An integrated approach for global profiling of multi-type constituents: Comprehensive chemical characterization of Lonicerae Japonicae Flos as a case study

Establishment of an at-line nanofractionation-based screening platform by coupling HPLC-MS/MS with high-throughput fluorescence polarization bioassay for natural SARS-CoV-2 fusion inhibitors

In this study, a novel at-line nanofractionation platform was established for screening SARS-CoV-2 fusion inhibitors from natural products for the first time by combining HPLC-MS/MS with high-throughput fluorescence polarization (FP) bioassay. A time-course FP bioassay in 384 well-plates was conducted in parallel with MS/MS to simultaneously obtain chemical and biological information of potential fusion inhibitors in Lonicerae Japonicae Flos (LJF) and Lianhua Qingwen capsules (LHQW). Semi-preparative liquid chromatography and orthogonal HPLC separation were employed to enrich and better identify the co-eluted components. After comprehensive evaluation and validation, 28 potential SARS-CoV-2 fusion inhibitors were screened out and identified. Several compounds at low micromolar activity were validated by in vitro inhibitory assay, molecular docking, cytotoxicity test, and pseudovirus assay. Moreover, four potential dual-target inhibitors against influenza and COVID-19 were discovered from LJF using this method, offering novel insights for the development of future pharmaceuticals targeting epidemic respiratory diseases.

Comparative study on chemical constituents of different medicinal parts of Lonicera japonica Thunb. Based on LC-MS combined with multivariate statistical analysis

Lonicerae japonicae flos (LJF), Lonicerae japonicae caulis (LJC), Lonicerae folium (LF) and Lonicerae fructus (LFR) are derived from Lonicera japonica Thunb., which are formed due to different medicinal parts. The efficacy of the 4 medicinal materials has similarities and differences. However, little attention has been paid to illustrate the differences in efficacy from the perspective of phytochemistry. In this study, ultra-high performance liquid chromatography coupled with hybrid quadrupole-orbitrap mass spectrometry (UPLC-Q-Exactive-Orbitrap-MS) was used to qualitatively analyze the ingredients in 4 herbs. A total of 86 compounds were plausibly or unambiguously identified, there were 54 common components among the 4 medicinal materials, and each kind of medicinal materials had its own unique components. On the basis of qualitative analysis, ultra-performance liquid chromatography coupled with triple-quadrupole tandem mass spectrometry (UPLC-QQQ-MS/MS) was used to quantitatively analyze 31 components contained in 4 medicinal materials, and principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA) and other multivariate statistical analysis were furtherly performed for comparing the component contents. The results showed that the samples from the same parts were clustered into one group, and the samples from different medicinal parts were significantly different. The analysis of variable importance projection (VIP) value of the OPLS-DA model showed that 10 components including chlorogenic acid, secologanic acid, isochlorogenic acid A, loganin, lonicerin, loganic acid, secoxyloganin, sweroside, luteolin and rhoifolin were the main difference components among the 4 medicinal materials. The study not only lays a solid foundation for the intrinsic quality control of 4 medicinal materials and the study of different effects of the 4 medicinal materials at the phytochemical level, but also provides a basis for more rational utilization of various parts of L. japonica and expansion of medicinal resources.

Reduction of flavonoid content in honeysuckle via Erysiphe lonicerae-mediated inhibition of three essential genes in flavonoid biosynthesis pathways

Honeysuckle, valued for its wide-ranging uses in medicine, cuisine, and aesthetics, faces a significant challenge in cultivation due to powdery mildew, primarily caused by the Erysiphe lonicerae pathogen. The interaction between honeysuckle and E. lonicerae, especially concerning disease progression, remains insufficiently understood. Our study, conducted in three different locations, found that honeysuckle naturally infected with E. lonicerae showed notable decreases in total flavonoid content, with reductions of 34.7%, 53.5%, and 53.8% observed in each respective site. Controlled experiments supported these findings, indicating that artificial inoculation with E. lonicerae led to a 20.9% reduction in flavonoid levels over 21 days, worsening to a 54.8% decrease by day 42. Additionally, there was a significant drop in the plant's total antioxidant capacity, reaching an 81.7% reduction 56 days after inoculation. Metabolomic analysis also revealed substantial reductions in essential medicinal components such as chlorogenic acid, luteolin, quercetin, isoquercetin, and rutin. Investigating gene expression revealed a marked decrease in the relative expression of the LjPAL1 gene, starting as early as day 7 post-inoculation and falling to a minimal level (fold change = 0.29) by day 35. This trend was mirrored by a consistent reduction in phenylalanine ammonia-lyase activity in honeysuckle through the entire process, which decreased by 72.3% by day 56. Further analysis showed significant and sustained repression of downstream genes LjFNHO1 and LjFNGT1, closely linked to LjPAL1. We identified the mechanism by which E. lonicerae inhibits this pathway and suggest that E. lonicerae may strategically weaken the honeysuckle's disease resistance by targeting key biosynthetic pathways, thereby facilitating further pathogen invasion. Based on our findings, we recommend two primary strategies: first, monitoring medicinal constituent levels in honeysuckle from E. lonicerae-affected areas to ensure its therapeutic effectiveness; and second, emphasizing early prevention and control measures against honeysuckle powdery mildew due to the persistent decline in crucial active compounds.

The "depict" strategy for discovering new compounds in complex matrices: Lycibarbarspermidines as a case

The comprehensive detection and identification of active ingredients in complex matrices is a crucial challenge. Liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) is the most prominent analytical platform for the exploration of novel active compounds from complex matrices. However, the LC-HRMS-based analysis workflow suffers from several bottleneck issues, such as trace content of target compounds, limited acquisition for fragment information, and uncertainty in interpreting relevant MS2 spectra. Lycibarbarspermidines are vital antioxidant active ingredients in Lycii Fructus, while the reported structures are merely focused on dicaffeoylspermidines due to their low content. To comprehensively detect the new structures of lycibarbarspermidine derivatives, a "depict" strategy was developed in this study. First, potential new lycibarbarspermidine derivatives were designed according to the biosynthetic pathway, and a comprehensive database was established, which enlarged the coverage of lycibarbarspermidine derivatives. Second, the polarity-oriented sample preparation of potential new compounds increased the concentration of the target compounds. Third, the construction of the molecular network based on the fragmentation pathway of lycibarbarspermidine derivatives broadened the comprehensiveness of identification. Finally, the weak response signals were captured by data-dependent scanning (DDA) followed by parallel reaction monitoring (PRM), and the efficiency of acquiring MS2 fragment ions of target compounds was significantly improved. Based on the integrated strategy above, 210 lycibarbarspermidine derivatives were detected and identified from Lycii Fructus, and in particular, 170 potential new compounds were structurally characterized. The integrated strategy improved the sensitivity of detection and the coverage of low-response components, and it is expected to be a promising pipeline for discovering new compounds.

