Glycomics is the systematic study of glycosylation in the context of a whole cell or organism. Glycosylated proteins are estimated to make up 50% of all proteins and cover the outside of the cell. Functional roles in glycosylation have been noted in pathogenesis, metastasis, and embryogenesis. However, the structure of these carbohydrates has been difficult to study due to the chemical nature of carbohydrates. Lectins, carbohydrate binding proteins excluding antibodies and enzymes, can be utilized to study glycosylation in a high throughput manner using a microarray format. Glycans, the carbohydrates attached to a protein or lipid, are not synthesized from a template. They are added co- or post-translationally by a concerted set of enzymes in the secretory pathway. In addition, the glycan structures may be altered by metabolism or trafficking. Cell type specific glycosylation has long been hypothesized due to observations of bacteria homing to tissues. We use lectin microarray technology to define the glycosylation in a subset of the NCI-60, a set of cell lines from different tissues. Using a customized gene expression microarray, we identify cell type dependent glycosylation genes and observe evidence of cell type dependent spliceforms for an O-glycosylated mucin. Data from the lectin microarray and a published gene expression data set were integrated using Generalized Singular Value Decomposition (GSVD), a linear matrix decomposition method. We have successfully decomposed the data into 3 cell type dependent meta patterns that segregate by glycosylation family. Correlation projection of the genes and subsequent gene ontology enrichment suggests that genes in different pathways covary with the types of glycosylation. An inverse relationship was revealed for the N- glycosylation pattern between the SVD of the lectins and the GSVD of the genes and lectins together. Whereas, the relationship was correlative for O-glycosylation, which was clearly illustrated in biplots. This work argues that types of glycosylation are regulated by different mechanisms in different cell types. / text

The glycoproteome is an intricate and diverse component of a cell, and it plays a key role in the definition of the interface between that cell and the rest of its world. Methods for studying the glycoproteome have been developed for released glycan glycomics and site-localized bottom-up glycoproteomics using liquid chromatography-coupled mass spectrometry and tandem mass spectrometry (LC-MS/MS), which is itself a complex problem. Algorithms for interpreting these data are necessary to be able to extract biologically meaningful information in a high throughput, automated context. Several existing solutions have been proposed but may be found lacking for larger glycopeptides, for complex samples, different experimental conditions, different instrument vendors, or even because they simply ignore fundamentals of glycobiology. I present a series of open algorithms that approach the problem from an instrument vendor neutral, cross-platform fashion to address these challenges, and integrate key concepts from the underlying biochemical context into the interpretation process. In this work, I created a suite of deisotoping and charge state deconvolution algorithms for processing raw mass spectra at an LC scale from a variety of instrument types. These tools performed better than previously published algorithms by enforcing the underlying chemical model more strictly, while maintaining a higher degree of signal fidelity. From this summarized, vendor-normalized data, I composed a set of algorithms for interpreting glycan profiling experiments that can be used to quantify glycan expression. From this I constructed a graphical method to model the active biosynthetic pathways of the sample glycome and dig deeper into those signals than would be possible from the raw data alone. Lastly, I created a glycopeptide database search engine from these components which is capable of identifying the widest array of glycosylation types available, and demonstrate a learning algorithm which can be used to tune the model to better understand the process of glycopeptide fragmentation under specific experimental conditions to outperform a simpler model by between 10% and 15%. This approach can be further augmented with sample-wide or site-specific glycome models to increase depth-of-coverage for glycoforms consistent with prior beliefs.

