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.”

项目概要/摘要： 随着单细胞转录组学分析变得越来越容易， 现在可以单独分类，使我们能够将细胞异质性理解为其中之一 神经元发育和肿瘤进化的关键驱动力。然而， 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的 细胞组分和信号传导的精确视图，包括关键的翻译后修饰 例如磷酸化。 在这里，我们建议联合收割机几种不同的策略，以开发一个高度敏感的 蛋白质组学方法以单细胞分辨率探测细胞异质性。具体而言，我们将1） 开发化学标记探针以增强肽离子化; 2）开发同量异位素 同位素物标记方法以定量来自各种细胞系的单个哺乳动物细胞; 3） 开发信息学工具和统计模型，以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。每一种提出的方法，都可以 使我们有可能测量单个哺乳动物细胞的蛋白质组。当结合时， 它们将产生一个高度敏感的平台，可能使我们能够探测 在单个线粒体或细菌水平上的蛋白质组。 本项目的长期目标是阐明 细胞异质性的起源和影响。这项研究与公众高度相关。 肿瘤演变、癌症转移、发育神经生物学和 神经退行性疾病了解细胞异质性将有助于我们开发更多 对许多疾病有效的药物治疗。因此，拟议的研究与以下方面有关： 国家卫生研究院的使命之一是促进“基本的创造性发现、创新研究 作为最终保护和改善健康的基础”， 它“支持对人类疾病的病因、诊断、预防和治疗的研究”。 拟议的研究与NIGMS 2015-2020年战略计划有关：“目标1-1： 投资并维持广泛而多样化的高度有价值的研究组合。“目标 1-2：促进研究人员追求新的研究方向、新的科学方法和新的科学方法的能力。 洞察力和创新思想”和“目标3-1：支持获得基本研究 资源和新技术的发展，使新的科学进步。”

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