Profiling the constituents of Dachuanxiong decoction by liquid chromatography with high‐resolution tandem mass spectrometry using target and nontarget data mining

Comprehensive characterization of the large number of compounds existing in traditional Chinese medicines is still a great challenge. In this study, a strategy of precursor ion selected acquisition coupled with target and nontarget data mining was established to systematically characterize the chemical constituents of traditional Chinese medicines. This strategy consisted of four steps: (1) precursor ion selected acquisition was developed to trigger additional tandem mass spectrometry fragmentation reactions, especially for trace constituents; (2) in‐house database of compounds was established and diagnostic characteristics were summarized; (3) compounds were identified by target and nontarget data mining; and (4) compound structures were elucidated based on accurate mass matching and comparison of fragment ions, and isomers were discriminated by the intensity of fragment ions, fragmentation pattern analysis, and calculated log P values. This strategy was successfully applied to comprehensively identify the constituents in Dachuanxiong decoction. Finally, a total of 218 compounds assigned to six categories were characterized, and 107 compounds were characterized by nontarget analysis for the first time. In addition, three new diagnostic characteristics of esters of citric acids were elucidated. This research enriched the material basis of Dachuanxiong decoction and provided a new strategy for identifying the chemical constituents of other traditional Chinese medicines.     

Metabolomics approach based on ultra‐high‐performance liquid chromatography coupled with quadrupole‐time‐of‐flight mass spectrometry to identify the chemical constituents of the Traditional Chinese Er‐Zhi‐Pill

Er‐Zhi‐Pill, which consists of Ligustri lucidi fructus and Ecliptae prostratae herba , is a classical traditional Chinese medicinal formulation widely used as a liver‐nourishing and kidney‐enriching tonic. To identify the bioactive ingredients of Er‐Zhi‐Pill and characterize the variation of chemical constituents between co‐decoction and mix of individually decocted L. lucidi fructus and E. prostratae herba , a novel metabolomics approach based on ultra high performance liquid chromatography coupled with quadrupole time‐of‐flight mass spectrometry in both positive and negative ion modes, was established to comprehensively analyze chemical constituents and probe distinguishable chemical markers. In total, 68 constituents were unambiguously or tentatively identified through alignment of accurate molecular weights within an error margin of 5 ppm, elemental composition and fragmentation characteristics, including eight constituents, which were confirmed by comparing to reference standards. Furthermore, principal component analysis and partial least squares discriminant analysis using Simca‐p+ 12.0 software were applied to investigate chemical differences between formulations obtained by co‐decoction and a mixture of individual decoctions. Global chemical differences were found in samples of two different decoction methods, and 16 components, including salidroside, specneuzhenide and wedelolactone, contributed most to the observed differences. This study provides a basic chemical profile for the quality control and further mechanism research of Er‐Zhi‐Pill.     

Study on the source and characteristics of Evodia rutaecarpa based on chemical pattern recognition

In this study, the appearance and texture of E. rutaecarpa were linked with the chemical constituents to explore methods of classification of E. rutaecarpa. The Chemometrics such as Hierarchical cluster analysis (HCA), principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) models were used for analysis. According to the models, samples of E. rutaecarpa were divided into three categories based on their source: Evodia, Stone Tiger and Sparse Evodia. The Evodia category could be subdivided into two categories, one representing large fruits with a greater degree of cracking and the other representing large fruits with little or no cracking. The method provided by this study combines chemometrics with HPLC fingerprints, which can provide a basis and reference for the identification of E. rutaecarpa and enables establishment of a grade standard.     

Accurate discrimination of Gastrodia elata from different geographical origins using high‐performance liquid chromatography fingerprint combined with boosting partial least‐squares discriminant analysis