A powerful two-dimensional chromatography method for the non-target analysis of depolymerised lignin

BACKGROUND

Lignin is an abundant natural polymer obtained as a by-product from the fractionation of lignocellulosic biomass. In the name of a circular economy, lignin should be valorised into valuable chemicals or biomaterials and utilised instead of petrochemicals. For the development of efficient valorisation processes, the structural characterisation of lignin can be highly beneficial. However, this is an arduous task, as the isolated (and sometimes processed) lignin mainly consists of various neutral monomers but also oligomers. In addition, the material contains isomers, which can be especially problematic to separate and identify.

RESULTS

We present a powerful off-line comprehensive two-dimensional (2D) chromatography method combining liquid chromatography (LC), supercritical fluid chromatography (SFC), and high-resolution mass spectrometry for the non-target analysis of depolymerised lignin. The implementation of a 1-aminoanthracene column in the second dimension enabled a class separation of potential lignin monomers, dimers, trimers, and tetramers with an additional separation based on the number of hydroxyl groups and steric effects. The pentafluorophenyl column in the first dimension additionally improved the separation based on hydrophobicity. The comparison of off-line 2D LC × SFC to 1D SFC showed that besides the overall improved performance, the first method is also superior for the separation of isomers. Advanced data analysis methods (MS-DIAL, SIRIUS, and Feature-Based Molecular Network) were integrated into the non-target workflow to rapidly visualise and study the detected compounds, which proved to be especially beneficial for the characterisation of the separated isomers.

SIGNIFICANCE

The method yielded the first 2D LC plot demonstrating a classification of lignin compounds, which can be applied to compare various lignin sources and processing methods. In addition, the technique demonstrated improved separation of compounds, including isomers, which was especially beneficial as 77 % of the detected compounds had at least one isomer in the same lignin sample.

Composition analysis of Compound Shenhua Tablet, a seven-herb Chinese medicine for IgA nephropathy: evaluation of analyte-capacity of the assays

Compound Shenhua Tablet, a medicine comprising seven herbs, is employed in treating IgA nephropathy. This study aimed to meticulously analyze its chemical composition. Based on a list of candidate compounds, identified through extensive literature review pertinent to the tablet's herbal components, the composition analysis entailed the systematic identification, characterization, and quantification of the constituents. The analyte-capacity of LC/ESI-MS-based and GC/EI-MS-based assays was evaluated. The identified and characterized constituents were quantified to determine their content levels and were ranked based on the constituents' daily doses. A total of 283 constituents, classified into 12 distinct categories, were identified and characterized in the Compound Shenhua Tablet. These constituents exhibited content levels of 1-10 982 μg·g-1, with daily doses of 0.01-395 μmol·d-1. The predominant constituents, with daily doses of ≥ 10 μmol·d-1, include nine organic acids (citric acid, quinic acid, chlorogenic acid, cryptochlorogenic acid, gallic acid, neochlorogenic acid, isochlorogenic acid C, isochlorogenic acid B, and linoleic acid), five iridoids (specnuezhenide, nuezhenoside G13, nuezhenidic acid, secoxyloganin, and secologanoside), two monoterpene glycosides (paeoniflorin and albiflorin), a sesquiterpenoid (curzerenone), a triterpenoid (oleanolic acid), and a phenylethanoid (salidroside). Additionally, there were 83, 126, and 55 constituents detected in the medicine with daily doses of 1-10, 0.1-1, and 0.01-0.1 μmol·d-1, respectively. The combination of the LC/ESI-MS-based and GC/EI-MS-based assays demonstrated a complementary relationship in their analyte-capacity for detecting the constituents present in the medicine. This comprehensive composition analysis establishes a solid foundation for further pharmacological research on Compound Shenhua Tablet and facilitates the quality evaluation of this complex herbal medicine.

Integration of non-targeted multicomponent profiling, targeted characteristic chromatograms and quantitative to accomplish systematic quality evaluation strategy of Huo-Xiang-Zheng-Qi oral liquid

Huo-Xiang-Zheng-Qi oral liquid (HXZQOL) is a well-known traditional Chinese medicine formula for the treatment of gastrointestinal diseases, with the pharmacologic effects of antiinflammatory, immune protection and gastrointestinal motility regulation. More significantly, HXZQOL is recommended for the treatment of COVID-19 patients with gastrointestinal symptoms, and it has been clinically proven to reduce the inflammatory response in patients with COVID-19. However, the effective and overall quality control of HXZQOL is currently limited due to its complex composition, especially the large amount of volatile and non-volatile active components involved. In this study, aimed to fully develop a comprehensive strategy based on non-targeted multicomponent identification, targeted authentication and quantitative analysis for quality evaluation of HXZQOL from different batches. Firstly, the non-targeted high-definition MSE (HDMSE) approach is established based on UHPLC/IM-QTOF-MS, utilized for multicomponent comprehensive characterization of HXZQOL. Combined with in house library-driven automated peak annotation and comparison of 47 reference compounds, 195 components were initially identified. In addition, HS-SPME-GC-MS was employed to analyze the volatile organic compounds (VOCs) in HXZQOL, and a total of 61 components were identified by comparison to the NIST database, reference compounds as well as retention indices. Secondly, based on the selective ion monitoring (SIM) of 24 "identity markers" (involving each herbal medicine), characteristic chromatograms (CCs) were established on LC-MS and GC-MS respectively, to authenticate 15 batches of HXZQOL samples. The targeted-SIM CCs showed that all marker compounds in 15 batches of samples could be accurately monitored, which could indicate preparations authenticity. Finally, a parallel reaction monitoring (PRM) method was established and validated to quantify the nine compounds in 15 batches of HXZQOL. Conclusively, this study first reports chemical-material basis, SIM CCs and quality evaluation of HXZQOL, which is of great implication to quality control and ensuring the authenticity of the preparation.

A practical strategy enabling more reliable identification of ginsenosides from Panax quinquefolius flower by dimension-enhanced liquid chromatography/mass spectrometry and quantitative structure-retention relationship-based retention behavior prediction

To accurately identify the metabolites is crucial in a number of research fields, and discovery of new compounds from the natural products can benefit the development of new drugs. However, the preferable phytochemistry or liquid chromatography/mass spectrometry approach is time-/labor-extensive or receives unconvincing identifications. Herein, we presented a strategy, by integrating offline two-dimensional liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (2D-LC/IM-QTOF-MS), exclusion list-containing high-definition data-dependent acquisition (HDDDA-EL), and quantitative structure-retention relationship (QSRR) prediction of the retention time (tR), to facilitate the in-depth and more reliable identification of herbal components and thus to discover new compounds more efficiently. Using the saponins in Panax quinquefolius flower (PQF) as a case, high orthogonality (0.79) in separating ginsenosides was enabled by configuring the XBridge Amide and CSH C18 columns. HDDDA-EL could improve the coverage in MS2 acquisition by 2.26 folds compared with HDDDA (2933 VS 1298). Utilizing 106 reference compounds, an accurate QSRR prediction model (R2 = 0.9985 for the training set and R2 = 0.88 for the validation set) was developed based on Gradient Boosting Machine (GBM), by which the predicted tR matching could significantly reduce the isomeric candidates identification for unknown ginsenosides. Isolation and establishment of the structures of two malonylginsenosides by NMR partially verified the practicability of the integral strategy. By these efforts, 421 ginsenosides were identified or tentatively characterized, and 284 thereof were not ever reported from the Panax species. The current strategy is thus powerful in the comprehensive metabolites characterization and rapid discovery of new compounds from the natural products.

