Midwest Murine-Tissue Mapping Center (MM-TMC)

中西部鼠组织绘图中心 (MM-TMC)

• 批准号: 10675007
• 负责人: David A Bernlohr
• 金额: $ 270万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 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: https://reporter.nih.gov/project-details/10675007
• 关键词: Ablation; Acceleration; Adipose tissue; Aging; Alzheimer' s Disease; Architecture; Atlases; Attenuated; Award; Bioinformatics; Biological; Biological Markers; Biological Process; Biology; Birth; Brain; Cell Aging; Cells; Cellular biology; Chromatin; Clinic; Clinical Trials; Collaborations; Collection; Communication; Communities; Complex; DNA Methylation; Data; Data Analyses; Data Collection; Data Coordinating Center; Data Discovery; Data Science; Data Set; Detection; Development; Disease; Disparate; Embryonic Development; Equipment; Evolution; Excision; FAIR principles; Gene Expression; Generations; Genetic; Genome; Genomics; Goals; Human; Human Resources; Image; Immune system; Immunology; Immunotherapy; Informatics; Infrastructure; Institution; International; Knowledge; Label; Lead; Learning; Link; Liver; Location; Longevity; Lung; Maps; Measurement; Measures; Metadata; Midwestern United States; Minnesota; Modeling; Molecular; Multiplexed Ion Beam Imaging; Mus; Muscle; Organ; Organism; Pathologic; Pathology; Pharmaceutical Preparations; Phenotype; Physiological; Physiology; Play; Procedures; Production; Proteomics; Quality Control; Reagent; Recording of previous events; Research; Research Personnel; Role; Structure of parenchyma of lung; Technology; Time; Tissue Sample; Tissues; Transgenic Animals; Transgenic Mice; Tumor Suppression; United States National Institutes of Health; Universities; Visualization; Visualization software; Wild Type Mouse; Work; age related; aged; aging population; biomarker identification; brain tissue; data management; data modeling; data sharing; digital; experience; extracellular; frailty; improved; innovation; member; mouse model; nano-string; novel; pharmacologic; phenotypic biomarker; quality assurance; resilience; response; senescence; single cell analysis; skeletal tissue; stressor; success; synergism; technology development; tissue mapping; wound healing

PROJECT SUMMARY Senescent cells (SnCs) play a causal role in aging and numerous age-related diseases. However, they also contribute to beneficial biology such as wound healing and tissue remodeling. Both physiological and pathological roles are linked to the secretome of SnCs and their complex interaction with the immune system, which is thought to play an important role in clearing SnCs. Much of what has been learned about SnCs is derived from studies in mice, where it has been clearly demonstrated that genetic or pharmacologic removal of SnCs in aged or diseased organisms reduces frailty; improves strength, endurance, and resilience; and attenuates a variety of age-related diseases, including Alzheimer’s. Discovering pharmacologic approaches to remove disease-causing SnCs in humans could have a tremendous impact on our aging population. However, much needs to be learned about SnCs to deploy such approaches safely and effectively in humans. This project aims to establish a Tissue Mapping Center (TMC) across multiple institutions with demonstrated expertise in SnCs and cell mapping to achieve a common goal; construction of a 4D atlas of SnCs in mouse tissues. The Midwest Murine-TMC (MM-TMC) proposes to focus on 5 key tissues: mouse liver, adipose, lung, muscle, and brain. This selection is based on MM-TMC’s expertise in the biology, cell biology, and immunology of these organs; lengthy experience studying SnCs in these organs; and applying single cell and spatial technologies to study these organs. The MM-TMC and its Administrative Core will be led by PIs with complementary expertise in organ biology and senescence. The Biological Analysis Core will be led by three MPIs who have a long history of collaboration around studying SnCs in aged mice and working with unique and innovative transgenic animals that enable the production or ablation of lineage-specific SnCs. The Data Analysis Core will be led by two bioinformaticians with expertise in single cell analysis, cell mapping, and multiplexing complex and disparate data sets to deeply phenotype cells. Other key personnel add expertise in pathology, imaging, spatial mapping of SnCs, tissue clearing, transgenic mice, and development of senolytics and immunotherapies to target SnCs. A unique feature of the proposed MM-TMC is that the data collection will be done within existing cores largely at the University of Minnesota by staff with expertise in state-of-the art spatial mapping platforms. This provides stability in the analytical pipeline and in-place quality control and assurance mechanisms. Through systematic and methodical study of SnCs in mouse tissues, the MM-TMC will make significant contributions informing and validating the SenNet human atlas and will work closely with NIH, other TMCs, Technology Development awardees, and the Consortium Organization and Data Coordinating Center to develop and adhere to standards created by SenNet to accelerate the production of rigorous SnC tissue maps in both species.

项目总结 衰老细胞(SNCs)在衰老和许多与年龄相关的疾病中起着因果作用。然而，他们也 有助于有益的生物学，如伤口愈合和组织重塑。无论是生理上的还是 病理作用与SNCs的分泌体及其与免疫系统的复杂相互作用有关， 它被认为在清算SNC方面发挥着重要作用。关于SNC的大部分知识都是从 从对小鼠的研究中，已经清楚地证明SNCs的遗传或药物去除在 衰老或患病的生物体可降低虚弱程度，提高力量、耐力和韧性，并可使 各种与年龄相关的疾病，包括阿尔茨海默氏症。发现药物治疗方法 人类中致病的SNCs可能会对我们老龄化的人口产生巨大影响。然而，很多 需要了解SNC才能在人类身上安全有效地部署这种方法。这个项目的目的是 在多个机构之间建立一个组织测绘中心(TMC)，这些机构在SNCS方面拥有公认的专业知识 和细胞图谱，以实现共同的目标；构建小鼠组织中SNCs的4D图谱。中西部 小鼠TMC(MM-TMC)建议关注5个关键组织：小鼠肝脏、脂肪、肺、肌肉和脑。这 选择是基于MM-TMC在这些器官的生物学、细胞生物学和免疫学方面的专业知识； 研究这些器官中的SNCs的经验；并应用单细胞和空间技术来研究这些 器官。MM-TMC及其行政核心将由在器官方面具有互补专业知识的个人主管领导 生物学和衰老。生物分析核心将由三名MPI领导，他们有很长的 围绕研究老年小鼠的SNCs以及研究独特和创新的转基因动物展开合作 能够产生或消融特定血统的SNC。数据分析核心将由两个人领导 在单细胞分析、细胞图谱以及复杂和不同的多路传输方面有专长的生物信息学家 数据集，以深入表型细胞。其他关键人员增加了病理学、成像、空间制图方面的专业知识 对SNCs的研究、组织清理、转基因小鼠，以及针对SNCs的感受剂和免疫疗法的开发。 拟议的MM-TMC的一个独特特点是，数据收集将在现有核心内进行，主要是 明尼苏达大学由拥有最先进的空间地图平台专业知识的工作人员提供。这提供了 分析管道和就地质量控制和保证机制的稳定性。通过系统化 以及对小鼠组织中SNCs的方法学研究，MM-TMC将在提供信息和 验证Sennet人类地图集，并将与NIH、其他TMC、技术开发密切合作 获奖者，以及财团组织和数据协调中心制定和遵守标准 由Sennet创建，以加速在这两个物种中制作严格的SNC组织图。