Gastrodia elata from different geographical origins varies in quality and pharmacological activity. This study focused on the classification and identification of Gastrodia elata from six producing areas using high‐performance liquid chromatography fingerprint combined with boosting partial least‐squares discriminant analysis. Before recognition analysis, a principal component analysis was applied to ascertain the discrimination possibility with high‐performance liquid chromatography fingerprints. And then, boosting partial least‐squares discriminant analysis and conventional partial least‐squares discriminant analysis were applied in this study. Experimental results indicated that the adaptive iteratively reweighted penalized least‐squares algorithm could eliminate the baseline drift of high‐performance liquid chromatography chromatograms effectively. And compared with partial least‐squares discriminant analysis, the total recognition rates using high‐performance liquid chromatography fingerprint combined with boosting partial least‐squares discriminant analysis for the calibration sets and prediction sets were improved from 94 to 100% and 86 to 97%, respectively. In conclusion, high‐performance liquid chromatography combined with boosting partial least‐squares discriminant analysis, which has such advantages as effective, specific, accurate, non‐polluting, has an edge for discrimination of traditional Chinese medicine from different geographical origins. And the proposed methodology is a useful tool to classify and identify Gastrodia elata from different geographical origins.     

Ultra high performance liquid chromatography with synapt high‐definition mass spectrometry and a pattern recognition approach to characterize chemical constituents and rat metabolites after the oral administration of Phellinus igniarius

Phellinus igniarius has antibacterial, antiviral, antioxidative, antitumor, and antimutagenic effects. In this study, an integrative pattern recognition approach using principal component analysis and orthogonal partial least squares discriminant analysis was successfully applied for the rapid analysis of natural compounds in traditional Chinese medicine. An ultra high performance liquid chromatography with synapt high‐definition mass spectrometry method and MassLynx software was used. This method employed gradient elution to rapidly analyze and characterize chemical constituents and metabolites after the oral administration of a P. igniarius ethanol extract. There were 24 peaks within 10 min of the analysis time and 20 of these were identified or tentatively characterized on the basis of their fragmentation behaviors. In the S‐plot of the orthogonal partial least squares discriminant analysis, 27 ions were extracted to make the serum. Among them, nine absorbed the prototype components and 18 metabolites were identified in vivo. Glucuronidation, oxidation, and methylation were the major metabolic reactions. This study is the first systematic analysis and characterization of the chemical constituents and metabolites in an ethanol extract of P. igniarius. This method can be applied to the rapid analysis and characterization of constituents in rat serum after the oral administration of other compounds used in traditional Chinese medicines.     

Qualitative and quantitative studies on chemical constituents of Ling-gui-zhu-gan decoction: In vitro and in vivo

Ling-gui-zhu-gan decoction has significant therapeutic effects in the treatment of diseases related to phlegm and fluid retention. In this study, we aimed to qualitatively characterize the chemical constituents of Ling-gui-zhu-gan decoction in vitro and in vivo by HPLC coupled to Fourier transform ion cyclotron resonance MS, and quantitively determine the contents of typical chemical constituents by HPLC method. As a result, a total of 75 chemical constituents were discovered including 37 flavonoids and their glycosides, 20 saponins, 9 sterols, 3 organic acids and their derivatives, 3 lactones, 2 coumarins, and 1 alcohol. Among them, 17 chemical constituents were specifically identified. Subsequently, an HPLC method was established for simultaneous determination of seven chemical constituents. Finally, a total of 40 prototype components were initially detected by HPLC-MS method in the biological samples of rats after their water extract was orally administrated. Among them, 29, 27, 12, and 32 prototype components were detected in plasma, bile, urine, and feces, respectively. Moreover, 34 metabolites, including 16 phase II metabolites, were detected for the first time. In conclusion, this study lays the foundation for the identification of chemical components in vitro and in vivo and the elucidation of the potential pharmacodynamic components of Ling-gui-zhu-gan decoction.     

Evaluation of the chemical consistency of Yin‐Chen‐Hao‐Tang prepared by combined and separated decoction methods using high‐performance liquid chromatography and quadrupole time‐of‐flight mass spectrometry coupled with multivariate statistical analysis

