Highly sensitive strategy for identification of trace chemicals in complex matrix: Application to analysis of monacolin analogues in monascus-fermented rice product

Li, Meng-Ning; Li, Chaoran; Gao, Wen; Li, Ping; Yang, Hua

doi:10.1016/j.aca.2017.05.030

Cited by 24 publications

(23 citation statements)

References 33 publications

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“…In the same way, the yellow azaphilone pigments with the classical monascin-type chromophore showed specific profiles with high intensity peaks at 227-233 and 386-392 nm and a very low intensity band at 285-291 nm, while the red ones with the rubropunctamine-type chromophore presented specific absorbances at 251-252, 302-307, 412-423 and 525-530 nm (Table 4), all these values being in agreement with literature reports [29][30][31][32][33][34]. Figure 2 for their chemical structures) were identified by comparing with the literature their elution sequence, their UV-Vis and MS profiles as well as the accurate mass measurements of their parent and fragment ions in High Resolution Electrospray Ionization (HR-ESI) MS and MS/MS [13,26]. Moreover, the identification of MK, CP, MKA, DeMK, DiMK, citrinin and monascin was confirmed by comparing their UV-Vis and MS and MS/MS chromatographic profiles with those of the corresponding standards.…”

Section: Identification Of Monacolins and Pigmentssupporting

confidence: 87%

“…RYR formulations were traced by UHPLC-DAD-MS. Among the great number of compounds observed, 23 (12 monacolins and 11 azaphilones; see Figure 2 for their chemical structures) were identified by comparing with the literature their elution sequence, their UV-Vis and MS profiles as well as the accurate mass measurements of their parent and fragment ions in High Resolution Electrospray Ionization (HR-ESI) MS and MS/MS [13,26]. Moreover, the identification of MK, CP, MKA, DeMK, DiMK, citrinin and monascin was confirmed by comparing their UV-Vis and MS and MS/MS chromatographic profiles with those of the corresponding standards.…”

Section: Identification Of Monacolins and Pigmentsmentioning

confidence: 99%

“…Moreover, the MS/MS product ions obtained were characteristic of the fragmentation pathway of monacolins (Table 4) [13,14,26]. So, the compound detected was a monacolin derivative that might be monacolin N (MN) or dehydromonacolin N hydroxyl acid (DeMNA) recently described by Li et al [26]. We propose that it was MN based on the fact that its tR at −0.16 min with respect to monacolin L in hydroxyl acid form (MLA) was in agreement with the value given by Li et al for MN (−0.22 min) and not for DeMNA (+1.72 min).…”

Section: Identification Of Monacolins and Pigmentsmentioning

confidence: 99%

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Comparative Chemical Profiling and Monacolins Quantification in Red Yeast Rice Dietary Supplements by 1H-NMR and UHPLC-DAD-MS

et al. 2020

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Red yeast rice dietary supplements (RYR DS) are largely sold in Western countries for their cholesterol-lowering/regulating effect due to monacolins, mainly monacolin K (MK), which is, in fact, lovastatin, the first statin drug on the market. 1H-NMR was used as an easy, rapid and accurate method to establish the chemical profiles of 31 RYR DS and to quantify their monacolin contents. Among all the 1H resonances of the monacolins found in RYR, only those of the ethylenic protons of the hexahydronaphthalenic ring at 5.84 and 5.56 ppm are suitable for quantification because they show no overlap with the matrix signals. The total content in monacolins per capsule or tablet determined in 28 DS (the content in 3 DS being below the limit of quantification of the method, ≈ 0.25 mg per unit dose) was close to that measured by UHPLC, as shown by the good linear correlation between the two sets of values (slope 1.00, y-intercept 0.113, r2 0.986). Thirteen of the 31 RYR DS analyzed (i.e., 42%) did not provide label information on the concentration of monacolins and only nine of the 18 formulations with an indication (i.e., 50%) actually contained the declared amount of monacolins.

