The manner in which a cell responds to many growth factor stimuli depends on interactions between glycosaminoglycans (GAGs), growth factors, and growth factor receptors. Extracellular matrix GAGs binds growth factors, creating morphogens gradients essential to tissue patterning. Because these events depend on the fine structure of the GAG chains present, regulation of GAG biosynthesis is a key factor for understanding normal and disease related cellular growth
The key to exploiting an understanding of GAG structure-function relationships for human disease therapy is to winnow oligosaccharide-protein binding patterns from heterogeneous biological preparations. Toward this end, we have developed mass spectral methods for GAGs that enable comparison of structures as a function of biological variables.
The long term research aims are (1) to develop a fundamental understanding of the manner in which glycosaminoglycan expression is varied according to the cellular growth environment related to human disease and (2) to identify HS chain structures useful as therapeutic targets.
New bioinformatics methods are essential to realizing these goals. The data produced using our methods are information rich and not amenable to manual interpretation. Further, the methods needed are distinct from those used in genomics and proteomics. We are developing bioinformatics methods appropriate for interpretation of structural data on glycosaminoglycans and other carbohydrates to identify targets for disease therapy.
Diversity, Equity, Inclusion and Accessibility
I serve as Chair of the Graduate Medical Sciences Diversity, Equity and Inclusion Steering Committee. Here is a statement that I developed on the need for BUSM to address the diversity deficit in its basic biomedical science departments.
BUSM needs to address the deficit of URM faculty in the basic biomedical sciences in order to meet its mission
The lack of faculty diversity in basic biomedical sciences harms these fields. There is compelling evidence that the fear of deviating from current faculty recruitment practices that fail to value diverse experiences and perspectives inhibits progress in basic biomedical research. One study of 1.2 million PhD students describes the Diversity-Innovation Paradox (https://doi.org/10.1073/pnas.1915378117) whereby higher rates of scientific novelty and impact are generated by PhD students from historically underrepresented groups, yet these same students are less likely to succeed in academic careers.
This reinforces stratification in academic careers that discounts the roles of diversity in innovation and helps explain the underrepresentation of some groups in academia. In order to remain competitive, BUSM must focus its faculty recruiting efforts to achieve inclusive excellence to insure diverse leadership in the coming decades.
Moving BUSM basic biomedical sciences towards the goal of inclusive excellence. According to the AAMC (https://www.aamc.org/data-reports/faculty-institutions/interactive-data/us-medical-school-faculty-trends-percentages), it will take centuries, at the present rate, to reach parity in basic biomedical sciences at the full professor level. This representation gap results from institutional cultures that lack transparent commitments to diversity, inclusion and equity during faculty recruitment.
BUSM must cultivate institutional culture change and enhance its biomedical research workforce diversity at the faculty level. Low diversity of faculty from underrepresented groups, compared with the available talent pool, results in part from the high attrition of academic researchers from these groups (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5153246/). However, reports (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5153246/) on faculty cluster hires in academia indicate that the cohort model is an effective strategy for improving faculty diversity. As a result, there is a compelling argument that BUSM will most effectively diversify its biomedical sciences faculty through the cohort hiring model. The idea is for BUSM to build a self-reinforcing community of basic biomedical scientist who are committed to diversity and inclusive excellence. The cohort model is supported by evidence (https://press.princeton.edu/books/hardcover/9780691176888/the-diversity-bonus) that diversity strengthens scientific discovery through improved innovation, problem-solving, evaluation, prediction, evaluation, and verification. The faculty cohort model aligns with the NIH UNITE (https://www.nih.gov/ending-structural-racism/unite) initiative goals to establish a diverse and equitable culture in biomedicine and reduce barriers to racial equity in the biomedical research workforce.
BUSM must build a culture of inclusive excellence in basic biomedical sciences to remain competitive with other major biomedical research institutions. Diversity does not come at the expense of excellence; rather, diversity drives excellence. Looking ahead, the business as usual approach whereby faculty are recruited solely based on publications in high profile journals and K99 funding as evidence of potential for success in winning funding as independent investigator fails to address the emerging importance of diverse viewpoints in addressing the heath needs in the coming decades. To address persistent health disparities and issues related to minority health inequities, NIH funding initiatives will increasingly require diverse academic research teams.
