Biological Analysis Core
生物分析核心
基本信息
- 批准号:10552988
- 负责人:
- 金额:$ 158.7万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-08-02 至 2026-07-31
- 项目状态:未结题
- 来源:
- 关键词:3 year oldAdipocytesAdipose tissueAgeAgingAmino Acid SequenceAnimal ModelArchitectureAstrocytesAtlasesAttenuatedAutomobile DrivingBiologicalBiological AssayBiological MarkersBiological ModelsBiologyBirthBrainCDKN2A geneCell AgingCellsChromatinChronic DiseaseClinicCollaborationsCre driverDataData AnalysesData SetDetectionDevelopmentDiseaseElectronic Health RecordEmerging TechnologiesEnsureEpigenetic ProcessEvolutionFVB/N MouseFundingGene ExpressionGenerationsGenesGeneticGenomeGenomicsGoalsHepatocyteHeterogeneityHumanHybridsImageInbreedingInfrastructureInstitutesIonsLaboratoriesLiverLungManagement Information SystemsManuscriptsMapsMass Spectrum AnalysisMethodologyMethodsMicrogliaMidwestern United StatesMinnesotaModelingMorbidity - disease rateMouse StrainsMusMuscleMuscle CellsNeuronsOrganPathologyPatternPharmaceutical PreparationsPhenotypePhysiologyPlayPopulationProteomicsPublishingQuality ControlReportingReproducibilityResourcesRoleSampling ErrorsScientistSensitivity and SpecificitySiteSkeletal MuscleStructure of parenchyma of lungSupercomputingTechnologyTimeTissue BanksTissue atlasTissuesTransgenic MiceUniversitiesWild Type Mouseagedanalytical toolanimal tissuebasebiomarker discoverybrain tissuecell killingcell preparationcell typecohesioncytokinedigitalexperiencefrailtyhealthspanimaging facilitiesimprovedin vivoinnovationinstrumentationmembermortalitynano-stringnew technologynovelpreservationprogenitorproteogenomicsresiliencescale upsenescencesingle-cell RNA sequencingspatiotemporaltherapeutic targettissue mappingtooltranscriptomicswound healing
项目摘要
PROJECT SUMMARY
Senescent cells (SnCs) accumulate with age and contribute to morbidity and mortality in model systems. SnCs
also play a role in normal physiology, e.g., wound healing. Currently it is unclear when and where SnCs arise in
tissues with age, how heterogenous SnCs are in vivo, and how to best identify them and their role in physiology
vs. pathology, especially in humans. The goal of the Midwest Murine-Tissue Mapping Center (MM-TMC)
Biological Analysis Core (BAC) is to leverage the utility of the mouse as a model organism to map SnCs, which
will help inform the human SnC atlases under development by SenNet. We propose to validate, optimize, and
apply state-of-the-art methodologies for bulk and single cell characterization and spatiotemporal analysis of
SnCs in healthy mouse tissues over a range of ages in two genetic backgrounds. The MM-TMC BAC will focus
on adipose, skeletal muscle, liver, brain, and lung tissues from inbred C57BL/6J and f1 hybrid (C57BL/6J:FVB/n)
mice. The data generated by the BAC will be delivered to the Data Analysis Core (DAC) for integration to develop
SnC atlases for the five tissues. The BAC will be led by Nathan LeBrasseur, an expert in the identification and
characterization of SnCs in skeletal muscle and lung in mice and humans, and in biomarker discovery; Paul
Robbins, an expert in senolytic development; and Laura Niedernhofer, an expert in the study of SnCs in
transgenic mice. The three MPIs are part of a P01 led by Overall PI Sundeep Khosla, which develops,
characterizes, and utilizes innovative transgenic mice that permit the induction of SnCs in a particular organ or
cell type, report expression of the SnC-driving genes p16Ink4a or p21Cip1, or specifically kill cells expressing those
genes. These mice will be important tools in SenNet for mapping efforts and validating probes to detect SnCs.
The BAC analytical workflow will be based within existing cores at Mayo Clinic and University of Minnesota
(UMN) to guarantee a stable infrastructure and high quality control standards: the UMN Imaging Centers, the
UMN Genomics Center, Mayo CyTOF Core, the UMN Center for Mass Spectrometry and Proteomics (CMSP),
the UMN Cytokine Reference Laboratory, and Minnesota Supercomputing Institute. These cores contain state-
of-the-art instrumentation available for mapping SnCs: Ionpath Multiplexed Ion Beam Mass Imaging, Visium
Spatial Gene Expression, and NanoString GeoMx Digital Spatial Profiling. In addition, the CMSP will use a
proteogenomic approach to identify novel SnC-specific protein sequences as biomarkers. These unique
resources, together with the MPIs’ expertise, will be valuable for building the 4D tissue atlases. Broadly, the BAC
proposes to: 1) Establish a pipeline of reproducible, validated, and quantitative assays to detect and characterize
SnCs in whole tissues and single cell preparations; 2) Use primary mouse cells as a controlled model for
validating analytical tools, studying the evolution of SnCs over time, and identifying novel SnC biomarkers; 3)
Scale-up the data generation pipeline and incorporate emerging technologies; and 4) Perform spatiotemporal
analysis of SnCs in the five tissues to enable the DAC to generate 4D SnC atlases.
