A novel predict-verify strategy for targeted metabolomics: Comparison of the curcuminoids between crude and fermented turmeric
Introduction
Turmeric (Curcuma longa L.) has been widely used as a folk medicine in Asia, and it is traditionally used as a spice in India. The major active components in turmeric are known to be curcuminoids such as curcumin, demethoxycurcumin, and bisdemethoxycurcumin. As a traditional medicine, turmeric has various therapeutic effects, including anti‐inflammatory, antihyperlipidemic, anticancer, and antimicrobial activities (Akyuz et al., 2016, Allegra et al., 2017, Sahebkar, 2014, Yun and Lee, 2016). However, the industrial application and popularization of curcuminoids are still developing slowly due to the unacceptable bitter taste and poor bioavailability of these components (Anand et al., 2007, Prasad et al., 2014). Therefore, the methods for solving these problems still must be improved in order to enable the further use of curcuminoids.
Biotransformation, known as microbial fermentation is an efficient method for enhancing the availability of medicinal plants. The technique has numerous advantages including its specificity, low cost, mild reaction conditions, and nonsecondary pollution (Han et al., 2010, Yu, 2007). In previous reports, it was shown that fermented turmeric had a range of pharmacological activities such as alleviating memory impairment and reducing body weight gain in mice (Eun et al., 2017, Ho et al., 2012). Fermented turmeric has numerous advantages, including greater potential contribution to pathology, pharmacology and healthcare (S. W. Kim et al., 2013; Y. Kim et al., 2014, Kuo et al., 2009). Monascus purpureus belongs to the class Ascomycetes and the family Monascaceae. It has been applied in the fermentation processing of red mold rice, alcoholic beverages, and pickled vegetables in China for over a thousand years. Additionally, it is commonly used in the fermentation of turmeric. A previous study suggested that Monascus purpureus fermented products collected from a turmeric-containing medium demonstrated higher antiatherosclerotic value than the regular products (Kuo et al., 2009). Eurotium cristatum belongs to the genus Eurotium (Du, Li, Li, Shang, & Wang, 2012) and is a kind of traditional probiotic commonly used in the fermentation of raw tea leaves in China. Water extracts of the fermented tea have shown significant anti-obesity and hypolipidemic functions (Li et al., 2013) that are closely related to the fermentation of Eurotium cristatum (Keller, Weir, Broeckling, & Ryan, 2013). During tea fermentation, hydroxyl-containing compounds such as polyphenols are massively transformed (Zhu et al., 2015). Since similar to polyphenols, curcuminoids also contain phenolic hydroxy groups, similar to polyphenols, we hypothesize that Eurotium cristatum may contribute to the transformation of curcuminoids. Therefore, this study applied Monascus purpureus and Eurotium cristatum fungi to the microbial fermentation of turmeric.
Although fermented turmeric has various pharmacological properties, few studies have been carried out for the systematic analyses of curcuminoids in fermented turmeric. Various techniques such as HPLC, GC–MS and LC-MS have been applied for the analyses of curcuminoids in turmeric (Hiserodt et al., 1996, Jayaprakasha et al., 2002, Shen et al., 2013). Metabolomics is the investigation of a biological system (cell, tissue or organism) by determining its overall metabolite profile at a given time point under a specified set of conditions (Heyman & Dubery, 2016). Applications of metabolomics have been mainly centered on the use of two analytical strategies of untargeted and targeted metabolomics. In MS-based metabolomics studies, untargeted analysis is the most commonly applied method, and does not require extensive prior knowledge of the compounds in samples. The other strategy is targeted analysis that only measures selected known metabolites. Currently, targeted metabolomics has made substantial advances in the discovery of bioactive compounds in natural herbs and plants (D. Wang et al., 2018; Z. Wang et al., 2019). Meanwhile, it has been successfully applied to screen potential biomarkers of diseases such as obesity (Zhong, Xu, Bruno, Ballard, & Zhu, 2017), hyperlipidemia (Jin et al., 2014), diabetes (Floegel et al., 2013), cancer (Kus et al., 2018) and coronary artery diseases (Zhang et al., 2017). Since curcuminoids are known major components of turmeric, targeted metabolomics was applied in this study due to its high selectivity. In our previous study, 96 curcuminoids in crude turmeric were identified and characterized using two LC-MS/MS platforms (Jin et al., 2017). However, the previous analytical strategy relied on the finite available samples for establishment of the characteristic profile and thus was limited to the compounds in the profile. For fitting different samples, the profile must be reestablished in different analyses. In this work, a novel predict-verify strategy was established, based on a custom library consisting of theoretical possible curcuminoids. This custom library included all of the possible curcuminoids based on the reported core skeletons and aryl substituent groups. Thus, the library can be applied to the analysis of curcuminoids in any turmeric sample and is not limited by the existing turmeric samples. Meanwhile, this analytical strategy was combined with data analysis software for automatic scanning based on the principle of matching precursor ions and characteristic fragment ions of compounds. This greatly accelerates the time required for the highly repetitive tasks for establishment of curcuminoid profile and qualitative analysis of individual compounds. Hence, the predict-verify strategy for targeted metabolomics was show to be efficient and appropriate for the analyses of curcuminoids in any sample due to our comprehensive customized library.
In the present work, Monascus purpureus and Eurotium cristatum fungi were applied to the microbial fermentation of turmeric in order to enhance its availability. Then, the targeted predict-verify strategy was established for the identification of curcuminoids in crude and fermented samples. Finally, the variations of curcuminoids in turmeric after fermentation were explored using targeted metabolomics and thus possible curcuminoids with better bioavailability were further screened.
Section snippets
Chemicals and reagents
HPLC grade acetonitrile and methanol were purchased from Fisher Scientific (Fair Lawn, NJ, USA). Deionized water was produced by a Milli-Q water system (Millipore, Bedford, MA, USA). Formic acid (≥98%) of analytical grade was purchased from Sinopharm Chemical Reagent Co., Ltd (Shanghai, China). Tanshinone IIA prepared in-house was used as the internal standard. Its purity was above 98% according to HPLC-UV analysis. The standards of ten curcuminoids were isolated in our previous study (Jin et
Design of the analytical strategy
As shown in Fig. 1, a predict-verify strategy was designed for the analysis of curcuminoids in crude and fermented turmeric. First, we collected all of the reported core skeletons and theoretical aryl substituent groups of curcuminoids in turmeric, including 15 core skeletons and 21 aryl substituent groups (Jia et al., 2017, Jin et al., 2017). Then, 5775 theoretical possible curcuminoids were predicted by the method of permutation and combination. Then, a customized library consisting of the
Conclusions
In this study, a novel predict-verify strategy for targeted metabolomics was established and applied to curcuminoids. In the exclusive method, 115 curcuminoids were fully characterized based on the LC-QTOF-MS/MS analysis with the targeted approach. It was found that the relative contents of major curcuminoids decreased in the extracts of the two fermented groups, while the contents of numerous minor curcuminoids increased significantly after fermentation. The transformation of curcuminoids may
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
Funds for this research were provided by grants from Natural Science Foundation of China (No. 81603331, 81703243) and Science Foundation of Department of Education of Hubei Province, China (Q20172002).
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These authors contributed equally to this article.