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Section: Identification Of Monacolins and Pigmentssupporting

confidence: 87%

Section: Identification Of Monacolins and Pigmentsmentioning

confidence: 99%

Section: Identification Of Monacolins and Pigmentsmentioning

confidence: 99%

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Comparative Chemical Profiling and Monacolins Quantification in Red Yeast Rice Dietary Supplements by 1H-NMR and UHPLC-DAD-MS

et al. 2020

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“…However, large deviations and many interfering compounds might still exist in the screening result when the conventional mass defect filtering method is applied in the analysis of complex samples. Since analogues commonly share similar skeletons and modifying groups, a predicted‐analogue table based on summarisation of the structural characteristics and MS data of reported analogues can facilitate dereplication in favour of the targeted analogues . Chromatographic behaviour prediction based on structure–retention relationships has been used to assist in structure elucidation, especially for some isomers with similar fragmentation behaviour .…”

Section: Introductionmentioning

confidence: 99%

“…Since analogues commonly share similar skeletons and modifying groups, a predicted-analogue table based on summarisation of the structural characteristics and MS data of reported analogues can facilitate dereplication in favour of the targeted analogues. 12,13 Chromatographic behaviour prediction based on structure-retention relationships has been used to assist in structure elucidation, especially for some isomers with similar fragmentation behaviour. [14][15][16] The present study combined analogue prediction-based selective filtering, fragmentation pattern analysis, and chromatographic behaviour prediction using UPLC-ESI-QTOF-MS/MS for efficient identification of triterpene acid analogues in poria ( Figure 1).…”

Section: Introductionmentioning

confidence: 99%

A dereplication strategy for identifying triterpene acid analogues in Poria cocos by comparing predicted and acquired UPLC‐ESI‐QTOF‐MS/MS data

Zou

Long

et al. 2018

Phytochemical Analysis

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Introduction Triterpene acids from the dried sclerotia of Poria cocos (Schw.) Wolf (poria) were recently found to possess anti‐cancer activities. Identification of more triterpene acid analogues in poria is worthwhile for high throughput screening in anti‐cancer drug discovery. Objective To establish an efficient dereplication strategy for identifying triterpene acid analogues in poria based on ultra‐performance liquid chromatography with electrospray ionisation quadrupole time‐of‐flight tandem mass spectrometry (UPLC‐ESI‐QTOF‐MS/MS). Methodology The structural characteristics and mass spectrometric data profiles of known triterpene acids previously reported in poria were used to establish a predicted‐analogue database. Then, the quasi‐molecular ions of components in a poria extract were automatically compared with those in the predicted‐analogue database to highlight compounds of potential interest. Tentative structural identification of the compounds of potential interest and discrimination of isomers were achieved by assessing ion fragmentation patterns and chromatographic behaviour prediction based on structure–retention relationship. Results A total of 62 triterpene acids were unequivocally or tentatively characterised from poria, among which 17 triterpene acids were tentatively identified for the first time in poria. Conclusion This study provided more structure information of triterpene acids in poria for future high throughput screening of anti‐cancer candidates. It is suggested that this semi‐automated approach in which MS data are automatically compared to a predictive database may also be applicable for efficient screening of other herbal medicines for structural analogues of proven bioactives.

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Nontargeted screening of veterinary drugs and their metabolites in milk based on mass defect filtering using liquid chromatography–high‐resolution mass spectrometry

et al. 2021

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The development of nontargeted screening strategy for veterinary drugs and their metabolites is very important for food safety. In this study, a nontargeted screening strategy was developed to find the potentially hazardous substances based on mass defect filtering (MDF) using liquid chromatography–high‐resolution mass spectrometry. First, the drug metabolites of 112 veterinary drugs from seven classes of antimicrobials were predicted. Second, three MDF models were established, including the traditional rectangular MDF, the enhanced parallelogram MDF, and the polygonal MDF. Finally, the strategy was applied to nontargeted screening of veterinary drugs in 36 milk samples. The polygonal MDF model based on the distribution area of parent drugs and their metabolites showed a better filtering effect. After removing food components and performing MDF, about 10% of the substances remained, and four veterinary drugs and six drug metabolites were discovered and identified, showing the effectiveness of this strategy. The nontargeted screening strategy can rapidly remove interfering substances and find the suspected compounds. It can also be used for nontargeted screening of veterinary drugs and their metabolites in other food matrices.

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Highly sensitive strategy for identification of trace chemicals in complex matrix: Application to analysis of monacolin analogues in monascus-fermented rice product

Cited by 24 publications

References 33 publications

Comparative Chemical Profiling and Monacolins Quantification in Red Yeast Rice Dietary Supplements by 1H-NMR and UHPLC-DAD-MS

Comparative Chemical Profiling and Monacolins Quantification in Red Yeast Rice Dietary Supplements by 1H-NMR and UHPLC-DAD-MS

A dereplication strategy for identifying triterpene acid analogues in Poria cocos by comparing predicted and acquired UPLC‐ESI‐QTOF‐MS/MS data

Nontargeted screening of veterinary drugs and their metabolites in milk based on mass defect filtering using liquid chromatography–high‐resolution mass spectrometry

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