A molecular networking-assisted automatic database screening strategy for comprehensive annotation of small molecules in complex matrices.

Liquid chromatography-tandem with high-resolution mass spectrometry (LCHRMS) has proven challenging for annotating multiple small molecules within complex matrices due to the complexities of chemical structure and raw LCHRMS data, as well as limitations in previous literatures and reference spectra related to those molecules. In this study, we developed a molecular networking assisted automatic database screening (MN/auto-DBS) strategy to examine the combined effect of MS1 exact mass screening and MS2 similarity analysis. We compiled all previously reported compounds from the relevant literatures. With the development of a Python software, the in-house database (DB) was created by automatically calculating the m/z and data from experimental MS1 hits were rapid screened with DB. We then performed a feature-based molecular network analysis on the auto-MS2 data for supplementary identification of unreported compounds, including clustered FBMN and annotated GNPS compounds. Finally, the results from both strategies were merged and manually curated for correct structural assignment. To demonstrate the applicability of MN/auto-DBS, we selected the Huangqi-Danshen herb pair (HD), commonly used in prescriptions or patent medicines to treat diabetic nephropathy and cerebrovascular disease. A total of 223 compounds were annotated, including 65 molecules not previously reported in HD, such as aromatic polyketides, coumarins, and diarylheptanoids. Using MN/auto-DBS, we can profile and mine a wide range of complex matrices for potentially new compounds.

A structural similarity networking assisted collision cross-section prediction interval filtering strategy for multi-compound identification of complex matrix by ion-mobility mass spectrometry.

Ion mobility coupled with mass spectrometry (IM-MS), an emerging technology for analysis of complex matrix, has been facing challenges due to the complexities of chemical structures and original data, as well as low-efficiency and error-proneness of manual operations. In this study, we developed a structural similarity networking assisted collision cross-section prediction interval filtering (SSN-CCSPIF) strategy. We first carried out a structural similarity networking (SSN) based on Tanimoto similarities among Morgan fingerprints to classify the authentic compounds potentially existing in complex matrix. By performing automatic regressive prediction statistics on mass-to-charge ratios (m/z) and collision cross-sections (CCS) with a self-built Python software, we explored the IM-MS feature trendlines, established filtering intervals and filtered potential compounds for each SSN classification. Chemical structures of all filtered compounds were further characterized by interpreting their multidimensional IM-MS data. To evaluate the applicability of SSN-CCSPIF, we selected Ginkgo biloba extract and dripping pills. The SSN-CCSPIF subtracted more background interferences (43.24%∼43.92%) than other similar strategies with conventional ClassyFire criteria (10.71%∼12.13%) or without compound classification (35.73%∼36.63%). Totally, 229 compounds, including eight potential new compounds, were characterized. Among them, seven isomeric pairs were discriminated with the integration of IM-separation. Using SSN-CCSPIF, we can achieve high-efficient analysis of complex IM-MS data and comprehensive chemical profiling of complex matrix to reveal their material basis.

Time-Series-Dependent Global Data Filtering Strategy for Mining and Profiling of Xenobiotic Metabolites in a Dynamic Complex Matrix: Application to Biotransformation of Flavonoids in the Extract of Ginkgo biloba by Gut Microbiota.

Efficient characterization of xenobiotic metabolites and their dynamics in a changing complex matrix remains difficult. Herein, we proposed a time-series-dependent global data filtering strategy for the rapid and comprehensive characterization of xenobiotic metabolites and their dynamic variation based on metabolome data. A set of data preprocessing methods was used to screen potential xenobiotic metabolites, considering the differences between the treated and control groups and the fluctuations over time. To further identify metabolites of the target, an in-house accurate mass database was constructed by potential metabolic pathways and applied. Taking the extract of Ginkgo biloba (EGB) co-incubated with gut microbiota as an example, 107 compounds were identified as flavonoid-derived metabolites (including 67 original from EGB and 40 new) from 7468 ions. Their temporal metabolic profiles and regularities were also investigated. This study provided a systematic and feasible method to elucidate and profile xenobiotic metabolism.

Comparative Analysis of Volatile Constituents in Root Tuber and Rhizome of Curcuma longa L. Using Fingerprints and Chemometrics Approaches on Gas Chromatography-Mass Spectrometry.

