Glycosylation is an important post-translational modification of proteins and lipids. This process controls cell recognition and signaling processes that regulate human development, immunity and disease. The current proposal aims to develop Systems Biology based computational and experimental methodologies to enhance our understanding of cellular glycosylation pathways. In particular, our focus is on better understanding the features that regulate the formation of O-linked glycans on human leukocytes. By binding adhesion molecules belonging to the selecting family, these O-glycans play a critical role in regulating leukocyte adhesion to vascular endothelial cells that line blood vessel walls at sites of inflammation and cardiovascular disease. Our overall hypothesis is that """"""""In silico modeling of glycosylation reaction networks can identify rate limiting steps that control the formation of selectin-ligands on human leukocytes. Defined and specific perturbation of these rate-limiting steps can reduce leukocyte-endothelial cell adhesion/migration in vivo during inflammation."""""""" The specific aims are: 1) to develop computational models to predict the rate-limiting steps that control cellular glycosylation. 2) To quantify the role of selected glycosyltransferases and the peptide backbone in regulating O-linked glycosylation and leukocyte selecting-binding function. 3) To test the effect of silencing glycosyltransferases on leukocyte retention in the bone marrow, and cell migration to sites of inflammation. The project involves collaboration between investigators with expertise in Systems Biology based modeling, quantitative bioengineering experimentation, proteomics, glycobiology, immunology and animal models. Experimental studies span multiple scales from genes, to proteins/enzymes, to carbohydrate structure and cell adhesion function, both in vitro and in vivo. The computer modeling integrates this information to determine the effect of system perturbation on glycan structure and function. Expected project outcomes include: I) Definition of a new standard called GlycoML for the description of glycosylation reaction networks. ii) Combined use of experiment and theory to reveal potential intra-cellular/metabolic targets of glycosylation that can quantitatively and definitively alter selectin-ligand structures. iii) Definition of the precise a (2, 3)sialyltransferase(s) and a (1, 3) fucosyltransferases(s) that regulate selectin-ligand biosynthesis in human leukocytes. iv) Improved understanding of the role of the peptide backbone in regulating O-glycosylation chain initiation, extension and termination. v) Validation in animal models of inflammation, peritonitis and COPD (chronic obstructive pulmonary disease), key hypothesis generated using computer simulation and ex vivo experimentation.

Public Health Relevance

Half of all proteins in nature are decorated/ modified by sugar structures that are called glycans, and these play an active role in regulating cell/tissue function during normal human development and during disease. The current proposal develops novel systems-level computational and experimental tools that will enhance our understanding of how nature regulates the structure of glycans. Such understanding will aid the identification of new strategies to control glycan structures and to reduce white blood cell adhesion at sites of human inflammatory disease.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL103411-02
Application #
8327859
Study Section
Special Emphasis Panel (ZRG1-VH-D (50))
Program Officer
Sarkar, Rita
Project Start
2011-09-05
Project End
2016-06-30
Budget Start
2012-09-01
Budget End
2013-06-30
Support Year
2
Fiscal Year
2012
Total Cost
$525,975
Indirect Cost
$136,101
Name
State University of New York at Buffalo
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
038633251
City
Buffalo
State
NY
Country
United States
Zip Code
14260
Zhang, Ming; An, Bo; Qu, Yang et al. (2018) Sensitive, High-Throughput, and Robust Trapping-Micro-LC-MS Strategy for the Quantification of Biomarkers and Antibody Biotherapeutics. Anal Chem 90:1870-1880
Chugh, Seema; Barkeer, Srikanth; Rachagani, Satyanarayana et al. (2018) Disruption of C1galt1 Gene Promotes Development and Metastasis of Pancreatic Adenocarcinomas in Mice. Gastroenterology 155:1608-1624
Wang, Xue; Niu, Jin; Li, Jun et al. (2018) Temporal Effects of Combined Birinapant and Paclitaxel on Pancreatic Cancer Cells Investigated via Large-Scale, Ion-Current-Based Quantitative Proteomics (IonStar). Mol Cell Proteomics 17:655-671
Ferguson, Scott W; Wang, Jinli; Lee, Christine J et al. (2018) The microRNA regulatory landscape of MSC-derived exosomes: a systems view. Sci Rep 8:1419
Shen, Xiaomeng; Shen, Shichen; Li, Jun et al. (2017) An IonStar Experimental Strategy for MS1 Ion Current-Based Quantification Using Ultrahigh-Field Orbitrap: Reproducible, In-Depth, and Accurate Protein Measurement in Large Cohorts. J Proteome Res 16:2445-2456
Buffone Jr, Alexander; Nasirikenari, Mehrab; Manhardt, Charles T et al. (2017) Leukocyte-borne ?(1,3)-fucose is a negative regulator of ?2-integrin-dependent recruitment in lung inflammation. J Leukoc Biol 101:459-470
Tu, Chengjian; Shen, Shichen; Sheng, Quanhu et al. (2017) A peptide-retrieval strategy enables significant improvement of quantitative performance without compromising confidence of identification. J Proteomics 152:276-282
Zhang, Changjie; Neelamegham, Sriram (2017) Application of microfluidic devices in studies of thrombosis and hemostasis. Platelets 28:434-440
Cheng, Kai; Zhou, Yusen; Neelamegham, Sriram (2017) DrawGlycan-SNFG: a robust tool to render glycans and glycopeptides with fragmentation information. Glycobiology 27:200-205
Liu, Gang; Cheng, Kai; Lo, Chi Y et al. (2017) A Comprehensive, Open-source Platform for Mass Spectrometry-based Glycoproteomics Data Analysis. Mol Cell Proteomics 16:2032-2047

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