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: 10697345
• 负责人: Yehia Mechref
• 金额: $ 30.29万
• 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/10697345
• 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; Disease; Drug Targeting; Fingerprint; Future; Gangliosides; Genes; Glucose; Glycoconjugates; Glycolipids; Glycoproteins; Goals; Heterogeneity; High temperature of physical object; Human Genome; Immune response; Inflammation; Investigation; Ions; Isomerism; Isotopes; Kidney Diseases; Label; Libraries; Malignant Neoplasms; Malignant neoplasm of esophagus; Malignant neoplasm of liver; Maps; Mass Spectrum Analysis; Metabolic Diseases; Metastatic malignant neoplasm to brain; Methods; Monitor; Nature; Oligosaccharides; Outcome; Parkinson Disease; Pattern; Polysaccharides; Porosity; 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; Symbiosis; System; Techniques; Time; Traumatic Brain Injury; Variant; Viral; Virion; Virus Diseases; analytical tool; base; bioinformatics tool; cancer biomarkers; carbohydrate structure; clinical diagnostics; computerized data processing; drug development; glycosylation; implementation tool; improved; indexing; interest; ionization; machine learning prediction; malignant breast neoplasm; nano; pathogen; 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 蛋白质是糖基化的。事实上，有100，000种蛋白质型仅由~20，300种编码， 在人类基因组中发现的基因强调了翻译后 修饰（PTM）如糖基化。异常的蛋白质糖基化与 许多疾病，如阿尔茨海默病，先天性/代谢紊乱，糖尿病， 炎症、帕金森病、细菌/病毒感染性疾病和各种癌症。更 最近，聚糖与冠状病毒刺突糖蛋白有关，包括SARS- CoV-2病毒粒子。聚糖的多种生物学作用及其在疾病中的意义已经引起了人们的广泛关注。 创造了对可靠的定性和定量糖组学方法的需求， 对不同生物和生物医学样品中聚糖变化的灵敏度研究。质量 质谱法（MS）是糖组学中最有效的技术，因为其灵敏度高， 获取结构信息的能力。然而，糖组学研究仍然是一个挑战， 由于复杂生物样品中聚糖组成的微观异质性， 自然界中相对低的丰度和MS分析中的低电离效率;以及 由生物合成过程引起的位置和连接异构体的变体。克服这些 尽管存在挑战，但几种分离方法已与MS结合。 在这些分离技术中，聚糖的异构体分离仍然不足。有一个 对更有效的异构体分离方法的需求不断增加，因为聚糖异构体 与不同的疾病有关。 该提案的主要目的是提供易于获得、适应性强和负担得起的 用于更好地分离和表征来自以下物质的聚糖和聚糖异构体的策略： 不同的糖复合物。目标1的重点是寻找多孔石墨碳的替代品 色谱柱重现性差，分辨率和效率随时间降低。的 将研究内部中孔石墨碳（MGC）-LC-MS， (Aim 1a）和天然（目的2b）N-和O-聚糖、糖脂聚糖的异构体分离，以及 游离寡糖。其他替代品（也是目标1a的一部分），如50厘米和200厘米微型 柱阵列柱（μ PAC）-C18-LC-MS和50 cm长的毛细管nanoC18-LC-MS也将 以实现聚糖异构体的改进的异构体分离。随后，GUI 将用于改进聚糖异构体的鉴定。一个GUI库， 将制定目标1中制定的策略，以规范可能的保留时间偏移 在不同的运行中（目标2）。将开发基于LC-M的糖组学定量策略 并在目标3中进行评估。全甲基化和TMT的组合将利用 这两种技术的优点，提供了更高的灵敏度和准确度的聚糖 定量（目标3a）。此外，8重同位素全甲基化和6重同位素全甲基化的组合可用于治疗癌症。 TMT将促进可靠的48-plex，从而显著增加分析的吞吐量（Aim 3 b）。此外，通过改进的分离和识别（目标1和2），PRM将被 用于帮助更好地定量聚糖和区分聚糖异构体。一 将创建包含每种聚糖异构体的片段指纹的文库，以帮助聚糖 异构体鉴定（目标3c）。自动化软件的开发， 精确的糖组学数据处理是目标4的主要焦点。最后，上述 策略和工具将应用于临床样本，以解决各种生物和 生物医学问题，如COVID-19，乳腺癌脑转移，肝癌与肝硬化， 肾脏疾病、藻类发育和其他（目标5）。发展拟议的 方法和算法将帮助我们和我们的合作者更好地理解属性， 聚糖异构体在食管癌发生和发展中的生物医学意义， 乳腺癌和肝癌。此外，我们期望所提出的分析工具和算法 在这里，有利于研究人员和科学家谁是有兴趣了解生物 其他系统中聚糖异构体的属性。

项目成果

Glucose unit index (GUI) of permethylated glycans for effective identification of glycans and glycan isomers.

• DOI: 10.1039/d0an00314j
• 发表时间: 2020-10-21
• 期刊: The Analyst
• 作者: Gautam S ;Peng W ;Cho BG ;Huang Y ;Banazadeh A ;Yu A ;Dong X ;Mechref Y
• 通讯作者: Mechref Y

Heat Stress of Algal Partner Hinders Colonization Success and Alters the Algal Cell Surface Glycome in a Cnidarian-Algal Symbiosis.

• DOI: 10.1128/spectrum.01567-22
• 发表时间: 2022-06-29
• 期刊: MICROBIOLOGY SPECTRUM
• 影响因子: 3.7
• 作者: Maruyama, Shumpei;Mandelare-Ruiz, Paige E.;McCauley, Mark;Peng, Wenjing;Cho, Byeong Gwan;Wang, Junyao;Mechref, Yehia;Loesgen, Sandra;Weis, Virginia M.
• 通讯作者: Weis, Virginia M.

Implication of the Kallikrein-Kinin system in neurological disorders: Quest for potential biomarkers and mechanisms.

• DOI: 10.1016/j.pneurobio.2018.01.003
• 发表时间: 2018-06
• 期刊: Progress in neurobiology
• 影响因子: 6.7
• 作者: Nokkari A;Abou-El-Hassan H;Mechref Y;Mondello S;Kindy MS;Jaffa AA;Kobeissy F
• 通讯作者: Kobeissy F

Isomeric separation of permethylated glycans by extra-long reversed-phase liquid chromatography (RPLC)-MS/MS.

• DOI: 10.1039/d2an00010e
• 发表时间: 2022-05-17
• 期刊: ANALYST
• 影响因子: 4.2
• 作者: Wang, Junyao;Dong, Xue;Yu, Aiying;Huang, Yifan;Peng, Wenjing;Mechref, Yehia
• 通讯作者: Mechref, Yehia

LC-MS/MS Isomeric Profiling of N-Glycans Derived from Low-Abundant Serum Glycoproteins in Mild Cognitive Impairment Patients.

• DOI: 10.3390/biom12111657
• 发表时间: 2022-11-08
• 期刊: Biomolecules
• 影响因子: 5.5