IDBR: TYPE A, Online Liquid Chromatography - Surface Enhanced Raman Detection for Metabolic Profiling

University Of Notre Dame, Notre Dame IN

Investigators

Abstract

An award is made to the University of Notre Dame to develop an online surface enhanced Raman scattering (SERS) detector compatible with liquid chromatography (LC) whose purpose is to identify metabolites. Developing the SERS detector for LC provides a unique training opportunity for graduate and undergraduate students. Training a diverse scientific workforce is essential to maintaining the high concentration of knowledge- and technology- intensive industries building and utilizing chemical instrumentation. This project will develop technology and intellectual property that can be licensed and marketed commercially while exposing students to this process. Integration of the research with the PI's teaching will provide a unified platform for promoting biochemical analysis, providing training opportunities for both graduate and undergraduate students to gain research skills relevant to academic research and commercial interests. An outreach program will provide these undergraduate research opportunities to students from the neighboring, all-woman, St. Mary's College. The PI is actively exploring leveraging research infrastructure for both formal coursework and student training. The pedagogical tools developed may reduce the fiscal cost of education while increasing student engagement in the scientific research process. Metabolic profiling has become a valuable tool for systems biology studies. SERS has demonstrated the ability to detect and identify molecules that are challenging to characterize by current technology, such as mass spectrometry (MS), and thus will provide new insights into biochemical pathways associated with metabolism. The approach builds from our recent results demonstrating high-throughput, high-sensitivity, SERS detection in flow. The vibrational modes that give rise to the SERS spectra are sensitive to molecular structure and can differentiate between isomeric species that are problematic in MS detection. LC-SERS should provide complementary characterization to the more common LC-MS, thus providing more complete coverage of the metabolome. To demonstrate the utility of the approach for metabolomics, metabolic profiling will be performed on beta-cells following glucose stimulation. By developing a method that works inline, different sample preparations can be avoided, facilitating adoption by others.