Project description:Protein N-glycosylation is ubiquitous in brain and closely related to cognition and memory. Alzheimer's disease (AD) is a multifactorial disorder that lacks clear pathogenesis and treatment. Aberrant N-glycosylation has been suggested to be involved in AD pathology. While the systematic variations of protein N-glycosylation and their roles in AD have not been thoroughly investigated due to technically challenging. Here, we applied multilayered N-glycoproteomics to quantify the global protein expression, N-glycosylation sites, N-glycans, and site-specific N-glycopeptides in AD mice brains (APP/PS1 transgenic) versus wild type. The N-glycoproteome landscape exhibited the highly complex site-specific heterogeneity in AD brains. Quantitative analyses explored the generally dysregulated N-glycosylations in AD, involving proteins such as glutamate receptors, as well as fucosylated and oligo-mannose glycans. Furthermore, functional study revealed the crucial roles of N-glycosylation on proteins and neuron cells. Our work provided a robust multilayered N-glycoproteomics workflow for AD and can be applied to widespread biological systems.
Project description:Precise and large-scale characterization of glycoproteome is critical for understanding the biological functions of glycoproteins. Due to the complexity of glycosylation, the overall throughput, data quality and accessibility of site-specific glycosylation analysis are overwhelmingly lower than those of routine proteomic studies. Here, we introduce a workflow that robustly identifies intact glycopeptides at a proteome scale using stepped-energy mass-spectrometry (MS) and pGlyco 2.0, a dedicated search engine for large-scale glycopeptide analysis with comprehensive quality control (false discovery rate evaluation on the glycan, peptide and glycopeptide matches).
Project description:Precise and large-scale characterization of glycoproteome is critical for understanding the biological functions of glycoproteins. Due to the complexity of glycosylation, the overall throughput, data quality and accessibility of site-specific glycosylation analysis are overwhelmingly lower than those of routine proteomic studies. Here, we introduce a workflow that robustly identifies intact glycopeptides at a proteome scale using stepped-energy mass-spectrometry (MS) and pGlyco 2.0, a dedicated search engine for large-scale glycopeptide analysis with comprehensive quality control (false discovery rate evaluation on the glycan, peptide and glycopeptide matches).
Project description:Precise and large-scale characterization of glycoproteome is critical for understanding the biological functions of glycoproteins. Due to the complexity of glycosylation, the overall throughput, data quality and accessibility of site-specific glycosylation analysis are overwhelmingly lower than those of routine proteomic studies. Here, we introduce a workflow that robustly identifies intact glycopeptides at a proteome scale using stepped-energy mass-spectrometry (MS) and pGlyco 2.0, a dedicated search engine for large-scale glycopeptide analysis with comprehensive quality control (false discovery rate evaluation on the glycan, peptide and glycopeptide matches).
Project description:Precise and large-scale characterization of glycoproteome is critical for understanding the biological functions of glycoproteins. Due to the complexity of glycosylation, the overall throughput, data quality and accessibility of site-specific glycosylation analysis are overwhelmingly lower than those of routine proteomic studies. Here, we introduce a workflow that robustly identifies intact glycopeptides at a proteome scale using stepped-energy mass-spectrometry (MS) and pGlyco 2.0, a dedicated search engine for large-scale glycopeptide analysis with comprehensive quality control (false discovery rate evaluation on the glycan, peptide and glycopeptide matches).