In this study, Yin‐Chen‐Hao‐Tang prepared by two decoction methods, namely, combined decoction (modern decoction method) and separated decoction (traditional decoction method), was analyzed by high‐performance liquid chromatography with quadrupole time‐of‐flight mass spectrometry. The acquired datasets containing sample codes, t_R‐m/z pairs and ion intensities were processed with multivariate statistical analyses, such as principal component analysis and an orthogonal partial least squared discriminant analysis model, to globally compare the chemical differences between the different decoction samples. Then, the chemical differences between the combined and separated decoctions were screened out by S‐plots generated from the orthogonal partial least squared discriminant analysis model and compared with chemical information from an established in‐house library. The six components that contributed the most to the chemical differences were identified as chlorogenic acid, caffeic acid, geniposide, genipin, scopoletin, and 3,5‐dicaffeoylquinic acid. The concentrations of genipin and caffeic acid from the separated decoction were higher than those from the combined decoction, indicating that the separated decoction may present a stronger hepatoprotective effect. However, the results still require further investigation through pharmacological and clinical studies. Our findings not only establish a strategy to evaluate chemical consistency of Yin‐Chen‐Hao‐Tang but also provide the scientific basis for using traditional separated decoction method.     

Total ion chromatographic fingerprints combined with chemometrics and mass defect filter to predict antitumor components of Picrasma quassioids

A method of total ion chromatogram combined with chemometrics and mass defect filter was established for the prediction of active ingredients in Picrasma quassioides samples. The total ion chromatogram data of 28 batches were pretreated with wavelet transformation and correlation optimized warping to correct baseline drifts and retention time shifts. Then partial least squares regression was applied to construct a regression model to bridge the total ion chromatogram fingerprints and the antitumor activity of P. quassioides. Finally, the regression coefficients were used to predict the active peaks in total ion chromatogram fingerprints. In this strategy, mass defect filter was employed to classify and characterize the active peaks from a chemical point of view. A total of 17 constituents were predicted as the potential active compounds, 16 of which were identified as alkaloids by this developed approach. The results showed that the established method was not only simple and easy to operate, but also suitable to predict ultraviolet undetectable compounds and provide chemical information for the prediction of active compounds in herbs.     

Determination of Quercetin in Extracts of Ginkgo biloba L. Leaves by Near‐Infrared Reflectance Spectroscopy Based on Interval Partial Least‐Squares (iPLS) Model

Abstract

This paper developed a multivariate method of analysis of quercetin in Ginkgo biloba leaf extracts, based on reflectance NIR measurements and partial least squares regression. In order to give a better correlation with the results obtained by HPLC, multiplicative scatter correction (MSC) was utilized to correct scattering effect and interval partial least squares (iPLS) to select optimum wavelength region. In general, good calibration statistics were obtained for the prediction of quercetin content, as demonstrated by some figures of merit, namely linearity, repeatability, and accuracy. And the iPLS model was more reliable than the full model.     

High‐performance liquid chromatography–based fingerprint analysis with chemical pattern recognition for evaluation of Mahonia bealei (Fort.) Carr

A simple and efficient high‐performance liquid chromatography method combined with chemical pattern recognition was established for quality evaluation of Mahonia bealei (Fort.) Carr. A common pattern of 30 characteristic peaks was applied for similarity analysis, hierarchical cluster analysis, principal component analysis, and partial least squares discriminant analysis in the 37 batches of M. bealei (Fort.) Carr. to discriminate wild M. bealei (Fort.) Carr., cultivated M. bealei (Fort.) Carr., and its substitutes. The results showed that partial least squares discriminant analysis was the most effective method for discrimination. Eight characteristics peaks with higher variable importance in projection values were selected for pattern recognition model. A permutation test and 26 batches of testing set samples were performed to validate the model that was successfully established. All of the training and testing set samples were correctly classified into three clusters (wild M. bealei (Fort.) Carr., cultivated M. bealei (Fort.) Carr., and its substitutes) based on the selected chemical markers. Moreover, 26 batches of unknown samples were used to predict the accuracy of the established model with a discrimination accuracy of 100%. The obtained results indicated that the method showed great potential application for accurate evaluation and prediction of the quality of M. bealei (Fort.) Carr.     

