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Project 2: High Resolution Mutation Spectra and Multi-Omics for Deducing Etiology and Predicting Disease

Project 2: High Resolution Mutation Spectra and Multi-Omics for Deducing Etiology and Predicting Disease
项目2:高分辨率突变谱和多组学用于推断病因和预测疾病
批准号:
10351933
负责人:
JOHN M ESSIGMANN
金额:
$52.07万
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
未结题
起止时间:
2017-09-01 至 2027-06-30
关键词:
AcuteAddressAffectAir PollutionAnimal ModelAnimalsBiologicalBiological MarkersCatchment AreaCell Culture SystemCell Culture TechniquesCell modelCellsCessation of lifeCharacteristicsChemical ExposureChemicalsCommunitiesComplex MixturesCustomDNA AdductionDNA AdductsDNA DamageDNA RepairDNA Repair GeneDNA sequencingDataData AnalysesData SetDetectionDimethylnitrosamineDiseaseDisease OutcomeDoseElderlyEmbryoEnvironmentEnvironmental ExposureEnvironmental Risk FactorEpidemiologyEtiologyExcisionExposure toFemaleFibroblastsGene ExpressionGeneticGenetic EngineeringGenetically Engineered MouseGenomicsGoalsGoldHazardous ChemicalsHazardous SubstancesHealthHumanHuman GenomeIndividualIndustrializationInflammationInformaticsInterventionIntraperitoneal InjectionsInvestigationKineticsKnowledgeLearningMGMT geneMaineMalignant NeoplasmsMammalian CellMeasurableMethodsModelingMolecularMolecular EpidemiologyMusMutagensMutationMutation SpectraN-nitrosodimethylamineNitrosaminesNitroso CompoundsPassamaquoddy Tribe of MainePathologyPathway interactionsPatternPersonsPhenotypePhosphorylationPredispositionPreventionProbioticsProceduresProcessPropylaminesProtein AnalysisProteinsProteomeProteomicsPublic HealthRecordsRegimenResearchResolutionRiskRisk AssessmentSamplingScreening procedureSignal Recognition ParticleSignal TransductionSiteSourceSuperfundSystemTechniquesTechnologyTestingThe Cancer Genome AtlasTissuesToxic Environmental SubstancesToxic effectToxicologyToxinTribal groupWaterWater PollutionWorkWorld Health Organizationbasebiological systemsburden of illnesscarcinogenicitycommunity engagementdata managementdata streamsdisorder preventiondrinking waterearly onsetenvironmental chemicalgene environment interactiongenome integritygenotoxicityhigh throughput screeninghuman datahuman diseaseinsightmalemembermouse modelmultiple omicsnoveloverexpressionphosphoproteomicsprogramsremediationresponsescreeningstressorsuperfund chemicalsuperfund sitetooltoxicanttranscriptomicstumorwelfare

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中文摘要
翻译
项目摘要/摘要--项目2 毫无疑问,人们在超级基金网站接触到单一化学品或混合物的情况已经发生。这个 这里讨论的悬而未决的问题是,这些暴露是否可以与可测量的风险相关联 基因组的完整性或表达,这将为以下论点提供生物学上的似是而非的证据 环境已经影响了人类的健康和福利。选择进行研究的化合物是受到启发的 通过与包含超级基金站点的当地社区和缅因州部落团体的接触努力。 致癌的N-亚硝胺(例如,N-亚硝基二甲胺或NDMA)以及其他有毒物质丰富。 在我们的两个集水区。这些试剂还没有作为诱变剂或蛋白质组干扰物在 这里提出的详细程度,而且它们肯定没有受到联合的多组学审查 本项目与项目1(DNA损伤和基因-环境相互作用)结合在一起。这项技术 项目2有五个组成部分:(A)我们使用了一个基因工程小鼠小组(项目1),它能对 以揭示对环境毒物易感性的潜在机制的方式 毒药。中毒的途径包括疾病的开始,伴随的并发症,如组织破坏性 炎症,通过癌症等终末期病理。(二)我们使用新开发的高保真DNA 测序程序,提供前所未有的高分辨率突变谱(HRMS);HRMS可以 用于识别因环境暴露而产生的特定化学突变模式。(C)我们使用 独特的蛋白质组平台,可以敏感地感知信令网络中数千个节点的中断。(D) 我们通过数据管理和分析核心使用了一个新的计算模块,该模块可以定量地 将我们模型中的HRMS和蛋白质组模式与快速扩展的人类数据集进行比较 癌症基因组图谱计划(TCGA),其他肿瘤测序工作,以及不断增长的 蛋白质组模式。(E)最后,我们引进了小鼠胚胎成纤维细胞系(MEF)。 可用作高通量筛选工具的模型,以帮助寻找复杂混合物中的遗传毒性组分 (项目3和4)。我们的多组学方法以动物和细胞模型为中心,但我们也展望了 这些新工具在分子流行病学和疾病预防中的应用。关于后者 可能,我们在工作中已经看到的蛋白质组和诱变生物标记物可以立即用于 通过我们与项目1的互动,评估益生菌缓解疾病的有效性。关于贡献 在流行病学方面,我们已经观察到的NDMA暴露后的独特突变谱 动物和细胞最终可能成为有价值的早发性生物标志物,预示着未来的疾病。 综上所述,该项目利用了基因组学、内收基因组学、基因表达和系统方面的基础研究 毒理学提供实用工具,帮助检测和减轻由特定疾病引起的人类疾病 我们的社区合作伙伴和监管机构都将环境化学品定义为令人担忧的代理。
英文摘要