More than half of all human proteins are glycosylated, making glycosylation one of the most abundant post-translational modifications in proteomics. N-Glycosylation is a prevalent and diverse type of glycosylation with key roles in regulating systems such as protein folding and host-pathogen recognition; without proper understanding of the heterogeneities of N-Glycosylation efforts to understand biological systems and efforts to combat the maladies that affect those systems will be hindered, knowingly and unknowingly. N-Glycosylation is a semi-stochastic process governed by local chemistries and enzymatic availability, and it is regulated by end process evaluation making modeling infeasible. This drives glycoproteomics to rely on observational data from tandem mass spectrometry; mass spectrometry is a powerful tool that comes with logistical and technical limitations on the availability and compatibility of data. N -Glycopeptides can be identified in tandem mass spectrometry data, but this is with greater uncertainty than traditional proteomics for a variety of factors. This uncertainty propagates into the quantification of these molecules, generating interdependent datasets with small sample sizes and high missing value rates. N-Glycans are inherently interrelated by the biosynthetic network that they’re processed in, and as a result they have a lot of shared information and chemical properties that make identification and quantification more difficult. While advances in N-Glycoproteomics continue there is still a lot needed for true and reliable understanding of quantitative N-Glycoproteomics. To make use of the existing data, an R-package called RAMZIS — Relative Assessment of m/z Identifications by Similarity — was developed. This toolkit focuses on data quality assessment and identifying broad differences between glycosylation sites. RAMZIS uses a series of permutation tests with a weighted Tanimoto similarity assessment, it provides researchers with information on their ability to use their data, the presence of outliers, the probable differentiability of glycosylation sites, and how to improve their future experimentations. Data Independent Acquisition (DIA) has enabled vast improvements in proteomic’s ability to quantify and identify proteins in complex samples, but these improvements cannot be directly applied to glycoproteomics. Glycoproteins are more heterogeneous than deglycosylated proteomic datasets and have lower overall signal, the latter compounding the issues made by the former. For glycoproteomics to make full use of the power of DIA and account for its idiosyncrasies, many bioinformatic advancements need to be made in glycopeptide identification, validation, and quantification. To this effort, we developed a python package called GlyLine as a framework to assess glycoproteomic DIA data; it tracks coeluting product ions of identified glycopeptides, splitting the signal from shared product ions to produce MS2 level quantifications of the identified glycopeptides and provide databases of information for further analysis. As glycoproteomics advances and comes into greater prominence, it is vital that experiments and bioinformatic workflows be repeatable, as quantitative glycoproteomic data are reported in many different ways that are often incompatible. We have worked with the MIRAGE Commission to develop a community based minimum reporting guideline for glycoproteomic experiments. / 2025-09-30T00:00:00Z

Cells can mediate intercellular communication by the secretion and uptake of microvesicles, nano-sized membranous particles that carry signaling molecules, antigens, lipids, mRNA and miRNA between cells. The biological function of these vesicles is dependent upon their composition and cellular origin which is regulated by mechanisms that are not well understood. Based on their molecular content, microvesicles may play a role in immune regulation, cancer progression, the spread of infectious agents and numerous other important normal and pathogenic processes. The proteomic content of microvesicles from diverse sources has been intensely studied. In contrast, little is known about their glycomic content. The glycosylation pattern of a protein or lipid plays a key role in determining its functional properties in several ways. Glycans can determine the trafficking of a protein to particular regions of the cell as well as the protein’s half life. In addition, the glycan-dervied oligomerization of glycolipids and glycoproteins is a known mechanism for the activation of receptors and recognition of ligands on the surface of the cell. Glycomic analysis may thus provide valuable insights into microvesicle function. I utilized lectin microarray technology to compare the glycosylation patterns of microvesicles derived from a variety of biological sources. When compared to cellular membranes, microvesicles were enriched in high mannose, polylactosamine, α2-6 sialic acid, and complex N-linked glycans but exclude terminal blood group A and B antigens. The polylactosamine signature in microvesicles from different cell lines derives from distinct glycoprotein cohorts. After treatment of Sk-Mel-5 cells with lactose to inhibit lectin-glycan interactions, secretion of microvesicle resident proteins was severely reduced. Taken together, this work provides evidence for a role of glycosylation in microvesicle-directed protein sorting. / text