A compounds annotation strategy using targeted molecular networking for offline two-dimensional liquid chromatography-mass spectrometry analysis: Yupingfeng as a case study

Component overlapping and long-time consumption hinder the data processing of offline two-dimensional liquid chromatography mass spectrometry (offline 2D-LC MS) system. Although molecular networking has been commonly employed in data processing of liquid chromatography mass spectrometry (LC-MS), its application in offline 2D-LC MS is challenged by voluminous and redundant data. In light of this, for the first time, a data deduplication and visualization strategy combining hand-in-hand alignment with targeted molecular networking (TMN) for compounds annotation of offline 2D-LC MS data was developed and applied to the chemical profile of Yupingfeng (YPF), a classical traditional Chinese medicine (TCM) prescription, as a case study. Firstly, an offline 2D-LC MS system was constructed for the separation and data acquisition of YPF extract. Then the data of 12 fractions derived from YPF were deconvoluted and aligned as a whole data file by hand-in-hand alignment, resulting in a 49.2% reduction in component overlapping (from 17951 to 9112 ions) and an improvement in the MS² spectrum quality of precursor ions. Subsequently, the MS²-similarity adjacency matrix of focused parent ions was computed by a self-building Python script, which realized the construction of an innovative TMN. Interestingly, the TMN was found to be able to efficiently distinguish and visualize the co-elution, in-source fragmentations and multi-type adduct ions in a clustering network. Consequently, a total of 497 compounds were successfully identified depending on only seven TMN analysis guided by product ions filtering (PIF) and neutral loss filtering (NLF) for the targeted compounds in YPF. This integrated strategy improved the efficiency of targeted compound discovery in offline 2D-LC MS data, also shown a huge scalability in accurate compound annotation of complex samples. In conclusion, our study developed available concepts and tools while providing a research paradigm for efficient and rapid compound annotation in complex samples such as TCM prescriptions, with YPF as an example.

Offline two-dimensional normal-phase × reversed-phase liquid chromatography coupled with high-resolution mass spectrometry for comprehensive analysis of chemical constituents in Euphorbia kansui

Euphorbia kansui is the dried root of Euphorbia kansui T. N. Liou ex T.P. Wang. Its main chemical components are diterpenoids, triterpenes, and volatile oil. In this study, an offline two-dimensional (2D) normal-phase × reversed-phase liquid chromatography method coupled with quadrupole time-of-flight mass spectrometry was established to comprehensively analyze the chemical constituents in E. kansui. A total of 240 compounds were identified from the E. kansui extract, including 218 diterpenoids (77 known, 141 new), 16 known volatile oils, and six known triterpenes. The relationship between the structural characteristics and tandem mass spectroscopy fragments of diterpenoids was further analyzed. Based on the characteristic fragment ions, 141 new diterpenoids were determined as 118 ingenane diterpenoids and 23 jatrophane diterpenoids. The newly identified diterpenoids may provide lead compounds for drug discovery, improving the medicinal value of E. kansui.

Enhanced profiling and quantification of ginsenosides from mountain-cultivated ginseng and comparison with garden-cultivated ginseng

Panax ginseng can be generally divided into mountain-cultivated ginseng (MCG) and garden-cultivated ginseng (GCG). The market price of MCG is significantly higher than that of GCG. However, the chemical compositions of MCG and the differences from GCG remained unclear. In this study, an integrated strategy combing an offline two-dimensional liquid chromatography separation, LTQ-orbitrap dual mode acquisition, and Q-trap full quantification/quasi-quantification was proposed to explore and compare the chemical compositions of MCG. Consequently, 559 ginsenosides were characterized, among which 437 ginsenosides were in-depth characterized with α-chain and β-chain annotated. Subsequently, enhanced quantification of 213 ginsenosides was conducted in 57 batches of MCG and GCG. Ginsenosides were found more abundant in MCG than GCG. In addition, 25-year-old MCG could be distinctly differentiated from 15/20-year-old MCG. This strategy facilitated the enhanced profiling and comparison of ginsenosides, improved the quality control tactics of MCG and provided a reference approach for other ginseng related products.

Progress and prediction of multicomponent quantification in complex systems with practical LC-UV methods

Complex systems exist widely, including medicines from natural products, functional foods, and biological samples. The biological activity of complex systems is often the result of the synergistic effect of multiple components. In the quality evaluation of complex samples, multicomponent quantitative analysis (MCQA) is usually needed. To overcome the difficulty in obtaining standard products, scholars have proposed achieving MCQA through the "single standard to determine multiple components (SSDMC)" approach. This method has been used in the determination of multicomponent content in natural source drugs and the analysis of impurities in chemical drugs and has been included in the Chinese Pharmacopoeia. Depending on a convenient (ultra) high-performance liquid chromatography method, how can the repeatability and robustness of the MCQA method be improved? How can the chromatography conditions be optimized to improve the number of quantitative components? How can computer software technology be introduced to improve the efficiency of multicomponent analysis (MCA)? These are the key problems that remain to be solved in practical MCQA. First, this review article summarizes the calculation methods of relative correction factors in the SSDMC approach in the past five years, as well as the method robustness and accuracy evaluation. Second, it also summarizes methods to improve peak capacity and quantitative accuracy in MCA, including column selection and two-dimensional chromatographic analysis technology. Finally, computer software technologies for predicting chromatographic conditions and analytical parameters are introduced, which provides an idea for intelligent method development in MCA. This paper aims to provide methodological ideas for the improvement of complex system analysis, especially MCQA.

Quality marker prediction in Trillium tschonoskii based on UHPLC-MS chemical characterisation and network pharmacology

INTRODUCTION

As a folk herbal medicine, Trillium tschonoskii has been used for thousands of years. However, due to the complexity of the chemical constituents of this herb, few investigations have acquired a comprehensive understanding of its quality markers.

OBJECTIVE

This study was conducted to characterise the chemical composition of T. tschonoskii and identify its potential quality markers.

MATERIAL AND METHODS

A systematic analytical method based on ultra-high-performance liquid chromatography coupled with mass spectrometry (UHPLC-MS) was used to characterise the constituents of T. tschonoskii. Multivariate statistical analysis was performed to investigate the chemical differences between different tissues, as well as the relationship between chemical compositions and habitats. The potential quality markers were predicted via network pharmacology and molecular docking, then confirmed by cellular assays.

RESULTS

A total of 77 compounds were co-isolated and identified, and among them, 26 were discovered from the genus Trillium for the first time. Ten batches of roots/rhizomes were explicitly clustered into five groups according to the climate types of the habitats, and the clusters of the fruits and roots/rhizomes from the same plants were independent due to the significant difference in chemical composition. Diosgenin had a good docking affinity with the relevant targets within the IL-17 pathway and cytokine pathway and could significantly inhibit TNF-α expression in hypoxic brain microvascular endothelial cells (BMECs).

