Assessment of Chinese medicinal herb metabolite profiles by UPLC‐MS‐based methodology for the detection of aristolochic acids

Abstract

In this study, aristolochic acid in different herbal medicines containing a mixture of varying herb species was identified through fingerprint pattern similarities. Aristolochic acid I and II are nephrotoxic compounds naturally present in the Aristolochia plant species that are commonly used in Chinese herbal medicines. Twenty-four commercially available herbal formulations were extracted into an aqueous solution and injected into a UPLC-MS system. All the samples were analysed by multiple reaction monitoring (MRM) to check for the presence of aristolochic acids I and II. The same samples were then fingerprinted using two different gradient methods and the chromatograms deconvoluted into retention time (RT) and masses for the chemicals present taking concentration into account. Statistical analysis of this data revealed that samples were highly heterogeneous, and that the main differences between the preparations were concentrations of polar compounds. A model was constructed where the samples could be separated into two groups differentiated by the presence of the two forms of aristolochic acid.

Analysis of alkaloids in Coptis chinensis Franch by accelerated solvent extraction combined with ultra performance liquid chromatographic analysis with photodiode array and tandem mass spectrometry detections

“…However, the acquisition of a fingerprint on HPLC is a rigorous operation as it generally needs about one or more hour for a single run [43,44]. In recent years, UPLC is emerging as a viable technique for natural product analysis, and two papers have appeared in the literature on its applications in the fingerprinting of Chinese herbal medicines [27,45]. The results obtained in this paper and the two quoted references demonstrate that UPLC is indeed a very powerful tool in chromatographic fingerprinting applications.…”

Evaluation of Chinese medicinal herbs fingerprinting by HPLC‐DAD for the detection of toxic aristolochic acids

“…Previously published methods for the determination of AA content in herbal mixtures have used a range of different analytical techniques. Most of these publications revolve around the identification and quantification of the acids using HPLC‐MS 7–9, UPLC‐MS 10, HPLC‐UV (or DAD) 9, 11–14, HPCE 15, and HPLC‐fluorescence 16, 17. Combination approaches have also been applied to the detection of AAs in herbs; for example, Ioset et al first tested for the presence of acid using TLC, and if detected then applied LC‐DAD/MS to its quantification 18.…”

“…Therefore, a method which is capable of providing a small molecule “fingerprint” of Chinese herbs, with particular focus on AA signatures would be extremely useful in the determination of which Chinese herbs are present in each treatment, as well as the content of AA present. There are previous examples of a “fingerprint” used in this way 10, 14; however, the first 14 fails to utilise the statistical models and approaches used here in this study, relying instead on direct chromatogram comparison, which can be subjective and unreliable, whereas the second 10 uses an expensive UPLC‐MS approach not available or affordable by many laboratories.…”

“…Within the context of this study, we employed conventional cost‐effective HPLC equipment to illustrate an alternative to direct identification and quantification commonly associated with LC‐MS techniques, in order to assess the presence of AA within a collection of traditional Chinese herbal preparations 10. This method provides not only a cost‐effective way for monitoring the presence of the herb, but also a specific herbal fingerprint which can be used to avoid contamination and mistaken identity.…”

New Opportunities in Metabolomics and Biochemical Phenotyping for Plant Systems Biology

“…For instance, Chinese medicinal herbs were tested for two secondary metabolites inducing nephrotoxicity. The UPLC-MS (MRM) run was 5 min and was amenable for high-throughput analyses (Jacob et al, 2007) This method was however impaired by a strong matrix effect that could not be prevented and another approach was preferred. At last, these techniques have been also shown to be a must for some classes of compounds such as hormones (Kojima et al, 2009), intermediates of central metabolism (Arrivault et al, 2009) and pesticides (Kmellar et al, 2010).…”