Sensitive and Quantitative MS-bases Glycomic Mapping Platform

基于 MS 的灵敏定量糖组图谱平台

• 批准号: 10318016
• 负责人: Yehia Mechref
• 金额: $ 31.61万
• 依托单位: TEXAS TECH UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-15 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10318016
• 关键词: 2019-nCoV; Address; Adhesions; Algae; Algorithms; Alzheimer' s Disease; Anabolism; Area; Bacterial Infections; Bioinformatics; Biological; Biological Process; Blood capillaries; COVID-19; Carbon; Cell Differentiation process; Cells; Cirrhosis; Clinical; Code; Communicable Diseases; Communities; Complex; Computer software; Coronavirus; Coronavirus spike protein; Coupled; Cystic Fibrosis; Development; Diabetes Mellitus; Diagnostic; Disease; Drug Targeting; Fingerprint; Future; Gangliosides; Genes; Glucose; Glycoconjugates; Glycolipids; Glycoproteins; Goals; High temperature of physical object; Human Genome; Immune response; Inflammation; Investigation; Ions; Isomerism; Isotopes; Kidney Diseases; Label; Libraries; Machine Learning; Malignant Neoplasms; Malignant neoplasm of esophagus; Malignant neoplasm of liver; Mass Spectrum Analysis; Medical; Metabolic Diseases; Metastatic malignant neoplasm to brain; Methods; Monitor; Natural graphite; Nature; Oligosaccharides; Outcome; Parkinson Disease; Pattern; Polysaccharides; Post-Translational Protein Processing; Process; Protein Glycosylation; Proteins; Public Health; Reaction; Recombinant Proteins; Research; Research Activity; Research Personnel; Resolution; Role; Running; Sampling; Scientist; Software Tools; Structure; Symbiosis; System; Techniques; Time; Traumatic Brain Injury; Variant; Viral; Virion; Virus Diseases; analytical tool; base; bioinformatics tool; cancer biomarkers; carbohydrate structure; computerized data processing; drug development; glycosylation; implementation tool; improved; indexing; interest; ionization; malignant breast neoplasm; nano; pathogen; predictive modeling; predictive signature; protein complex; side effect; software development; tandem mass spectrometry; therapeutic protein; tool; tool development

Glycosylation is one of the most complex protein modifications; more than 50% of mammalian proteins are glycosylated. The fact that there are 100,000 proteoforms coded by only ~20,300 genes identified in the human genome emphasizes the importance of posttranslational modifications (PTMs) like glycosylation. Aberrant protein glycosylation has been implicated in many diseases, such as Alzheimer’s disease, congenital/metabolic disorders, diabetes, inflammation, Parkinson’s disease, bacterial/viral infectious diseases, and various cancers. More recently, glycans have been associated with coronavirus spike glycoproteins, including the SARS- CoV-2 virion. The diverse biological roles of glycans and their implications in diseases have created a demand for reliable qualitative and quantitative glycomic approaches, which facilitates sensitive investigation of glycan changes in different biological and biomedical samples. Mass spectrometry (MS) is the most efficient technique in glycomics due to its high sensitivity and capacity for acquiring structural information. However, glycomic research remains a challenge because of the microheterogeneity of glycan compositions in complex biological samples; the relatively low abundance in nature and low ionization efficiency in MS analysis; and the existence of variant positional and linkage isomers caused by the biosynthesis process. To overcome these challenges, several separation methods have been coupled to MS. Despite the development of these separation techniques, isomeric separation of glycans remains insufficient. There is an increasing demand for more efficient isomeric separation approaches since glycan isomers have been related to different diseases. The main aim of this proposal is to provide easily accessible, adaptable, and affordable strategies for better separation and characterization of glycans and glycan isomers derived from different glycoconjugates. Aim 1 is focused on finding a replacement for porous craphitic carbon columns that sufferes from low reprodcubility and loss of resolution and efficiency with time. The in-house mesoporous graphitic carbon (MGC)-LC-MS will be investigated for both permethylated (Aim 1a) and native (Aim 2b) isomeric separation of N- and O-glycans, glycolipid glycans, and free oligosaccharides. Other alternatives (also part of Aim 1a), such as 50 cm and 200 cm micro pillar array columns (μPAC)-C18-LC-MS, and a 50 cm long capillary nanoC18-LC-MS, will also be evaluated to achieve an improved isomeric separation of glycan isomers. Subsequently, GUI will be utilized to improve the identification of glycan isomers. A GUI libraries for the separation strategies developed in Aim 1 will be established to normalize the possible retention time shift among different runs (Aim 2). LC-M based glycomics quantitative strategies will be developed and assessed in Aim 3. The combination of permethylation and TMT will capitalize on the advantages of both techniques, providing enhanced sensitivity and accuracy in glycan quantitation (Aim 3a). Additionally, the combination of 8-plex isotopic permethylation and 6-plex TMT will facilitate a reliable 48-plex, thus significantly increasing the throughput of analysis (Aim 3b). Furthermore, with the improved separation and identification (Aim 1 and 2), PRM will be employed to assist the better quantitation of glycans and the differentiation of glycan isomers. A library containing the fragments fingerprint of each glycan isomer will be created to aid the glycan isomeric identification (Aim 3c). The development of automated software for easy, fast, and accurate glycomic data processing is the main focus of Aim 4. Finally, the aforementioned strategies and tools will be applied to clinical samples to address a variety of biological and biomedical issues such as COVID-19, breast cancer brain metastasis, liver cancer vs. cirrhosis, kidney diseases, algae development, and others (Aim 5). The development of the proposed methods and algorithms will help us and our collaborators to better understand the attributes and biomedical significance of glycan isomers in the development and progression of esophageal, breast, and liver cancer. Furthermore, we expect the analytical tools and algorithms proposed here to benefit researchers and scientists who are interested in understanding the biological attributes of glycan isomers in other systems.

糖基化是最复杂的蛋白质修饰之一；超过50%的哺乳动物