Joseph Zaia, PhD
Professor
Boston University School of Medicine
Dept of Biochemistry

PhD, Massachusetts Institute of Technology




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.

Member
Boston University
Bioinformatics Graduate Program


Member
Boston University
BU-BMC Cancer Center


Member
Boston University
Genome Science Institute


Center Faculty Member
Boston University School of Medicine
Mass Spectrometry


Graduate Faculty (Primary Mentor of Grad Students)
Boston University 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 Sciences
1R35GM144090-01

Cerebrovascular Remodeling and Neurodegenerative Changes in Alzheimer's Disease
02/01/2022 - 01/31/2027 (Multi-PI)
PI: Joseph Zaia, PhD
NIH/National Institute on Aging
1R01AG075876-01

Selecting HA glycosylation for improved vaccine responses
06/09/2021 - 05/31/2026 (PI)
NIH/National Institute of Allergy & Infectious Diseases
5R01AI155975-02

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


Glycomics and proteomics of brain specimens
03/15/2018 - 12/31/2022 (Subcontract PI)
The Scripps Research Institute NIH NIDA
5R01DA046170-03

Involvement of the Extracellular Matrix in the pathophysiology of Alzheimer's disease: a Glycomics and Proteomics study
09/01/2020 - 08/31/2022 (Key Person / Mentor)
PI: Manveen K. Sethi, PhD
Bright Focus Foundation


Methods for determination of glycoprotein glycosylation similarities among disease states
09/01/2019 - 06/30/2022 (PI)
NIH/National Institute of General Medical Sciences
5R01GM133963-03

An open-source software suite for processing glycomics and glycoproteomics mass spectral data
08/14/2017 - 07/31/2021 (PI)
NIH/National Cancer Institute
5U01CA221234-03

Thalamic Axonal Pathways and Extracellular Matrix Abnormalities in Schizophrenia
09/01/2015 - 12/31/2019 (Subcontract PI)
McLean Hospital Corporation NIH NIMH
5R01MH105608-04

Showing 10 of 26 results. Show All Results


Title


Yr Title Project-Sub Proj Pubs
2022 Methods for measuring matrisome molecule similarity during disease processes 1R35GM144090-01
2022 Cerebrovascular Remodeling and Neurodegenerative Changes in Alzheimer's Disease 1R01AG075876-01
2022 Selecting HA glycosylation for improved vaccine responses 5R01AI155975-02
2021 Selecting HA glycosylation for improved vaccine responses 1R01AI155975-01A1
2021 Methods for determination of glycoprotein glycosylation similarities among disease states 5R01GM133963-03 4
2020 Methods for determination of glycoprotein glycosylation similarities among disease states 5R01GM133963-02 4
2020 Methods for determination of glycoprotein glycosylation similarities among disease states 3R01GM133963-02S1 4
2019 Methods for determination of glycoprotein glycosylation similarities among disease states 1R01GM133963-01 4
2019 An open-source software suite for processing glycomics and glycoproteomics mass spectral data 5U01CA221234-03 11
2018 An open-source software suite for processing glycomics and glycoproteomics mass spectral data 5U01CA221234-02 11
Showing 10 of 139 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 login to make corrections and additions.

iCite Analysis       Copy PMIDs To Clipboard

  1. Downs M, Zaia J, Sethi MK. Mass spectrometry methods for analysis of extracellular matrix components in neurological diseases. Mass Spectrom Rev. 2022 Jun 20; e21792.View Related Profiles. PMID: 35719114
     
  2. Lageveen-Kammeijer GSM, Rapp E, Chang D, Rudd PM, Kettner C, Zaia J. The minimum information required for a glycomics experiment (MIRAGE): reporting guidelines for capillary electrophoresis. Glycobiology. 2022 06 13; 32(7):580-587. PMID: 35348694
     
  3. Nalehua MR, Zaia J. Measuring change in glycoprotein structure. Curr Opin Struct Biol. 2022 Jun; 74:102371. PMID: 35452871; PMCID: PMC9188990; DOI: 10.1016/j.sbi.2022.102371;
     
  4. Wu J, Chopra P, Boons GJ, Zaia J. Influence of saccharide modifications on heparin lyase III substrate specificities. Glycobiology. 2022 Mar 30; 32(3):208-217. PMID: 33822051; PMCID: PMC8966481; DOI: 10.1093/glycob/cwab023;
     
