LIVE IMAGING OF BONE REGENERATION IN ZEBRAFISH
LIVE IMAGING OF BONE REGENERATION IN ZEBRAFISH
批准号:
10549315
负责人:
Stefano Di Talia
金额:
$52.04万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-02-01 至 2025-01-31
关键词:
AdultAgeAmericanAutomobile DrivingBehaviorBiographyBiosensorBone DiseasesBone MatrixBone RegenerationCell ProliferationCell divisionCellsCessation of lifeChemicalsClinicalCompetenceComplementComplexComputer AnalysisCytoskeletonData SetDaughterDermalEmbryoEpithelial CellsEventExtracellular Signal Regulated KinasesFGF12 geneFractureGene ExpressionGenesGeneticGenetic TranscriptionGoalsGrowthGrowth FactorHeterogeneityHypertrophyImageIndividualInjuryJawLabelLaboratoriesLifeLigandsLimb structureLinkMapsMediatingMessenger RNAMethodologyMethodsMitogensModelingMolecularMolecular GeneticsMonitorMorphogenesisNatural regenerationOsteoblastsOsteoclastsPathway interactionsPatternPopulationPrimordiumProcessProliferatingProtein AnalysisPublishingRegenerative capacityRegulationRiskSignal TransductionSkeletal boneSkinStructureSystemTestingTissuesTransgenic OrganismsTraumaTravelWorkZebrafishbonebone imagingcell behaviorcraniofacial developmenteconomic impactexperimental studygenetic approachimaging modalityimaging platformimprovedin vivo imaginginsightlimb amputationlive cell imagingmathematical modelmembermigrationnovelpharmacologicprogramsregeneration potentialregenerative growthresponsesingle cell sequencingsocioeconomicsspatiotemporaltranscription factortranscriptometranscriptomic profilingtransmission process
中文摘要
摘要
哺乳动物的骨骼在整个生命过程中都有再生的能力,以应对骨折损伤。 但
是这种再生潜力的上限,在肢体等重大创伤后再生障碍
截肢这对社会经济产生了重大影响,因为据估计,
预计50岁以上的人患有或有患骨病的风险,每年估计有150万人
个体由于骨疾病而遭受骨折。最近,我们开发了成像方法来研究
成骨细胞驱动斑马鱼的骨再生,在骨损伤后显示出强大的再生能力。
鳍、鳞和颚等结构。 我们的目标是利用这种再生能力,
我们已经创建的平台,以及在斑马鱼中可用的分子遗传方法,
来理解和控制骨骼的再生能力。该提案的目标是在
细胞和信号事件的toto地图再生模式的骨骼骨。我们的实验将测试
假设再生骨的正确模式需要动态信号事件,
成骨细胞行为的个体和群体水平。 1)我们将使用长期的实时成像,标记
光生物可转换蛋白质,以及计算机分析,以生成细胞增殖的详细地图,
肥大和细胞流动以及与邻近组织的相互作用驱动骨再生。 2)我们将
使用尖端的生物传感器,实时成像,计算方法和数学建模来解剖
化学信号的行波如何刺激再生成骨细胞群体的生长。 3)我们
将使用转录组分析方法来进一步了解生长因子信号传导的动力学,
包括基于单细胞测序的方法将基因表达程序与成骨细胞联系起来
行为。 这些实验将为理解成骨细胞如何
行为协调骨再生。
英文摘要
Abstract
Mammalian bone has the capacity throughout life to regenerate in response to fracture injury. However, there
is a ceiling for this regenerative potential, with hurdles to regeneration after a major trauma like limb
amputation. This has a significant socioeconomic impact, as it is estimated that at least one in two Americans
over age 50 is expected to have or be at risk of bone disease, and every year an estimated 1.5 million
individuals suffer a fracture due to bone disease. Recently, we have developed imaging methods to study how
osteoblasts drive bone regeneration in zebrafish, which display robust regeneration after major injury to bony
structures like their fins, scales, and jaws. Our goal is to exploit this regenerative capacity, new imaging
platforms we have created, and the molecular genetic approaches available in zebrafish to improve our ability
to understand and manipulate the regenerative capacity of bone. The goal of this proposal is to generate an in
toto map of the cellular and signaling events that regenerate patterned skeletal bone. Our experiments will test
the hypothesis that correct patterning of regenerating bone requires dynamic signaling events that control
osteoblast behaviors at individual and population levels. 1) We will use long-term live imaging, labeling with
photo-convertible proteins, and computational analysis to generate a detailed map of how cell proliferation,
hypertrophy and cellular flows, and interactions with neighboring tissues drive bone regeneration. 2) We will
use cutting edge biosensors, live imaging, computational approaches, and mathematical modeling to dissect
how traveling waves of chemical signals stimulate the growth of a regenerating osteoblast population. 3) We
will use transcriptome profiling approaches to derive further insights on the dynamics of growth factor signaling,
including single-cell sequencing-based approaches to link gene expression programs with osteoblast
behaviors. These experiments will define a novel quantitative framework for understanding how osteoblast
behaviors orchestrate bone regeneration.
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会议论文
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