Capturing Low-Abundance Glycopeptides for Decoding the Glycoproteome
Capturing Low-Abundance Glycopeptides for Decoding the Glycoproteome
批准号:
10260575
负责人:
Ronghu Wu
金额:
$29.79万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-09-20 至 2024-07-31
关键词:
AcidsAffectBackBiological MarkersBiomedical ResearchBoronic AcidsCell SurvivalCellsCleaved cellClinicalComplexCovalent InteractionCultured CellsDataDendrimersDetectionDevelopmentDiseaseDrug TargetingEnzymesEventGlycopeptidesGlycoproteinsHealthHeterogeneityHumanInfectionKnowledgeLeadLifeMalignant NeoplasmsMalignant neoplasm of ovaryMass Spectrum AnalysisMethodsMissionModificationMolecularPatientsPlayPolysaccharidesPost-Translational Protein ProcessingProtein AnalysisProtein GlycosylationProteinsProteomicsPublic HealthResearchRoleSamplingSiteStructureSurfaceTestingTissuesUnited States National Institutes of Healthbasebiological researchbiological systemsbiomarker discoverycellular developmentdensitydesigndisabilityearly detection biomarkersglycoproteomicsglycosylationhuman diseasehydroxyl groupinnovationinsightmonomernew therapeutic targetnoveloperationpotential biomarkerprotein functionsugar
中文摘要
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英文摘要
SUMMARY
Glycosylation is one of the most common protein modifications and is essential for cell survival. Glycoproteins
contain a wealth of valuable information regarding the development and disease statuses of cells. Global
analysis of protein glycosylation aids in a better understanding of glycoprotein functions and the molecular
mechanisms of disease, and leads to the identification of glycoproteins as biomarkers. However, it is
extraordinarily challenging to comprehensively analyze glycoproteins because of the heterogeneity of glycans
and the low abundance of many glycoproteins. The objective of this project is to develop an innovative and
effective method to enrich glycopeptides with diverse glycan structures, especially those with low abundance,
and apply this method to globally and site-specifically analyze protein N- and O-glycosylation by mass
spectrometry (MS). Guided by strong preliminary data, this objective will be fulfilled by pursuing four specific
aims. 1) Effective enrichment of glycopeptides through the synergistic interactions using different types of
dendrimers. Based on the common feature that every glycan contains multiple hydroxyl groups, a novel method
benefiting from the synergistic interactions between a glycan and multiple boronic acid (BA) molecules
conjugated to one dendrimer will be developed to capture low-abundance glycopeptides. Different types of
dendrimers will be synthesized and tested, especially from monomers containing the 1→3 branching motif that
will increase the density of BA at the dendrimer surface and enhance the interactions with a glycan. 2)
Enhancement of the synergistic interactions by minimizing the steric effect and forming the ternary complex.
Different kinds of BAs will be studied, especially vinylboronic acids with a small size. This will decrease the steric
hindrance and strengthen the overall interaction between one glycan and BAs. Moreover, the formation of the
ternary complex will be studied to further enhance the interactions. 3) Global and site-specific analysis of O-
glycoproteins with glycan structure information. Through reversible covalent interactions, enriched glycopeptides
contain intact glycans, allowing for site-specific analysis of O-glycoproteins with glycan structure information.
This is especially important for O-glycosylation due to the lack of an enzyme to universally cleave O-glycans and
generate a common tag. 4) Comprehensive analysis of glycoproteins in tissues and sera from patients with
ovarian cancer. Combining the proposed method with multiplexed proteomics, glycoproteins in clinical samples
will be systematically and quantitatively analyzed. The results will provide insights into the molecular
mechanisms of the disease and lead to the discovery of biomarkers for early detection. Eventually, the best
dendrimer conjugated with the right BA will enable us to effectively capture low-abundance glycopeptides.
Because of the ease of operation and no sample restrictions, the method will have extensive applications in the
biological and biomedical research fields and will significantly advance glycoscience.
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Capturing Low-Abundance Glycopeptides for Decoding the Glycoproteome
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批准号:10440467
-
项目类别:
-
资助金额:$29.27万
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财政年份:2020
-
负责人:Ronghu Wu
-
依托单位:
Capturing Low-Abundance Glycopeptides for Decoding the Glycoproteome
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批准号:10669037
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项目类别:
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资助金额:$29.68万
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财政年份:2020
-
负责人:Ronghu Wu
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依托单位:
Supplemental Funds for a Thermo Scientific Q Exactive HF Mass Spectrometer
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批准号:10384259
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项目类别:
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资助金额:$20.0万
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财政年份:2020
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负责人:Ronghu Wu
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依托单位:
Effective MS-Based Methods for Unraveling Cell Surface Protein Interactions
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批准号:10671551
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项目类别:
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资助金额:$35.47万
-
财政年份:2017
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负责人:Ronghu Wu
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依托单位:
Effective MS-Based Methods for Unraveling Cell Surface Protein Interactions
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批准号:10522689
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项目类别:
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资助金额:$34.98万
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财政年份:2017
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负责人:Ronghu Wu
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依托单位:
Effective Methods to Globally Analyze Cell Surface Proteins and Glycoproteins
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批准号:9239644
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项目类别:
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资助金额:$31.59万
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财政年份:2017
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负责人:Ronghu Wu
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依托单位:
Effective Methods to Globally Analyze Cell Surface Proteins and Glycoproteins
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批准号:9417031
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项目类别:
-
资助金额:$34.85万
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财政年份:2017
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负责人:Ronghu Wu
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依托单位:
海外基金