Bioengineering partnership to improve chemical hazard testing paradigms

描述（由申请人提供）：目前的化学危害测试程序没有考虑到可能有接触风险的人群的遗传多样性;然而，我们最近的数据表明，小鼠近交系之间的遗传差异对毒性剂的时间、剂量和器官特异性影响有深远影响。因此，我们假设，有毒物质的作用模式的知识可以有效地结合组织工程，在硅片建模，遗传学和基因组学的进步，开发新的方法，提高在体外和体内化学危害测试范例，优先环境代理商的选择和增加吞吐量的筛选在生物学上有意义的和明智的方式。本申请建议在环境健康科学家、生物工程师、化学信息学家、生物统计学家和遗传学家之间建立伙伴关系。这个多学科的团队将应用一个综合的，系统的方法：（1）开发一个三维微型小鼠肝脏组织生物反应器，可应用于高通量筛选的化学品。这是一个设计导向的努力，以产生一个独特的工具，可以增加吞吐量的测试，同时减少动物的数量;（2）建立，测试和验证定量结构-毒性关系（QSTR）模型，采用化学和生物描述符的分子结构，并考虑到个体之间的遗传多样性。这一目标是一种发现驱动的方法，将产生一种计算方法，用于根据化学结构、包括组学终点在内的多维毒性数据和关于种群遗传多样性的信息确定化合物的优先次序;以及（3）通过产生基于遗传变异性的知识，对一类烯丙基苯衍生物进行体内和体外毒性筛选在人口中。这一目标将检验以下假设：个体间的遗传变异是化学危害的毒性效应的主要决定因素，使用一组小鼠近交系可以成功阐明易感性的遗传基础。该合作伙伴关系将由医学博士伊万·鲁辛（Ivan Rusyn）指导，博士(UNC公共卫生），他是一位环境卫生科学家，在肝脏毒理学和小鼠毒性模型方面有经验。其他主要研究者为：琳达格里菲斯博士。（马萨诸塞州理工学院），世界著名的肝脏组织工程领域研究者; Alex Tropsha博士，(UNC药学），定量结构活性/毒性关系建模领域的领导者;和大卫Threadgill，博士。(UNC他是一位遗传学家，他的工作开创了小鼠遗传学在癌症研究和毒理学中的应用。总体而言，这一努力将导致在了解遗传多样性人口中化学品特性与化学品危害之间的关系方面取得重大和及时的进展。它还将说明如何将环境健康、遗传学、化学信息学和生物工程方面的基础科学结合起来，通过提高我们将化学测试的结果外推和转化为人类的能力，并通过为限制与疾病相关的环境因子接触的监管决定提供信息，来预防人类疾病。

DESCRIPTION (provided by applicant): Current chemical hazard testing procedures do not take into account the genetic diversity of the population that may be at risk of exposure; however, our recent data show that genetic differences between mouse inbred strains have a profound impact on time-, dose- and organ-specific effects of toxic agents. Thus, we hypothesize that the knowledge on the modes of action of toxic agents can be efficiently combined with advances in tissue engineering, in silico modeling, genetics and genomics to develop novel approaches that improve in vitro and in vivo chemical hazard testing paradigms, prioritize environmental agents for selection and increase throughput of screening in a biologically meaningful and sensible way. This application proposes to establish a partnership between environmental health scientists, biological engineers, chem- informaticians, biostatisticians and geneticists. This multidisciplinary team will apply an integrative, systems approach to: (1) Develop a 3D microscale mouse liver tissue bioreactor that can be applied to high- throughput screening of chemicals. This is a design-directed effort to produce a unique tool that can increase throughput of testing while reducing the number of animals; (2) To build, test and validate Quantitative Structure-Toxicity Relationship (QSTR) models that employ both chemical and biological descriptors of molecular structures and take into account genetic diversity between individuals. This aim is a discovery- driven approach that will produce a computational method for compound-prioritization based on the chemical structure, multi-dimensional toxicity data that includes -omics endpoints, and information on genetic diversity of the population; and (3) Validate a fiscally sensible in vivo and in vitro toxicity screening paradigm for a class of allylbenzene derivatives by producing knowledge anchored on the genetic variability present within the population. This aim will test the hypothesis that genetic variability among individuals is a major determinant in the toxic effects of chemical hazards and that the genetic basis for susceptibility can be successfully elucidated using a panel of mouse inbred strains. The partnership will be directed by Ivan Rusyn, M.D., Ph.D. (UNC Public Health) who is an environmental health scientist with experience in liver toxicology and mouse models of toxicity. Other Lead Investigators are: Linda Griffith, Ph.D. (Massachusetts Institute of Technology), a world-renowned researcher in the field of liver tissue engineering; Alex Tropsha, Ph.D., (UNC Pharmacy), a leader in the field of quantitative structure activity/toxicity relationship modeling; and David Threadgill, Ph.D. (UNC Medicine), a geneticist whose work pioneers the applications of mouse genetics into cancer research and toxicology. Collectively, this effort will lead to significant and timely advances in understanding the relationship between chemical identity and chemical hazard within a genetically diverse population. It will also illustrate how basic science in environmental health, genetics, chem-informatics and bioengineering can be combined to prevent human disease by improving our ability to extrapolate and translate findings from chemical testing to human populations and by informing regulatory decisions that limit exposures to disease-associated environmental agents.