycan chains, which provided the first evidence for the feasibility of a nanopore-glycosidase-compatible system in glycan sequencing. Compared to traditional methods, this strategy enhances sequencing efficiency by over 5-fold. Additionally, we introduced the concept of 'inverse sequencing', which focuses on electrical signal changes rather than monosaccharide identification....