The root tuber and rhizome of Curcuma longa L., abbreviated, respectively, as RCL and RHCL, are used as different medicines in China. In this work, volatile oils were extracted from RCL and RHCL. Then, gas chromatography-mass spectrometry (GC-MS) was used for RCL and RHCL volatile oils analysis, and 45 compounds were identified. The dominant constituents both in volatile oils of RCL and RHCL were turmerone, (-)-zingiberene, and ß-turmerone, which covered more than 60% of the total area. The chromatographic fingerprint similarities between RCL and RHCL were not less than 0.943, indicating that their main chemical compositions were similar. However, there were also some compounds that were varied in RCL and RHCL. Based on the peak area ratio of 45 compounds, the RCL and RHCL samples were separated into principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). Then, 20 compounds with a variable importance for the projection (VIP) value of more than 1 were the high potential contributors for RCL and RHCL differences. Furthermore, ferric ion-reducing antioxidant power (FRAP) assay results demonstrated that the volatile oils of RCL and RHCL had antioxidant activities. This study provided the material basis for the research of volatile components in RCL and RHCL and contributed to their further pharmacological research and quality control.

From non-targeted to targeted GC-MS metabolomics strategy for identification of TCM preparations containing natural and artificial musk.

BACKGROUND: Moschus is a rare and precious natural medicine. Due to the properties of resources scarcity and expensive price of natural musk, artificial musk has been developed as substitute materials in some prescriptions. Rapid and accurate identification of natural or artificial musk in complex traditional Chinese medicine (TCM) preparations is also a challenge. METHOD: A strategy from non-targeted to targeted gas chromatography-mass spectrometry (GC-MS) metabolomics was developed for discrimination of natural and artificial musk. Firstly, GC-MS-based non-targeted analysis combined with chemometrics was used to find the potential chemical markers to distinguish natural musk and artificial musk. Subsequently, targeted metabolomics was used to analyze musk in preparations with multiple reaction monitoring (MRM) mode by use gas chromatography coupled with triple quadrupole mass spectrometry (GC-QQQ MS). RESULTS: Two chemical markers named prasterone and androsterone have been selected and could be detected in all Compound Pien Tze Huang preparations (CPZHs) containing artificial musk, while the CPZHs containing natural musk did not detect two markers with S/N (signal to noise ratio) less than 3. CONCLUSION: Our work provides an applicable approach to select the practical chemical markers for the assessment of musk in preparations to realize the traceability of musk in TCM and improve the quality control of musk-containing preparations.

An integrated two-step filtering strategy of collision cross-section interval predicting and mass defect filtering for targeted identification of analogues in herbal medicines using liquid chromatography-ion mobility-mass spectrometry.

Rapid identification of chemical analogues in herbal medicines using liquid chromatography-mass spectrometry was an efficient tool for discoveries of potentially active ingredients. Multi-dimensional combination of various separation technologies could significantly enhance the capacities for detection of trace components and discrimination of multiple isomers. In this study, an integrated two-step filtering strategy on liquid chromatography-ion mobility tandem with quadrupole-time-of-flight mass spectrometry (LC-IM-QTOF MS) was developed for identification of analogues in complex matrixes. The extracted raw data were preliminarily filtered by a collision-cross section (CCS) interval generated from power regression with confidence level at 99% for prediction of analogues. Then, the remained ions were further screened using a mass defect filtering (MDF) window based on m/z and decimal m/z of potential skeletons and substituents. By applying this strategy, 86, 102, 73, and 57 isoquinoline alkaloids were identified in herbal materials of Coptis chinensis Franch (CC), C. deltoidea C.Y.Cheng et Hsiao (CD), C. teeta Wall (CT), and Corydalis yanhusuo W.T.Wang (CY). The integrated two-step filtering presented higher efficiencies on exclusion of the background interference and reducing the false-positive rates than previously reported approaches. This study facilitated the application of LC-IM-MS on small molecular analysis and promoted the discoveries of bioactive components of herbal medicines for further pharmacological researches and quality control.