The cell surface is enveloped with a myriad of carbohydrates that form complex matrices of oligosaccharides. Carbohydrate recognition plays crucial and varying roles in cellular trafficking, differentiation, and bacterial pathogenesis. Lectin microarray technology presents a unique platform for the high-throughput analysis of these structurally diverse classes of biopolymers. One significant hinderance of this technology has been the limitation imposed by the set of commercially available plant lectins used in the array. To enhance the reproducibility and scope of the lectin panel, our lab generated a small set of bacteria-derived recombinant lectins. This dissertation describes the unique advantages that recombinant lectins have over traditional plant-derived lectins. The recombinant lectins are expressed with a common fusion tag, glutathione-S-transferase (GST), which can be used as an immobilization handle on glutathione (GSH)-modified substrates. Although protein immobilization via fusion tags in a microarray format is not novel, our work demonstrates that protein activity through site-specific immobilization is enhanced when the protein is properly oriented. Although orientation enhanced the activity of our GST-tagged recombinant lectins, the GSH-surface modification precluded the printing of non-GST-tagged lectins, such as the traditional plant lectins, thus limiting the structural resolution of our arrays. To solve this issue, we developed a novel print technique which allows the one-step deposition and orientation of GST-tagged proteins in a microarray format. To expand our view of the glycome, we further adapt this method for the in situ orientation of unmodified IgG and IgM antibodies using GST-tagged antibody-binding proteins. Another advantage of recombinant lectins is in the ease of genomic manipulation, wherein we could tailor the binding domain to bind a different antigen. We demonstrate this by producing non-binding variants of the recombinant lectins to act as negative controls in our microarrays. Along with the non-binding variants, we developed a lectin displayed on the surface of phage. In the hopes generating more novel lectins, I will describe our current efforts of lectin evolution using phage-displayed GafD. By generating novel tools in lectin microarray technology, we enhance our understanding of the role of carbohydrates on a global scale. / text

This thesis includes studies on N-, mucin type O-, and glycosaminoglycan (GAG)-linked glycosylation in human biospecimens. Glycosylation plays a central role in biological processes, including protein folding, immune surveillance, and regulation of cell growth. The structures of GAG are regulated in a tissue-specific manner. Heparan sulfate (HS) and chondroitin sulfate (CS) are the two types of GAGs targeted in this thesis. Human leukocytes express both CS and HS GAGs with CS being the more abundant type; however, little is known regarding the properties and structures of GAG chains, their ranges of variability among normal subjects, and changes in structure associated with disease conditions. We measured the relative and absolute disaccharides abundances of HS and CS for purified B, T, NK cells, monocytes, and polymorphonuclear leukocytes (PMNs) using size exclusion chromatography-mass spectrometry (SEC-MS). We found that all leukocytes express HS chains with levels of sulfation more similar to heparin than to organ-derived HS. In addition, CS abundances varied considerably in a leukocyte cell type specific manner. Therefore, our results established the ranges of GAG structures expressed on normal leukocytes as well as necessary for subsequent inquiry into disease conditions. Glioblastoma (GBM) accounts for 30% of human primary brain tumors. It is deadly and highly invasive. In past decades, most GBM research focused on pathophysiological changes in genome. There remains a dearth of knowledge regarding alterations in glycomics, glycoproteomics, and proteomics during GBM tumorigenesis. Therefore, we developed a comprehensive platform for high-throughput sample preparation with surface digestion for tissue microarrays, LC-MS/MS data dependent acquisition, and semi-automated data analysis to integrate glycomics, glycoproteomics, and proteomics for different grade of tumor and different subtypes of GBM. By analyzing GBM tissue microarrays, we found tumor grade and subtype specific changes to the expression of biomolecules. We also identified approximately 100 site-specific N- and mucin type O-glycosylations, the majority of which were previously unreported. Overall, our results improved the fundamental understandings about GBM pathogenesis. / 2018-11-02T00:00:00Z

