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: 10687979
• 负责人: JOHN M ESSIGMANN
• 金额: $ 48.05万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10687979
• 关键词: Acute; Address; Affect; Air Pollution; Animal Model; Animals; Biological; Biological Markers; Catchment Area; Cell Culture System; Cell Culture Techniques; Cell model; Cells; Cessation of life; Characteristics; Chemical Exposure; Chemicals; Collaborations; Communities; Complex Mixtures; Custom; DNA Adduction; DNA Adducts; DNA Damage; DNA Repair; DNA Repair Gene; DNA sequencing; Data; Data Analyses; Data Set; Detection; Dimethylnitrosamine; Disease; Disease Outcome; Dose; Elderly; Embryo; Environment; Environmental Exposure; Environmental Risk Factor; Epidemiology; Etiology; Excision; Exposure to; Female; Fibroblasts; Gene Expression; Genetic; Genetic Engineering; Genetically Engineered Mouse; Genomics; Goals; Hazardous Chemicals; Hazardous Substances; Health; Human; Human Genome; Individual; Industrialization; Inflammation; Informatics; Intervention; Intraperitoneal Injections; Investigation; Kinetics; Knowledge; Learning; MGMT gene; Maine; Malignant Neoplasms; Mammalian Cell; Measurable; Methods; Modeling; Molecular; Molecular Epidemiology; Mus; Mutagens; Mutation; Mutation Spectra; N-nitrosodimethylamine; Nitrosamines; Nitroso Compounds; Passamaquoddy Tribe of Maine; Pathology; Pathway interactions; Pattern; Persons; Phenotype; Phosphorylation; Predisposition; Prevention; Probiotics; Procedures; Process; Propylamines; Protein Analysis; Proteins; Proteome; Proteomics; Public Health; Records; Regimen; Research; Resolution; Risk; Risk Assessment; Risk Reduction; Sampling; Screening procedure; Signal Recognition Particle; Signal Transduction; Site; Source; Superfund; System; Techniques; Technology; Testing; The Cancer Genome Atlas; Tissues; Toxic Environmental Substances; Toxic effect; Toxicology; Toxin; Tribal group; Water; Water Pollution; Work; World Health Organization; animation; biological systems; burden of illness; carcinogenicity; community engagement; data management; data streams; disorder prevention; drinking water; early onset; efficacy evaluation; environmental chemical; gene environment interaction; genome integrity; genotoxicity; high throughput screening; human data; human disease; insight; male; member; mouse model; multiple omics; novel; overexpression; phosphoproteomics; programs; remediation; response; screening; stressor; superfund chemical; superfund site; tool; toxicant; transcriptomics; tumor; welfare

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.

项目摘要/摘要-项目2