项目总结
衰老细胞(SNCs)随着年龄的增长而积累,并在模型系统中导致发病率和死亡率。SNC
在正常生理方面也起作用,例如,伤口愈合。目前尚不清楚SNC在何时何地出现
组织与年龄、体内SNCs的异质性、如何最好地识别它们以及它们在生理学中的作用
与病理学,尤其是在人类身上。中西部鼠组织测绘中心(MM-TMC)的目标
生物分析核心(BAC)是利用小鼠作为模式生物来绘制SNC图,这是
将帮助为Sennet正在开发的人类SNC地图集提供信息。我们建议验证、优化和
应用最先进的方法进行批量和单细胞表征以及时空分析
在两种遗传背景下,在一系列年龄范围内的健康小鼠组织中的SNC。MM-TMC BAC将专注于
近交系C57BL/6J和F1(C57BL/6J:FVB/n)脂肪、骨骼肌、肝、脑和肺组织的研究
老鼠。BAC生成的数据将交付给数据分析核心(DAC)进行集成开发
五种组织的SNC图谱。BAC将由Nathan LeBrasseur领导,他是身份识别和
小鼠和人类骨骼肌和肺中SNCs的特征,以及生物标记物的发现
罗宾斯,感觉性发育专家;劳拉·尼德恩霍费尔,研究SNCs的专家
转基因小鼠。这三个MPI是P01的一部分,该P01由整体PI SunDeep Khosla领导,该公司开发,
表征并利用创新的转基因小鼠,允许在特定器官或
细胞类型,报告SNC驱动基因p16INK4a或p21Cip1的表达,或特异性地杀伤表达这些基因的细胞
基因。这些小鼠将成为Sennet的重要工具,用于测绘工作和验证探测SNC的探针。
BAC分析工作流程将基于梅奥诊所和明尼苏达大学的现有核心
(UMN)保证稳定的基础设施和高质量控制标准:UMN成像中心,
UMN基因组学中心、Mayo CyTOF Core、UMN质谱学和蛋白质组学中心(CMSP)、
密歇根大学细胞因子参考实验室和明尼苏达超级计算研究所。这些核心包含状态-
可用于测绘SNC的最先进的仪器:离子路径多路复用离子束质量成像,维西姆
空间基因表达和纳米串GeoMx数字空间剖面图。此外,CMSP将使用
用蛋白质基因组学方法鉴定新的SNC特异蛋白质序列作为生物标志物。这些独特的
资源,加上MPI的专业知识,对于建立4D组织地图集将是宝贵的。大体上,BAC
建议:1)建立一套可重复、有效和定量的检测和表征方法
全组织和单细胞制剂中的SNCs;2)以原代小鼠细胞为对照模型
验证分析工具,研究SNC随时间的演变,并确定新的SNC生物标志物;3)
扩大数据生成渠道并采用新兴技术;以及4)执行时空
分析五种组织中的SNC,以使DAC能够生成4D SNC图谱。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Nathan K LeBrasseur其他文献
Nathan K LeBrasseur的其他文献
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{{ truncateString('Nathan K LeBrasseur', 18)}}的其他基金
Senescence and Growth Differentiation Factors as Modifiers of Aging
衰老和生长分化因子作为衰老调节剂
- 批准号:
9755279 - 财政年份:2018
- 资助金额:
$ 158.7万 - 项目类别:
Senescence and Growth Differentiation Factors as Modifiers of Aging
衰老和生长分化因子作为衰老调节剂
- 批准号:
10378047 - 财政年份:2018
- 资助金额:
$ 158.7万 - 项目类别:
Interdisciplinary Infrastructure for Aging Research: Rochester Epidemiology Project
老龄化研究的跨学科基础设施:罗切斯特流行病学项目
- 批准号:
10208373 - 财政年份:2018
- 资助金额:
$ 158.7万 - 项目类别:
Interdisciplinary Infrastructure for Aging Research: Rochester Epidemiology Project
老龄化研究的跨学科基础设施:罗切斯特流行病学项目
- 批准号:
10409783 - 财政年份:2018
- 资助金额:
$ 158.7万 - 项目类别:
Interdisciplinary Infrastructure for Aging Research: Rochester Epidemiology Project
老龄化研究的跨学科基础设施:罗切斯特流行病学项目
- 批准号:
10224079 - 财政年份:2018
- 资助金额:
$ 158.7万 - 项目类别:
Senescence and Growth Differentiation Factors as Modifiers of Aging
衰老和生长分化因子作为衰老调节剂
- 批准号:
9894701 - 财政年份:2018
- 资助金额:
$ 158.7万 - 项目类别:
Senescence and Growth Differentiation Factors as Modifiers of Aging
衰老和生长分化因子作为衰老调节剂
- 批准号:
10116228 - 财政年份:2018
- 资助金额:
$ 158.7万 - 项目类别:
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