Abstract The improvement of implant biocompatibility is constantly under investigation. Titanium is a standard biomaterial that performs well in dental and orthopedic implantations. However, detrimental adverse effects resulting from e.g. biomaterial properties, inflammatory responses and surgical procedures occasionally occur. Coating the biomaterials aims at increasing the proportion of successful operations. Pectins, large plant cell wall polysaccharides, are innovative, modifiable, and potentially anti-inflammatory candidates for biomaterial nanocoatings. In this thesis, covalently-grafted pectin fragments (modified hairy regions, MHRs) modified either in vitro (from apple) or in vivo (from potato) were tested. Cell culture vessels and titanium substratum coated with the apple-MHRs, MHR-A and a further-tailored fragment type, MHR-B, were compared with controls for their ability to support proliferation and differentiation of osteoclasts and osteoblasts. Cells grew and differentiated on MHR-B and on the control surfaces; MHR-A did not perform well in these assays. Genetically-engineered potato MHRs did not support bone cell growth to the same extent as apple MHR-B, but nonetheless the possibility to manipulate cellular proliferation with specific in vivo – modifications of pectins was introduced. When implanted into rat soft tissues, neither of the apple MHRs provoked severe acute inflammatory reactions, which indicates good in vivo - tolerance of these botanical macromolecules. These studies illustrate the biocompatibility of MHRs, and the directions towards which they could be further tailored. In terms of clinical use, their tolerability in vivo is especially significant.

Morindae Officinalis Radix (MOR), Bajitian in Chinese, is the dried root of Morinda officinalis F.C.How. (Rubiaceae). It is one of the most popular herbal medicines used in the southeast region of China. Various types of chemical constituents have been experimentally shown to be bioactive components of MOR, among which secondary metabolites and saccharides predominate. Pharmacological studies revealed MOR shows kidney tonifying, anti- osteoporosis, antidepressant, anti-inflammatory and antioxidant effect. Since 2002, MOR has been approved as a food supplement for daily healthcare, hence increasing consumption and demand for better quality of MOR. However, selection of MOR with superior quality is largely based on traditional experience which lacks scientific basis. For example, 3-4-year-old MOR is usually used without xylem; and processed MOR are believed to show different bioactivities. Therefore, to promote the rational utilization and ensure efficacy of MOR, overall qualitative and quantitative characterization of MOR in different traditional usage is needed. Anthraquinones, iridoid glycosides and oligosaccharides are the common reference compounds for chemical characterization of MOR. However, they are usually selectively characterized, which is not comprehensive enough in herbal quality evaluation. To deal with this, metabolomics targeting secondary metabolome and glycomics targeting glycome can be applied. And the integration of metabolomics and glycomics could be a promising approach to investigate overall chemical variations in MOR according to its traditional usage. Therefore, in this study, chromatographic methods for metabololmics and glycomics were firstly developed to study the traditional usage of MOR. In Chapter 2, they were applied for studying chemical variation and differences in growth year and plant tissue of MOR. In Chapter 3, chemical differences in processed products of MOR were also studied using the established metabololmics and glycomics methods. Further bioactivity differences of them were studied by cell metabolomics with HEK 293 cells under high glucose microenvironment. Besides that, in Chapter 4, consumption method of not only MOR, but other herbal medicines were studied. Conventional boiling water extraction (BWE) and ultrasound-assisted extraction (UAE) were compared to understand their effects on polysaccharides. For the study of growth year and tissues of MOR, the results showed that various types of bioactive components reached a maximum between 3-4 years of growth; and that xylem contained more potentially toxic constituents, but less bioactive components, than cortex. For the study of processing products, the results showed that secondary metabolome and glycome of raw MOR and other processing products was found qualitatively and quantitatively different. Contents of secondary metabolites were generally increased in processed products, while saccharides were decreased instead. Also, steamed MOR (F) seemed to show preventive effect of diabetic nephropathy and different MOR processing products had induced different metabolic changes on high glucose induced HEK 293 cells. In the study of extraction methods, the results showed that the polysaccharides from the herbal medicines by UAE were quantitatively and qualitatively different with those by BWE. The powerful extraction ability and polysaccharide degradation caused by ultrasound collectively contributed to these differences. It was revealed that not only the UAE conditions but also the polysaccharide structures could affect the extraction ability and polysaccharide degradation To conclude, metabolomics and glycomics were integrated in this study to investigate the variations in secondary metabolome and glycome in MOR. We had successfully applied these methods to study and provide scientific basis for traditional practice of MOR. We had proved that 3rd to 4th years of growth are the key period for the development of the biochemical signature of MOR. Xylem and cortex of MOR were qualitatively and quantitatively different and removing xylem could help to remove potentially toxic components. This study also provided scientific evidences for the justification of MOR and its processed products, as well as their metabolic effects on high glucose induced DN in HEK 293 cells. Besides, this study revealed both UAE parameters and structural properties of polysaccharides affects extraction recovery of polysaccharides in herbal medicines. Hence, we suggest UAE should be carefully considered before employing it in relevant chemical and pharmacological analysis.

