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

圣母大学被授予开发一种在线表面增强拉曼散射(SERS)检测器，该检测器与液相色谱(LC)兼容，目的是识别代谢物。为LC开发SERS探测器为研究生和本科生提供了一个独特的培训机会。培训一支多样化的科学队伍对于保持知识和技术密集型工业的高度集中、建设和利用化学仪器是至关重要的。这个项目将开发技术和知识产权，这些技术和知识产权可以被授权并在商业上销售，同时让学生接触到这一过程。将这项研究与PI的教学相结合，将为促进生化分析提供一个统一的平台，为研究生和本科生提供培训机会，以获得与学术研究和商业兴趣相关的研究技能。一项外展计划将为邻近的全女性圣玛丽学院的学生提供这些本科生研究机会。PI正在积极探索利用研究基础设施进行正式课程作业和学生培训。开发的教学工具可能会减少教育的财政成本，同时增加学生对科学研究过程的参与。代谢谱已成为系统生物学研究的宝贵工具。SERS已经证明了检测和识别当前技术(如质谱学)难以表征的分子的能力，从而将为与新陈代谢相关的生化途径提供新的见解。该方法建立在我们最近展示的高通量、高灵敏度、流动中的SERS检测结果基础上。产生SERS光谱的振动模式对分子结构很敏感，可以区分在MS检测中有问题的同分异构体。LC-SERS应该为更常见的LC-MS提供补充特征，从而提供对代谢物的更完整的覆盖。为了证明代谢组学方法的实用性，将在葡萄糖刺激后对β细胞进行代谢谱分析。通过开发一种在线工作的方法，可以避免不同的样本制备，便于其他人采用。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.