Modeling transcriptional and post-transcriptional systems for regulating non-genetic heterogeneity in mammalian cells
Modeling transcriptional and post-transcriptional systems for regulating non-genetic heterogeneity in mammalian cells
批准号:
10623648
负责人:
Tian Hong
金额:
$33.05万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-06-01 至 2028-05-31
关键词:
BindingCellsComputing MethodologiesDataDegenerative DisorderDevelopmentDiseaseEpithelial CellsEpitheliumFoundationsGene ExpressionGene Expression ProfileGenesGenetic TranscriptionHeterogeneityMalignant NeoplasmsMammalian CellMeasurementMesenchymalMethodsMicroRNAsModelingMolecularMotor NeuronsNeuronal DifferentiationPatternPattern FormationPhysiologyPlayRoleSignal TransductionSiteSpinal CordStem Cell FactorSystemTechniquesTestingTherapeuticcancer cellcancer drug resistancedevelopmental diseaseepithelial to mesenchymal transitionexperimental studygene regulatory networkinsightlung cancer cellmathematical modelnon-geneticnovelposttranscriptionalstemstem cellssuccesstheoriestissue degenerationtumortumor progression
中文摘要
项目概要
实验技术的最新进展允许对非
哺乳动物细胞的遗传异质性是干细胞动力学的关键因素
分化潜能以及癌细胞的耐药性。然而,仍然具有挑战性
了解关于这种类型的潜在基因异质性的许多令人费解的观察结果
监管网络。例如,祖细胞在数天的时间尺度上恢复其异质性
具有极端基因表达模式的亚群,并且这些细胞从可塑性转变
分化过程中强有力的承诺和模式形成的动力;上皮细胞可以是
在接收到信号后,分布在上皮间质谱中的稳定连续体中
肿瘤。现有理论对这些重要的动态和模式提供的见解非常有限。我们
提议将数学模型、分析基因调控网络的新方法和
基因表达数据、运动神经元分化系统中的实验以及涉及的系统
上皮间质转化研究转录和转录后机制
哺乳动物细胞中潜在的非遗传异质性。
我们建议测试一种用于控制祖细胞的发散振荡器的新颖理论框架
计算方法和实验系统的动力学。我们将严格制定并
测试运动神经元分化的振荡器到开关转换的新假设
脊髓发育。源于我们最近关于令人惊讶的转录后机制的结果
对于多稳定性和振荡,我们将使用新颖的代数方法来建立关系
microRNA 结合位点的数量与生物学上合理的细胞状态之间的关系。我们将测试
microRNA 结合在上皮细胞可塑性中的实验作用。我们将研究以下角色
肺癌细胞动力学中的上皮可塑性和 microRNA。拟议研究的成功
将为解释和理解动态基因提供新的理论基础和新方法
哺乳动物细胞非遗传异质性的表达数据。其理论和方法可作为
开发治疗与发育、组织退化和癌症相关疾病的疗法的基金会。
英文摘要
PROJECT SUMMARY
Recent advances of experimental techniques allow quantitative and systems‐wide measurements of non‐
genetic heterogeneity of mammalian cells, which serves as a crucial factor for stem cell dynamics and
differentiation potentials, as well as drug resistance of cancer cells. However, it remains challenging to
understand many puzzling observations regarding this type of heterogeneity in terms of underlying gene
regulatory networks. For example, progenitor cells restore their heterogeneity on timescales of days from
subpopulation with extreme gene expression patterns, and these cells switch from plasticity‐enabling
dynamics to robust commitment and pattern formation during differentiation; epithelial cells can be
distributed in a stable continuum in the epithelial‐mesenchymal spectrum upon receiving signals in
tumors. Existing theories provide very limited insights into these important dynamics and patterns. We
propose to combine mathematical modeling, new methods of analyzing gene regulatory networks and
gene expression data, and experiments in a motor neuron differentiation system, and systems involving
epithelial‐mesenchymal transition to study transcriptional and post‐transcriptional mechanisms
underlying non‐genetic heterogeneity in mammalian cells.
We propose to test a novel theoretical framework of a diverging oscillator for controlling progenitor cell
dynamics with both computational methods and experimental systems. We will rigorously formulate and
test a new hypothesis of an oscillator‐to‐switch transition for motor neuron differentiation in the
developing spinal cord. Stemming from our recent results on surprising post‐transcriptional mechanisms
for multistability and oscillation, we will use novel algebraic approaches to establish the relationship
between the number of microRNA bindings sites and biologically plausible cell states. We will test the
roles of microRNA binding in epithelial cell plasticity experimentally. We will examine the roles of
epithelial plasticity and microRNAs in dynamics of lung cancer cells. The success of the proposed study
will provide a new theoretical basis and new methods for interpreting and understanding dynamical gene
expression data on non‐genetic heterogeneity in mammalian cells. The theories and methods can used as
a foundation to develop therapeutics for diseases related to development, tissue degeneration and cancer.
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Mathametical modeling of cell fate transitions regulated by ultra-feedbacks
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批准号:10457831
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项目类别:
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资助金额:$20.0万
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财政年份:2020
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负责人:Tian Hong
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依托单位:
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财政年份:2020
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负责人:Tian Hong
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依托单位:
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