CONCLUSION

This is the first study to establish the chemical composition profile of T. tschonoskii by UHPLC-MS systematically, and diosgenin was confirmed to be a potential quality marker of T. tschonoskii for the treatment of headaches.

Chemical and metabolic profiling of Codonopsis Radix extract with an integrated strategy using ultra-high-performance liquid chromatography coupled with mass spectrometry

Codonopsis radix was commonly used as food materials or herbal medicines in many countries. However, the comprehensive analysis of chemical constituents, and in vivo xenobiotics of Codonopsis radix remain unclear. In the present study, an integrated strategy with feature-based molecular networking using ultra-high-performance liquid chromatography coupled with mass spectrometry was established to systematically screen the chemical constituents and the in vivo xenobiotics of Codonopsis radix. A step-by-step manner based on a composition database, visual structure classification, discriminant ions, and metabolite software prediction was proposed to overcome the complexities due to the similar structure of chemical constituents and metabolites of Codonopsis radix. As a result, 103 compounds were tentatively characterized, 20 of which were identified by reference standards. Besides, a total of 50 xenobiotics were detected in vivo, including 26 prototypes and 24 metabolites, while the metabolic features of the pyrrolidine alkaloids were elucidated for the first time. The metabolism reactions of pyrrolidine alkaloids and sesquiterpene lactones included oxidation, methylation, hydration, hydrogenation, demethylation, glucuronidation, and sulfation. This study provided a generally applicable approach to the comprehensive investigation of the chemical and metabolic profile of traditional Chinese medicine and offered reasonable guidelines for further screening of quality control indicators and pharmacodynamics mechanism of Codonopsis radix.

Targeted isolation and identification of bioactive pyrrolidine alkaloids from Codonopsis pilosula using characteristic fragmentation-assisted mass spectral networking

Codonopsis pilosula (CP), a well-known food medicine homology plant, is commonly used in many countries. In our preliminary study, a series of pyrrolidine alkaloids with high MS responses were detected as characteristic absorbed constituents in rat plasma after oral administration of CP extract. However, their structures were unclear due to the presence of various isomers and the lack of reference standards. In the present study, an MS-guided targeted isolation of pyrrolidine alkaloids of CP extract was performed by ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC/Q-TOF MS). For data analysis under fast data directed acquisition mode (Fast-DDA), an effective approach named characteristic fragmentation-assisted mass spectral networking was successfully applied to discover new pyrrolidine alkaloids with high MS response in CP extract. As a result, seven new pyrrolizidine alkaloids [codonopyrrolidiums C-I (3-9)], together with two known ones (1 and 2), were isolated and identified by NMR spectral analysis. Among them, codonopyrrolidium B (1), codonopyrrolidium D (4) and codonopyrrolidium E (5) were evaluated for lipid-lowering activity, and they could improve high fructose-induced lipid accumulation in HepG2 cells. In addition, the characteristic MS/MS fragmentation patterns of these pyrrolizidine alkaloids were investigated, and 17 pyrrolidine alkaloids were identified. This approach could accelerate novel natural products discovery and characterize a class of natural products with MS/MS fragmentation patterns from similar chemical scaffolds. The research also provides a chemical basis for revealingin vivo effective substances in CP.

Integrating Anti-Influenza Virus Activity and Chemical Pattern Recognition to Explore the Quality Evaluation Method of Lonicerae Japonicae Flos

Lonicerae japonicae flos (LJF, Lonicera japonica Thunb.) is adopted as a core herb for preventing and treating influenza. However, the anti-influenza virus components of LJF and the impact of quality-affecting factors on the anti-influenza activity of LJF have not been systematically investigated. In this study, a strategy integrating anti-influenza virus activity, ultrahigh-performance liquid chromatography fingerprint and chemical pattern recognition was proposed for the efficacy and quality evaluation of LJF. As a result, six bioactive compounds were screened out and identified as neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, 4,5-Di-O-caffeoylquinic acid, sweroside and secoxyloganin. Based on the bioactive compounds, chemical pattern recognition models of LJF were established by a linear discriminant analysis (LDA). The results of the LDA models and anti-influenza virus activity demonstrated that cultivation pattern significantly affected the anti-influenza effect of LJF and that the neuraminidase inhibition rate of wild LJF was significantly higher than that of cultivated LJF. Moreover, the quality of LJF samples with different processing methods and geographical origins showed no obvious difference. Overall, the proposed strategy in the current study revealed the anti-influenza virus components of LJF and provided a feasible method for thequality evaluation of LJF, which has great importance for assuring the clinical effect against influenza of LJF.

Integrating Enhanced Profiling and Chemometrics to Unveil the Potential Markers for Differentiating among the Leaves of Panax ginseng, P. quinquefolius, and P. notoginseng by Ultra-High Performance Liquid Chromatography/Ion Mobility-Quadrupole Time-of-Flight Mass Spectrometry

The leaves of Panax species (e.g., Panax ginseng-PGL, P. quinquefolius-PQL, and P. notoginseng-PNL) can serve as a source for healthcare products. Comprehensive characterization and unveiling of the metabolomic difference among PGL, PQL, and PNL are critical to ensure their correct use. For this purpose, enhanced profiling and chemometrics were integrated to probe into the ginsenoside markers for PGL/PQL/PNL by ultra-high performance liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (UHPLC/IM-QTOF-MS). A hybrid scan approach (HDMS^E-HDDDA) was established achieving the dimension-enhanced metabolic profiling, with 342 saponins identified or tentatively characterized from PGL/PQL/PNL. Multivariate statistical analysis (33 batches of leaf samples) could unveil 42 marker saponins, and the characteristic ginsenosides diagnostic for differentiating among PGL/PQL/PNL were primarily established. Compared with the single DDA or DIA, the HDMS^E-HDDDA hybrid scan approach could balance between the metabolome coverage and spectral reliability, leading to high-definition MS spectra and the additional collision-cross section (CCS) useful to differentiate isomers.

An off-line three-dimensional liquid chromatography/Q-Orbitrap mass spectrometry approach enabling the discovery of 1561 potentially unknown ginsenosides from the flower buds of Panax ginseng, Panax quinquefolius and Panax notoginseng

To comprehensively elucidate the herbal metabolites is crucial in natural products research to discover new lead compounds. Ginsenosides are an important class of bioactive components from the Panax plants exerting the significant tonifying effects. However, to identify new ginsenosides by the conventional strategies trends to be more and more difficult because of the large spans of acid-base property (the neutral and acidic saponins), molecular mass (400-1400 Da), and rather low content. Herein, an off-line multidimensional chromatography/high-resolution mass spectrometry approach was presented: ion exchange chromatography (IEC) as the first dimension of separation, hydrophilic interaction chromatography (HILIC) in the second dimension, and reversed-phase chromatography (RPC) for the third dimension which was hyphenated to a Q Exactive Q-Orbitrap mass spectrometer. By applying to the flower buds of P. ginseng (PGF), P. quinquefolius (PQF), and P. notoginseng (PNF), IEC using a PhenoSphere^TM SAX column could fractionate the total extracts into the neutral (unretained) and acidic (retained) fractions, while HILIC (an XBridge Amide column) and RPC (BEH Shield RP18 column) achieved the hydrophilic interaction and hydrophobic interaction separations, respectively. Q-Orbitrap mass spectrometry offered rich structural information and complementary resolution to the co-eluting components, particular to those minor ones by including precursor ion lists in data-dependent acquisition. We could characterize 803 ginsenosides from PGF, 795 from PQF, and 833 from PNF, and 1561 thereof are potentially unknown. These results can indicate the great potential of this multidimensional approach in the ultra-deep characterization of complex herbal samples supporting the efficient discovery of potentially novel natural compounds.

