Computational Modeling Core

计算建模核心

• 批准号: 10353542
• 负责人: Qiang Zhang
• 金额: $ 23.18万
• 依托单位: MICHIGAN STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-04-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10353542
• 关键词: Address; Adopted; Aryl Hydrocarbon Receptor; B-Lymphocytes; Bacteria; Binding Proteins; Bioinformatics; Biological; Biological Availability; Biological Models; Biomedical Engineering; Bioremediations; CYP1A2 gene; Carbon; Cells; Cobalamin; Collaborations; Communities; Complement; Complex; Computer Models; Data; Data Set; Decision Making; Dioxins; Dose; Engineering; Environmental Engineering technology; Environmental Pollution; Enzymes; Evaluation; Event; Exposure to; Fatty Liver; Feedback; Foundations; Furans; Generations; Genetic Transcription; Health; Hepatic; Hepatocyte; Hepatotoxicity; Homeostasis; Human; Immunity; Immunoglobulin M; Immunosuppression; In Vitro; Informatics; Investigation; Laboratory Study; Link; Lipids; Liver; Mediating; Metabolic; Michigan; Modeling; Molecular; Mus; Nonlinear Dynamics; Organism; Outcome; Pathway interactions; Pharmacodynamics; Physiological; Population; Receptor Activation; Regimen; Research; Research Personnel; Research Support; Resolution; Risk Assessment; Role; Signal Recognition Particle; Signal Transduction Pathway; Soil; Spleen; Structure; Superfund; System; Systems Analysis; Systems Theory; Techniques; Testing; Thyroid Hormones; Tissues; Toxic effect; Toxicant exposure; Toxicology; Training; Transcription Alteration; Universities; Vitamin B 12; adverse outcome; aryl hydrocarbon receptor ligand; base; bioinformatics tool; biological research; computational suite; computational toxicology; computerized tools; design; dibenzo(1,4)dioxin; dosimetry; dynamic system; environmental toxicology; gene network; gene regulatory network; high dimensionality; hormone metabolism; human model; hypothalamic-pituitary-thyroid axis; immunotoxicity; improved; in silico; in vitro Assay; in vivo; innovation; laboratory experiment; large datasets; lipid metabolism; microbial; model development; mouse model; next generation; novel; novel marker; pharmacodynamic model; pharmacokinetic model; pharmacokinetics and pharmacodynamics; physiologically based pharmacokinetics; pollutant; population health; predictive marker; response; simulation; single-cell RNA sequencing; superfund site; support tools; thyroid disruption; tool; university student

Pharmacokinetics (PK) and pharmacodynamics (PD) together define the continuum from toxicant exposure to biological perturbations that can cause adverse outcomes. Toxicology increasingly involves computational approaches that complement laboratory studies and provide a more integrated, quantitative and mechanistic basis for human health risk assessment. The Computational Modeling Core (CMC) will provide a suite of computational capabilities to support both the Biomedical and Environmental Engineering Projects. The CMC will: (i) develop physiologically based PK (PBPK) and PD models of dioxins and dioxin-like compounds, (ii) provide Project-oriented bioinformatic support for high-dimensional omic studies, and (iii) provide cross- disciplinary training in computational toxicology. Model development will be coordinated iteratively with laboratory experiments carried out by the Projects. Prior CMC interactions with the Michigan State University (MSU) Superfund Projects have shown that this iterative approach is efficient for hypothesis generation and evaluation. In Specific Aim 1 (SA1) we will develop PBPK models for 2,3,7,8-tetrachlorodiben-p-dioxin (TCDD) and Superfund site-relevant polychlorinated dibenzo-p-dioxins and furans (PCDD/Fs). The models will include induction of hepatic CYP1A2 as a dioxin-binding protein and liver lipid accumulation for more accurate predictions of free PCDD/F concentrations. The models will support hepatotoxicity studies in mice in Project 3 and PCDD/F bioavailability studies of activated carbon-treated soil in Project 5. Human PBPK models will also be developed to help establish tissue dose equivalency between mice and humans for Project 3 and for extrapolation of in vivo PCDD/F exposure levels based on in vitro assays in Projects 1 and 2. In SA2 we will use bioinformatic tools to parse out aryl hydrocarbon receptor (AHR)-mediated cell state trajectories from single- cell RNA sequencing data in human CD5+ B cells (Project 1) and mouse hepatocytes (Project 3), and apply nonlinear dynamical systems analysis to identify novel biomarkers predictive of onset of AHR-mediated toxicity. We will also identify AHR-perturbed gene regulatory networks to inform pathway modeling in SA3. In SA3, dynamical pathway modeling for Project 1 will address the effects of AHR activation on the PD-1 inhibitory signal transduction pathway in CD5+ B cells. For Project 2, a model of induction of hepatic thyroid hormone metabolism by PCDD/Fs will be developed to support population health risk assessment. For Project 3, pathway modeling will focus on disruption of hepatic lipid metabolism through AHR-mediated transcriptional alteration of key liver enzymes. These models will support rigorous investigation of nonlinear dose-responses and provide a strong foundation for research supporting mechanistically-driven risk assessment. CMC will also support Project 4 to model the vitamin B12 salvaging and de novo synthesis pathways in bacteria dehalogenating PCDD/Fs. In SA4, in collaboration with RETCC, a 3-day course on PBPK modeling and a 5-day course on Computational Systems Toxicology: Modeling and Informatics will be offered in alternate years to SRP and risk assessment communities.

