Highly sensitive proteomics method to probe cell heterogeneity at single cell resolution

高灵敏度蛋白质组学方法以单细胞分辨率探测细胞异质性

• 批准号: 10693198
• 负责人: Yu Gao
• 金额: $ 39.41万
• 依托单位: UNIVERSITY OF ILLINOIS AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10693198
• 关键词: Bacteria; Cell Line; Cells; Cellular Structures; Chemicals; Classification; Coupled; Creativeness; Data; Detection; Development; Diagnosis; Disease; Event; Evolution; Fostering; Goals; Health; Heterogeneity; Individual; Investments; Knowledge; Label; Mammalian Cell; Measures; Messenger RNA; Methods; Mission; Mitochondria; National Institute of General Medical Sciences; Neoplasm Metastasis; Neurodegenerative Disorders; Peptides; Pharmaceutical Preparations; Pharmacotherapy; Phosphorylation; Post-Translational Protein Processing; Prevention; Proteome; Proteomics; Public Health; Research; Research Personnel; Research Support; Resolution; Resources; Scientific Advances and Accomplishments; Signal Transduction; Statistical Models; Strategic Planning; United States National Institutes of Health; developmental neurobiology; driving force; human disease; improved; informatics tool; innovation; insight; ionization; neuron development; neuronal tumor; new technology; novel; protein expression; transcriptomics; tumor

Project Summary/Abstract: As the single-cell transcriptomics analysis becomes more accessible, individual cells can now be classified individually, allowing us to understand cell heterogeneity as one of the key driving forces in neuron development and tumor evolution. However, the presence of mRNA is not always coupled with protein expression, single-cell proteomics will provide a more precise view of the cell components and signaling, including key post-translational modification events such as phosphorylation. Here we propose to combine several different strategies to develop a highly sensitive proteomics method to probe cell heterogeneity at single cell resolution. Specifically, we will 1) develop chemical labeling probes to enhance peptide ionization; 2) develop an isobaric isotopologue labeling approach to quantify single mammalian cell from various cell lines; 3) develop informatics tools and statistical models to resolve cell heterogeneity at single-cell resolution with non-single-cell proteomics data. Each of these proposed methods alone, could potentially enable us to measure the proteome of a single mammalian cell. When combined, they will result in a highly sensitive platform that could potentially allow us to probe the proteome at the level of a single mitochondria or bacteria. The long-term goal of this project is to elucidate the fundamental mechanisms of the origin and implications of cell heterogeneity. This proposed research is highly relevant to public health in the fields of tumor evolution, cancer metastasis, developmental neurobiology and neurodegenerative disease. Understanding cell heterogeneity will help us to develop more effective drug treatments to many diseases. Therefore, the proposed research is relevant to the part of NIH's mission that fosters “fundamental creative discoveries, innovative research strategies, and their applications as a basis for ultimately protecting and improving health” and that “supports research in the causes, diagnosis, prevention, and cure of human diseases.” The proposed research is relevant to the NIGMS 2015-2020 strategic plan: “Objective 1-1: Invest in and sustain a broad and diverse portfolio of highly meritorious research.”, “Objective 1-2: Promote the ability of investigators to pursue new research directions, novel scientific insights and innovative ideas”, and “Objective 3-1: Support access to essential research resources and the development of new technologies that enable novel scientific advances.”

项目摘要/摘要： 随着单细胞转录组学分析变得更加容易，单个细胞 现在可以单独分类，使我们能够将细胞异质性理解为一种 神经元发育和肿瘤进化的关键驱动力。然而，存在 mRNA并不总是与蛋白质表达相结合，单细胞蛋白质组学将提供更多 细胞成分和信号传导的精确视图，包括关键的翻译后修饰 磷酸化等事件。 在这里，我们建议结合几种不同的策略来开发高度敏感的 以单细胞分辨率探测细胞异质性的蛋白质组学方法。具体来说，我们将 1) 开发化学标记探针以增强肽电离； 2) 开发同量异位素 同位素体标记方法可量化不同细胞系中的单个哺乳动物细胞； 3） 开发信息学工具和统计模型来解决单细胞的细胞异质性 非单细胞蛋白质组学数据的分辨率。单独提出的每一种方法都可以 有可能使我们能够测量单个哺乳动物细胞的蛋白质组。当组合起来时， 它们将产生一个高度敏感的平台，可能使我们能够探测 单个线粒体或细菌水平的蛋白质组。 该项目的长期目标是阐明其基本机制 细胞异质性的起源和影响。这项拟议的研究与公众高度相关 肿瘤进化、癌症转移、发育神经生物学等领域的健康 神经退行性疾病。了解细胞异质性将有助于我们开发更多 对许多疾病有有效的药物治疗。因此，拟议的研究与 NIH 使命的一部分是促进“基础创造性发现、创新研究” 策略及其应用作为最终保护和改善健康的基础”和 “支持人类疾病的原因、诊断、预防和治疗的研究。” 拟议的研究与 NIGMS 2015-2020 战略计划相关：“目标 1-1： 投资并维持广泛且多样化的高度有价值的研究组合。”, “目标 1-2：提升研究者追求新研究方向、新颖科学的能力 见解和创新想法”，以及“目标 3-1：支持获得必要的研究 资源和新技术的开发，以实现新的科学进步。”

项目成果

Sequence Coverage Visualizer: A Web Application for Protein Sequence Coverage 3D Visualization.

• DOI: 10.1021/acs.jproteome.2c00358
• 发表时间: 2023-02-03
• 期刊: JOURNAL OF PROTEOME RESEARCH
• 影响因子: 4.4
• 作者: Shao, Xinhao;Grams, Christopher;Gao, Yu
• 通讯作者: Gao, Yu

Evaluation of the Binding Preference of Microtubes for Nanoproteomics Sample Preparation.

• DOI: 10.1021/acs.jproteome.2c00477
• 发表时间: 2023-01-06
• 期刊: JOURNAL OF PROTEOME RESEARCH
• 影响因子: 4.4
• 作者: Zhang, Ziwei;Gao, Yu
• 通讯作者: Gao, Yu

MatrisomeDB 2.0: 2023 updates to the ECM-protein knowledge database.

• DOI: 10.1093/nar/gkac1009
• 发表时间: 2023-01-06
• 期刊: NUCLEIC ACIDS RESEARCH
• 影响因子: 14.9
• 作者: Shao, Xinhao;Gomez, Clarissa D.;Kapoor, Nandini;Considine, James M.;Grams, Christopher;Gao, Yu (Tom);Naba, Alexandra
• 通讯作者: Naba, Alexandra