Identify chemical and herbal components of an unknown natural product capsule using LC/MS coupled with a novel informatics platform

Abstract

We here present a novel workflow that allows quick identification of chemical constituents from a single LC/MS injection, and deduce possible herbal content from an unknown Traditional Chinese Medicine (TCM) product. Sample was injected into an UPLC/Qtof MS. Data was processed, reviewed with report automatically generated by a vendor supplied informatics platform that contains a Traditional Medicine (TM) Library. Typical approach for profiling herbal ingredients is a multiple step procedure: 1. manually extract individual chromatographic peak, propose molecular formula with MS Full scan data. 2. Search online library for potential hits. 3. Confirm positive hit using MS/MS fragment information. This approach is time consuming and labor intensive. Here, we present a novel approach with all steps incorporated into a streamlined: First of all, both intact and fragment ion information is obtained from a single LC/MS injection in a data independent MS acquisition mode. Data are searched against the TM Library (provided within the informatics platform from the instrument vendor). Structures of the matched components are automatic verified by an in silico tool (also imbedded within this informatics platform) using each component's corresponding fragment ions. Results are displayed automatically with pre-set workflow templates. All steps were carried automatically once the user sets up the processing method. Initial non-targeted screening identified 86 major compounds from 473 detected components. Through multi-step approach, we proposed that this unknown sample is the product commercially named XinKeShu, which contains Dan Shen (Salvia miltiorrhiza), San Qi (Panax notoginseng), Ge Gen (Lobed kudzuvine root), Shan Cha (Crataegus pinnatifida Bunge) and Mu Xiang (Saussurea costus). Among the 229 compounds listed within the Traditional Medicine Scientific Library that are associated with the XinKeShu recipe, 183 were identified and confirmed.