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

基本信息

  • 批准号:
    10713565
  • 负责人:
  • 金额:
    $ 37.21万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 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

项目摘要

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细胞的基本功能,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,细胞生存下来,但也专门在多细胞系统中。虽然亚细胞定位机制得到了广泛的研究,但亚细胞邻域在决定细胞对刺激和多种药物的反应中的作用仅限于少数低通量和低敏感性的分子研究。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,以及它们如何在不同的亚细胞体积的组织状态和表型中调节细胞功能,人们知之甚少。基于图像的分子邻域可视化只探索了几个目标分子,证明了转录本和蛋白质因子亚细胞定位的重要性。亚细胞调控的一个瓶颈是缺乏模型来解释分子之间的邻域相互作用,这些分子正在推动组织中不同异常的细胞反应。以前的工作建立了多路基因表达测量来模拟亚细胞RNA邻域,并建立了多参数蛋白质分析来量化空间信号蛋白质邻域,这些空间信号蛋白质邻域因扰动而改变。然而,在广泛使用的间充质细胞和上皮细胞中,主要的信号蛋白和RNA邻域尚未建立在物理上有意义的分辨率上,因为它们响应扰动、经历分化事件或适应组织环境,这些个体接受了基于细胞或小分子干预的治疗,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空间分辨的基因组和蛋白质测量来模拟种群和组织环境中的分子邻域。为了实现这些任务,利用序列荧光原位杂交和多重蛋白质成像的最新进展,该建议计划1)使用邻近连接分析来机械地剖析分子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来研究分子邻域的时间演化,3)评估从健康恢复干预措施中分离的人类标本中血管附近的亚细胞邻域组织和衬里附近的间质细胞的组织结构和组织背景。分子基准和正常组织注释将与信号生物学、生物信息学、生物制造和病理学专家合作进行。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变异来重新分层系统对治疗的反应。Mira的这一建议揭示了健康和疾病中空间分辨的亚细胞组织,为破译组织状态控制和许多疾病中的变化提供了一个预测性指标。

项目成果

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Ahmet F. Coskun其他文献

Clinically relevant clot resolution via a thromboinflammation-on-a-chip
通过芯片上血栓炎症实现临床相关的血栓溶解
  • DOI:
    10.1038/s41586-025-08804-7
  • 发表时间:
    2025-04-02
  • 期刊:
  • 影响因子:
    48.500
  • 作者:
    Yongzhi Qiu;Jessica Lin;Audrey Wang;Zhou Fang;Yumiko Sakurai;Hyoann Choi;Evelyn K. Williams;Elaissa T. Hardy;Kristin Maher;Ahmet F. Coskun;Gary Woods;Wilbur A. Lam
  • 通讯作者:
    Wilbur A. Lam
A Dynamic Personalized Human 3D Organoid for the Study of the Tumor Microenvironment and Metabolism in Acute Myeloid Leukemia Using Patient-Derived Xenografts
  • DOI:
    10.1182/blood-2022-170225
  • 发表时间:
    2022-11-15
  • 期刊:
  • 影响因子:
  • 作者:
    Alejandro De Janon;Madison Stout;Diana Fridlyand;Zhou Fang;Ahmet F. Coskun;Douglas K Graham;Athanasios Mantalaris;Deborah DeRyckere;Nicki Panoskaltsis
  • 通讯作者:
    Nicki Panoskaltsis
Decoding senescence of aging single cells at the nexus of biomaterials, microfluidics, and spatial omics
在生物材料、微流控和空间组学的交汇处解码衰老的衰老单细胞
  • DOI:
    10.1038/s41514-024-00178-w
  • 发表时间:
    2024-11-26
  • 期刊:
  • 影响因子:
    6.000
  • 作者:
    Abhijeet Venkataraman;Ivan Kordic;JiaXun Li;Nicholas Zhang;Nivik Sanjay Bharadwaj;Zhou Fang;Sandip Das;Ahmet F. Coskun
  • 通讯作者:
    Ahmet F. Coskun

Ahmet F. Coskun的其他文献

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{{ truncateString('Ahmet F. Coskun', 18)}}的其他基金

Decoding Spatially Resolved Single Cell Metabolic Trajectory of Tonsil Tissues and Organoids
解码扁桃体组织和类器官的空间分辨单细胞代谢轨迹
  • 批准号:
    10751125
  • 财政年份:
    2023
  • 资助金额:
    $ 37.21万
  • 项目类别:
Tissue systems biology of immune dysregulation in aging by single cell spatial metabolomics
通过单细胞空间代谢组学研究衰老过程中免疫失调的组织系统生物学
  • 批准号:
    10647249
  • 财政年份:
    2023
  • 资助金额:
    $ 37.21万
  • 项目类别:
Tracing spatial organization of germinal centers in rhesus macaques
追踪恒河猴生发中心的空间组织
  • 批准号:
    10762072
  • 财政年份:
    2023
  • 资助金额:
    $ 37.21万
  • 项目类别:
Spatial transcriptional phenotyping of Sjögren’s disease tissue-resident mesenchymal stromal cells and neighbors in labial salivary glands
干燥病组织驻留间充质基质细胞和唇唾液腺邻近细胞的空间转录表型
  • 批准号:
    10575107
  • 财政年份:
    2023
  • 资助金额:
    $ 37.21万
  • 项目类别:
Spatial Epigenomic Profiling of Immune Cell Signatures at Subcellular Resolution in Health and Disease
健康和疾病中免疫细胞特征的亚细胞分辨率空间表观基因组分析
  • 批准号:
    10425357
  • 财政年份:
    2018
  • 资助金额:
    $ 37.21万
  • 项目类别:
Spatial Epigenomic Profiling of Immune Cell Signatures at Subcellular Resolution in Health and Disease
健康和疾病中免疫细胞特征的亚细胞分辨率空间表观基因组分析
  • 批准号:
    10065913
  • 财政年份:
    2018
  • 资助金额:
    $ 37.21万
  • 项目类别:
Spatial Epigenomic Profiling of Immune Cell Signatures at Subcellular Resolution in Health and Disease
健康和疾病中免疫细胞特征的亚细胞分辨率空间表观基因组分析
  • 批准号:
    10201436
  • 财政年份:
    2018
  • 资助金额:
    $ 37.21万
  • 项目类别:

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