Dissecting subcellular and cellular organization by spatial molecular neighborhood networks

通过空间分子邻域网络剖析亚细胞和细胞组织

• 批准号: 10713565
• 负责人: Ahmet F. Coskun
• 金额: $ 37.21万
• 依托单位: GEORGIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-22 至 2028-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10713565
• 关键词: 3-Dimensional; Affect; Automobile Driving; Benchmarking; Bioinformatics; Biological Assay; Biology; Biomanufacturing; Cell Survival; Cell model; Cell physiology; Cells; Collaborations; Crowding; Data Analyses; Data Set; Disease; Environment; Epithelial Cells; Event; Fluorescent in Situ Hybridization; Functional disorder; Gene Expression; Genes; Genetic; Genomics; Goals; Growth; Health; Human; Image; Imaging technology; Individual; Intervention; Ligation; Light; Mathematics; Measurement; Mesenchymal; Modeling; Molecular; Molecular Evolution; Neighborhoods; Normal Cell; Normal tissue morphology; Outcome; Pathology; Pharmaceutical Preparations; Phenotype; Population; Proliferating; Protein Analysis; Proteins; Public Health; RNA; Regulation; Research; Resolution; Role; Signal Transduction; Signaling Protein; Specificity; Specimen; Stimulus; System; Technology; Tissues; Transcript; Visualization; Work; biological systems; experience; high throughput screening; molecular imaging; molecular modeling; molecular scale; response; small molecule; superresolution microscopy; tissue/cell culture; treatment response

Subcellular organization of intracellular molecules regulates basic cell functions such as growth, division, proliferation, and differentiation. By regulating subcellular neighborhoods of RNAs and proteins, cells survive but also specialize in a multicellular system. While subcellular localization mechanisms are widely studied, the role of subcellular neighborhoods in determining the cellular response to stimuli and multiple drugs has been limited to a few low-throughput and low-sensitivity molecular studies. Little is known about how these highly coordinated subcellular neighborhoods give rise to tissue-specificity, tissue-sate, and how they regulate cell function in distinct subcellular volumes of tissue states and phenotypes. Image-based visualization of molecular neighborhoods has explored only a few target molecules, yielding evidence of the importance of subcellular localization of transcripts and protein factors. One bottleneck in subcellular regulation is the lack of models explaining neighborhood interactions of molecules that are driving cellular response in tissues from distinct abnormalities. Previous work established multiplexed gene expression measurements to model subcellular RNA neighborhoods and multiparameter protein analysis to quantify spatial signaling protein neighborhoods that are altered in response to perturbations. However, dominant signaling protein and RNA neighborhoods have not been established at a physically meaningful resolution in widely employed mesenchymal and epithelial cells as they respond to perturbations, experience differentiation events, or adapt to tissue environments of individuals treated with cell-based or small molecule interventions for correcting abnormalities due to genetic or molecular dysfunction. Thus, the long-term goal of this project is to leverage advanced high-throughput screening and spatially resolved genomic and protein measurements in single cells for modeling molecular neighborhoods in populations and tissue contexts. To achieve these tasks, using recent advances in sequential fluorescence in situ hybridization and multiplexed protein imaging, this proposal plans to 1) mechanistically dissect the molecular RNA and protein neighborhoods using proximity ligation assays, 2) enhance the spatial information capacity of molecular neighborhoods using 3D super-resolution microscopy and temporal evolution of molecular neighborhoods by pseudo-temporal differentiation models, 3) evaluate the outcome of subcellular neighborhood organization and tissue context of mesenchymal cells near vessels and epithelial cells near linings from human specimens isolated from health restoring interventions. Molecular benchmarking and normal tissue annotations will be performed in collaboration with signaling biology, bioinformatics, biomanufacturing, and pathology experts. Cross-scale molecular control from subcellular neighborhoods to tissue organization will reveal how a systemic response to treatments can be re-stratified by network variance of molecular neighborhoods. This MIRA proposal sheds light on the spatially resolved subcellular organization in health and disease, providing a predictive metric for deciphering tissue-state control and alterations in many disorders.

细胞内分子的亚细胞组织调节基本细胞功能，如生长、分裂、增殖和分化。通过调节 RNA 和蛋白质的亚细胞邻域，细胞不仅可以生存，而且还可以专门形成多细胞系统。虽然亚细胞定位机制得到了广泛研究，但亚细胞邻域在确定细胞对刺激和多种药物的反应中的作用仅限于一些低通量和低灵敏度的分子研究。关于这些高度协调的亚细胞邻域如何产生组织特异性、组织状态，以及它们如何在组织状态和表型的不同亚细胞体积中调节细胞功能，人们知之甚少。基于图像的分子邻域可视化仅探索了少数目标分子，提供了转录本和蛋白质因子亚细胞定位重要性的证据。亚细胞调节的一个瓶颈是缺乏解释分子邻域相互作用的模型，这些分子驱动组织中不同异常的细胞反应。先前的工作建立了多重基因表达测量来模拟亚细胞RNA邻域和多参数蛋白质分析来量化响应扰动而改变的空间信号蛋白邻域。然而，在广泛使用的间充质和上皮细胞中，主导信号蛋白和RNA邻域尚未以物理上有意义的分辨率建立起来，因为它们对扰动做出反应，经历分化事件，或适应接受基于细胞或小分子干预治疗的个体的组织环境，以纠正由于遗传或分子功能障碍引起的异常。因此，该项目的长期目标是利用先进的高通量筛选和单细胞中的空间分辨基因组和蛋白质测量来模拟群体和组织环境中的分子邻域。为了实现这些任务，利用顺序荧光原位杂交和多重蛋白质成像方面的最新进展，该提案计划 1) 使用邻近连接分析机械地剖析分子 RNA 和蛋白质邻域，2) 使用 3D 超分辨率显微镜增强分子邻域的空间信息能力，并通过伪时间分化模型增强分子邻域的时间演化，3) 评估从健康恢复干预措施中分离出的人体标本中血管附近的间充质细胞和内壁附近的上皮细胞的亚细胞邻域组织和组织背景的结果。将与信号生物学、生物信息学、生物制造和病理学专家合作进行分子基准测试和正常组织注释。从亚细胞邻域到组织组织的跨尺度分子控制将揭示如何通过分子邻域的网络方差重新分层对治疗的系统反应。 MIRA 的这项提案揭示了健康和疾病中空间分辨的亚细胞组织，为破译许多疾病的组织状态控制和改变提供了预测指标。