A complementary chromatographic strategy for integrated components characterization of Imperatae Rhizoma based on convergence and liquid chromatography combined with mass spectrometry and molecular network

The complexity of natural ingredients and the diversity of preparations are the major obstacles to the quality evaluation of traditional Chinese medicines (TCMs). A more comprehensive characterization of herbal compounds using different types of chromatographic separation techniques and covering a diverse polarity range can help evaluate the quality of TCMs. In this study, we first proposed a comprehensive method for characterizing compounds derived from Imperatae Rhizoma by combining the complementary strengths of UPCC-QTOF-MS (ultra-performance convergence chromatography coupled with quadrupole-time of flight mass spectrometry) with UPLC-QTOF-MS (ultra-performance liquid chromatography coupled with quadrupole-time of flight mass spectrometry). The method based on the UNIFI scientific platform significantly shortened the analysis time and enabled a more comprehensive characterization of known and unreported compounds. Meanwhile, a feature-based molecular network (FBMN) was established on the Global Natural Product Social (GNPS) to infer potential compounds by rapidly classifying and visualizing these components. A total of 62 compounds in Imperatae Rhizoma were jointly characterizedand classified into six types. In comparison, the UPCC-QTOF-MS technology individually characterized 17 components, including lactones, phenols, aldehydes, phenylpropanoids, and small polar organic acids. The UPLC-QTOF-MS technology characterized 16 compounds mainly phenylpropionic acids, flavonoid glycosides, and chromone glycosides. Furthermore, three types of characteristic compounds could be well aggregated into an FBMN approach. Five possible potential new compounds were detected through the supplementary identification of GNPS and the correlation analysis of vicinal known compounds. The strategy was first applied to Imperatae Rhizoma and facilitated the characterization of a large quantity of data to provide comprehensive chemical composition results. This approach can be easily extended to the study of the material basis of other herbs or preparations in order to improve the accuracy of herb quality evaluation.

Integrated Chemical Interpretation and Network Pharmacology Analysis to Reveal the Anti-Liver Fibrosis Effect of Penthorum chinense

Liver fibrosis is a disease with complex pathological mechanisms. Penthorum chinense Pursh (P. chinense) is a traditional Chinese medicine (TCM) for liver injury treatment. However, the pharmacological mechanisms of P. chinense on liver fibrosis have not been investigated and clarified clearly. This study was designed to investigate the chemicals in P. chinense and explore its effect on liver fibrosis. First, we developed a highly efficient method, called DDA-assisted DIA, which can both broaden mass spectrometry (MS) coverage and MS² quality. In DDA-assisted DIA, data-dependent acquisition (DDA) and data-independent acquisition (DIA) were merged to construct a molecular network, in which 1,094 mass features were retained in Penthorum chinense Pursh (P. chinense). Out of these, 169 compounds were identified based on both MS¹ and MS² analysis. After that, based on a network pharmacology study, 94 bioactive compounds and 440 targets of P. chinense associated with liver fibrosis were obtained, forming a tight compound–target network. Meanwhile, the network pharmacology experimental results showed that multiple pathways interacted with the HIF-1 pathway, which was first identified involved in P. chinense. It could be observed that some proteins, such as TNF-α, Timp1, and HO-1, were involved in the HIF-1 pathway. Furthermore, the pharmacological effects of P. chinense on these proteins were verified by CCl₄-induced rat liver fibrosis, and P. chinense was found to improve liver functions through regulating TNF-α, Timp1, and HO-1 expressions. In summary, DDA-assisted DIA could provide more detailed compound information, which will help us to annotate the ingredients of TCM, and combination with computerized network pharmacology provided a theoretical basis for revealing the mechanism of P. chinense.

Application of Large-Scale Molecular Prediction for Creating the Preferred Precursor Ions List to Enhance the Identification of Ginsenosides from the Flower Buds of Panax ginseng

This work was designed to evaluate the coverage of data-dependent acquisition (DDA) extensively utilized in the untargeted metabolite/component identification in the food sciences and pharmaceutical analysis. Using saponins from the flower buds of Panax ginseng (PGF) as an example, precursor ions list (PIL)-including DDA on a Q-Orbitrap mass spectrometer could enable higher coverage than the other four MS² acquisition approaches in characterizing PGF ginsenosides. A "Virtual Library of Ginsenoside" containing 13,536 ginsenoside molecules was established by C-language-programmed large-scale molecular prediction, which in combination with mass defect filtering could create a new PIL involving 1859 PGF saponin precursors. We could newly obtain the MS² spectra of at least 17 components and characterize 36 ginsenosides with unknown masses, among the 164 compounds identified from PGF. Conclusively, a molecular-prediction-oriented PIL in DDA can assist to discover more potentially novel molecules benefiting to the development of functional foods and new drugs.

Rapid identification of chemical constituents in Yinqiao Powder using ultra-high-performance liquid chromatography coupled to quadrupole-time-of-flight tandem mass spectrometry with data filtering strategy

Yinqiao Powder is a classic and effective prescription for the treatment of many kinds of pneumonia in China. To date, the chemical constituents had not been uncovered. Comprehensive identification of chemical constituents provided a structure basis to discover the potential anti-pneumonia ingredients in Yinqiao Powder. In this paper, ultra-high performance liquid chromatography coupled to quadrupole time of flight tandem mass spectrometry (UHPLC-QTOF-MS/MS) analysis with diagnostic product ions and neutral loss filtering strategy were established and applied for the comprehensive chemical profiling of Yinqiao Powder, which simplified structure elucidation of chemical constituents in Yinqiao Powder. A total of 124 compounds, including 8 C6-C2 glucoside conjugates, 28 iridoid glycosides, 14 lignans, 21 phenylethanol glycosides, 20 triterpenoid saponins, 9 chlorogenic acids and 24 flavonoids were rapidly identified in Yinqiao Powder, and 32 of them were characterized by comparing their MS/MS data and retention time with reference standards. The results indicated that UHPLC-QTOF-MS/MS method coupled with data filtering strategy was feasible and rational to identify the complex chemical constituents of Yinqiao Powder, which would be conducive to discover the active ingredients of Yinqiao Powder for the treatment of pneumonia and establish its quality standard.

