Arizona Metabolomics Laboratory

Metabolomics has emerged as a powerful approach for providing detailed and multilayered information about complex biological processes and systems. Metabolomics studies have resulted in a number of important findings in systems biology and biomarker discovery, including a deeper understanding of cancer metabolism, and drug toxicity, the potential for improved early disease detection or therapy monitoring, as well as applications in environmental science, nutrition, etc. It is clear from these studies and numerous others that significant potential exists for major breakthroughs in metabolomics that will impact many fields.

At the AMRL, our research interests focus on mass spectrometry (MS)-based metabolomics and its applications in early disease diagnosis, drug metabolism, and biological sciences. We are skilled in the development, optimization, and applications of MS methods for both qualitative and quantitative measurements. We have both theoretical knowledge and hands-on access with LC-MS, GC-MS, ambient MS, and metabolic analysis of various bio-samples. Meanwhile, we have extensive experience with advanced multivariate statistical analysis methods, including PCA, PLS-DA, SVM, etc. We can proficiently program in Matlab, R, and Pathyn to analyze MS and NMR data, both individually and in combination. In addition, we are working closely with a number of scientific researchers and clinical practitioners in various studies for identifying metabolic markers used to detect and monitor cancer, assess environmental contamination, investigate disease mechanisms, examine the metabolic interactions between diet and gut microbiome, inspect age-dependent changes of cardiac metabolites, etc.

Furthermore, to promote metabolomics in Arizona and beyond, we spend 10% of our efforts collaborating with outside collaborators. This is non-profit. The main purpose is to contribute to the realization of full potential of metabolomics in a wide variety of areas, eventually leading to improved human health.