Cryptosporidium parvum and Toxoplasma gondii are obligate intracellular parasites transmitted by ingestion of resilient walled structures called oocysts. Infection is self-limiting in adults with normal immune systems. However, severe disease can occur in immunocompromised individuals, or those without cellular immunity. Cryptosporidium is a leading cause of infant mortality in developing countries, due to diarrhea. There are no human vaccines and no broad effective drug treatments. Several vaccine candidates have been described: the glycoproteins Gp900, Gp40, and Gp15 and the protein Cp23, the immuno-dominant-antigen. Details about modifications to these proteins have not previously been reported. Using mass spectrometry, we identified 16 Cryptosporidium N-glycosylated proteins, including Gp900 and a possible oocyst wall protein. The observed N-glycan structures exhibited only two compositions: HexNAc2Hex5 and HexNAc2Hex6; these glycoforms had a single extended arm. The simplicity of Cryptosporidium N-glycans contrasts with the complexity of host N-glycans. Four heavily O-glycosylated proteins included Gp900, Gp40, Gp15, and a novel mucin-like protein, Gp20. Single O-HexNAc residues modified Ser/Thr in low density regions of Gp15 and Gp900, while attachment of O-HexNAc residues on tandem Ser/Thr repeats of Gp20 and Gp40 approached saturation. Identification of N-acetylgalactosamine (GalNAc) as the HexNAc released from proteins suggests that most Cryptosporidium O-glycans resemble the immunogenic Tn antigen (O-GalNAc). The immunodominant antigen Cp23, while not glycosylated, was discovered to be N-myristoylated and S-palmitoylated on the first and second residues, respectively. This is the first identification in Cryptosporidium of these modifications. Information about the N-glycans, O-glycans, and lipid modifications may be useful for design of better serodiagnostic reagents and more effective vaccines. To date, there are no vaccines against Toxoplasma infection, and the only available pharmaceutical therapies are expensive. In the second study, a novel O-fucose modification was discovered on nuclear pore-associated proteins including nucleoporins. This observation has profound implications on how the organism may regulate trafficking in/out of the nucleus by employing a system parallel to that described for O- linked N-acetylglucosamine in other organisms. In summary, the new details regarding the vaccine candidates of Cryptosporidium and the discovery of the novel O-fucose modifications in T. gondii provide information that could prove useful for development of effective drugs and vaccines. / 2018-11-01T00:00:00Z

Parkinson’s disease (PD) is a neurological disorder characterized by the lack of functional dopaminergic neurons in the nigrostriatal pathway in the brain. Current therapeutic strategies for the disease provide temporary symptomatic relief. Gene therapy has the potential to improve dopamine production in Parkinson’s disease patients. Adeno-associated viruses (AAV) are the vectors of choice in gene therapy for PD, due to their well-characterized safety and efficacy profiles, with all primary receptors being glycans. The problem with using AAV in PD gene therapy is that the aged brain is resistant to transduction of the virus, while PD primarily occurs with age. Thus, in Aim 1 we characterize the age-related changes in glycan receptors in the nigrostriatal pathway as a baseline to address current challenges in gene delivery in Parkinson’s disease. To make these measurements from specific regions of tissue, we develop a platform that incorporates on-slide digestion followed by LC-MS/MS for integrated glycomics and proteomics. Further, we apply this to understand aging- and PD-related changes in the human pre-frontal cortex in Aims 2 and 3, to understand normal and pathological aging processes as well as integrate this information with transcriptomics data, to assess risk factors that may contribute to Parkinson’s disease. Finally, we also apply the method to investigate cancer premalignancy and heterogeneity. Our on-slide method, used herein to study aging, Parkinson’s disease and cancer, can be applied to any precious biopsy specimens to enable glycomic and proteomic profiling in diverse diseases, and thus may have a broad impact on biomedical research.