A critical review on clinical evidence of the efficacy of lavender in sleep disorders

Sleep disorders are one of the most prevalent psychiatric diseases. Insomnia is the most common sleep disorder amongst the general population. It is also one of the most frequent complaints in primary healthcare centers. Lavender is called "the broom of the brain" in different oriental traditional medicines. It is one of the most used plants for patients with sleep disorders. This study reviews what is currently known about the use of lavender for sleep disorders in patients with different diseases, from cancers and end-stage renal disease to neurological-psychiatric diseases (e.g., depression, dementia, and autism), respiratory, cardiac, and metabolic diseases. Additionally, its most used administration route is the inhalation of its essential oil (i.e., aromatherapy) alone or in combination by massage. Some limitations of the reviewed literature were discussed briefly. Overall, this critical review provides promising evidence of the lavender efficacy for sleep disorders in a wide variety of populations and diseases. However, further clinical studies with robust design and longer durations of intervention are necessary for more evidence-based judgment on its effect on sleep problems and to investigate its mechanism of action.

A novel hybrid scan approach enabling the ion-mobility separation and the alternate data-dependent and data-independent acquisitions (HDDIDDA): Its combination with off-line two-dimensional liquid chromatography for comprehensively characterizing the multicomponents from Compound Danshen Dripping Pill

Data-dependent acquisition (DDA) and data-independent acquisition (DIA)-based MSⁿ strategies are extensively applied in metabolites characterization. DDA gives accurate MSⁿ information, but receives low coverage, while DIA covers the entire mass range, but the precursor-product ions matching often yields false positives. Currently available MS scan approaches rarely integrate DIA and DDA within a duty circle. Utilizing a Vion™ IM-QTOF (ion mobility-quadrupole time-of-flight) mass spectrometer, we report a novel hybrid scan approach, namely HDDIDDA, which involves three scan events: 1) IM-enabled full scan (MS¹), 2) high-definition MS^E (HDMS^E) of all precursor ions (MS²); and 3) high-definition DDA (HDDDA) of top N precursors (MS²). As a proof-of-concept, the HDDIDDA approach combined with off-line two-dimensional liquid chromatography (2D-LC) was applied to characterize the multiple ingredients from a reputable Chinese patent medicine, Compound Danshen Dripping Pill (CDDP) used for treating the cardiovascular diseases. An off-line 2D-LC system by configuring an XBridge Amide column and an HSS T3 column showed a measurable orthogonality of 0.92 and enhanced the separation of co-eluting components. A fit-for-purpose HDDIDDA methodology was developed in the negative mode to characterize saponins and salvianolic acids, while tanshinones in the positive mode. Computational workflows to efficiently process the acquired HDMS^E and HDDDA data were established, and the searching of an in-house CDDP library (recording 712 compounds) eventually characterized 403 components from CDDP, indicating approximate 12-fold improvement compared with the previous report. The HDDIDDA approach can measure collision cross section of each component, and merges the merits of DIA and DDA in MS² data acquisition.

Chemical Pattern Recognition for Quality Analysis of Lonicerae Japonicae Flos and Lonicerae Flos Based on Ultra-High Performance Liquid Chromatography and Anti-SARS-CoV2 Main Protease Activity

Lonicerae japonicae flos (L. japonicae flos, Lonicera japonica Thunb.) is one of the most commonly prescribed botanical drugs in the treatment or prevention of corona virus disease 2019. However, L. japonicae flos is often confused or adulterated with Lonicerae flos (L. flos, Lonicera macrantha (D.Don) Spreng., Shanyinhua in Chinese). The anti-SARS-CoV2 activity and related differentiation method of L. japonicae flos and L. flos have not been documented. In this study, we established a chemical pattern recognition model for quality analysis of L. japonicae flos and L. flos based on ultra-high performance liquid chromatography (UHPLC) and anti-SARS-CoV2 activity. Firstly, chemical data of 59 batches of L. japonicae flos and L. flos were obtained by UHPLC, and partial least squares-discriminant analysis was applied to extract the components that lead to classification. Next, anti-SARS-CoV2 activity was measured and bioactive components were acquired by spectrum-effect relationship analysis. Finally, characteristic components were explored by overlapping feature extracted components and bioactive components. Accordingly, eleven characteristic components were successfully selected, identified, quantified and could be recommended as quality control marker. In addition, chemical pattern recognition model based on these eleven components was established to effectively discriminate L. japonicae flos and L. flos. In sum, the demonstrated strategy provided effective and highly feasible tool for quality assessment of natural products, and offer reference for the quality standard setting.

Comprehensive multicomponent characterization and fingerprinting analysis of Lanqin Oral Liquid by ultra-high-performance liquid chromatography coupled with ion mobility-quadrupole time-of-flight mass spectrometry

Comprehensive characterization of the chemical constituents of Chinese patent medicine poses a great challenge due to the frustrating complexity resulting from superposition of multiple drugs. Lanqin Oral Liquid is a five-component Chinese patent medicine widely applied to treat pharyngeal inflammation in clinic. Here, we streamline a universal three-dimensional separation approach to efficiently identify the multicomponents from Lanqin Oral Liquid by ultra-high-performance liquid chromatography/ion mobility quadrupole time-of-flight mass spectrometry and UNIFI/in-house library-driven automatic peak annotation. Because of the systematic optimization, the use of an HSS T3 column enabled good separation of the multiple components within 42 min, while high-definition MS^E in both the negative and positive modes could characterize more classes of herbal components, thus providing the retention, collision cross-section, and MS information for each component. Benefiting from the ion mobility separation, cleaner MS¹ and MS² spectra were acquired. Aided by comparison and analysis of the fragmentation pathways of 49 reference compounds, we could characterize 175 compounds from Lanqin Oral Liquid. A validated high-performance liquid chromatography fingerprinting approach unveiled good similarity (0.985-1.000) among 22 batches of commercial samples. Conclusively, we demonstrated a practical solution to elucidating the chemical composition of Chinese patent medicines, with the potential of popularization.

Untargeted metabolomics coupled with chemometric analysis deducing robust markers for discrimination of processing procedures: Wine-processed Angelica sinensis as a case study

Wine-processed Angelica Sinensis is a widely used Chinese medicinal decoction piece in China. However, there are hardly any robust markers indicating the processing procedure of wine-processed Angelica Sinensis, including the amount of rice wine and processing degree. A strategy integrating untargeted metabolomics and chemometric analysis for deducing robust markers was provided and applied to the discrimination of processing procedure. First, 86 compounds were tentatively identified in wine-processed Angelica Sinensis by ultra-high-performance liquid chromatography coupled with quadrupole-time of flight mass spectrometry. Second, 93 potential chemical markers were selected using multivariate analysis, among which nine robust chemical markers were selected by verification with commercial samples. Finally, the effects of processing temperature, time, and amount of rice wine on the three selected chemical markers were investigated through a rapid analytical method. It was demonstrated that both m/z 258.1097 and 238.1189 were positively correlated with the amount of rice wine and processing degree. In summary, this study introduced two candidate processing markers as robust markers for discriminating the processing procedures of wine-processed Angelica sinensis. It also proposed a strategy to provide the reference for the research of other decoction pieces.