PROJECT SUMMARY/ABSTRACT – PROJECT 2 Exposure of people to single chemicals or mixtures at Superfund sites has unquestionably occurred. The unanswered question addressed here is whether those exposures can be associated with measurable risks to genome integrity or expression, which would provide biological plausibility to the argument that the chemicals in the environment have affected human health and welfare. The compounds chosen for investigation were inspired by engagement efforts with a local community containing a Superfund site and with Tribal groups in Maine. Carcinogenic N-nitrosamines (e.g., N-nitrosodimethylamine or NDMA) as well as other toxicants are abundant in both of our catchment areas. These agents have not been studied as mutagens or proteome disruptors at the level of detail proposed here, and they certainly have not been subjected to the combined multi-omic scrutiny of this Project taken together with Project 1 (DNA damage and gene-environment interactions). The technology of Project 2 has five components: (a) We employ a genetically engineered panel of mice (Project 1) that responds to environmental toxicants in a manner that reveals underlying mechanisms that confer susceptibility to a toxicant. The pathway to toxicity involves disease initiation, concomitant complications such as tissue-destructive inflammation, through end stage pathologies such as cancers. (b) We use a newly developed high-fidelity DNA sequencing procedure that provides unprecedentedly high-resolution mutational spectra (HRMS); HRMS can be used to identify chemical-specific mutational patterns resulting from environmental exposures. (c) We use a unique proteomic platform that sensitively senses disruptions in thousands of nodes in signaling networks. (d) We use a novel computational module via the Data Management and Analysis Core that quantitatively compares HRMS and proteomic patterns from our models with the rapidly expanding human data sets of The Cancer Genome Atlas Project (TCGA), other tumor sequencing efforts, and the growing body of knowledge of proteomic patterns. (e) Lastly, we introduce mouse embryo fibroblast (MEF) lines isogenic with our mouse models that can be used as high-throughput screening tools to help find genotoxic fractions in complex mixtures (Projects 3 and 4). Our multi-omic approach centers on animal and cellular models, but we also look ahead to application of these novel tools for molecular epidemiology and for disease prevention. Regarding the latter possibility, the proteomic and mutagenic biomarkers we already see in our work can be immediately be used to assess the efficacy of probiotic mitigation of disease, via our interactions with Project 1. Regarding contributions to epidemiology, the distinctive mutational spectra we have already observed following NDMA exposure to animals and cells could eventually become valuable early-onset biomarkers that portend later life diseases. Taken together, this Project leverages basic studies on genomics, adductomics, gene expression, and systems toxicology to provide practical tools that can help detect and mitigate human diseases caused by specific environmental chemicals that both our community partners and regulators have defined as agents of concern.
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Core D: Research Experience and Training Coordination Core
Core D: Research Experience and Training Coordination Core
Science and Engineering for Sensors, Mechanisms, and Biomarkers of Exposures
Project 2: High Resolution Mutation Spectra and Multi-Omics for Deducing Etiology and Predicting Disease
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