The study of glycoproteomics presents a set of unique challenges, primarily due to the low abundance of glycopeptides and their intricate heterogeneity, which is specific to each site. Glycoproteins play a crucial role in numerous biological functions, including cell signaling, adhesion, and intercellular communication, and are increasingly recognized as vital markers in the diagnosis and study of various diseases. Consequently, a quantitative approach to glycopeptide research is essential. One effective strategy to address this need is the use of multiplex glycopeptide labeling. By harnessing the synergies of (15)N metabolic labeling via the isotopic detection of amino sugars with glutamine (IDAWG) technique for glycan parts and tandem mass tag (TMT)pro labeling for peptide backbones, we have developed a method that allows for the accurate quantification and comparison of multiple samples simultaneously. The adoption of the liquid chromatography-synchronous precursor selection (LC-SPS-MS3) technique minimizes fragmentation interference, enhancing data reliability, as shown by a 97% TMT labeling efficiency. This method allows for detailed, high-throughput analysis of 32 diverse samples from 231BR cell lines, using both (14)N and (15)N glycopeptides at a 1:1 ratio. A key component of our methodology was the precise correction for isotope and TMTpro distortions, significantly improving quantification accuracy to less than 5% distortion. This breakthrough enhances the efficiency and accuracy of glycoproteomic studies, increasing our understanding of glycoproteins in health and disease. Its applicability to various cancer cell types sets a new standard in quantitative glycoproteomics, enabling deeper investigation into glycopeptide profiles.
(15)N metabolic labeling-TMT multiplexing approach to facilitate the quantitation of glycopeptides derived from cell lines.
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作者:Atashi Mojgan, Jiang Peilin, Nwaiwu Judith, Gutierrez Reyes Cristian D, Nguyen Hanh Minh Thu, Li Yunxiang, Ahmadi Parisa, Purba Waziha Tasnim, Mechref Yehia
| 期刊: | Analytical and Bioanalytical Chemistry | 影响因子: | 3.800 |
| 时间: | 2024 | 起止号: | 2024 Jul;416(18):4071-4082 |
| doi: | 10.1007/s00216-024-05352-3 | ||
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