Comprehensive feature-based molecular networking and metabolomics approaches to reveal the differences components in Cinnamomum cassia and Cinnamomum verum

Cinnamon was been a widely used plant in medicinal and spices for a long time and has spread all over the world. However, the differences in the components of the bark from Cinnamomum cassia and Cinnamomum verum, the two most common types of cinnamon, have not been thoroughly investigated. In the present experiment, ultra-high-performance liquid chromatography LTQ-Orbitrap Velos Pro hybrid mass spectrometer-based metabolomics coupled with chemometrics and feature-based molecular networking were employed to dramatically distinguish and annotate Cinnamomum cassia Bark and Cinnamomum verum bark. As a consequence, principal component analysis, orthogonal projection to latent structures discriminates analysis, and heat map analysis demonstrated clear discrimination between the profiles of metabolites in cinnamon. Besides, as the known compounds, proanthocyanidins (cinnamtannin B1 and procyanidin B2) and alkaloids (norboldine, norisoboldine) with variable importance in the projection scores >6, and an unknown alkaloid (formula C₂₄ H₃₃ NO₆ ) were selected as the best markers to discriminate cinnamon. Furthermore, large numbers of proanthocyanidins and alkaloids components were identified through feature-based molecular networking for the first time. Our investigation provides new ideas for the discovery of quality markers and identification of unknown components in natural products.

A five-dimensional data collection strategy for multicomponent discovery and characterization in Traditional Chinese Medicine: Gastrodia Rhizoma as a case study

Establishing the identity of bioactive compounds to control the quality of Traditional Chinese Medicines is made more challenging by the complexity of the metabolite matrix, the existence of isomers, and the range of compound concentration and polarity observed between individual samples of the same plant in a multicomponent preparation. In addition, LC-MS analysis has limited capability for the separation and analysis of potentially important trace compounds and isomers, which hinders the comprehensive metabolite characterization of functional foods and Traditional Natural Medicine. To facilitate and improve the chemical composition characterization and enhance metabolite discernment, a comprehensive strategy was developed which integrates ion mobility mass spectrometry (IMS) with offline two-dimensional liquid chromatography based on hydrophilic interaction chromatography (HILIC) and conventional reversed phase (RP) C18 chromatography. Through application of the HILIC × RP offline 2D-LC approach, trace compounds were enriched and separated promoting a more efficient and detailed analysis of the matrix complexity. Comprehensive non-targeted multidimensional data (Rt1D, Rt2D, MS, CCS and MS/MS) and data-independent-acquisition (DIA) mass data of the metabolites in complex food and drug samples were obtained in the IMS-DIA-MS/MS mode on a Waters-SYNAPT G2-Si mass spectrometer with an ESI source. Through the application of high-efficiency neutral loss (NLs) and diagnostic product ions (DPIs) filter strategies, information from DIA mass data permitted the rapid detection and identification of compounds. The identification coverage of metabolites with low-quality MS/MS data was also improved. In the absence of analytical standards, Collision Cross Section (CCS) prediction and matching strategies based on theoretical chemical structures provided a method to distingish isomers. To demonstrate the efficacy of the technique this comprehensive strategy was applied to the compound characterization of Gastrodia Rhizoma (GR). Characterization of 272 compounds was achieved, including 146 unreported compounds. The results affirm that this comprehensive five-dimensional data collection strategy has the capacity to support the in-depth study of the high level of chemical diversity in Traditional Chinese Medicines.

Insight into chemical basis of traditional Chinese medicine based on the state-of-the-art techniques of liquid chromatography-mass spectrometry

Traditional Chinese medicine (TCM) has been an indispensable source of drugs for curing various human diseases. However, the inherent chemical diversity and complexity of TCM restricted the safety and efficacy of its usage. Over the past few decades, the combination of liquid chromatography with mass spectrometry has contributed greatly to the TCM qualitative analysis. And novel approaches have been continuously introduced to improve the analytical performance, including both the data acquisition methods to generate a large and informative dataset, and the data post-processing tools to extract the structure-related MS information. Furthermore, the fast-developing computer techniques and big data analytics have markedly enriched the data processing tools, bringing benefits of high efficiency and accuracy. To provide an up-to-date review of the latest techniques on the TCM qualitative analysis, multiple data-independent acquisition methods and data-dependent acquisition methods (precursor ion list, dynamic exclusion, mass tag, precursor ion scan, neutral loss scan, and multiple reaction monitoring) and post-processing techniques (mass defect filtering, diagnostic ion filtering, neutral loss filtering, mass spectral trees similarity filter, molecular networking, statistical analysis, database matching, etc.) were summarized and categorized. Applications of each technique and integrated analytical strategies were highlighted, discussion and future perspectives were proposed as well.

Systematic characterization of chemical constituents in Mahuang decoction by UHPLC tandem linear ion trap-Orbitrap mass spectrometry coupled with feature-based molecular networking

Comprehensive characterization of traditional Chinese medicine prescriptions has long been a hurdle due to the chemical complexity and the lack of analytical tools. Mahuang decoction is a well-known traditional Chinese medicine prescription widely used for sweating and relieving the exterior, relieving cough and asthma, but it was insufficiently chemically scrutinized. In this study, the chemical component information of Mahuang decoction was investigated by ultrahigh-performance liquid chromatography tandem linear ion trap-Orbitrap mass spectrometry. A new data processing tool, feature-based molecular networking, was introduced for grouping and elucidating the compounds. In this way, 156 chemical components were identified or tentatively characterized, including alkaloids, triterpenoid saponins, flavanone-O-glycosides, flavone-C-glycosides, and procyanidins. Thus, this research provides a solid foundation for further development of Mahuang decoction, and the adopted method is expected to be applied to other traditional Chinese medicine prescriptions.

Molecular-networking-guided discovery of species-specific markers for discriminating five medicinal Paris herbs

BACKGROUND

Paridis Rhizoma (PR) is a famous traditional herbal medicine. Apart from two officially recorded species, viz. Paris polyphylla Smith var. yunnanensis (Franch.) Hand. - Mazz. (PPY) and P. polyphylla Smith var. chinensis (Franch.) Hara (PPC), there are still many other species used as folk medicine. It is necessary to understand the metabolic differences among Paris species.

PURPOSE

To establish a strategy that can discover species-specific steroidal saponin markers to distinguish closely-related Paris herbs for quality and safety control.

METHODS

A new strategy of molecular-networking-guided discovery of species-specific markers was proposed. Firstly, the ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) was applied to obtain the MS and MS/MS data of all samples. Then, molecular networking (MN) was created using MS/MS data to prescreen the steroidal saponins for subsequent analysis. Next, the principal component analysis (PCA) and orthogonal partial least square discriminant analysis (OPLS-DA) models were established to discover potential markers. Finally, the verification, identification and distribution of chemical markers were performed.

