Because of the pressing needs to comprehensively understand the biological attributes of glycosylation in many important biological functions such as the immune response, cell development, cellular differentiation/adhesion and host-pathogen interactions, glycomics and glycoproteomics continue to be highly dynamic and interesting research areas. Moreover, aberrant glycosylation for decades has been recognized as the attribute of many mammalian diseases, including osteoarthritis, cystic fibrosis and cancer. The diverse biological roles of glycans and their implications in diseases have created a demand for reliable quantitative glycomic approaches, permitting sensitive monitoring of glycans in biological systems.
The aim of this proposal is the creation of glycomic mapping platform enabling the automated identification, annotation and quantitation of glycans derived from biological samples. The platform comprises of both analytical methods and bioinformatic tools. The analytical methods are based on reversed-phase liquid chromatography and mass spectrometry of permethylated glycans while the bioinformatic tools facilitate automation of interpretation and quantitation. The glycomic mapping platform will be employed to understand the biological attributes of glycan in disease development, such as cancer and cardiovascular diseases.

Public Health Relevance

The proposed research activities are aimed at the creation of analytical methods and bioinformatic tools to facilitate rapid and detailed characterization of glycoproteins. Such effort is aimed at facilitating better understanding of the biological roles of glycosylation. The resulting methods and tools will create a glycomic mapping platform that will allow sensitive, reliable and reproducible monitoring of alteration in glycosylation as a result of perturbation in biological systems such as changes in glycosylation as a result of disease progression.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM112490-02
Application #
8927045
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Sheeley, Douglas
Project Start
2014-09-15
Project End
2017-08-31
Budget Start
2015-09-01
Budget End
2016-08-31
Support Year
2
Fiscal Year
2015
Total Cost
Indirect Cost
Name
Texas Tech University
Department
Chemistry
Type
Schools of Arts and Sciences
DUNS #
041367053
City
Lubbock
State
TX
Country
United States
Zip Code
79409
Veillon, Lucas; Fakih, Christina; Abou-El-Hassan, Hadi et al. (2018) Glycosylation Changes in Brain Cancer. ACS Chem Neurosci 9:51-72
Banazadeh, Alireza; Peng, Wenjing; Veillon, Lucas et al. (2018) Carbon Nanoparticles and Graphene Nanosheets as MALDI Matrices in Glycomics: a New Approach to Improve Glycan Profiling in Biological Samples. J Am Soc Mass Spectrom :
Nokkari, Amaly; Abou-El-Hassan, Hadi; Mechref, Yehia et al. (2018) Implication of the Kallikrein-Kinin system in neurological disorders: Quest for potential biomarkers and mechanisms. Prog Neurobiol 165-167:26-50
Zhong, Jieqiang; Banazadeh, Alireza; Peng, Wenjing et al. (2018) A carbon nanoparticles-based solid-phase purification method facilitating sensitive MALDI-MS analysis of permethylated N-glycans. Electrophoresis 39:3087-3095
Banazadeh, Alireza; Williamson, Seth; Zabet, Masoud et al. (2018) Magnetic carbon nanocomposites as a MALDI co-matrix enhancing MS-based glycomics. Anal Bioanal Chem 410:7395-7404
Yu, Aiying; Zhao, Jingfu; Peng, Wenjing et al. (2018) Advances in mass spectrometry-based glycoproteomics. Electrophoresis 39:3104-3122
Gaye, M M; Ding, T; Shion, H et al. (2017) Delineation of disease phenotypes associated with esophageal adenocarcinoma by MALDI-IMS-MS analysis of serum N-linked glycans. Analyst 142:1525-1535
Zhou, Shiyue; Veillon, Lucas; Dong, Xue et al. (2017) Direct comparison of derivatization strategies for LC-MS/MS analysis of N-glycans. Analyst 142:4446-4455
Banazadeh, Alireza; Veillon, Lucas; Wooding, Kerry M et al. (2017) Recent advances in mass spectrometric analysis of glycoproteins. Electrophoresis 38:162-189
Al Hariri, Moustafa; Elmedawar, Mohamad; Zhu, Rui et al. (2017) Proteome profiling in the aorta and kidney of type 1 diabetic rats. PLoS One 12:e0187752

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