A validated UHPLC-MS/MS method for pharmacokinetic and brain distribution studies of twenty constituents in rat after oral administration of Jia-Wei-Qi-Fu-Yin.

A rapid ultra-high performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry (UHPLC-QqQ MS/MS) approach with high sensitivity and selectivity was developed for the quantification of twenty compounds, including 9 saponins, 8 flavonoids, 2 oligosaccharide esters and 1 phenolic acid, in rat plasma and brain, which was administrated intragastrically with Jia-Wei-Qi-Fu-Yin (JWQFY), Mass spectrometric detection was operated under multiple reaction monitoring (MRM) mode. All calibration curves possessed good linearity with correlation coefficients ( r2) higher than 0.9916 in their respective linear ranges. For intra- and inter-day precision, all the relative standard deviations (RSDs) at different levels were less than 14.68 %. Based on the UHPLC-QqQ MS/MS quantitative results, pharmacokinetic study and brain distribution of multiple components in JWQFY was then successfully performed. As a result, constituents with discrepancy structures showed diverse pharmacokinetic and distribution characteristics. For instance, ferulic acid (phenolic acid), 3, 6'-disinapoyl sucrose and tenuifoliside A (oligosaccharide esters) showed short Tmax (< 10 min), whereas the Tmax of ginsenosides Rb1, Rb2 and Rc (ppd-type terpenoid saponins) were much longer (> 4 h). Besides, ferulic acid, epimedin C, icariin, glycyrrhizin, ginsenoside Rb1 and ginsenoside Rg1 were considered as the potential effective ingredients of JWQFY because of their relatively high exposure to blood and brain. Our study would provide relevant information for discovery of pharmacodynamic ingredients, as well as further action mechanisms investigations of JWQFY.

Diagnostic ions guided 2D-locating strategy for characterization of chemical analogues in complex herbal medicines using liquid chromatography-ion mobility-mass spectrometry.

Rapid characterization of chemical analogues in potentially toxic complex matrix was essential for prevention of accidental poisoning. On the basis of the fragment ions possessed not only the same retention times (RT) but the same drift times (DT) on liquid chromatography-ion mobility-mass spectrometry (LC-IM-MS), an alternating frames (AF)-data independent acquisition (DIA) was utilized for simultaneous detection and rapid match of precursor/product ions with a fast switch of low/high collision energy (CE). A diagnostic ions guided 2D-locating strategy was developed for identification of chemical analogues in potentially toxic herbal medicines using LC-IM-MS. Firstly, the 2D-locations (RT, DT) of diagnostic ions were screened from high-fragment IM-MS frames according to their m/z. Then, the correlated precursor ions were extracted from the complex background interference in low-fragment IM-MS frames based on diagnostic ions' 2D-locations. Finally, the remained ions were characterized using double-bond equivalent analysis combined with MS/MS fragment interpretation. Totally, 236 diterpene alkaloids including eight compounds with potential new esterification types were characterized in processed lateral roots of Aconitum carmichaelii Debx. Moreover, the LC-IM-MS distribution regularities of diterpene alkaloids with various chemical structure types were further investigated and discussed. This study presented an innovative idea for revealing the chemical basis related to the toxicities of potentially poisonous herbal medicines to ensure the medication safety.

A modified data filtering strategy for targeted characterization of polymers in complex matrixes using drift tube ion mobility-mass spectrometry: Application to analysis of procyanidins in the grape seed extracts.

BACKGROUNDS: Polymers, widely existing in food or dietary materials, have been attracting researchers, facing challenges, and needing effective strategies on targeted characterization in complex matrixes. METHODS: A modified data filtering strategy (including locating with drift time and m/z ranges, multiple mass defect filtering, validating MS information, and evaluating MS/MS spectra) was developed and applied for procyanidins in the grape seed extracts (GSE) using drift tube ion mobility-mass spectrometry. The procyanidin ions' trendlines were predicted by multi-model regression. Their collision cross-sections (CCSs) were calculated using single-field methods. RESULTS AND DISCUSSION: Totally, 769 CCSs belonging to 686 procyanidins with polymer degrees at 1-15 were characterized. The exponent regression was the most reasonable model (r2 ≥ 0.9379) to reveal the trendlines. The change tendency of CCSs with their polymer degrees, charge states, and linkage types were investigated. CONCLUSION: This study provided an innovative strategy for targeted characterization of polymers in complex matrixes.

