SGER: Reverse Engineering Cellular Pathways from Human Cells Exposed to Nanomaterials-Development of Novel Risk Assessment Methods

新的和独特的数学建模和逆向工程方法来评估纳米材料的毒性的基础将奠定。基因组学，通过使用基因表达微阵列（GEM）将被用于评估暴露于单壁碳纳米管（SWNT）培养的人表皮角质形成细胞（HEK）样本。这些数据将通过统计学、相似性和预测方法以及逆向工程来分析，以确定涉及的遗传调控网络。这项研究将为建立新的数学和工程建模方法来推断纳米材料对人类的风险的最终目标奠定基础。纳米材料在医疗、能源和通信领域的应用远远超过了目前的传统材料。然而，最近，一些初步研究，但不是全部，暗示了毒性可能与纳米材料有关。这些研究大多是在SWNT上进行的，并使用传统的毒性试验。这里提出的研究计划将使用基因组学来调查基因的毒性迹象，并将为新开发的数学和逆向工程算法奠定基础，以预测暴露于人类健康的风险。本研究计划的新颖和独特之处在于优化的实验设计和对结果数据文件的综合分析方案，包括对所涉及的基因调控网络的逆向工程。这项研究将为建立新的数学和工程建模方法来推断纳米材料对人类的风险的最终目标奠定基础。

0436366 Cunningham The foundation for new and unique mathematical modeling and reverse engineering approaches to assess the toxicity of nanomaterials will be laid. Genomics, through the use of gene expression microarrays (GEM) will be used to evaluate samples from human epidermal keratinocytes (HEK) exposed to single-walled carbon nanotubes (SWNT) in culture. The data will be analyzed by statistical, similarity and predictive approaches as well as reverse engineered to determine the genetic regulatory networks which are involved. This research will set the stage for the ultimate goal of establishing new mathematical and engineering modeling methods to extrapolate the risk of nanomaterials to humans. Nanomaterials have been shown to have attributes, which far exceed the current traditional materials for medical, energy, and communications applications. Recently, however, several preliminary studies, but not all, have hinted that toxicity may be associated with nanomaterials. Most of these studies were performed on SWNT and using traditional toxicity assays. The research plan proposed here will use genomics to survey genes for indications of toxicity and will form the foundation for newly developed mathematical and reverse engineering algorithms to predict risk of exposure to human health. The novel and unique aspects of this research plan is the optimized experimental design as well as the comprehensive analysis scheme on the resulting data files, including reverse engineering of the genetic regulatory networks involved. This research will set the stage for the ultimate goal of establishing new mathematical and engineering modeling methods to extrapolate the risk of nanomaterials to humans.