The design principles of the eukaryotic cell: uncovering the coordination of systems-level organelle dynamics, metabolism and growth
The design principles of the eukaryotic cell: uncovering the coordination of systems-level organelle dynamics, metabolism and growth
批准号:
10673651
负责人:
Arindam Shankar Mukherji
金额:
$39.38万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-08-01 至 2026-07-31
关键词:
AgingBiochemicalBiogenesisBiologicalCalibrationCategoriesCell ProliferationCell SeparationCellsCellular biologyChemicalsComplexDataDiabetes MellitusDiseaseEukaryotaEukaryotic CellFoundationsFutureGene ExpressionGene Expression RegulationGoalsGrowthHealthIndividualInvestigationKnowledgeMachine LearningMalignant NeoplasmsMammalsMeasurementMeasuresMediatingMetabolicMetabolismModelingOrganellesOrganismOutputPathologyPhysiologicalPlayPositioning AttributeProliferatingPropertyResearchRoleRouteShapesSiteSystemTestingVisualizationcell growthcell typecellular developmentdesignflexibilityfungusgenetic manipulationimaging platforminsightmathematical modelmetabolic profilemetabolomicsnew therapeutic targetpredictive modelingprogramspublic health relevance
中文摘要
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英文摘要
Project Summary
Perhaps the defining feature of the eukaryotic cell is its organization into biochemically distinct compartments
known as organelles. While the biochemical functions of individual organelles are often well known,
how cells regulate the copy numbers, sizes, and subcellular positions of its diverse organelles in a coordinated
fashion and how organelles interact to produce integrated physiological outputs remain one of the grand
challenges in cell biology. The goal of my research program is to discover the quantitative principles
governing how cells regulate systems-level organelle dynamics to coordinate metabolism, growth, and
proliferation. To achieve this goal, my research strategy will proceed along two directions. In the first
direction, I will quantitatively determine how cells coordinate systems-level organelle dynamics with cellular
growth demands. Specifically, I will quantify and build a mathematical model of the relationship between
cellular organelle composition and cell growth. The model will be calibrated from data obtained by
simultaneously visualizing all major metabolic organelles using our machine learning-based hyperspectral
imaging platform, exerting chemical biological control over cell growth and proliferation rates, and genetically
perturbing key organelle biogenesis, organization, and interaction factors. In the second direction, I will
determine how cells coordinate systems-level organelle dynamics and gene expression to control metabolism
during growth and proliferation. I will categorize single cells according to their organelle content and
systematically measure the temporal correlations in their expression of genes whose products execute
organelle-specific functions. I will concomitantly measure the metabolomic profile of these cells sorted by
organelle content. I will then combine these measurements to develop a mathematical model that quantitatively
captures the connection between gene expression and metabolism as mediated by the cell's organelle
makeup. I will subsequently test predictions of this model by systematically tuning organelle interaction
strengths by modulating the expression of organelle biogenesis factors and organelle contact sites. Successful
investigations along these two directions will yield mechanistic insight into how to untangle the complex
interdependencies between organelle dynamics, metabolism, and cell growth and proliferation. A systems-
level understanding of how organelle composition and interactions coordinate metabolism to control cellular
growth and development will lay a rigorous foundation into future investigations into how the cell actively
shapes its organelle composition to match biochemical supply with physiological demand through, how this
plasticity is leveraged in health by multicellular organisms to provide the metabolic flexibility needed to develop
its myriad cell types, but also in disease by allowing for multiple routes to metabolic pathologies in cancer,
diabetes, and aging.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
DOI:
10.1103/physrevlett.130.018401
发表时间:
2023-01
期刊:
Physical review letters
影响因子:
8.6
作者:
[K. P. Amiri;Asa Kalish;S. Mukherji]
通讯作者:
K. P. Amiri;Asa Kalish;S. Mukherji
The design principles of the eukaryotic cell: uncovering the coordination of systems-level organelle dynamics, metabolism and growth
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批准号:10274898
-
项目类别:
-
资助金额:$39.38万
-
财政年份:2021
-
负责人:Arindam Shankar Mukherji
-
依托单位:
The design principles of the eukaryotic cell: uncovering the coordination of systems-level organelle dynamics, metabolism and growth
-
批准号:10458074
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项目类别:
-
资助金额:$39.38万
-
财政年份:2021
-
负责人:Arindam Shankar Mukherji
-
依托单位:
Regulation of organelle function by spatiotemporal control of gene expression
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批准号:8450415
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项目类别:
-
资助金额:$5.22万
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财政年份:2013
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负责人:Arindam Shankar Mukherji
-
依托单位:
海外基金