Reverse Engineering Cellular Pathways from Human Cells Exposed to Nanomaterials-Development of Novel Risk Assessment Methods
Project Information
| Principal Investigator | Mary Jane Cunningham |
| Institution | Houston Advanced Research Center |
| Project URL | View |
| Relevance to Implications | High |
| Class of Nanomaterial | Engineered Nanomaterials |
| Impact Sector | Human Health |
| Broad Research Categories |
Hazard Risk Assessment |
| NNI identifier |
Funding Information
| Country | USA |
| Anticipated Total Funding | $200,000.00 |
| Annual Funding | $100,000.00 |
| Funding Source | NSF |
| Funding Mechanism | Extramural |
| Funding Sector | Government |
| Start Year | 2004 |
| Anticipated End Year | 2006 |
Abstract/Summary
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.