RESULTS

A total of 126 steroidal saponins were screened out from five species using MN. Five species were classified successfully by OPLS-DA model, and 18 species-specific markers were discovered combining the variable importance in the projection (VIP) value, P value (one-way ANOVA) and their relative abundance. These markers could predict the species of Paris herbs correctly.

CONCLUSION

These results revealed that this new strategy could be an efficient way for chemical discrimination of medicinal herbs with close genetic relationship.

An integrated approach for structural characterization of Gui Ling Ji by traveling wave ion mobility mass spectrometry and molecular network

Gui Ling Ji (GLJ), an ancient reputable traditional Chinese medicine (TCM) formula prescription, has been applied for the treatment of oligospermia and asthenospermia in clinical practice. However, its inherent compounds have not yet been systematically elucidated, which hampers developing standards or guidelines for quality evaluation and even the understanding of pharmacological effects. In this study, an integrated approach has been established for comprehensive structural characterization of GLJ. Mass spectrometry datasets of GLJ and each of the single herb medicines in this prescription have been developed by dynamic exclusion fast data-dependent acquisition and high-definition data-independent acquisition modes on ultra-high-performance liquid chromatography coupled with travelling wave ion mobility quadrupole time-of-flight mass spectrometry (UPLC-TWIMS-QTOF-MS). A global natural product social molecular networking (GNPS) platform was then applied for the visualization of chemical space of GLJ and further for the high throughput identification of the targeted or untargeted compounds due to the support of data-transmitting from each single herbal medicine to the formula GLJ. Moreover, drift time, predicted CCS, and diagnostic fragment ions were induced for annotating isomer compounds. Consequently, based on molecular network and library hits, a total of 257 compounds from GLJ, which were classified into 4 structural types, were positively or tentatively characterized. Among them, 20 potential new compounds were detected and 30 pairs of isomers were comprehensively distinguished. The established strategy was effective for attribution, classification, recognition of various constituents, and also was valuable for integrating large amounts of disordered MS/MS data and mining trace compounds in other complex chemical or biochemical systems.

An integrated approach for structural characterization of Gui Ling Ji by traveling wave ion mobility mass spectrometry and molecular network.

An enhanced strategy integrating offline superimposed two-dimensional separation with mass defect filter and diagnostic ion filter: Comprehensive characterization of steroid alkaloids in Fritillariae Pallidiflorae Bulbus as a case study

The inherent complexity of traditional Chinese medicines necessitates the application of multi-dimensional information to accomplish comprehensive profiling and confirmative identification of their chemical components. In this study, we display an enhanced strategy by integrating offline superimposed two-dimensional separation (S-2D-LC) with mass defect filter and diagnostic ion filter to comprehensively characterize the alkaloid composition of Fritillariae Pallidiflorae Bulbus (FPB). The superimposed HILIC × RP and UPCC × RP offline two-dimensional liquid chromatography system was constructed with superior orthogonality (R²=0.004 and R²=0.001) for chromatographic separation. In total, 70 fractions were collected after the first-dimensional chromatographic separation (HILIC and UPCC) and then analyzed by the second-dimensional reversed phase (RP) liquid chromatography coupled with Q-TOF/MS/MS in FAST DDA acquisition mode. A four-step interpretation strategy combining mass defect filter with diagnostic ion filter was developed to rapidly characterize alkaloids in Fritillaria species. Ultimately, a sum of 529 Fritillaria alkaloids were characterized from two botanical origins of FPB. The integrated strategy is practical to efficiently expose and comprehensively characterize more trace and isomeric components in complex herbal medicines.

A global profiling strategy using comprehensive two-dimensional liquid chromatography coupled with dual-mass spectrometry platforms: Chemical analysis of a multi-herb Chinese medicine formula as a case study

Although ultraviolet detector or mass spectrometer could be coupled with two-dimensional liquid chromatography (2DLC) to analyze complex constituents, full detection and identification of the compounds are difficult. Suffering from biased UV detection and insufficient MS data interpretation, a number of minor compounds are neglected though they are separated. In this study, we report a global chemical profiling strategy using comprehensive 2DLC coupled with dual-MS platforms, including Orbitrap-MS and QqQ-MS. It was exemplified by an 11-herb Chinese medicine formula Xiaoer-Feire-Kechuan (XFK). Firstly, constituents in XFK were separated on a CSH C₁₈ × Phenyl-Hexyl 2DLC system with a practical peak capacity of 990.5 and an orthogonality of 90.3%. Secondly, untargeted mass spectral data was collected using dd-MS² scan on an Orbitrap-MS. In total 542 peaks were detected, which was 4 times of that detected by 2DLC/UV (131 peaks). A total of 108 compounds were tentatively identified. Thirdly, targeted mass spectral data was collected for 8 characteristic substructures using neutral loss and precursor ion (NL/PRE) scan on a QqQ-MS. Extracted ion chromatogram was used to recognize minor constituents. An additional of 151 compounds were detected. Our study indicated that comprehensive 2DLC coupled with dd-MS² and NL/PRE-MS is a powerful technique for the global profiling of multi-component systems.

A Mass Spectrometry Based Metabolite Profiling Workflow for Selecting Abundant Specific Markers and Their Structurally Related Multi-Component Signatures in Traditional Chinese Medicine Multi-Herb Formulae

In Traditional Chinese Medicine (TCM), herbal preparations often consist of a mixture of herbs. Their quality control is challenging because every single herb contains hundreds of components (secondary metabolites). A typical 10 herb TCM formula was selected to develop an innovative strategy for its comprehensive chemical characterization and to study the specific contribution of each herb to the formula in an exploratory manner. Metabolite profiling of the TCM formula and the extract of each single herb were acquired with liquid chromatography coupled to high-resolution mass spectrometry for qualitative analyses, and to evaporative light scattering detection (ELSD) for semi-quantitative evaluation. The acquired data were organized as a feature-based molecular network (FBMN) which provided a comprehensive view of all types of secondary metabolites and their occurrence in the formula and all single herbs. These features were annotated by combining MS/MS-based in silico spectral match, manual evaluation of the structural consistency in the FBMN clusters, and taxonomy information. ELSD detection was used as a filter to select the most abundant features. At least one marker per herb was highlighted based on its specificity and abundance. A single large-scale fractionation from the enriched formula enabled the isolation and formal identification of most of them. The obtained markers allowed an improved annotation of associated features by manually propagating this information through the FBMN. These data were incorporated in the high-resolution metabolite profiling of the formula, which highlighted specific series of related components to each individual herb markers. These series of components, named multi-component signatures, may serve to improve the traceability of each herb in the formula. Altogether, the strategy provided highly informative compositional data of the TCM formula and detailed visualizations of the contribution of each herb by FBMN, filtered feature maps, and reconstituted chromatogram traces of all components linked to each specific marker. This comprehensive MS-based analytical workflow allowed a generic and unbiased selection of specific and abundant markers and the identification of multiple related sub-markers. This exploratory approach could serve as a starting point to develop more simple and targeted quality control methods with adapted marker specificity selection criteria to given TCM formula.