Single cell, multi-parametric high throughput platform to classify endocrine disruptor potential of mixtures

单细胞、多参数高通量平台对混合物的内分泌干扰物潜力进行分类

• 批准号: 9903372
• 负责人: MICHAEL A. MANCINI
• 金额: $ 21.27万
• 依托单位: TEXAS A&M UNIVERSITY
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9903372
• 关键词: Address; Advisory Committees; Androgen Receptor; Area; Bioinformatics; Biological Assay; Biology; Cell Line; Cell Proliferation; Cell model; Cells; Cellular Assay; Chemical Exposure; Chemicals; Classification; Collaborations; Communities; Complex; Complex Mixtures; DNA; DNA Binding; Data; Data Analyses; Data Science Core; Decision Making; Deposition; Detection; Development; Disasters; Disease; Elements; Emergency Situation; Endocrine; Endocrine Disruptors; Endocrine disruption; Engineering; Environment; Environmental Exposure; Environmental Pollutants; Environmental Pollution; Epigenetic Process; Estrogen Receptor 2; Estrogen Receptors; Evaluation; Event; Exposure to; Family; Fingerprint; Floods; Genes; Goals; Hazardous Substances; Health; Health Hazards; Heavy Metals; Human; Hurricane; Image; Image Analysis; Immunofluorescence Immunologic; Individual; Industrialization; Information Dissemination; Ligands; Link; Malignant Neoplasms; Measures; Mediating; Messenger RNA; Metabolic; Metabolism; Methodology; Methods; Modeling; Modification; Nuclear Hormone Receptors; Nuclear Receptors; Pathway interactions; Pesticides; Pharmacologic Substance; Physiology; Population; Reproducibility; Reproduction; Research; Risk; Sampling; Science; Ships; Signal Recognition Particle; Site; Source; Steroid Receptors; Superfund; System; Techniques; Testing; Texas; Thyroid Hormone Receptor; Translating; Translational Research; Translations; Weather; Work; base; bisulfite; cost; cost effective; design; environmental chemical; epigenome; epigenomics; exposed human population; genome-wide; high throughput screening; improved; in vitro Assay; innovation; insight; man; predictive modeling; public health relevance; receptor; response; screening; single cell analysis; superfund site; tool; toxicant; transcription factor

Project 4 Abstract Human health is at risk due to environmental exposures to a wide range of chemical toxicants and endocrine disrupting chemicals (EDCs). EDCs are commonly found in natural and industrial sources and represent a large and growing family of compounds and mixtures with high chemical diversity. The Texas A&M Superfund Research Center is focused on evaluating and reducing the human health risks posed by exposure to hazardous substances, including EDCs, that are mobilized from sediments and other sources by environmental disaster events such as tropical storms, hurricanes, and floods. The overarching goal of Project 4 is to develop fast, robust, and cost-effective assays to determine the endocrine disrupting potential of complex, environmentally relevant chemical mixtures in the highly industrial Galveston Bay/Houston Ship Channel area (GB/HSC) and other Superfund sites. The availability of a set of fast, sensitive, and reproducible EDC assays will facilitate health hazard evaluation and improve decision-making in response to environmental emergencies. The central hypothesis that will be tested in Project 4 is that multi-parametric, highly mechanistic contextual in vitro assays, and bioinformatics analyses will serve as a robust, fast, and cost- effective framework to evaluate the endocrine disrupting potential of environmentally-derived complex chemical mixtures. Nuclear Receptors (NRs), a large class of transcription factors, are key mechanistic targets of EDCs. The assays developed in Project 4 will focus on three NRs identified by the Endocrine Disruptor Screening and Testing Advisory Committee: estrogen receptor (ER), androgen receptor (AR), and thyroid hormone receptor (TR). We will use advanced high throughput imaging and image analysis, genome-wide epigenomics, and integrative bioinformatics to address critical needs in assessing the risk to human health posed by hazardous substances: 1) Development of fast, robust, and cost effective high throughput assays to identify the presence of EDCs and classify their bioactivity. Cell-based platforms in endocrine-relevant systems will be used to analyze both single compounds (~50, including heavy metals, pesticides, pharmaceuticals, etc.), and complex mixtures, including samples from Superfund sites. 2) Comprehensive analysis of EDC impact on the epigenome and the identification of EDC-specific epigenetic “fingerprints.” The epigenetic impact of EDCs has not previously been considered as a way to identify and classify EDCs, and has the potential to provide new insights into EDC- and NR-specific mechanisms of pathway disruption. 3) Assessment of the endocrine disrupting potential of chemical mixtures in the environment. While previous work has primarily focused on EDC activity of single compounds mediated by the ER, we will increase the scope and relevance of EDC assessment by measuring effects on AR and TR, and by moving from single compounds to mixtures. High content, cell-based, and epigenomic data will be translated into a bioinformatics-based framework to determine and predict the endocrine disrupting potential of complex, environmentally relevant chemical mixtures.

项目4 由于环境暴露于各种化学毒物和内分泌， 破坏性化学物质（EDCs）。内分泌干扰物通常存在于自然和工业来源中， 具有高度化学多样性的化合物和混合物的大家族。德克萨斯A&M超级基金 研究中心的重点是评估和减少暴露于 有害物质，包括内分泌干扰物，通过以下方式从沉积物和其他来源移动 环境灾害事件，如热带风暴、飓风和洪水。的首要目标 项目4是开发快速、稳健和具有成本效益的测定方法，以确定 在高度工业化的加尔维斯顿湾/休斯顿船上， 渠道地区（GB/HSC）和其他超级基金网站。一套快速、灵敏、可重复的 EDC分析将促进健康危害评估，并改善对环境影响的决策 突发事件项目4将检验的中心假设是， 机械上下文体外测定和生物信息学分析将作为一个强大的，快速的，和成本- 评估环境衍生复杂化学品的内分泌干扰潜力的有效框架 混合物。核受体（Nuclear Receptors，NRs）是一大类转录因子，是内分泌干扰物的重要作用靶点。 项目4中开发的检测方法将侧重于内分泌干扰物筛查和 检测咨询委员会：雌激素受体（ER）、雄激素受体（AR）和甲状腺激素受体 （TR）。我们将使用先进的高通量成像和图像分析，全基因组表观基因组学， 综合生物信息学，以满足评估危险化学品对人类健康构成的风险方面的关键需求 1）开发快速、稳健和具有成本效益的高通量测定法，以鉴定 并对其生物活性进行了分类。内分泌相关系统中基于细胞的平台将用于 分析单一化合物（约50种，包括重金属、农药、药物等），和复杂 混合物，包括来自超级基金场地的样本。2)全面分析EDC对 表观基因组和鉴定EDC特异性表观遗传“指纹”。内分泌干扰物的表观遗传影响 以前没有被认为是一种识别和分类内分泌干扰物的方法，并有可能提供新的 对EDC和NR特异性通路破坏机制的深入了解。3)内分泌评估 破坏环境中化学混合物的可能性。虽然以前的工作主要集中在 单个化合物的EDC活性是由ER介导的，我们将增加EDC的研究范围和相关性 通过测量对AR和TR的影响，以及从单一化合物到混合物进行评估。高 内容，基于细胞的，和表观基因组数据将被翻译成一个基于生物信息学的框架，以确定 并预测复杂的、与环境有关的化学混合物的内分泌干扰潜力。