Rapid characterization of chemical markers for discrimination of Moutan Cortex and its processed products by direct injection-based mass spectrometry profiling and metabolomic method.

BACKGROUND: Processing of herbal medicines is a characteristic pharmaceutical technique in Traditional Chinese Medicine, which can reduce toxicity and side effect, improve the flavor and efficacy, and even change the pharmacological action entirely. It is significant and crucial to perform a method to find chemical markers for differentiating herbal medicines in different processed degrees. PURPOSE: The aim of this study was to perform a rapid and reasonable method to discriminate Moutan Cortex and its processed products, and to reveal the characteristics of chemical components depend on chemical markers. METHODS: Thirty batches of Moutan Cortex and its processed products, including 11 batches of Raw Moutan Cortex (RMC), 9 batches of Moutan Cortex Tostus (MCT) and 10 batches of Moutan Cortex Carbonisatus (MCC), were directly injected in electrospray ionization quadrupole time-of-flight mass spectrometry (ESI-QTOF MS) for rapid analysis in positive and negative mode. Without chromatographic separation, each run was completed within 3 min. The raw MS data were automatically extracted by background deduction and molecular feature (MF) extraction algorithm. In negative mode, a total of 452 MFs were obtained and then pretreated by data filtration and differential analysis. After that, the filtered 85 MFs were treated by principal component analysis (PCA) to reduce the dimensions. Subsequently, a partial least squares discrimination analysis (PLS-DA) model was constructed for differentiation and chemical markers detection of Moutan Cortex in different processed degrees. The positive mode data were treated as same as those in negative mode. RESULTS: RMC, MCT and MCC were successfully classified. Moreover, 14 and 3 chemical markers from negative and positive mode respectively, were screened by the combination of their relative peak areas and the parameter variable importance in the projection (VIP) values in PLS-DA model. The content changes of these chemical markers were employed in order to illustrate chemical changes of Moutan Cortex after processed. CONCLUSION: These results showed that the proposed method which combined non-targeted metabolomics analysis with multivariate statistics analysis is reasonable and effective. It could not only be applied to discriminate herbal medicines and their processing products, but also to reveal the characteristics of chemical components during processing.

An UPLC-MS/MS method for simultaneous determination of multiple constituents in Guizhi Fuling capsule with ultrafast positive/negative ionization switching.

Guizhi Fuling capsule (GFC), a traditional Chinese medicine (TCM) with effects of promoting blood circulation and dissipating blood stasis, has been widely used in the clinic. Because of the complex matrix and various chemical structure types, quality control of GFC remains great challenge. In the present study, an ultra performance liquid chromatography hybrid triple-quadrupole mass spectrometry (UPLC-QQQ MS) method with ultrafast positive/negative ionization switching was developed for simultaneous determination of 18 bioactive components in GFC, including methyl gallate, ethyl gallate, oxypaeoniflorin, benzoic acid, albiflorin, paeonolide, paeoniflorin, 1, 2, 3, 4, 6-pentagalloylglucose, mudanpioside C, benzoyloxypaeoniflorin, benzoylpaeoniflorin, pachymic acid, amygdalin, cinnamaldehyde, paeonol, cinnamic acid, 4-hydroxybenzoic acid, and gallic acid. Separation was performed on an Agilent Zorbax Extend-C18 column (2.1 mm × 50 mm, 1.8 µm), using a gradient elution with acetonitrile and water containing 0.1% formic acid. Cholic acid was selected as the internal standard. This newly developed method was fully validated for linearity, precision, accuracy, and stability, and then applied to quality assessment of GFC. Finally, the batch-to-batch reproducibility of GFC samples was evaluated by the cosine ration and Euclidean distance method, which showed high quality consistency. The results demonstrated that the developed method pro vided a reasonable and powerful manner for quality control of GFC.