  5. Sethi MK, Downs M, Shao C, Hackett WE, Phillips JJ, Zaia J. In-Depth Matrisome and Glycoproteomic Analysis of Human Brain Glioblastoma Versus Control Tissue. Mol Cell Proteomics. 2022 Apr; 21(4):100216.View Related Profiles. PMID: 35202840; PMCID: PMC8957055; DOI: 10.1016/j.mcpro.2022.100216;
     
  6. Downs M, Sethi MK, Raghunathan R, Layne MD, Zaia J. Matrisome changes in Parkinson's disease. Anal Bioanal Chem. 2022 Apr; 414(9):3005-3015.View Related Profiles. PMID: 35112150; PMCID: PMC8944212; DOI: 10.1007/s00216-022-03929-4;
     
  7. Cavallero GJ, Zaia J. Resolving Heparan Sulfate Oligosaccharide Positional Isomers Using Hydrophilic Interaction Liquid Chromatography-Cyclic Ion Mobility Mass Spectrometry. Anal Chem. 2022 02 08; 94(5):2366-2374. PMID: 35090117; PMCID: PMC8943687; DOI: 10.1021/acs.analchem.1c03543;
     
  8. Kawahara R, Chernykh A, Alagesan K, Bern M, Cao W, Chalkley RJ, Cheng K, Choo MS, Edwards N, Goldman R, Hoffmann M, Hu Y, Huang Y, Kim JY, Kletter D, Liquet B, Liu M, Mechref Y, Meng B, Neelamegham S, Nguyen-Khuong T, Nilsson J, Pap A, Park GW, Parker BL, Pegg CL, Penninger JM, Phung TK, Pioch M, Rapp E, Sakalli E, Sanda M, Schulz BL, Scott NE, Sofronov G, Stadlmann J, Vakhrushev SY, Woo CM, Wu HY, Yang P, Ying W, Zhang H, Zhang Y, Zhao J, Zaia J, Haslam SM, Palmisano G, Yoo JS, Larson G, Khoo KH, Medzihradszky KF, Kolarich D, Packer NH, Thaysen-Andersen M. Author Correction: Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis. Nat Methods. 2022 Jan; 19(1):130. PMID: 34893784; PMCID: PMC8748192; DOI: 10.1038/s41592-021-01368-0;
     
  9. Kawahara R, Chernykh A, Alagesan K, Bern M, Cao W, Chalkley RJ, Cheng K, Choo MS, Edwards N, Goldman R, Hoffmann M, Hu Y, Huang Y, Kim JY, Kletter D, Liquet B, Liu M, Mechref Y, Meng B, Neelamegham S, Nguyen-Khuong T, Nilsson J, Pap A, Park GW, Parker BL, Pegg CL, Penninger JM, Phung TK, Pioch M, Rapp E, Sakalli E, Sanda M, Schulz BL, Scott NE, Sofronov G, Stadlmann J, Vakhrushev SY, Woo CM, Wu HY, Yang P, Ying W, Zhang H, Zhang Y, Zhao J, Zaia J, Haslam SM, Palmisano G, Yoo JS, Larson G, Khoo KH, Medzihradszky KF, Kolarich D, Packer NH, Thaysen-Andersen M. Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis. Nat Methods. 2021 11; 18(11):1304-1316. PMID: 34725484; PMCID: PMC8566223; DOI: 10.1038/s41592-021-01309-x;
     
  10. Chang D, Klein JA, Nalehua MR, Hackett WE, Zaia J. Data-independent acquisition mass spectrometry for site-specific glycoproteomics characterization of SARS-CoV-2 spike protein. Anal Bioanal Chem. 2021 Dec; 413(29):7305-7318. PMID: 34635934; PMCID: PMC8505113; DOI: 10.1007/s00216-021-03643-7;
     
Showing 10 of 212 results. Show More

This graph shows the total number of publications by year, by first, middle/unknown, or last author.

Bar chart showing 212 publications over 33 distinct years, with a maximum of 22 publications in 2011

YearPublications
19851
19872
19911
19921
19943
19951
19964
19971
19983
19993
20003
20014
20022
20034
20043
20053
20068
20072
20087
20098
201011
201122
201211
201316
201410
20158
201610
20175
201811
201911
202014
202111
20228


UMass Medical School researchers, Waters share in $8.3M for research

Worcester Business Journal 9/9/2020
In addition to these self-described keywords below, a list of MeSH based concepts is available here.

glycomics
glycosaminoglycan
heparan sulfate
heparin
mass spectrometry
proteoglycan
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