Qualitative and quantitative analysis of the chemical constituents in Mahuang‐Fuzi‐Xixin decoction based on high performance liquid chromatography combined with time‐of‐flight mass spectrometry and triple quadrupole mass spectrometers

High‐performance liquid chromatography coupled with time‐of‐flight mass spectrometry (HPLC‐TOF/MS) and high‐performance liquid chromatography–triple quadrupole mass spectrometry (HPLC‐QQQ/MS/MS) were utilized to clarify the chemical constituents of Mahuang‐Fuzi‐Xixin Decoction. There are 52 compounds, including alkaloids, amino acids and organic acids were identified or tentatively characterized by their characteristic high resolution mass data by HPLC‐QQQ/MS/MS. In the subsequent quantitative analysis, 10 constituents, including methyl ephedrine, aconine, songrine, fuziline, neoline, talatisamine, chasmanine, benzoylmesaconine, benzoylaconine and benzoylhypaconine were simultaneously determined by HPLC‐QQQ/MS/MS with multiple reaction monitoring mode. Satisfactory linearity was achieved with wide linear range and fine determination coefficient (r > 0.9992). The relative standard deviations (RSD) of inter‐ and intra‐day precisions were <3%. This method was also validated by repeatability, stability and recovery with RSD <3% respectively. A highly sensitive and efficient method was established for chemical constituents studying, including identification and quantification of Mahuang‐Fuzi‐Xixin decoction.     

Identification of the absorptive constituents and their metabolites in vivo of Puerariae Lobatae Radix decoction orally administered in WZS‐miniature pigs by HPLC‐ESI‐Q‐TOFMS

In this study, the technique of high‐performance liquid chromatography coupled with electrospray ionization quadrupole time‐of‐flight mass spectrometry (HPLC‐ESI‐Q‐TOFMS) was used to analyze and identify the absorptive constituents and their metabolites in drug‐containing urine of Wuzhishan (WZS)‐miniature pigs administered with Puerariae Lobatae Radix (PLR) decoction. With the accurate mass measurements (<5 ppm) and effective MS² fragment ions, 96 compounds, including eight original constituents and 88 metabolites, were identified from the drug‐containing urine. Among these, 64 metabolites were new ones and their structures can be categorized into five types: isoflavones, puerols, O‐desmethylangolensins, equols and isoflavanones. In particular, puerol‐type constituents in PLR were first proved to be absorptive in vivo. Meanwhile, the metabolic pathways of PLR in vivo were investigated. On the basis of relative content of the identified compounds, 13 major metabolites accounting for approximately 50% of the contents, as well as their corresponding 12 prototype compounds, were determined as the major original absorptive constituents and metabolites of PLR in vivo. The HPLC‐ESI‐Q‐TOFMS technique proved to be powerful for characterizing the chemical constituents from the complicated traditional Chinese medicine matrices in this research. Copyright © 2013 John Wiley & Sons, Ltd.     

Differentiating Westlake Longjing tea from the first‐ and second‐grade producing regions using ultra high performance liquid chromatography with quadrupole time‐of‐flight mass spectrometry‐based untargeted metabolomics in combination with chemometrics

There are numerous articles published for geographical discrimination of tea. However, few research works focused on the authentication and traceability of Westlake Longjing green tea from the first‐ and second‐grade producing regions because the tea trees are planted in a limited growing zone with identical cultivate condition. In this work, a comprehensive analytical strategy was proposed by ultrahigh performance liquid chromatography‐quadrupole time‐of‐flight mass spectrometry‐based untargeted metabolomics coupled with chemometrics. The automatic untargeted data analysis strategy was introduced to screen metabolites that expressed significantly among different regions. Chromatographic features of metabolites can be automatically and efficiently extracted and registered. Meanwhile, those that were valuable for geographical origin discrimination were screened based on statistical analysis and contents in samples. Metabolite identification was performed based on high‐resolution mass values and tandem mass spectra of screened peaks. Twenty metabolites were identified, based on which the two‐way encoding partial least squares discrimination analysis was built for geographical origin prediction. Monte Caro simulation results indicated that prediction accuracy was up to 99%. Our strategy can be applicable for practical applications in the quality control of Westlake Longjing green tea.     

