Glycans are vital biomolecules with diverse functions in biological processes. Mass spectrometry (MS) has become the most widely employed technology for glycomics studies. However, in the traditional data-dependent acquisition mode, only a subset of the abundant ions during MS1 scans are isolated and fragmented in subsequent MS2 events, which reduces reproducibility and prevents the measurement of low-abundance glycan species. Here, we reported a new method termed 6-plex SUGAR isobric-labeling uide figerprint embeddng (MAGNI), to achieve multiplexed, quantitative, and targeted glycan analysis. The glycan peak signature was embedded by a triplicate-labeling strategy with a 6-plex SUGAR tag, and using ultrahigh-resolution mass spectrometers, the low-abundance glycans that carry the mass fingerprints can be recognized on the MS1 spectra through an in-house developed software tool, MAGNIFinder. These embedded unique fingerprints can guide the selection and fragmentation of targeted precursor ions and further provide rich information on glycan structures. Quantitative analysis of two standard glycoproteins demonstrated the accuracy and precision of MAGNI. Using this approach, we identified 304 N-glycans in two ovarian cancer cell lines. Among them, 65 unique N-glycans were found differentially expressed, which indicates a distinct glycosylation pattern for each cell line. Remarkably, 31 N-glycans can be quantified in only 1 × 10 cells, demonstrating the high sensitivity of our method. Taken together, our MAGNI method offers a useful tool for low-abundance N-glycan characterization and is capable of determining small quantitative differences in N-glycan profiling. Therefore, it will be beneficial to the field of glycobiology and will expand our understanding of glycosylation.
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http://dx.doi.org/10.1021/acs.analchem.3c03342 | DOI Listing |
Gen Comp Endocrinol
May 2020
College of Animal Science and Veterinary Medicine, Tianjin Agriculture University, 22 Jinjing Road, Tianjin 300384, China. Electronic address:
The molecular mechanism underlying myostatin (MSTN)-regulated metabolic cross-talk remains poorly understood. In this study, we performed comparative proteomic and phosphoproteomic analyses of gluteus muscle tissues from MSTN transgenic cattle using a shotgun-based tandem mass tag (TMT) 6-plex labeling method to explore the signaling pathway of MSTN in metabolic cross-talk and cellular metabolism during muscle development. A total of 72 differentially expressed proteins (DEPs) and 36 differentially expressed phosphoproteins (DEPPs) were identified in MSTN cattle compared to wild-type cattle.
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