Yu Ping Feng San (YPFS) is a three herb TCM formulation which has been traditionally used for treatment of immune system related diseases. The LC-MS data generated from such multiple herbs contain fragments from co-eluting multiple precursor ions. This makes the fragment data more complex and hence difficult to make correct compound identification. Here we describe the application of a novel data-independent acquisition (DIA) approach called SONAR™ for improved spectral clarity and confident compound identification from complex samples such as TCM.
SONAR™ utilizes a low resolution quadrupole mass filter, which is scanned continuously and both precursor and MS/MS data are acquired. Data were also collected for comparison purposes using a traditional DIA method such as MSe, which provides both precursor and fragment ion information but without a resolving quadrupole. From the results, the specificity of SONAR™ provides cleaner precursor and fragment ion spectra compared to the traditional DIA acquisition method. As an example, the identification of prim-O-glucosylcimifugin acquired using a traditional DIA and SONAR™ was compared. When using the traditional DIA there are multiple co-eluting compounds which could confound the structural analysis. The presence of these co-eluting precursor ions with prim-O-glucosylcimifugin provided a high complexity with 97 high energy fragment ions, making compound identification very complex and challenging. On the other hand when the data were acquired using SONAR™, cleaner precursor and fragment ion spectra were generated. The selected narrow precursor mass window from SONAR™ provided specific fragment ions and contained only the parent ions prim-O-glucosylcimifugin [M+H]+ and [M+Na]+. Eight clean relevant fragment ions were generated only from the parent ion prim-O-glucosylcimifugin which led to correct and confident compound identification. In summary, compared to the traditional DIA method, the specificity of SONAR™ provided cleaner precursor and high energy fragment ion spectra, which resulted in confident compound identification.