Developing qualitative LC-MS methods for characterization of Vaccinium berry Standard Reference Materials.

Standard Reference Materials (SRMs) offer the scientific community a stable and homogenous source of material that holds countless application possibilities. Traditionally, the National Institute of Standards and Technology (NIST) has provided SRMs with associated quantitative information (certified values) for a select group of targeted analytes as measured in a solution or complex matrix. While the current needs of the SRM community are expanding to include non-quantitative data, NIST is attempting to broaden the scope of how and what information is offered to the SRM community by providing qualitative information about biomaterials, such as chromatographic fingerprints and profiles of untargeted identifications. In this work, metabolomic and proteomic profiling efforts were employed to characterize a suite of six Vaccinium berry SRMs. In the discovery phase, liquid chromatography-tandem mass spectrometry (LC-MS/MS) data was matched to mass spectral libraries; a subsequent validation phase based on multiple-reaction monitoring LC-MS/MS relied on both retention time matching of authentic standards along with fragmentation data for a qualitative overview of the most prominent organic compounds present. Definitive and putative identifications were determined for over 70 metabolites based on reporting guidelines set forth by the Metabolomics Standards Initiative (Metabolomics 3(3):211-221, 2007), and the capability of electrospray ionization mass spectrometry (ESI-MS) to profile untargeted metabolites within a complex matrix using mass spectral matching is demonstrated. Bottom-up proteomic analyses were possible using peptide databases translated from expressed sequence tags (ESTs). Homology searches provided identification of novel Vaccinium proteins based on homology to related genera. Chromatographic fingerprints of these berry materials were acquired for supplemental qualitative information to be provided to users of these SRMs. An unbounded set of qualitative data about a biomaterial is a valuable complement to quantitative information traditionally provided in NIST Certificates of Analysis.