global CHARACTERIZATION OF SRM 1950 (mETABOLITES IN HUMAN PLASMA) Using Liquid Chromatography-Mass Spectrometry

 

Kelly H. Telu, William E. Wallace III, Stephen E. Stein, and Yamil Simón-Manso

 

SRM 1950 was recently produced through a collaborative effort with the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) to provide a stable, well-characterized human plasma standard reference material for metabolomics research. It was certified for concentrations of 95 different species including electrolytes, amino acids, hormones, vitamins, carotenoids, and fatty acids.

 

Complex biological reference materials such as SRM 1950 often have many “off-label” uses because analysts are interested in compounds that are not certified.  In these situations, qualitative assignments are better than having no information. The Standard Reference Material and Data (SRM/D) website (http://srmd.nist.gov/) was recently launched to provide users access to qualitative assignments, spectral data and information about the analysis method.

 

Our objective is to develop tools and methods for the profiling of complex biological materials like SRM 1950. Liquid chromatography-Mass spectrometry (LC-MS) has emerged as an excellent tool for metabolite characterization; however most of the published results focus on a single metabolite or class of metabolites. A workflow for the analysis of the matrix of complex materials like SRM 1950 will benefit metabolomics research. In addition, the information acquired will be presented on the SRM/D website and can extend the applications of SRM 1950. 

 

SRM 1950 was disinfected with ethanol which also resulted in protein precipitation. After removal of the precipitated protein and evaporation of the supernatant, the re-suspended metabolites were analyzed by LC-MS with a high mass accuracy instrument. Initial experiments were carried out to determine the best percent of ethanol to use for sample preparation. Subsequent experiments focused on comparing nano-LC, conventional HPLC and UHPLC for the profiling of metabolites. Our goal is to find the best platform and computational tools for global metabolite analysis. This includes work on chromatographic reproducibility and pattern comparison, improving our database search algorithm for mass spectral matching and increasing the number of positive identifications.