Shotgun chemome characterization of Artemisia rupestris L. Using direct infusion-MS/MSALL.
2021
Abstract In comparison of liquid chromatography, direct infusion is a superior choice to achieve high-throughput measurements. The specificity and selectivity of tandem mass spectrometry (MS/MS) actually result in a so-called MS separation potential when chemical characterization of herbal medicines. Here, a MS/MSALL program was introduced to promote DI–MS/MS to be an eligible tool for shotgun chemome characterization of Artemisia rupestris L. that is currently drawing worldwide interests because of the promising antiviral activity. After MS1 spectral acquisition for the crude extract, the gas phase fractionation concept enabled the precursor ion cohort sequentially entered the collision cell with a stepped unit mass window (step-size as 1 Da) to generate MS2 spectra, thus generating a unique property integrating the advantages of both data-dependent and data-independent acquisition manners. Even though being free of chromatographic separation, spectrometric separations were accomplished for by MS/MSALL program unless the components shared identical nominal molecular weights. Extensive efforts such as the correlations of MS1 signals with MS2 spectra, structural annotations of fragment ion species, information retrieval in some accessible databases, and referring to the literature data, were devoted for chemical characterization, and as a result, 44 compounds, in total, were structurally identified from 50% aqueous methanol exact of A. rupestris, including 8 caffeoyl quinic acid derivatives, 13 flavonoids, 15 monomeric and dimeric sesquiterpenoids, 4 fatty acids, 2 penylpropanoids, along with 2 other compounds. However, isomers were assigned as an isomeric mixture because their precursor ions always co-existed in a single mass window. Above all, DI–MS/MSALL provides an alternative tool for chemome characterization of herbal medicines, in particular when the great measurement workload for a large sample cohort, attributing to the high-throughput advantage.
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