Chemical profiling approach to evaluate the influence of traditional and simplified decoction methods on the holistic quality of Da‐Huang‐Xiao‐Shi decoction using high‐performance liquid chromatography coupled with diode‐array detection and time‐of‐flight mass spectrometry

Da‐Huang‐Xiao‐Shi decoction, consisting of Rheum officinale Baill, Mirabilitum, Phellodendron amurense Rupr. and Gardenia jasminoides Ellis, is a traditional Chinese medicine used for the treatment of jaundice. As described in “Jin Kui Yao Lue”, a traditional multistep decoction of Da‐Huang‐Xiao‐Shi decoction was required while simplified one‐step decoction was used in recent repsorts. To investigate the chemical difference between the decoctions obtained by the traditional and simplified preparations, a sensitive and reliable approach of high‐performance liquid chromatography coupled with diode‐array detection and electrospray ionization time‐of‐flight mass spectrometry was established. As a result, a total of 105 compounds were detected and identified. Analysis of the chromatogram profiles of the two decoctions showed that many compounds in the decoction of simplified preparation had changed obviously compared with those in traditional preparation. The changes of constituents would be bound to cause the differences in the therapeutic effects of the two decoctions. The present study demonstrated that certain preparation methods significantly affect the holistic quality of traditional Chinese medicines and the use of a suitable preparation method is crucial for these medicines to produce special clinical curative effect. This research results elucidated the scientific basis of traditional preparation methods in Chinese medicines.     

Differentiation of Cultivars of Flos Chrysanthemum with the Use of High-Performance Liquid Chromatography Fingerprints and Chemometrics

Flos Chrysanthemum is a generic name for a particular group of edible plants, which also have medicinal properties. There are, in fact, twenty to thirty different cultivars, which are commonly used in beverages and for medicinal purposes. In this work, four Flos Chrysanthemum cultivars, Hangju, Taiju, Gongju, and Boju, were collected and chromatographic fingerprints were used to distinguish and assess these cultivars for quality control purposes. Chromatography fingerprints contain chemical information but also often have baseline drifts and peak shifts, which complicate data processing, and adaptive iteratively reweighted, penalized least squares, and correlation optimized warping were applied to correct the fingerprint peaks. The adjusted data were submitted to unsupervised and supervised pattern recognition methods. Principal component analysis was used to qualitatively differentiate the Flos Chrysanthemum cultivars. Partial least squares, continuum power regression, and K-nearest neighbors were used to predict the unknown samples. Finally, the elliptic joint confidence region method was used to evaluate the prediction ability of these models. The partial least squares and continuum power regression methods were shown to best represent the experimental results.     

Analytical investigation of secondary metabolites extracted from Camellia sinensis L. leaves using a HPLC‐DAD‐ESI/MS data fusion strategy and chemometric methods

Considerable attention has been paid to the study of green tea leaves because of their high consume and beneficial effects on human health. In this work, an appropriate strategy is proposed to investigate and resolve the major metabolites extracted from Camellia sinensis tea leaves. Statistical design mixtures of ethanol, ethyl acetate, dichloromethane, and chloroform were used to study the effects of different solvents and their mixtures on the extraction of the secondary metabolites of C. sinensis tea leaves from two different harvest seasons. Extracted samples were analyzed by high performance liquid chromatography‐diode array detection‐electrospray ionization mass spectrometer allowing the resolution of a large amount of tea metabolites with high relative abundances, especially when their extraction was performed in pure ethanol and with solvent mixtures with ethanol. Resolution of the more relevant metabolites was achieved by the simultaneous analysis of the fused diode array detection and mass spectrometer detectors data from the same samples using the multivariate curve resolution‐alternating least squares chemometric method. Peak areas finally resolved were further analyzed by orthogonal signal correction and partial least squares‐discrimination analysis to discriminate among C. sinensis tea samples. Using the Variable Importance in Projection variable selection method, epigallocatechin and caffeine were finally selected as the two more important chemical constituents of tea leaves that were discriminating more between the tea samples from two different harvest seasons. Copyright © 2016 John Wiley & Sons, Ltd.     

Chemical composition differentiation of Shen‐Shuai‐Ning granule between combined decoction and separated decoction using HPLC‐DAD‐ESI‐QTOF‐MS

Shen‐Shuai‐Ning (SSN) granule, a traditional Chinese medicine formula, is widely used in clinical practice for treating chronic renal failure. However, its detailed chemical profile is unknown. Here, HPLC‐ESI‐QTOF‐MS was employed for the systematic chemical analysis of SSN. A total of 52 compounds were identified and the characteristic ions of the compounds were described. Furthermore, chemical consistency between the combined decoction and the separated decoction of SSN was evaluated using HPLC‐DAD. A chemical comparison between two preparations of SSN granule (combined decoction and separated decoction of Coptides Rhizoma) indicated a significant difference in the content of many compounds, including salvianolic acid A, salvianolic acid B, berberine, palmatine and epiberberine. As a result, separated decoction of Coptides Rhizoma would lead to a significantly decrease in depsides in Salviae Miltiorrhizae Radix et Rhizoma and an increase in alkaloids in Coptidis Rhizoma.     