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

Trace analysis of chemical analogues was always a hot topic and attracted the researchers' attentions. In this study, a database/multi-step filtering strategy was developed by using HPLC-Chip-MS system for comprehensive characterization of monacolin analogues in monascus-fermented rice product (MFRP). This strategy mainly included three steps, including chemical profile of MFRP by HPLC-Chip-MS, establishment of monacolin analogue database, multi-step filtering of monacolins based on modified mass defect filtering. All target compounds showed the symmetrical peak shapes and high MS response by using nanoflow HPLC-Chip-MS. According to the previous literature and experimental MS data, a database including 720 monacolin analogues was established. The original 522 ions in MFRP were automatically extracted by molecular feature extraction function. And then, through rectangular mass defect filtering and analogues distribution area filtering, 298 ions were further excluded. Finally, a total of 84 monacolins including 16 new compounds were unambiguously identified or tentatively characterized based on MS/MS information. In comparison with conventional mass defect filtering method, the proposed method was accurately able to exclude false positive results. The 438 false positive results were excluded in our study, while only 250 ones would be filtered out by using conventional method. This study provided a sensitive and powerful method for rapidly characterization of trace chemicals in complex matrix.

Petroleum ether sub-fraction of rosemary extract improves hyperlipidemia and insulin resistance by inhibiting SREBPs.

As a culinary and medicinal herb, rosemary is widely used. The present work aimed to investigate the effects of rosemary extracts on metabolic diseases and the underlying mechanisms of action. Liver cells stably expressing SREBP reporter were used to evaluate the inhibitory effects of different fractions of rosemary extracts on SREBP activity. The obese mice induced by Western-type diet were orally administered with rosemary extracts or vehicle for 7 weeks, the plasma and tissue lipids were analyzed. SREBPs and their target genes were measured by quantitative RT-PCR. We demonstrated that the petroleum ether sub-fraction of rosemary extracts (PER) exhibited the best activity in regulating lipid metabolism by inhibiting SREBPs, while water and n-BuOH sub-fraction showed the SREBPs agonist-effect. After PER treatment, there was a significant reduction of total SREBPs in liver cells. PER not only decreased SREBPs nuclear abundance, but also inhibited their activity, resulting in decreased expression of SREBP-1c and SREBP-2 target genes in vitro and in vivo. Inhibiting SREBPs by PER decreased the total triglycerides and cholesterol contents of the liver cells. In the mice fed with Western-type diet, PER treatment decreased TG, TC, ALT, glucose, and insulin in blood, and improved glucose tolerance and insulin sensitivity. Furthermore, PER treatment also decreased lipid contents in liver, brown adipose tissue, and white adipose tissue. Our results from the present study suggested that petroleum ether fraction of rosemary extracts exhibited the best potential of improving lipid metabolism by inhibiting SREBPs activity.

Global identification and quantitative analysis of chemical constituents in traditional Chinese medicinal formula Qi-Fu-Yin by ultra-high performance liquid chromatography coupled with mass spectrometry.

Qi-Fu-Yin (QFY), a classical traditional Chinese medicine formula, is proven to have significant neuroprotective effects by modern pharmacological studies. However, the chemical constituents of QFY have not been fully explored. In this study, an ultra-high performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UHPLC-QTOF MS) was developed for comprehensive analysis of chemical constituents in QFY. By using characteristic ions and fragmentation rules, a reliable identification of 156 compounds was described here, including 69 triterpene saponins, 23 oligosaccharide esters, 22 flavanoids, 9 alkaloids, 9 phenolic acids, 8 phthalides, 7 phenylethanoid glycosides, 3 xanthones, 3 sesquiterpene lactones, 2 ionones and 1 iridoid glycoside. Twenty-six major compounds were then determined in a single run by UHPLC coupled with triple quadrupole tandem mass spectrometry (QQQ MS) with fast positive/negative polarity switching. It allows for the acquisition of MS data in both ionization modes from a single run. The proposed method was then validated in terms of linearity, accuracy, precision and recovery. The overall recoveries for 26 analytes ranged from 91.35% to 109.58%, with RSDs ranging from 0.82% to 4.83%. In addition, the content of 26 analytes in QFY prepared by five batches of herbal materials was also analyzed. These results demonstrated that our present method was effective and reliable for comprehensive quality evaluation of QFY. Meanwhile, the study might provide the chemical evidence for revealing the material basis of its therapeutic effects.