药代动力学(PK)和药效学(PD)共同定义了毒物暴露于 可能导致不良后果的生物扰动。毒理学越来越多地涉及计算 补充实验室研究的方法，并提供更全面、更定量和更机械化的 人类健康风险评估的基础。计算建模核心(CMC)将提供一套 支持生物医学和环境工程项目的计算能力。中央军委 将：(I)开发基于生理的二恶英和二恶英类化合物的PK(PBPK)和PD模型，(Ii) 为高维基因组研究提供面向项目的生物信息学支持，以及(Iii)提供交叉 计算毒理学的学科培训。模型开发将与实验室迭代协调 由这些项目进行的实验。之前CMC与密歇根州立大学(MSU)的互动 超级基金项目已经表明，这种迭代方法对于假设的生成和评估是有效的。 在特定目标1(SA1)中，我们将建立2，3，7，8-四氯二苯-对二恶英(TCDD)和 超级基金现场相关的多氯二苯并-对二恶英和呋喃(二恶英/呋喃)。这些型号将包括 诱导肝脏CYP1A2作为二恶英结合蛋白和肝脏脂质蓄积以获得更准确的结果 对游离PCDD/F浓度的预测。这些模型将支持项目3中对小鼠的肝毒性研究 和项目5中活性碳处理土壤的PCDD/F生物有效性研究。人类PBPK模型也将 被开发来帮助在项目3和 在项目1和项目2中，基于体外测试的体内PCDD/F暴露水平的外推。在SA2中，我们将 利用生物信息学工具解析芳香烃受体(AHR)介导的细胞状态轨迹 人CD5+B细胞(方案1)和小鼠肝细胞(方案3)的细胞RNA测序数据，并应用于 非线性动力系统分析以确定预测AHR介导的毒性开始的新的生物标记物。 我们还将识别AHR干扰的基因调控网络，为SA3中的途径建模提供信息。在SA3中， 项目1的动态通路建模将解决AHR激活对PD-1抑制信号的影响 CD5+B细胞的信号转导途径。项目2：诱导肝脏甲状腺激素代谢的模型 将制定多氯二苯并二恶英/氟，以支持人口健康风险评估。对于项目3，路径建模 将专注于通过AHR介导的关键肝脏转录改变来扰乱肝脏的脂代谢 酵素。这些模型将支持对非线性剂量响应的严格研究，并提供强大的 支持机械驱动风险评估的研究基础。CMC还将支持项目4以 模拟细菌脱卤化PCDD/FS中维生素B12的回收和从头合成途径。在SA4中， 与RETCC合作，为期3天的PBPK建模课程和5天的计算系统课程 毒理学：建模和信息学将每隔一年向SRP和风险评估社区提供。