A metabolomics strategy for authentication of plant medicines with multiple botanical origins,a case study of Uncariae Rammulus Cum Uncis

Source authentication of herbal medicines was essential for ensuring their safety, efficacy and quality consistency, especially those with multiple botanical origins. This study proposed a metabolomics strategy for species discrimination and source recognition. Uncariae Rammulus Cum Uncis, officially stipulating the stems with hooks of five Uncaria species as its origins, was taken as a case study. Firstly, an untargeted MS^E method was developed by ultra‐high performance liquid chromatography hyphenated with quadrupole time‐of‐flight mass spectrometry for global metabolite characterization. Subsequently, data pretreatment was conducted by using Progenesis QI software and screening rules. The obtained metabolite features were defined as variables for statistical analyses. Principal component analysis and chemical fingerprinting spectra suggested that five official species were differentiated from each other except for Uncaria hirsuta and Uncaria sinensis. Furthermore, orthogonal partial least squares discrimination analysis was performed to discriminate confused two species, and resulted in the discovery of nine contributing markers. Ultimately, a Support Vector Machine model was developed to recognize five species and predict origins of commercial materials. The study demonstrated that the developed strategy was effective in discrimination and recognition of confused species, and promising in tracking botanical origins of commercial materials.     

Orthogonal signal correction‐based prediction of total antioxidant activity using partial least squares regression from chromatograms

The multivariate calibration methods—partial least squares (PLS), orthogonal signal correction and partial least squares (OSC‐PLS)—were employed for the prediction of total antioxidant activities of four Prunella L. species. High‐performance liquid chromatography (HPLC) and spectrophotometric approaches were used to determine the total antioxidant activity of the Prunella L. samples. Several preprocessing techniques such as smoothing and normalization were employed to extract the chemically relevant information from the data after alignment with correlation optimized warping. The importance of the preprocessing was investigated by calculating the root mean square error for the calibration set for the total antioxidant activity of Prunella L. samples. The models developed on the basis of the preprocessed data were able to predict the total antioxidant activity with a precision comparable to that of the reference 2,2‐azino‐di‐(3‐ethylbenzothialozine‐sulfonic acid) and 2,2‐diphenyl‐1‐picrylhydrazyl methods. The OSC‐PLS model seems preferable because of its predictive and describing abilities and good interpretability of the contribution of compounds to the total antioxidant activity. The contribution of individual phenolic compounds to the total antioxidant activity was identified by HPLC. Copyright © 2012 John Wiley & Sons, Ltd.     

Application of HPLC‐NMR for the Rapid Chemical Profiling of a Southern Australian Sponge,Dactylospongia sp.

Rapid chemical profiling of the antitumour active crude dichloromethane extract of the marine sponge, Dactylospongia sp. was undertaken. A combination of both offline (HPLC followed by NMR and MS) and on‐line (on‐flow and stop‐flow HPLC‐NMR) chemical profiling approaches was adopted to establish the exact nature of the major constituents present in the dichloromethane extract of this sponge. On‐flow HPLC‐NMR analysis was employed to initially identify components present in the dichloromethane extract, while stop‐flow HPLC‐NMR experiments were then conducted on the major component present, resulting in the partial identification of pentaprenylated p‐quinol ( 5 ). Subsequent off‐line RP semi‐preparative HPLC isolation of 5 followed by detailed spectroscopic analysis using NMR and MS permitted the complete structure to be established. This included the first complete carbon NMR chemical shift assignment of 5 based on the heteronuclear 2‐D NMR experiments, together with the first report of its antitumour activity. This study represents one of the few reports describing the application of HPLC‐NMR to chemically profile secondary metabolites from a marine organism.