DNA-Encoded and Spatial Proximity Replaced Glycoprotein Analysis Reveals Glycosylation Heterogeneity of Extracellular Vesicles.
Ping LiQi ChangMengmeng LiuKe LeiShuai PingJia WangYueqing GuHe RenYi MaPublished in: Analytical chemistry (2023)
Glycosylation of proteins is an essential feature of extracellular vesicles (EVs). However, while the glycosylation heterogeneity focusing on specific EV subtypes and proteins will better reveal the functions of EVs, the determination of their specific glycans remains highly challenging. Herein, we report a method of protein-specific glycan recognition using DNA-encoded affinity ligands to label proteins and glycans. Manipulating the sequences of DNA tags and employing a DNA logic gate to trigger a spatial proximity-induced DNA replacement reaction enabled the release of glycan-representative DNA strands for the quantitative detection of multiple glycoforms. After size-dependent isolation of EV subgroups and decoding of three typical glycoforms on the epithelial growth factor receptor (EGFR), we found that the different EV subgroups of the EGFR glycoprotein varied with respect to glycan types and abundance. The distinctive glycoforms of the EV subgroups could interfere with the EGFR-related EV functions. Furthermore, the sialylation of small EVs possessed the potential as a cancer biomarker. This method provides new insights into the role of protein-specific glycoforms in EV functions.
Keyphrases
- circulating tumor
- cell free
- small cell lung cancer
- growth factor
- single molecule
- epidermal growth factor receptor
- cell surface
- tyrosine kinase
- single cell
- nucleic acid
- machine learning
- binding protein
- cross sectional
- drug induced
- oxidative stress
- papillary thyroid
- deep learning
- gene expression
- small molecule
- protein protein
- mass spectrometry
- dna methylation
- label free
- squamous cell
- real time pcr
- neural network