Faculty

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  • Xiaoyang Su
  • Assistant Professor
  • Department: Department of Medicine
  • Phone: 1.7322355447
  • Email: xs137@rwjms.rutgers.edu
  • Robert Wood Johnson Medical School
  • Clinical Academic Bldg
  • 125 Paterson Street
  • New Brunswick, NJ 08904
  • Key Words: Metabolomics, mass spectrometry, metabolic flux analysis
  • Lab Site URL

Su lab uses mass spectrometry to study metabolism in a variety of biological systems in a quantitative manner. Students in my lab will be trained in biochemistry, analytical chemistry and computational biology. Our lab has strong expertise in the design, data acquisition, result interpretation and data visualization of LC-MS metabolomics experiments, especially in the non-radioactive isotope labeling studies. Specific research topics in my lab include:

1. Metabolic vulnerability of tumor cells
One of the hallmarks of tumor cells is the altered metabolism. Tumor cells reprogram the metabolic network in order to support the proliferation demand. Therefore, tumor cells exhibit the dependence on certain metabolic pathways or nutrients. LC-MS metabolomics enables us to profile metabolic features associated with specific oncogenotypes, disease progression, and drug responses. This information will help us to discover new therapeutic targets and improve cancer treatment.

2. Gluconeogenesis in Type 2 Diabetes
Type 2 diabetes is characterized by elevated glucose in the blood, which can cause heart and vascular diseases, nerve damages and kidney problems. In addition to insulin resistance and decreased glucose uptake by peripheral tissues, there is elevated hepatic glucose production in type 2 diabetes patients. We are using LC-MS metabolomics to study the substrate preference in hepatic gluconeogenesis. By using non-radioactive isotope labeling technique, we can quantify the contribution of each nutrient to glucose production.

3. Identifying new metabolites and small molecule biomarkers
LC-MS metabolomics allows a comprehensive profiling of the small molecule metabolites in the biological samples. We constantly observe metabolites that are not well-documented in biochemistry textbooks. We are utilizing high-resolution tandem mass spectrometry and advance computational tools to identify these novel metabolites. We are interested in metabolites that are associated with certain diseases.

 

Publications