The manner in which a cells respond to growth factor stimuli depends on interactions among cell surface receptors, growth factor ligands, and extracellular matrix molecules. Cell surface and extracellular matrix molecules bind growth factors, creating morphogens gradients essential to tissue patterning. Cell surface proteoglycans catalyzes the binding of growth factors to receptors, initiating downstream signaling. These events depend on the fine structure of in a given spatial and temporal context in normal and disease biochemistry.
The key to exploiting an understanding of cell surface and extracellular matrix molecular structure-function relationships for human disease therapy is to determine their roles in normal and diseased tissue. Toward this end, we have developed mass spectral methods for glycomics, proteomics, and glycoproteomics that enable comparison of structures as a function of biological variables.
We aim to develop a fundamental understanding of the manner in which cell surface and extracellular matrix molecular structure varies according to disease mechanisms. We have collaborative projects concerning cancer, neurological diseases, and viral disease. Our effort is divided among methods development, applied biochemistry, and bioinformatics.
A summary of current research projects follows.
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- Mass spectral and bioinformatics methods for sequencing glycosaminoglycans
- Bioinformatics methods for glycoproteomics and glycomics
- Extracellular matrix structure and cancer
a. Breast cancer
b. Glioma and glioblastoma
- Extracellular matrix structure and neurological diseases
a. Schizophrenia
b. Parkinson’s disease
- Method for proteomics and glycomics from tissue slides
- Glycoproteomics of influenza virus
Laboratory members
Gustavo Cavallero – Postdoctoral associate
Margaret Downs—Graduate Student
Manveen Sethi – Instructor
Deborah Chang – Graduate Student
William Hackett – Graduate Student, Bioinformatics
Mary Rachel Stimson – Graduate student, Bioinformatics
Representative Publications
- Muraoka, S.; DeLeo, A. M.; Sethi, M. K.; Yukawa-Takamatsu, K.; Yang, Z.; Ko, J.; Hogan, J. D.; Ruan, Z.; You, Y.; Wang, Y.; Medalla, M.; Ikezu, S.; Chen, M.; Xia, W.; Gorantla, S.; Gendelman, H. E.; Issadore, D.; Zaia, J.; Ikezu, T. Proteomic and biological profiling of extracellular vesicles from Alzheimer’s disease human brain tissues. Alzheimer’s & Dementia 2020, doi: 10.1002/alz.12089. Pubmed Link
- Klein, J. A.; Zaia, J. Assignment of coronavirus spike protein site-specific glycosylation using GlycReSoft. bioRxiv 2020, , 2020.05.31.125302. Pubmed Link
- Klein, J.; Zaia, J. Relative Retention Time Estimation Improves N-Glycopeptide Identifications By LC-MS/MS. J Proteome Res 2020, 19, 2113-2121. Pubmed Link
- Chang, D.; Hackett, W. E.; Zhong, L.; Wan, X. F.; Zaia, J. Measuring site-specific glycosylation similarity between influenza A virus variants with statistical certainty. Mol Cell Proteomics 2020, . Pubmed Link
- Wu, J.; Wei, J.; Chopra, P.; Boons, G. J.; Lin, C.; Zaia, J. Sequencing Heparan Sulfate Using HILIC LC-NETD-MS/MS. Anal. Chem. 2019, 91, 11738-11746. Pubmed Link
- Wei, J.; Wu, J.; Tang, Y.; Ridgeway, M. E.; Park, M. A.; Costello, C. E.; Zaia, J.; Lin, C. Characterization and Quantification of Highly Sulfated Glycosaminoglycan Isomers by Gated-Trapped Ion Mobility Spectrometry Negative Electron Transfer Dissociation MS/MS. Anal. Chem. 2019, 91, 2994-3001. Pubmed Link
- Klein, J. A.; Zaia, J. psims – A declarative writer for mzML and mzIdentML for Python. Mol Cell Proteomics 2019, 18, 571-575. Pubmed Link
- Chang, D.; Zaia, J. Why glycosylation matters in building a better flu vaccine. Mol Cell Proteomics 2019, 18, 2348-2358. Pubmed Link
- Raghunathan, R.; Polinski, N. K.; Klein, J. A.; Hogan, J. D.; Shao, C.; Khatri, K.; Leon, D.; McComb, M. E.; Manfredsson, F. P.; Sortwell, C. E.; Zaia, J. Glycomic and Proteomic Changes in Aging Brain Nigrostriatal Pathway. Molecular & Cellular Proteomics 2018, 17, 1778-1787. Pubmed Link
- Klein, J. A.; Meng, L.; Zaia, J. Deep sequencing of complex proteoglycans: a novel strategy for high coverage and site-specific identification of glycosaminoglycan-linked peptides. Mol Cell Proteomics 2018, 17, 1578-1590. Pubmed Link
- Klein, J.; Carvalho, L.; Zaia, J. Application of Network Smoothing to Glycan LC-MS Profiling. Bioinformatics 2018, 34, 3511-3518. Pubmed Link
- Hogan, J. D.; Klein, J. A.; Wu, J.; Chopra, P.; Boons, G. J.; Carvalho, L.; Lin, C.; Zaia, J. Software for peak finding and elemental composition assignment for glycosaminoglycan tandem mass spectra. Mol Cell Proteomics 2018, 17, 1448-1456. Pubmed Link