Bioinformatics Graduate Program
BU-BMC Cancer Center
Genome Science Institute
Center Faculty Member
Boston University Chobanian & Avedisian School of Medicine
Graduate Faculty (Primary Mentor of Grad Students)
Boston University Chobanian & Avedisian School of Medicine, Graduate Medical Sciences
Methods for measuring matrisome molecule similarity during disease processes
03/01/2022 - 02/28/2027 (PI)NIH/National Institute of General Medical Sciences5R35GM144090-02
Cerebrovascular Remodeling and Neurodegenerative Changes in Alzheimer's Disease
02/01/2022 - 01/31/2027 (Multi-PI)
PI: Joseph Zaia, PhDNIH/National Institute on Aging5R01AG075876-02
Selecting HA glycosylation for improved vaccine responses
06/09/2021 - 05/31/2026 (PI)NIH/National Institute of Allergy & Infectious Diseases5R01AI155975-03
Developing new glycosylation analysis techniques and software to enable generation of more effective Influenza A virus vaccines
10/01/2020 - 09/30/2023 (PI)Waters Technologies Corporation
Measuring glycosylation to improve the influenza A virus vaccine
07/01/2020 - 06/30/2023 (PI)Massachusetts Life Sciences Center
Involvement of the Extracellular Matrix in the pathophysiology of Alzheimer's disease: a Glycomics and Proteomics study
09/01/2020 - 12/31/2022 (Key Person / Mentor)
PI: Manveen K. Sethi, PhDBright Focus Foundation
Methods for determination of glycoprotein glycosylation similarities among disease states
09/01/2019 - 12/31/2022 (PI)NIH/National Institute of General Medical Sciences5R01GM133963-03
Glycomics and proteomics of brain specimens
03/15/2018 - 12/31/2022 (Subcontract PI)The Scripps Research Institute NIH NIDA5R01DA046170-03
An open-source software suite for processing glycomics and glycoproteomics mass spectral data
08/14/2017 - 07/31/2021 (PI)NIH/National Cancer Institute5U01CA221234-03
Thalamic Axonal Pathways and Extracellular Matrix Abnormalities in Schizophrenia
09/01/2015 - 12/31/2019 (Subcontract PI)McLean Hospital Corporation NIH NIMH5R01MH105608-04
Showing 10 of 26 results.
Show All Results
Showing 10 of 143 results.
Show All Results
Publications listed below are automatically derived from MEDLINE/PubMed and other
sources, which might result in incorrect or missing publications. Faculty can
to make corrections and additions.
Showing 10 of 224 results.
Zaia J. Recent advances and future developments in ultrasensitive omics. Anal Bioanal Chem. 2023 Oct 03. PMID: 37787855
Downs M, Curran J, Zaia J, Sethi MK. Analysis of complex proteoglycans using serial proteolysis and EThcD provides deep N- and O-glycoproteomic coverage. Anal Bioanal Chem. 2023 Sep 20.View Related Profiles. PMID: 37728749
Wei J, Papanastasiou D, Kosmopoulou M, Smyrnakis A, Hong P, Tursumamat N, Klein JA, Xia C, Tang Y, Zaia J, Costello CE, Lin C. De novo glycan sequencing by electronic excitation dissociation MS2-guided MS3 analysis on an Omnitrap-Orbitrap hybrid instrument. Chem Sci. 2023 Jun 21; 14(24):6695-6704.View Related Profiles. PMID: 37350811; PMCID: PMC10284134; DOI: 10.1039/d3sc00870c;
Hackett WE, Chang D, Carvalho L, Zaia J. RAMZIS: a bioinformatic toolkit for rigorous assessment of the alterations to glycoprotein structure that occur during biological processes. bioRxiv. 2023 Jun 01. PMID: 37398011; PMCID: PMC10312533; DOI: 10.1101/2023.05.30.542895;
Zaia J. The 2022 Nobel Prize in Chemistry for the development of click chemistry and bioorthogonal chemistry. Anal Bioanal Chem. 2023 Feb; 415(4):527-532. PMID: 36602567
Zaia J, Ricard-Blum S. Editorial overview: Protein-carbohydrate complexes and glycosylation. Curr Opin Struct Biol. 2022 Dec; 77:102468. PMID: 36179500
This graph shows the total number of publications by year, by first, middle/unknown,
or last author.